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Richard Feynman on Computation (Stephen Wolfram) | AI Podcast Clips

When you were at Caltech, did you get to interact with Richard Feynman at all? Do you have any memories of Richard? We worked together quite a bit actually. In fact, both when I was at Caltech and after I left Caltech, we were both consultants at this company called Thinking Machines Corporation, which was just down the street from here actually. It was ultimately an ill-fated company, but I used to say this company is not going to work with the strategy they have. Dick Feynman always used to say, what do we know about running companies? Just let them run their company. He was not into that kind of thing. He always thought that my interest in doing things like running companies was a distraction, so to speak. For me, it's a mechanism to have a more effective machine for actually figuring things out and getting things to happen. Did he think of it, because essentially what you did with the company, I don't know if you were thinking of it that way, but you're creating tools to empower the exploration of the university. Did he understand that point? The point of tools? I think not as well as he might have done. He was actually my first company, which was involved with more mathematical computation kinds of things. He had lots of advice about the technical side of what we should do and so on. Do you have examples, memories, or thoughts? Oh yeah, yeah. In the business of doing sort of, one of the hard things in math is doing integrals and so on. He had his own elaborate ways to do integrals and so on. He had his own ways of thinking about getting intuition about how math works. His meta idea was, take those intuitional methods and make a computer follow those intuitional methods. Now, it turns out, for the most part, like when we do integrals and things, what we do is we build this kind of bizarre industrial machine that turns every integral into products of major g functions and generates this very elaborate thing. Actually, the big problem is turning the results into something a human will understand. It's not, quote, doing the integral. Actually, Feynman did understand that to some extent. I'm embarrassed to say, he once gave me this big pile of calculational methods for particle physics that he worked out in the 50s. He said, it's more used to you than to me type thing. I was like, I've intended to look at it and give it back. I still have my files now. But that's what happens when it's finiteness of human lives. Maybe if he'd lived another 20 years, I would have remembered to give it back. But I think that was his attempt to systematize the ways that one does integrals that sharpen particle physics and so on. Turns out the way we've actually done it is very different from that way. What do you make of that difference, Eugene? So Feynman was actually quite remarkable at creating intuitive frameworks for understanding difficult concepts. I'm smiling because the funny thing about him was that the thing he was really, really, really good at is calculating stuff. But he thought that was easy because he was really good at it. And so he would do these things where he would do some complicated calculation in quantum field theory, for example, come out with a result. Wouldn't tell anybody about the complicated calculation because he thought that was easy. He thought the really impressive thing was to have the simple intuition about how everything works. So he invented that at the end. And because he'd done this calculation and knew how it worked, it was a lot easier. It's a lot easier to have good intuition when you know what the answer is. And then he would just not tell anybody about these calculations. And he wasn't meaning that maliciously, so to speak. He thought that was easy. And that led to areas where people were just completely mystified and they kind of followed his intuition, but nobody could tell why it worked. Because actually the reason it worked was because he'd done all these calculations and he knew that it would work. And he and I worked a bit on quantum computers, actually, back in 1980, 81, before anybody had heard of those things. And the typical mode of, I mean, he always used to say, and I now think about this because I'm about the age that he was when I worked with him. And I see that people are one third my age, so to speak. And he was always complaining that I was one third his age and therefore various things. But he would do some calculation by hand, blackboard and things, come up with some answer. I'd say, I don't understand this. I do something with a computer and he'd say, I don't understand this. So there'd be some big argument about what was going on. But it was always, and I think actually many of the things that we sort of realized about quantum computing that were sort of issues that have to do particularly with the measurement process are kind of still issues today. And I kind of find it interesting. It's a funny thing in science that there's a remarkable, it happens in technology too, there's a remarkable sort of repetition of history that ends up occurring. Eventually things really get nailed down, but it often takes a while and it often things come back decades later. Well, for example, I could tell a story actually happened right down the street from here. When we were both at Thinking Machines, I had been working on this particular cellular automaton called Rule 30 that has this feature that from very simple initial conditions, it makes really complicated behavior. So and actually of all silly physical things, using this big parallel computer called the connection machine that that company was making, I generated this giant printout of Rule 30 on actually on the same kind of printer that people use to make layouts for microprocessors. So one of these big, large format printers with high resolution and so on. So okay, so print this out lots of very tiny cells. And so there was sort of a question of how some features of that pattern. And so it was very much a physical, on the floor with meter rules trying to measure different things. So, so Feynman kind of takes me aside. We've been doing that for a little while and takes me aside and he says, I just want to know this one thing. He says, I want to know, how did you know that this Rule 30 thing would produce all this really complicated behavior that is so complicated that we're, you know, going around with this big printout and so on. And I said, well, I didn't know. I just enumerated all the possible rules and then observed that that's what happened. He said, oh, I feel a lot better. You know, I thought you had some intuition that he didn't have that would let one. I said, no, no, no, no intuition, just experimental science. So that's such a beautiful sort of dichotomy there of that's exactly what you showed is you really can't have an intuition about an irreducible, I mean, you have to run it. Yes, that's right. That's so hard for us humans and especially brilliant physicists like Feynman to say that you can't have a compressed, clean intuition about how the whole thing works. Yes, yes. No, he was, I mean, I think he was sort of on the edge of understanding that point about computation. And I think he found that, I think he always found computation interesting. And I think that was sort of what he was a little bit poking at. I mean, that intuition, you know, the difficulty of discovering things like even you say, oh, you know, you just enumerate all the cases and just find one that does something interesting, it sounds very easy. Turns out like I missed it when I first saw it because I had kind of an intuition that said it shouldn't be there. So I had kind of arguments, oh, I'm going to ignore that case because whatever. How did you have an open mind enough? Because you're essentially the same person as Richard Feynman, like the same kind of physics type of thinking. How did you find yourself having a sufficiently open mind to be open to watching rules and them revealing complexity? Yeah, I think that's an interesting question. I've wondered about that myself because it's kind of like, you know, you live through these things and then you say, what was the historical story? And sometimes the historical story that you realize after the fact was not what you lived through, so to speak. And so, you know, what I realized is I think what happened is, you know, I did physics kind of like reductionistic physics where you're thrown in the universe and you're told go figure out what's going on inside it. And then I started building computer tools and I started building my first computer language, for example. And a computer language is not like, it's sort of like physics in the sense that you have to take all those computations people want to do and kind of drill down and find the primitives that they can all be made of. But then you do something that's really different because you're just saying, okay, these are the primitives. Now, you know, hopefully they'll be useful to people. Let's build up from there. So you're essentially building an artificial universe in a sense where you make this language, you've got these primitives, you're just building whatever you feel like building. And that's, and so it was sort of interesting for me because from doing science where you're just thrown in the universe as the universe is, to then just being told, you know, you can make up any universe you want. And so I think that experience of making a computer language, which is essentially building your own universe, so to speak, is, you know, that's kind of the, that's what gave me a somewhat different attitude towards what might be possible. It's like, let's just explore what can be done in these artificial universes rather than thinking the natural science way of let's be constrained by how the universe actually is. Yeah. By being able to program, essentially you've, as opposed to being limited to just your mind and a pen, you now have, you've basically built another brain that you can use to explore the universe by, computer program, you know, is a kind of a brain. Right. And it's, well, it's, or a telescope or, you know, it's a tool. It lets you see stuff. But there's something fundamentally different between a computer and a telescope. I mean, it just, I'm hoping not to romanticize the notion, but it's more general. The computer is more general than the telescope. It is. It's more general. And this point about, you know, people say, oh, such and such a thing was almost discovered at such and such a time. The distance between, you know, the building, the paradigm that allows you to actually understand stuff or allows one to be open to seeing what's going on. That's really hard. And, you know, I think in, I've been fortunate in my life that I've spent a lot of my time building computational language, and that's an activity that in a sense works by sort of having to kind of create another level of abstraction and kind of be open to different kinds of structures. But, you know, it's, it's always, I mean, I'm fully aware of, I suppose, the fact that I have seen it a bunch of times of how easy it is to miss the obvious, so to speak, that at least is factored into my attempt to not miss the obvious, although it may not succeed.

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When will the 200 billionth person be born?

Current population of Earth is 7.8 billion people. Since about 50,000 years ago, when modern Homo sapiens first appeared, the number of people who have lived is 109 billion, which naturally leads to the other number that gives me pause. Since the origin of modern humans, 101 billion people have died. 101 billion stories of suffering, of triumph, of death in infancy, of living beyond 100 years old, of wars, of hatred, of love and beauty. The data sources, estimates, and projections for this video are from the United Nations and the Population Reference Bureau. So the natural question I had when looking at these numbers is, what are the next milestones? When will the 110th, the 150th, the 200 billionth person be born? And of course, let me say that predicting the future of anything beyond 10 to 20 years is very difficult. So this is more of an exercise of building intuition about the prospects of human civilization. This is the plot of the world population on the y-axis in billions from 0 to 12 and the x-axis from the 1500s to 2100. We'll reach 8 billion people in 2022 and 10 billion people in 2056. Based on UN projections, the population of Earth should level out by 2100 at about 11 billion people. By the way, there are a lot of estimates of Earth carrying capacity, the median of those estimates being around 10 billion people. So there's a lot of debates on whether we'll eventually exceed the human carrying capacity of Earth. It should also be noted that since we're living in the times of COVID, the estimates for excess deaths in 2020 should be anywhere from 0 to 20%. In several studies of the topic, the estimate rests at about 20% excess deaths. So 20% more deaths than otherwise would be expected for a non-pandemic year. But when we look at 2020 as a whole, it's very possible it levels out to much closer to 0% excess deaths given the effects of lockdown on the patterns of human behavior. Now we take these projections of the world population and the birth rates estimated by the United Nations and talk about the number of people who have ever lived projected out into the future. Now we hit the 50 billion person born mark just about a century and a half after the common era began. And we hit the 100 billionth mark just before 1950. The 110th billion person will be born in 2028. The 120th billion in 2102. The 150th billion about three centuries from now in 2340. And the 200 billionth person will be born in 2736, which is about seven centuries from now. Unless, as described in the global catastrophic risk survey about existential risk, that estimates the probability of the destruction of human civilization in a century at a terrifying 19%. And if we take that out to 2736, the probability that the 200 billionth person will never be born, at least on earth at a terrifying 77%. Of course, it's possible that the 200 billionth person will be born on Mars, or maybe even Proxima b, the closest earth like planet outside of our solar system that we currently know. Hope you enjoy these little videos. They're easy and fun to make. Give me a chance to talk about some cool ideas. So if you enjoy these, subscribe, and remember, try to learn something new every day.

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What is Real? (Lee Smolin) | AI Podcast Clips

What is real? Let's start with an easy question. Put another way, how do we know what is real and what is merely a creation of our human perception and imagination? We don't know. We don't know. This is science. I presume we're talking about science. And we believe, or I believe, that there is a world that is independent of my existence and my experience about it and my knowledge of it. And this I call the real world. So you said science, but even bigger than science. Sure, sure. I need not have said this is science. I just was warming up. Warming up. Okay, now that we're warmed up, let's take a brief step outside of science. Is it completely a crazy idea to you that everything that exists is merely a creation of our mind? So there's a few, not many, this is outside of science now, people who believe perception is fundamentally what's in our human perception. The visual cortex and so on, the cognitive constructs that's being formed there is the reality. And then anything outside is something that we can never really grasp. Is that a crazy idea to you? There's a version of that that is not crazy at all. What we experience is constructed by our brains and by our brains in an active mode. So we don't see the raw world, we see a very processed world. We feel something that's very processed through our brains and our brains are incredible. But I still believe that behind that experience, that mirror or veil or whatever you wanna call it, there is a real world and I'm curious about it. Can we truly, how do we get a sense of that real world? Is it through the tools of physics from theory to the experiments? Or can we actually grasp it in some intuitive way that's more connected to our ape ancestors? Or is it still fundamentally the tools of math and physics that really allow us to grasp it? Well, let's talk about what tools they are. What you say are the tools of math and physics. I mean, I think we're in the same position as our ancestors in the caves or before the caves or whatever. We find ourselves in this world and we're curious. We also, it's important to be able to explain what happens when there are fires, when there are not fires, what animals and plants are good to eat and all that stuff. But we're also just curious. We look up in the sky and we see the sun and the moon and the stars and we see some of those move and we're very curious about that. And I think we're just naturally curious. So we make, this is my version of how we work. We make up stories and explanations. And there are two things which I think are just true of being human. We make judgments fast because we have to. We're to survive, is that a tiger or is that not a tiger? And we go. Act. We have to act fast on incomplete information. So we judge quickly and we're often wrong, or at least sometimes wrong, which is all I need for this. We're often wrong. So we fool ourselves and we fool other people readily. And so there's lots of stories that get told and some of them result in a concrete benefit and some of them don't. And so you said we're often wrong, but what does it mean to be right? Right, that's an excellent question. To be right, well, since I believe that there is a real world, I believe that to be, you can challenge me on this if you're not a realist. A realist is somebody who believes in this real objective world which is independent of our perception. If I'm a realist, I think that to be right is to come closer. I think, first of all, there's a relative scale. There's not right and wrong. There's right or more right and less right. And you're more right if you come closer to an exact, true description of that real world. Now, can we know that for sure? No. And the scientific method is ultimately what allows us to get a sense of how close we're getting to that real world? No on two counts. First of all, I don't believe there's a scientific method. I was very influenced when I was in graduate school by the writings of Paul Feyerabend who was an important philosopher of science who argued that there isn't a scientific method. There is or there isn't? There is not. There's not. Can you elaborate? I'm sorry if you were going to, but can you elaborate on the, what does it mean for there not to be a scientific method, this notion that I think a lot of people believe in in this day and age? Sure. Paul Feyerabend, he was a student of Popper who taught Karl Popper. And Feyerabend argued both by logic and by historical example that you name anything that should be part of the practice of science, say you should always make sure that your theories agree with all the data that's already been taken. And he'll prove to you that there have to be times when science contradicts, when some scientist contradicts that advice for science to progress overall. So it's not a simple matter. I think that, I think of science as a community. Of people. Of people, and as a community of people bound by certain ethical precepts, percepts, whatever that is. So in that community, a set of ideas they operate under, meaning ethically, of kind of the rules of the game they operate under. Don't lie, report all your results, whether they agree or don't agree with your hypothesis. Check the training of a scientist. Mostly consists of methods of checking, because again, we make lots of mistakes. We're very error prone. But there are tools, both on the mathematics side and the experimental side, to check and double check and triple check. And a scientist goes through a training, and I think this is part of it. You can't just walk off the street and say, yo, I'm a scientist. You have to go through the training, and the training, the test that lets you be done with the training is can you form a convincing case for something that your colleagues will not be able to shout down, because they'll ask, did you check this, and did you check that, and did you check this, and what about a seeming contradiction with this? And you've gotta have answers to all those things or you don't get taken seriously. And when you get to the point where you can produce that kind of defense and argument, then they give you a PhD. And you're kind of licensed. You're still gonna be questioned, and you still may propose or publish mistakes, but the community is gonna have to waste less time fixing your mistakes. Yes, but if you can maybe linger on it a little longer, what's the gap between the thing that that community does and the ideal of the scientific method? The scientific method is you should be able to repeat an experiment. There's a lot of elements to what construes the scientific method, but the final result, the hope of it is that you should be able to say with some confidence that a particular thing is close to the truth. Right, but there's not a simple relationship between experiment and hypothesis or theory. For example, Galileo did this experiment of dropping a ball from the top of a tower, and it falls right at the base of the tower. And Aristotelian would say, wow, of course it falls right to the base of the tower. That shows that the Earth isn't moving while the ball is falling. And Galileo says no weight is a principle of inertia and has an inertia in the direction with the Earth isn't moving, and the tower and the ball and the Earth all move together. When the principle of inertia tells you it hits the bottom, it does look, therefore my principle of inertia is right. And Aristotelian says no, Aristotle's science is right. The Earth is stationary. And so you've gotta get an interconnected bunch of cases and work hard to line up, it took centuries to make the transition from Aristotelian physics to the new physics. It wasn't done till Newton in 1680-something, 1687. So what do you think is the nature of the process that seems to lead to progress, if we at least look at the long arc of science, of all the community of scientists, they seem to do a better job of coming up with ideas that engineers can then take on and build rockets with or build computers with or build cool stuff with? I don't know, a better job than what? Than this previous century. So century by century, we'll talk about string theory and so on and kind of possible, what you might think of as dead ends and so on. We did not do anything with string theory. We'll straighten it out. We'll get on with string theory. But there is, nevertheless, in science, very often at least temporary dead ends. But if you look through centuries, the century before Newton and the century after Newton, it seems like a lot of ideas came closer to the truth that then could be usable by our civilization to build the iPhone, right? To build cool things that improve our quality of life. That's the progress I'm kind of referring to. Let me, can I say that more precisely? Yes. It's a low bar. I think it's important to get the time places right. There was a scientific revolution that partly succeeded between about 1900 or late 1890s and into the 1930s, 1940s and so on. And maybe some, if you stretched it, into the 1970s. And the technology, this was the discovery of relativity and that included a lot of developments of electromagnetism. The confirmation, which wasn't really well confirmed into the 20th century that matter was made of atoms and the whole picture of nuclei with electrons going around. This is early 20th century. And then quantum mechanics was from 1905, took a long time to develop, to the late 1920s and then it was basically in final form. And the basis of this partial revolution, we can come back to why it's only a partial revolution, is the basis of the technologies you mentioned. All of, I mean, electrical technology was being developed slowly with this. And in fact, there's a close relation between the development of electricity and the electrification of cities in the United States and Europe and so forth. And the development of the science. The fundamental physics since the early 1970s doesn't have a story like that so far. There's not a series of triumphs and progresses and there's not any practical application. So just to linger briefly on the early 20th century and the revolutions in science that happened there, what was the method by which the scientific community kept each other in check about when you get something right, when you get something wrong? Is experimental validation ultimately the final test? It's absolutely necessary. And the key things were all validated. The key predictions of quantum mechanics and of the theory of electricity and magnetism. So before we talk about Einstein, your new book before string theory, quantum mechanics, let's take a step back at a higher level question. What is, that you mentioned, what is realism? What is anti-realism? And maybe why do you find realism, as you mentioned, so compelling? Realism is the belief in an external world independent of our existence, our perception, our belief, our knowledge. A realist, as a physicist, is somebody who believes that there should be possible some completely objective description of each and every process at the fundamental level, which describes and explains exactly what happens and why it happens. That kind of implies that that system, in a realist view, is deterministic. Meaning there's no fuzzy magic going on that you can never get to the bottom of. You can get to the bottom of anything and perfectly describe it. Some people would say that I'm not that interested in determinism, but I could live with the fundamental world, which had some chance in it. So do you, you said you could live with it, but do you think God plays dice in our universe? I think it's probably much worse than that. In which direction? I think that theories can change and theories can change without warning. I think the future is open. You mean the fundamental laws of physics can change? Yeah. Okay, we'll get there. I thought we would be able to find some solid ground, but apparently the entirety of it, temporarily so. Okay, so realism is the idea that while the ground is solid, you can describe it. What's the role of the human being, our beautiful, complex human mind, in realism? Do we have a, are we just another set of molecules connected together in a clever way? Or the observer, does the observer, our human mind, consciousness, have a role in this realism view of the physical universe? There's two ways, there's two questions you could be asking. Does our conscious mind, do our perceptions play a role in making things become, in making things real or things becoming? That's question one. Question two is, does this, we can call it a naturalist view of the world, that is based on realism, allow a place to understand the existence of and the nature of perceptions and consciousness in mind? And that's question two. Question two I do think a lot about, and my answer, which is not an answer, is I hope so, but it certainly doesn't yet. Question one, I don't think so. But of course, the answer to question one depends on question two. So I'm not up to question one yet. So question two is the thing that you can kind of struggle with at this time. What about the anti-realists? So what flavor, what are the different camps of anti-realists that you've talked about? I think it would be nice if you can articulate for the people for whom there is not a very concrete real world, or there's divisions, or there's a, it's messier than the realist view of the universe. What are the different camps? What are the different views? I'm not sure I'm a good scholar and can talk about the different camps and analyze it. But some, many of the inventors of quantum physics were not realists, were anti-realists. And there are scholars, they lived in a very perilous time between the two world wars. And there were a lot of trends in culture which were going that way. But in any case, they said things like the purpose of science is not to give an objective, realist description of nature as it would be in our absence. This might be saying Niels Bohr. The purpose of science is as an extension of our conversations with each other to describe our interactions with nature. And we're free to invent and use terms like particle, or wave, or causality, or time, or space if they're useful to us and they carry some intuitive implication. But we shouldn't believe that they actually have to do with what nature would be like in our absence, which we have nothing to say about. Do you find any aspect of that, because you kind of said that we human beings tell stories. Do you find aspects of that kind of anti-realist view of Niels Bohr compelling? That we're fundamentally are storytellers and then we create tools of space and time and causality and whatever this fun quantum mechanics stuff is to help us tell the story of our world. Sure, I just would like to believe that there's an aspiration for the other thing. The other thing being what? The realist point of view. Do you hope that the stories will eventually lead us to discovering the real world as it is? Yeah. Is perfection possible, by the way? No. You mean will we ever get there and know that we're there? Yeah, exactly. That's for people 5,000 years in the future. We're certainly nowhere near there yet. Do you think reality that exists outside of our mind, do you think there's a limit to our cognitive abilities as, again, descendants of apes who are just biological systems? Is there a limit to our mind's capability to actually understand reality? Sort of there comes a point, even with the help of the tools of physics, that we just cannot grasp some fundamental aspects of that reality. Again, I think that's a question for 5,000 years in the future. I think there is a universality. Here, I don't agree with David Deutsch about everything, but I admire the way he put things in his last book. And he talked about the role of explanation. And he talked about the universality of certain languages or the universality of mathematics or of computing and so forth. And he believed that universality, which is something real, which somehow comes out of the fact that a symbolic system or a mathematical system can refer to itself and can, I forget what that's called, can reference back to itself and build, in which he argued for a universality of possibility for our understanding, whatever is out there. But I admire that argument. But it seems to me we're doing okay so far, but we'll have to see. Whether there is a limit or not. For now, we've got plenty to play with. Yeah.

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Moore's Law is Not Dead (Jim Keller) | AI Podcast Clips

For over 50 years now, Moore's Law has served for me and millions of others as an inspiring beacon of what kind of amazing future brilliant engineers can build. I'm just making your kids laugh all of today. That's great. So, first, in your eyes, what is Moore's Law, if you could define for people who don't know? Well, the simple statement was, from Gordon Moore, was double the number of transistors every two years. Something like that. And then my operational model is we increase the performance of computers by 2x every two or three years. And it's wiggled around substantially over time. And also, in how we deliver performance has changed. But the foundational idea was 2x the transistors every two years. The current cadence is something like, they call it a shrink factor, like 0.6 every two years, which is not 0.5. But that's referring strictly, again, to the original definition of just... Yeah, of transistor count. A shrink factor, just getting them smaller and smaller and smaller. Because for a constant chip area, if you make the transistors smaller by 0.6, then you get one over 0.6 more transistors. So, can you linger on it a little longer? What's the broader... What do you think should be the broader definition of Moore's Law? When you mentioned how you think of performance, just broadly, what's a good way to think about Moore's Law? Well, first of all, I've been aware of Moore's Law for 30 years. In which sense? Well, I've been designing computers for 40. You're just watching it before your eyes, kind of thing. Well, and somewhere where I became aware of it, I was also informed that Moore's Law was going to die in 10 to 15 years. And I thought that was true at first, but then after 10 years, it was going to die in 10 to 15 years. And then at one point, it was going to die in five years. And then it went back up to 10 years, and at some point, I decided not to worry about that particular prognostication for the rest of my life. Which is fun. And then I joined Intel, and everybody said Moore's Law is dead. And I thought, that's sad, because it's the Moore's Law company. And it's not dead, and it's always been going to die. And humans like these apocryphal kind of statements like, we'll run out of food, or we'll run out of air, or we'll run out of room, or we'll run out of something. Right, but it's still incredible that it's lived for as long as it has. And yes, there's many people who believe now that Moore's Law is dead. You know, they can join the last 50 years of people who had the same idea. Yeah, there's a long tradition. But why do you think, if you can try to understand it, why do you think it's not dead currently? Well, first, let's just think, people think Moore's Law is one thing, transistors get smaller. But actually, under the sheet, there's literally thousands of innovations. And almost all those innovations have their own diminishing return curves. So if you graph it, it looks like a cascade of diminishing return curves. I don't know what to call that. But the result is an exponential curve. At least it has been. And we keep inventing new things. So if you're an expert in one of the things on a diminishing return curve, right, and you can see its plateau, you will probably tell people, well, this is done. Meanwhile, some other pile of people are doing something different. So that's just normal. So then there's the observation of how small could a switching device be? So a modern transistor is something like a thousand by a thousand by a thousand atoms, right? And you get quantum effects down around two to ten atoms. So you can imagine a transistor as small as ten by ten by ten. So that's a million times smaller. And then the quantum computational people are working away at how to use quantum effects. So a thousand by a thousand by a thousand atoms. That's a really clean way of putting it. Well, a fan, like a modern transistor, if you look at the fan, it's like 120 atoms wide. But we can make that thinner. And then there's a gate wrapped around it. And then there's spacing. There's a whole bunch of geometry. And a competent transistor designer could count both atoms in every single direction. Like there's techniques now to already put down atoms in a single atomic layer. And you can place atoms if you want to. It's just, you know, from a manufacturing process, if placing an atom takes ten minutes and you need to put ten to the 23rd atoms together to make a computer, it would take a long time. So the methods are both shrinking things and then coming up with effective ways to control what's happening. Manufacture stably and cheaply. Yeah. So the innovation stack is pretty broad. There's equipment, there's optics, there's chemistry, there's physics, there's material science, there's metallurgy. There's lots of ideas about when you put different materials together, how do they interact? Are they stable? Are they stable over temperature? You know, like are they repeatable? You know, there's like literally thousands of technologies involved. But just for the shrinking, you don't think we're quite yet close to the fundamental limits of physics. I did a talk on Moore's Law and I asked for a road map to a path of 100. And after two weeks, they said we only got to 50. 100 what, sorry? 100x shrink. 100x shrink? We only got to 50? And I said, why don't you give it another two weeks? Well, here's the thing about Moore's Law, right? So I believe that the next 10 or 20 years of shrinking is going to happen, right? Now, as a computer designer, you have two stances. You think it's going to shrink, in which case you're designing and thinking about architecture in a way that you'll use more transistors. Or conversely, not be swamped by the complexity of all the transistors you get. Right? You have to have a strategy. So you're open to the possibility and waiting for the possibility of a whole new army of transistors ready to work. I'm expecting more transistors every two or three years by a number large enough that how you think about design, how you think about architecture has to change. Like imagine you build buildings out of bricks, and every year the bricks are half the size, or every two years. Well, if you kept building bricks the same way, so many bricks per person per day, the amount of time to build a building would go up exponentially. Right. Right. But if you said, I know that's coming, so now I'm going to design equipment that moves bricks faster, uses them better, because maybe you're getting something out of the smaller bricks, more strength, thinner walls, less material efficiency out of that. So once you have a roadmap with what's going to happen, transistors, we're going to get more of them, then you design all this collateral around it to take advantage of it and also to cope with it. That's the thing people don't understand. It's like if I didn't believe in Moore's Law and then Moore's Law transistors showed up, my design teams were all drowned. So what's the hardest part of this influx of new transistors? I mean, even if you just look historically throughout your career, what's the thing, what fundamentally changes when you add more transistors in the task of designing an architecture? Well, there's two constants, right? One is people don't get smarter. By the way, there's some science showing that we do get smarter because of nutrition, whatever. Sorry to bring that up. Yeah, I'm familiar with it. Nobody understands it. Nobody knows if it's still going on. Or whether it's real or not. I sort of... But not exponentially. I would believe for the most part people aren't getting much smarter. The evidence doesn't support it. That's right. And then teams can't grow that much. Right. So human beings, we're really good in teams of 10, up to teams of 100, they can know each other. And beyond that, you have to have organizational boundaries. So you're kind of... Those are pretty hard constraints. So then you have to divide and conquer. As the designs get bigger, you have to divide it into pieces. The power of abstraction layers is really high. We used to build computers out of transistors. Now we have a team that turns transistors into logic cells, and another team that turns them into functional units, and another one that turns them into computers. So we have abstraction layers in there. And you have to think about when do you shift gears on that. We also use faster computers to build faster computers. So some algorithms run twice as fast on new computers. But a lot of algorithms are N-squared. So a computer with twice as many transistors in it might take four times as long to run. So you have to refactor the software. Simply using faster computers to build bigger computers doesn't work. So you have to think about all these things. So in terms of computing performance and the exciting possibility that more powerful computers bring, is shrinking the thing we've just been talking about, for you, one of the biggest exciting possibilities of advancement in performance? Or is there other directions that you're interested in, like in the direction of sort of enforcing given parallelism, or like doing massive parallelism in terms of many, many CPUs, stacking CPUs on top of each other, that kind of parallelism, or any kind of parallelism? Well, think about it a different way. So old computers, slow computers, you said A equal B plus C times D. Pretty simple, right? And then we made faster computers with vector units, and you can do proper equations and matrices. And then modern like AI computations, or like convolutional neural networks, where you convolve one large data set against another. And so there's sort of this hierarchy of mathematics, from simple equation to linear equations to matrix equations, to deeper kind of computation. And the data sets are getting so big that people are thinking of data as a topology problem. Data is organized in some immense shape. And then the computation, which sort of wants to be get data from immense shape and do some computation on it. So what computers have allowed people to do is have algorithms go much, much further. So that paper you referenced, the Sutton paper, they talked about, you know, like when AI started, it was apply rule sets to something. That's a very simple computational situation. And then when they did first chess thing, they solved deep searches. So have a huge database of moves and results, deep search, but it's still just a search. Right? Now we take large numbers of images, and we use it to train these weight sets that we convolve across. It's a completely different kind of phenomena. We call that AI. Now they're doing the next generation, and if you look at it, they're going up this mathematical graph. Right? And then computations, both computation and data sets support going up that graph. Yeah, the kind of computation that might, I mean, I would argue that all of it is still a search. Right? Just like you said, a topology problem of data sets, you're searching the data sets for valuable data, and also the actual optimization of neural networks is a kind of search for the... I don't know. If you had looked at the inner layers of finding a cat, it's not a search. It's a set of endless projections. So, you know, a projection, here's a shadow of this phone. Yeah. Right? And then you can have a shadow of that on something, a shadow on that on something. If you look in the layers, you'll see this layer actually describes pointy ears and round eyedness and fuzziness. But the computation to tease out the attributes is not search. Right. I mean, well... Like the inference part might be search, but the training is not search. Okay. And then in deep networks, they look at layers and they don't even know it's represented. And yet, if you take the layers out, it doesn't work. Okay. So, I don't think it's search. All right. Well... But you have to talk to a mathematician about what that actually is. We could disagree, but it's just semantics, I think. It's not... But it's certainly not... I would say it's absolutely not semantics, but... Okay. All right. Well, if you want to go there. So, optimization to me is search. And we're trying to optimize the ability of a neural network to detect cat ears. And the difference between chess and the space, the incredibly multi-dimensional, 100,000 dimensional space that neural networks are trying to optimize over, is nothing like the chessboard database. So, it's a totally different kind of thing. Okay. In that sense, you can say that it loses the meaning. I can see how you might say. The funny thing is, it's the difference between given search space and found search space. Right. Exactly. Yeah, maybe that's a different way to describe it. That's a beautiful way to put it. Okay. But you're saying, what's your sense in terms of the basic mathematical operations and the architectures, hardware that enables those operations? Do you see the CPUs of today still being a really core part of executing those mathematical operations? Yes. Well, the operations continue to be add, subtract, load, store, compare, and branch. It's remarkable. So, it's interesting that the building blocks of computers are transistors, and under that, atoms. So, you've got atoms, transistors, logic gates, computers, functional units of computers. The building blocks of mathematics at some level are things like adds and subtracts and multiplies. But the space mathematics can describe is, I think, essentially infinite. But the computers that run the algorithms are still doing the same things. Now, a given algorithm might say, I need sparse data, or I need 32-bit data, or I need a convolution operation that naturally takes 8-bit data, multiplies it, and sums it up a certain way. So, the data types in TensorFlow imply an optimization set. But when you go right down and look at the computers, it's and and or gates, do and adds, and multiplies. That hasn't changed much. Now, the quantum researchers think they're going to change that radically, and then there's people who think about analog computing, because you look in the brain, and it seems to be more analog-ish. That maybe there's a way to do that more efficiently. But we have a million X on computation, and I don't know the relationship between computational, let's say, intensity, and ability to hit mathematical abstractions. I don't know anybody who's described that. But just like you saw in AI, you went from rule sets to simple search to complex search to, say, found search. Those are orders of magnitude more computation to do. And as we get the next two orders of magnitude, like a friend, Roger Godori, said, every order of magnitude changes the computation. Fundamentally changes what the computation is doing. Oh, you know the expression, the difference in quantity is the difference in kind. The difference between ant and anthill, right? Between neuron and brain. There's this indefinable place where the quantity changed the quality. And we've seen that happen in mathematics multiple times, and my guess is it's going to keep happening. So your sense is, yeah, if you focus head down and shrinking the transistor... Well, it's not just head down. We're aware of the software stacks that are running the computational loads, and we're kind of pondering what do you do with a petabyte of memory that wants to be accessed in a sparse way and have the kind of calculations AI programmers want. So there's a dialogue and interaction, but when you go in the computer chip, you find adders and subtractors and multipliers. So if you zoom out then with, as you mentioned, Rich Sutton, the idea that most of the development in the last many decades in AI research came from just leveraging computation and just simple algorithms waiting for the computation to improve. Well, software guys have a thing that they call the problem of early optimization. So you write a big software stack, and if you start optimizing the first thing you write, the odds of that being the performance limiter is low. But when you get the whole thing working, can you make it 2x faster by optimizing the right things? Sure. While you're optimizing that, could you have written a new software stack, which would have been a better choice? Maybe. Now you have creative tension. But the whole time as you're doing the writing, that's the software we're talking about. The hardware underneath gets faster and faster. Well, this goes back to the Moore's Law. If Moore's Law is going to continue, then your AI research should expect that to show up. And then you make a slightly different set of choices. We've hit the wall. Nothing's going to happen. And from here, it's just us rewriting algorithms. That seems like a failed strategy for the last 30 years of Moore's Law's death. So can you just linger on it? I think you've answered it, but I'll just ask the same dumb question over and over. Why do you think Moore's Law is not going to die? Which is the most promising, exciting possibility of why it won't die in the next 5-10 years? Is it the continued shrinking of the transistor, or is it another S-curve that steps in? The shrinking of the transistor is literally thousands of innovations. Right. So there's stacks of S-curves in there. There's a whole bunch of S-curves just kind of running their course and being reinvented and new things. The semiconductor fabricators and technologists have all announced what's called nanowires. So they took a fin which had a gate around it and turned that into little wires, so you have better control of that, and they're smaller. And then from there, there are some obvious steps about how to shrink that. So the metallurgy around wire stacks and stuff has very obvious abilities to shrink. And there's a whole combination of things there to do. Your sense is that we're going to get a lot if this innovation from just that shrinking. Yeah, like a factor of 100 is a lot. Yeah, I would say. That's incredible. It's only 10 or 15 years. Now, you're smart and you might know, but to me it's totally unpredictable of what that 100x would bring in terms of the nature of the computation that people would be doing. Yeah, are you familiar with Bell's Law? So for a long time, it was mainframes, minis, workstation, PC, mobile. Moore's Law drove faster, smaller computers. And then when we were thinking about Moore's Law, Rajagirdari said every 10x generates a new computation. So scalar, vector, matrix, topological computation. And if you go look at the industry trends, there was mainframes and minicomputers and PCs. And then the internet took off and then we got mobile devices. And now we're building 5G wireless with one millisecond latency. And people are starting to think about the smart world where everything knows you, recognizes you. Like the transformations are going to be unpredictable. How does it make you feel that you're one of the key architects of this kind of future? So we're not talking about the architects of the high level people who build Angry Bird apps and Snapchat. Angry Bird apps, who knows? Maybe that's the whole point of the universe. I'm going to take a stand at that and the attention distracting nature of mobile phones. I'll take a stand. But anyway, in terms of the side effects of smartphones or the attention distraction, which part? Well, who knows where this is all leading? It's changing so fast. My parents used to yell at my sisters for hiding in the closet with a wired phone with a dial on it. Stop talking to your friends all day. My wife yells at my kids for talking to their friends all day on text. It looks the same to me. It's always echoes of the same thing. But you are one of the key people architecting the hardware of this future. How does that make you feel? Do you feel responsible? Do you feel excited? So we're in a social context. So there's billions of people on this planet. There are literally millions of people working on technology. I feel lucky to be doing what I do and getting paid for it. There's an interest in it. But there are so many things going on in parallel. The actions are so unpredictable. If I wasn't here, somebody else would do it. The vectors of all these different things are happening all the time. There's, I'm sure, some philosopher or meta-philosopher wondering about how we transform our world. So you can't deny the fact that these tools are changing our world. That's right. Do you think it's changing for the better? I read this thing recently that said the two disciplines with the highest GRE scores in college are physics and philosophy. And they're both sort of trying to answer the question, why is there anything? And the philosophers are on the theological side and the physicists are obviously on the material side. And there's a hundred billion galaxies with a hundred billion stars. It seems, well, repetitive at best. So, you know, there's on our way to 10 billion people. I mean, it's hard to say what it's all for, if that's what you're asking. Yeah, I guess I am. Things do tend to significantly increase in complexity. And I'm curious about how computation, like our world, our physical world inherently generates mathematics. It's kind of obvious, right? So we have XYZ coordinates. You take a sphere, you make it bigger, you get a surface that grows by R squared. Like it generally generates mathematics. And the mathematicians and the physicists have been having a lot of fun talking to each other for years. And computation has been, let's say, relatively pedestrian. Like computation in terms of mathematics has been doing binary algebra, and all those guys have been gallivanting through the other realms of possibility. Now, recently, the computation lets you do mathematical computations that are sophisticated enough that nobody understands how the answers came out. Machine learning. Machine learning. It used to be you get data set, you guess at a function. Computation is considered physics if it's predictive of new functions, new data sets. Modern, you can take a large data set with no intuition about what it is and use machine learning to find a pattern that has no function. And it can arrive at results that I don't know if they're completely mathematically describable. So computation has kind of done something interesting compared to A equal B plus C.

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Neural networks learning spirals

Let's use TensorFlow Playground to see what kind of neural network can learn to partition the space for the binary classification problem between the blue and the orange dots. First is an easier binary classification problem with a circle and a ring distribution around it. Second is a more difficult binary classification problem of two dueling spirals. This little visualization tool on playground.tensorflow.org is really useful for getting an intuition about how the size of the network and the various hyperparameters affect what kind of representations that network is able to learn. The input to the network is the position of the point in the 2D plane and the output of the network is the classification of whether it's an orange or a blue dot. We'll hold all the hyperparameters constant for this little experiment and just vary the number of neurons and hidden layers. The hyperparameters are batch size of 1, learning rate of 0.03, the activation function is ReLU, and L1 regularization with a rate of 0.001. So let's start with one hidden layer and one neuron and gradually increase the size of the network to see what kind of representation it's able to learn. Keep your eye on the right side of the screen that shows the test loss and the training loss and the plot that shows sample points from the two distributions. And then the shading in the background of the plot shows the partitioning function that the neural network is learning. So a successful function is able to separate the orange and the blue dots. One hidden layer with one neuron. Two neurons. Three neurons. Four neurons. Eight neurons. Now let's take a look at the trickier spiral dataset, keeping most of the hyperparameters the same but decreasing the learning rate to 0.01 and adding to the input to the neural network extra features than just the coordinate of the point but also the squares of the coordinates, the multiplication, and the sign of each coordinate. Let's start with one hidden layer, one neuron. Two neurons. Four neurons. Six neurons. Eight neurons. Two hidden layers, two neurons in the second layer. Four neurons. Six neurons. Eight neurons. There you go. That's a basic illustration with the playground.tensorflow.org that I recommend you try that shows the connection between neural network architecture, dataset characteristics, and different training hyperparameters. It's important to note that the initialization of the neural network has a big impact in many of the cases, but the purpose of this video is not to show the minimal neural network architecture that's able to represent the spiral dataset but rather to provide a visual intuition about which kind of networks are able to learn which kinds of datasets. There you go. I hope you enjoyed these quick little videos, whether they make you think, give you a new kind of insights, or just fun and inspiring. See you next time, and remember, try to challenge yourself and learn something new every day.

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2+2=5 in Java

This video is about how we can hack Java by using reflection of its own source code to make this 2 plus 2 statement, output 5. Just as George Orwell, one of my favorite writers, warned us about in 1984, about propaganda machines that sublimate the nature of truth. This video is not about politics, philosophy, nor is it about the apparent, as I have just learned, woke Twitter madness around 2 plus 2 equals 5. Though perhaps if we're living in the simulation and it's written in Java, this might be a way to make the simulation just a bit more dystopian. So here's what the full source code looks like and it uses Java's ability to do reflection, which is the ability of a programming language to inspect itself. So if we look at the code, it actually dives into the implementation of the integer class, pulls out the integer cache class from that implementation, makes it accessible and writable, pulls it into an array of integer object of size 256, and modifies that array. Now what does this array contain? So interestingly, if we look at the integer cache class inside the integer object implementation in Java, it defines a hard-coded low of negative 128 and a high that's passed in as a parameter, that's 127 as a default. And what that does is create a cache of integer objects from negative 128 to 127 and then reuses this cache every time an integer object with a value in this range is used. Now this is exactly the cache with reflection that we pull out and modify. It so happens that the 132nd element in the cache is where the 4 resides and so by way of obfuscation, it takes the 133rd element, which has the number 5 in it and it sizes it to 132nd, but you can just assign value 5 here. And then the result and your else in the code, if you use the integer objects and the number 4 comes up, it will instead output the number 5. There you go, 2 plus 2 equals 5. Check out the link in the description that points to the Stack Exchange Code Golf has a bunch of interesting discussions around this, including the possibility of taking the entire 256 element array and shuffling it, thereby not only making 2 plus 2 equals 5, but messing with the entirety of low value arithmetic in Java. So there you go, that's how you hack the simulation. Let me quickly thank the sponsors that somehow amazingly support the podcast and the videos I make. This time it's Asleep Mattress. Click the link to get a discount in the description. And by the way, I have a conversation with James Gosling, the creator of Java, coming up on the podcast, so check that out. And remember, try to learn something new every day.

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Eric Weinstein's Harvard Story - The System Breaks Down in Novel Situations | AI Podcast Clips

Without naming names, can you tell the story of your struggle during your time at Harvard? Maybe in a way that tells the bigger story of the struggle of young, bright minds that are trying to come up with big, bold ideas within the institutions that we're talking about. You can start. I mean, in part, it starts with coffee with a couple of Croatians in the math department at MIT. And we used to talk about music and dance and math and physics and love and all this kind of stuff, as Eastern Europeans love to, and I ate it up. And my friend, Gordana, who was an instructor in the MIT math department when I was a graduate student at Harvard, said to me, and I'm probably going to do a bad version of her accent. Here we go. Eric, will I see you tomorrow at the secret seminar? And I said, what secret seminar? Eric, don't joke. I said, I'm not used to this style of humor, Gordana. The secret seminar that your advisor is running. I said, what are you talking about? Ha ha ha ha. You know, your advisor is running a secret seminar on this aspect. I think it was like the Chern-Simons invariant. Not sure what the topic was again, but she gave me the room number and the time and she was like not cracking a smile. I've never known her to make this kind of a joke. And I thought this was crazy. And I was trying to have an advisor. I didn't want an advisor, but people said you have to have one, so I took one. And I went to this room at like 15 minutes early and there was not a soul inside it. It was outside of the math department. And it was still in the same building, the science center at Harvard. And I sat there and I let five minutes go by, I let seven minutes go by, 10 minutes go by, there's nobody. I thought, okay, so this was all an elaborate joke. And then like three minutes to the hour, this graduate student walks in and like sees me and does a double take. And then I start to see the professors in geometry and topology start to file in. And everybody's like very disconcerted that I'm in this room. And finally the person who was supposed to be my advisor walks in to the seminar and sees me and goes white as a ghost. And I realized that the secret seminar is true, that the department is conducting a secret seminar on the exact topic that I'm interested in, not telling me about it. And that these are the reindeer games that the Rudolphs of the department are not invited to. And so then I realized, okay, I did not understand it. There's a parallel department. And that became the beginning of an incredible odyssey in which I came to understand that the game that I had been sold about publication, about blind refereeing, about openness and scientific transmission of information was all a lie. I came to understand that at the very top, there's a second system that's about closed meetings and private communications and agreements about citation and publication that the rest of us don't understand. And that in large measure, that is the thing that I won't submit to. And so when you ask me questions like, well, why wouldn't you feel good about talking to your critics or why wouldn't you fit? The answer is, oh, you don't know. Like if you stay in a nice hotel, you don't realize that there is an entire second structure inside of that hotel where like there's usually a worker's cafe in a resort complex that isn't available to the people who are staying in the hotel. And then there are private hallways inside the same hotel that are parallel structures. So that's what I found, which was in essence, just the way you can stay hotels your whole life and not realize that inside of every hotel is a second structure that you're not supposed to see as the guest. There is a second structure inside of academics that behaves totally differently with respect to how people get dinged, how people get their grants taken away, how this person comes to have that thing named after them. And by pretending that we're not running a parallel structure, I have no patience for that anymore. So I got a chance to see how the game, how hardball is really played at Harvard. And I'm now eager to play hardball back with the same people who played hardball with me. Let me ask two questions on this. So one, do you think it's possible, so I call those people assholes, that's the technical term. Do you think it's possible that that's just not the entire system, but a part of the system? You can navigate, you can swim in the waters and find the groups of people who do aspire to open this. The guy who rescued my PhD was one of the people who filed in to the secret seminar. Right, but are there people who are outside of this? Is he an asshole? Well, yes, I was a bad- No, but I'm trying to make this point, which is, this isn't my failure to correctly map these people. It's yours. You have a simplification that isn't going to work. I think, okay, asshole is the wrong term. I would say lacking of character. What would you have had these people do? Why did they do this? Why have a secret seminar? I don't understand the exact dynamics of a secret seminar, but I think the right thing to do is to see individuals like you. There might be a reason to have a secret seminar, but they should detect that an individual like you, a brilliant mind, who's thinking about certain ideas, could be damaged by this. I don't think that they see it that way. The idea is we're going to sneak food to the children we want to survive. Yeah, so that's highly problematic, and there should be people within that room. I'm trying to say, this is the thing, the ball is thrown but it won't be caught. The problem is they know that most of their children won't survive, and they can't say that. I see. Sorry to interrupt. You mean that the fact that the whole system is underfunded, that they naturally have to pick favorites. They live in a world which reached steady state at some level, let's say, in the early 70s. In that world, before that time, you have a professor like Norman Steenrod, and you'd have 20 children that is graduate students, and all of them would go on to be professors, and all of them would want to have 20 children. You start taking higher and higher powers of 20, and you see that the system could not, it's not just about money, the system couldn't survive. The way it's supposed to work now is that we should shut down the vast majority of PhD programs, and we should let the small number of truly top places populate mostly teaching and research departments that aren't PhD producing. We don't want to do that because we use PhD students as a labor force. The whole thing has to do with growth, resources, dishonesty. In that world, you see all of these adaptations to a ruthless world where the key question is where are we going to bury this huge number of bodies of people who don't work out? My problem was I wasn't interested in dying. You clearly highlight that there's aspects of the system that are broken, but as an individual, is your role to exit the system or just acknowledge that it's a game and win it? My role is to survive and thrive in the public eye. In other words, when you have an escapee of the system. Like yourself. Such as. And that person says, you know, I wasn't exactly finished. Let me show you a bunch of stuff. Let me show you that the theory of telomeres never got reported properly. Let me show you that all of marginal economics is supposed to be redone with a different version of the differential calculus. Let me show you that you didn't understand the self dual Yang-Mills equations correctly in topology and physics because they're in fact much more broadly found and it's only the mutations that happen in special dimensions. There are lots of things to say, but this particular group of people, like if you just take where are all the Gen X and millennial university presidents. Right. Okay. They're all, they're all in a holding pattern. Now where, why in this story, you know, was it a telomeres, was it an older professor and a younger graduate student? It's this issue of what would be called interference competition. So for example, orcas try to drown minky whales by covering their blow holes so that they suffocate because the needed resource is air. Okay. Well, what are the universities do? They try to make sure that you can't be viable, that you need them, that you need their grants. You need to be zinged with overhead charges or fringe rates or all of the games that the locals love to play. Well, my point is, okay, what's the cost of this? How many people died as a result of these interference competition games? You know, when you take somebody like Douglas Prasher who did green fluorescent protein and he drives a shuttle bus, right? Cause his grant runs out and he has to give away all of his research and all of that research gets a Nobel prize and he gets to drive a shuttle bus for $35,000 a year. What do you mean by died? Do you mean their career, their dreams? Yeah, the whole, as an academic, Doug Prasher was dead for a long period of time. Okay. So as a person who's escaped the system, can't you at this, cause you also have in your mind a powerful theory that may turn out to be useful, maybe not. Let's hope. Can't you also play the game enough like with the children, so like publish and, but also- If you told me that this would work, really what I want to do, you see, is I would love to revolutionize a field with an H index of zero. Like we have these proxies that count how many papers you've written, how cited are the papers you've written. All this is nonsense. That's interesting, sorry, what do you mean by a field with an H index of zero? So a totally new field. H index counts somehow how many papers have you gotten that get so many citations. Let's say H index undefined. Like for example, I don't have an advisor for my PhD, but I have to have an advisor as far as something called the math genealogy project that tracks who advised who, who advised whom down the line. So I am my own advisor, which sets up a loop, right? How many students do I have? An infinite number. Or descendants. They don't want to have that story. So I have to be, I have to have formal advisor, Raoul Bott. And my Wikipedia entry, for example, says that I was advised by Raoul Bott, which is not true. So you get fit into a system that says, well, we have to know what your H index is. We have to know, you know, where are you a professor if you want to apply for a grant? It makes all of these assumptions. What I'm trying to do is to impart, to show all of this is nonsense. This is proxy BS that came up in the institutional setting. And right now it's important for those of us who are still vital like Elon, it would be great to have Elon as a professor of physics and engineering. Yeah. Right? It seems ridiculous to say, but. Just as a shot in the arm. You know, like, it'd be great to have Elon at Caltech. Even one day a week. One day a month. Okay, well, why can't we be in there? It's the same reason. Well, why can't you be on The View? Why can't you be on Bill Maher? We need to know what you're going to do before we take you on the show. Well, I don't want to tell you what I'm going to do. Do you think you need to be able to dance the dance a little bit? I can dance the dance fine. To be on The View. Oh, come on. So you can't. I can do that fine. Here's where it's, the place that it goes south is, there's like a set of questions that get you into this more adversarial stuff. And you've in fact asked some of those more adversarial questions, this setting. And they're not things that are necessarily aggressive, but they're things that are making assumptions. Right. Right? So when you make, I have a question, it's like, you know, Lex, are you avoiding your critics? You know, it's just like, okay, well, why did you frame that that way? Or the next question would be, it's like, do you think that you should have a special exemption and that you should have the right to break rules and everyone else should have to follow them? Like that question I find innervating. It doesn't really come out of anything meaningful. It's just like, we feel we're supposed to ask that of the other person to show that we're not captured by their madness. That's not the real question you want to ask me. If you want to get really excited about this, you want to ask, do you think this thing is right? Yeah, weirdly I do. Do you think that it's going to be immediately seen to be right? I don't. I think it's going to, it's going to have an interesting fight and it's going to have an interesting evolution. And well, what do you hope to do with it in non-physical terms? I gosh, I hope it revolutionizes our relationship of well with people outside of the institutional framework and it re-inflicts us into the institutional framework where we can do the most good to bring the institutions back to health. You know, it's like, these are positive uplifting questions. And if you had Frank Wilczek, you wouldn't say, Frank, let's be honest, you have done very little with your life after the original huge show that you used to break under the physics scene. Like we weirdly ask people different questions based upon how they sit down. Yeah, that's very strange. Right. But you have to understand that. So here's the thing. I get these days a large number of emails from people with the equivalent of a theory of everything for AGI. And I use my own radar, BS radar to detect unfairly perhaps whether they're full of shit or not. Right. I love where you're going with this, by the way. My concern I often think about is there's elements of brilliance in what people write to me. And I'm trying to right now, as you made it clear, the kind of judgments and assumptions we make, how am I supposed to deal with you who are an outsider of the system and think about what you're doing? Because my radar is saying you're not full of shit. But I'm also not completely outside of the system. That's right. You've danced beautifully. You've actually got all the credibility that you're supposed to get, all the nice little stamps of approval. Not all, but a large enough amount. I mean, it's hard to put into words exactly why you sound, whether your theory turns out to be good or not, you sound like a special human being. I appreciate that. In a good way. But what am I supposed to do with that flood of emails from AGI folks? Why do I sound different? I don't know. And I would like to systemize that, I don't know. Look, when you're talking to people, you very quickly can surmise. Am I claiming to be a physicist? No, I say it every turn, I'm not a physicist. When you say something about bundles, you say, well, can you explain it differently? I'm pushing around on this area, that lever over there. I'm trying to find something that we can play with and engage. And another thing is that I'll say something at scale. So if I was saying completely wrong things about bundles on the Joe Rogan program, you don't think that we wouldn't hear a crushing chorus? Yes. Absolutely. And the same thing with geometric unity. So I put up this video from this Oxford lecture. I understand that it's not a standard lecture. But you haven't heard the most brilliant people in the field say, well, this is obviously nonsense. They don't know what to make of it. And they're going to hide behind, well, he hasn't said enough details. Where's the paper? Where's the paper? I've seen the criticism. I've gotten the same kind of criticism. I've published a few things, especially stuff related to Tesla. We did studies on Tesla vehicles. And the kind of criticism I've gotten showed that they're completely... Oh, right. Like the guy who had Elon Musk on his program twice is going to give us an accurate assessment. Yeah, exactly. Exactly. It's just very low level. Without actually ever addressing the content. You know, Lex, I think that in part you're trying to solve a puzzle that isn't really your puzzle. I think you know that I'm sincere. You don't know whether the theory is going to work or not. And you know that it's not coming out of somebody who's coming out of left field. The story makes sense. There's enough that's new and creative and different in other aspects where you can check me. That your real concern is, are you really telling me that when you start breaking the rules, you see the system for what it is and it's become really vicious and aggressive? And the answer is yes. And I had to break the rules in part because of learning issues. Because I came into this field with a totally different set of attributes. My profile just doesn't look like anybody else's remotely. But as a result, what that did is it showed me, is the system true to its own ideals? Or does it just follow these weird procedures? And then when you take it off the rails, it behaves terribly. And that's really what my story I think does, is it just says, well, he completely takes the system into new territory where it's not expecting to have to deal with somebody with these confusing sets of attributes. And I think what he's telling us is he believes it behaves terribly. Now if you take somebody with perfect standardized tests and a winner of math competitions and you put them in a PhD program, they're probably gonna be okay. I'm not saying that the system breaks down for everybody under all circumstances. I'm saying when you present the system with a novel situation, at the moment it will almost certainly break down with probability approaching 100%. But to me the painful and the tragic thing is it, sorry to bring out my motherly instinct, but it feels like it's too much, it could be too much of a burden to exist outside the system. Maybe, but- Psychologically. First of all, I've got a podcast that I kind of like. I've got amazing friends. I have a life which has more interesting people passing through it than I know what to do with. And they haven't managed to kill me off yet. So so far so good.

https://youtu.be/fgGZMRJ15oY

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Vsauce: Elon Musk and the Responsibility of a Large Following | AI Podcast Clip with Michael Stevens

So you're a curious lover of science. What do you think of the efforts that Elon Musk is doing with space exploration, with electric vehicles, with autopilot sort of getting into the space of autonomous vehicles, with boring under L.A., and Neuralink trying to communicate brain-machine interfaces, communicate between machines and human brains? Well, it's really inspiring. I mean, look at the fandom that he's amassed. It's not common for someone like that to have such a following. And so it's- Engineering nerd. Yeah. So it's really exciting, but I also think that a lot of responsibility comes with that kind of power. So if I met him, I would love to hear how he feels about the responsibility he has when there are people who are such a fan of your ideas and your dreams and share them so closely with you. You have a lot of power. And he didn't always have that. He wasn't born as Elon Musk. Well, he was, but- Well, he was named that later. But the point is that I want to know the psychology of becoming a figure like him. Well, I don't even know how to phrase the question right, but it's a question about what do you do when you're following, your fans become so large that it's almost bigger than you? And how do you responsibly manage that? And maybe it doesn't worry him at all, and that's fine too, but I'd be really curious. And I think there are a lot of people that go through this when they realize, whoa, there are a lot of eyes on me. There are a lot of people who really take what I say very earnestly and take it to heart and will defend me. And that can be dangerous and you have to be responsible with it. Both in terms of impact on society and psychologically for the individual, just the burden psychologically on Elon? Yeah, yeah. How does he think about that part of his persona? Well, let me throw that right back at you, because in some ways you're just a funny guy that's gotten a humongous following, a funny guy with a curiosity. You've got a huge following. How do you psychologically deal with the responsibility? In many ways, you have a reach in many ways bigger than Elon Musk. What is the burden that you feel in educating, being one of the biggest educators in the world where everybody's listening to you? And actually, most of the world that uses YouTube for educational material trust you as a source of good, strong scientific thinking. It's a burden and I try to approach it with a lot of humility and sharing. I'm not out there doing a lot of scientific experiments. I am sharing the work of real scientists and I'm celebrating their work and the way that they think and the power of curiosity. But I want to make it clear at all times that, look, we don't know all the answers and I don't think we're ever going to reach a point where we're like, wow, and there you go. That's the universe. It's this equation, you plug in some conditions or whatever, and you do the math and you know what's going to happen tomorrow. I don't think we're ever going to reach that point. But I think that there is a tendency to sometimes believe in science and become elitist and become, I don't know, hard, when in reality it should humble you and make you feel smaller. I think there's something very beautiful about feeling very, very small and very weak and to feel that you need other people. So I try to keep that in mind and say, look, thanks for watching. Vsauce is not, I'm not Vsauce, you are. When I start the episodes, I say, hey, Vsauce, Michael here. Vsauce and Michael are actually a different thing in my mind. I don't know if that's always clear, but yeah, I have to approach it that way because it's not about me. Yeah, so it's not even, you're not feeling responsibility. You're just sort of plugging into this big thing that is scientific exploration of our reality and you're a voice that represents a bunch, but you're just plugging into this big Vsauce ball that others, millions of others are plugged into. Yeah. So I encourage curiosity and responsible thinking and an embracement of doubt and being okay with that.

https://youtu.be/kNqI-PWJsX4

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How to Build AGI? (Ilya Sutskever) | AI Podcast Clips

What do you think it takes to, let's talk about AGI a little bit. What do you think it takes to build a system of human level intelligence? We talked about reasoning, we talked about long-term memory, but in general, what does it take, do you think? Well, I can't be sure, but I think that deep learning, plus maybe another small idea. Do you think self-play will be involved? So like you've spoken about the powerful mechanism of self-play where systems learn by sort of exploring the world in a competitive setting against other entities that are similarly skilled as them, and so incrementally improve in this way. Do you think self-play will be a component of building an AGI system? Yeah, so what I would say to build AGI, I think is going to be deep learning plus some ideas, and I think self-play will be one of those ideas. I think that that is a very, self-play has this amazing property that it can surprise us in truly novel ways. For example, like we, I mean, pretty much every self-play system, both our Dota bot, I don't know if OpenAI had a release about multi-agent where you had two little agents who were playing hide and seek, and of course also AlphaZero, they will all produce surprising behaviors. They all produce behaviors that we didn't expect. They are creative solutions to problems. And that seems like an important part of AGI that our systems don't exhibit routinely right now. And so that's why I like this area, I like this direction because of its ability to surprise us. To surprise us, and an AGI system would surprise us fundamentally. Yes, and to be precise, not just a random surprise, but to find a surprising solution to a problem is also useful. Right. Now, a lot of the self-play mechanisms have been used in the game context, or at least in the simulation context. How much, how far along the path to AGI do you think will be done in simulation? How much faith, promise do you have in simulation versus having to have a system that operates in the real world, whether it's the real world of digital real-world data, or real-world, like actual physical world of robotics? I don't think it's an either or. I think simulation is a tool, and it helps. It has certain strengths and certain weaknesses, and we should use it. Yeah, but, okay, I understand that. That's true, but one of the criticisms of self-play, one of the criticisms of reinforcement learning is one of the, its current power, its current results, while amazing, have been demonstrated in its simulated environments, or very constrained physical environments. Do you think it's possible to escape them, escape the simulated environments, and be able to learn in non-simulated environments, or do you think it's possible to also just simulate in a photorealistic and physics-realistic way the real world in a way that we can solve real problems with self-play in simulation? So, I think that transfer from simulation to the real world is definitely possible, and has been exhibited many times by many different groups. It's been especially successful in vision. Also, OpenAI in the summer has demonstrated a robot hand which was trained entirely in simulation in a certain way that allowed for seem-to-real transfer to occur. Is this for the Rubik's Cube? Yes, right. I wasn't aware that was trained in simulation. It was trained in simulation entirely. Really, so it wasn't in the physical, the hand wasn't trained? No, 100% of the training was done in simulation, and the policy that was learned in simulation was trained to be very adaptive, so adaptive that when you transfer it, it could very quickly adapt to the physical world. So the kind of perturbations with the giraffe or whatever the heck it was, were those part of the simulation? Well, the simulation was generally, so the simulation was trained to be robust to many different things, but not the kind of perturbations we've had in the video. So it's never been trained with a glove, it's never been trained with a stuffed giraffe. So in theory, these are novel perturbations. Correct, it's not in theory, in practice. That those are novel perturbations? Well, that's okay. That's a clean, small-scale but clean example of a transfer from the simulated world to the physical world. Yeah, and I will also say that I expect the transfer capabilities of deep learning to increase in general, and the better the transfer capabilities are, the more useful simulation will become. Because then you could take, you could experience something in simulation and then learn a moral of the story, which you could then carry with you to the real world. As humans do all the time when they play computer games. So let me ask sort of a embodied question, staying on AGI for a sec. Do you think AGI says that we need to have a body? We need to have some of those human elements of self-awareness, consciousness, sort of fear of mortality, sort of self-preservation in the physical space, which comes with having a body. I think having a body will be useful. I don't think it's necessary. But I think it's very useful to have a body for sure, because you can learn a whole new, you can learn things which cannot be learned without a body. But at the same time, I think that you can, if you don't have a body, you could compensate for it and still succeed. You think so? Yes. Well, there is evidence for this. For example, there are many people who were born deaf and blind, and they were able to compensate for the lack of modalities. I'm thinking about Helen Keller specifically. So even if you're not able to physically interact with the world, and if you're not able to, I mean, I actually was getting at, maybe let me ask on the more particular, I'm not sure if it's connected to having a body or not, but the idea of consciousness, and a more constrained version of that is self-awareness. Do you think an AGI system should have consciousness? We can't define consciousness, whatever the heck you think consciousness is. Yeah, hard question to answer, given how hard it is to define it. Do you think it's useful to think about? I mean, it's definitely interesting. It's fascinating. I think it's definitely possible that our systems will be conscious. Do you think that's an emergent thing that just comes from, do you think consciousness could emerge from the representation that's stored within your networks? So like that, it naturally just emerges when you become more and more, you're able to represent more and more of the world? Well, I'd say, I'd make the following argument, which is, humans are conscious, and if you believe that artificial neural nets are sufficiently similar to the brain, then there should at least exist artificial neural nets we should be conscious to. You're leaning on that existence proof pretty heavily. Okay. But that's the best answer I can give. No, I know, I know, I know. There's still an open question if there's not some magic in the brain that we're not, I mean, I don't mean a non-materialistic magic, but that the brain might be a lot more complicated and interesting than we give it credit for. If that's the case, then it should show up, and at some point, we will find out that we can't continue to make progress. But I think it's unlikely. So we talk about consciousness, but let me talk about another poorly defined concept of intelligence. Again, we've talked about reasoning, we've talked about memory. What do you think is a good test of intelligence for you? Are you impressed by the test that Alan Turing formulated with the imitation game with natural language? Is there something in your mind that you would be deeply impressed by if a system was able to do? I mean, lots of things. There's a certain frontier of capabilities today. Yes. And there exist things outside of that frontier, and I would be impressed by any such thing. For example, I would be impressed by a deep learning system which solves a very pedestrian task, like machine translation or computer vision task or something which never makes mistake a human wouldn't make under any circumstances. I think that is something which have not yet been demonstrated, and I would find it very impressive. Yeah, so right now they make mistakes in different, they might be more accurate than human beings, but they still, they make a different set of mistakes. So my, I would guess that a lot of the skepticism that some people have about deep learning is when they look at their mistakes and they say, well, those mistakes, they make no sense. Like if you understood the concept, you wouldn't make that mistake. And I think that changing that would be, that would inspire me. That would be, yes, this is progress. Yeah, that's a really nice way to put it. But I also just don't like that human instinct to criticize a model as not intelligent. That's the same instinct as we do when we criticize any group of creatures as the other. Because it's very possible that GPT-2 is much smarter than human beings at many things. That's definitely true. It is a lot more breadth of knowledge. Yes, breadth of knowledge, and even perhaps depth on certain topics. It's kind of hard to judge what depth means, but there's definitely a sense in which humans don't make mistakes, these models do. Yes, the same is applied to autonomous vehicles. The same is probably gonna continue being applied to a lot of artificial intelligence systems. We find, this is the annoying, this is the process of, in the 21st century, the process of analyzing the progress of AI is the search for one case where the system fails in a big way where humans would not, and then many people writing articles about it, and then broadly as the public generally gets convinced that the system is not intelligent. And we pacify ourselves by thinking it's not intelligent because of this one anecdotal case. And this seems to continue happening. Yeah, I mean, there is truth to that. Although I'm sure that plenty of people are also extremely impressed by the system that exists today. But I think this connects to the earlier point we discussed that it's just confusing to judge progress in AI. Yeah. And you have a new robot demonstrating something. How impressed should you be? And I think that people will start to be impressed once AI starts to really move the needle on the GDP. So you're one of the people that might be able to create an AGI system here, not you, but you and OpenAI. If you do create an AGI system and you get to spend sort of the evening with it, him, her, what would you talk about, do you think? The very first time? First time. Well, the first time I would just, I would just ask all kinds of questions and try to make it, to get it to make a mistake. And I would be amazed that it doesn't make mistakes. And I just keep asking broad. What kind of questions do you think, would they be factual or would they be personal, emotional, psychological? What do you think? All of the above. Would you ask for advice? Definitely. I mean, why would I limit myself talking to a system like this? Now, again, let me emphasize the fact that you truly are one of the people that might be in the room where this happens. So let me ask sort of a profound question about, I just talked to a Stalin historian. I've been talking to a lot of people who are studying power. Abraham Lincoln said, nearly all men can stand adversity, but if you want to test a man's character, give him power. I would say the power of the 21st century, maybe the 22nd, but hopefully the 21st, would be the creation of an AGI system and the people who have control, direct possession and control of the AGI system. So what do you think, after spending that evening having a discussion with the AGI system, what do you think you would do? Well, the ideal world I'd like to imagine is one where humanity, I like the board members of a company where the AGI is the CEO. So it would be, I would like, the picture which I would imagine is you have some kind of different entities, different countries or cities, and the people that leave their vote for what the AGI that represents them should do, and then AGI that represents them goes and does it. I think a picture like that, I find very appealing. You could have multiple, you would have an AGI for a city, for a country, and it would be trying to, in effect, take the democratic process to the next level. And the board can always fire the CEO. Essentially, press the reset button, say. Press the reset. Rerandomize the parameters. But let me sort of, that's actually, okay, that's a beautiful vision, I think, as long as it's possible to press the reset button. Do you think it will always be possible to press the reset button? So I think that it's definitely will be possible to build. So you're talking, so the question that I really understand from you is, will humans or, humans, people have control over the AI systems that they build? Yes, and my answer is, it's definitely possible to build AI systems which will want to be controlled by their humans. Wow, that's part of their, so it's not that just they can't help but be controlled, but that's, they exist, that one of the objectives of their existence is to be controlled. In the same way that human parents generally want to help their children, they want their children to succeed. It's not a burden for them. They are excited to help the children and to feed them and to dress them and to take care of them. And I believe with high conviction that the same will be possible for an AGI. It will be possible to program an AGI, to design it in such a way that it will have a similar deep drive, that it will be delighted to fulfill, and the drive will be to help humans flourish. But let me take a step back to that moment where you create the AGI system. I think this is a really crucial moment. And between that moment and the Democratic board members with the AGI at the head, there has to be a relinquishing of power. So as George Washington, despite all the bad things he did, one of the big things he did is he relinquished power. He, first of all, didn't want to be president. And even when he became president, he didn't keep just serving as most dictators do for indefinitely. Do you see yourself being able to relinquish control over an AGI system, given how much power you can have over the world? At first, financial, just make a lot of money, right? And then control by having possession of this AGI system. I'd find it trivial to do that. I'd find it trivial to relinquish this kind of power. I mean, you know, the kind of scenario you are describing sounds terrifying to me. That's all. I would absolutely not want to be in that position. Do you think you represent the majority or the minority of people in the AI community? Well, I mean. It's an open question and an important one. Are most people good is another way to ask it. So I don't know if most people are good, but I think that when it really counts, people can be better than we think. That's beautifully put, yeah. Are there specific mechanism you can think of of aligning AI gene values to human values? Is that, do you think about these problems of continued alignment as we develop the AI systems? Yeah, definitely. In some sense, the kind of question which you are asking is, so if I were to translate the question to today's terms, it would be a question about how to get an RL agent that's optimizing a value function which itself is learned. And if you look at humans, humans are like that because the reward function, the value function of humans is not external, it is internal. That's right. And there are definite ideas of how to train a value function. Basically an objective, and as objective as possible perception system that will be trained separately to recognize, to internalize human judgments on different situations. And then that component would then be integrated as the base value function for some more capable RL system. You could imagine a process like this. I'm not saying this is the process, I'm saying this is an example of the kind of thing you could do.

https://youtu.be/i0UyKsAEaNI

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Yann LeCun: Human-Level Artificial Intelligence | AI Podcast Clips

What do you think it takes to build a system with human level intelligence? You talked about the AI system in the movie, Her, being way out of reach, our current reach. This might be outdated as well, but- It's still way out of reach. It's still way out of reach. What would it take to build Her, do you think? So I can tell you the first two obstacles that we have to clear, but I don't know how many obstacles there are after this. So the image I usually use is that there is a bunch of mountains that we have to climb and we can see the first one, but we don't know if there are 50 mountains behind it or not. And this might be a good sort of metaphor for why AI researchers in the past have been overly optimistic about the result of AI. You know, for example, Newell and Simon, right, wrote the general problem solver and they called it a general problem solver. General problem solver. And of course, the first thing you realize is that all the problems you want to solve are exponential. And so you can't actually use it for anything useful. But, you know. Yeah, so yeah, all you see is the first peak. So what are the first couple of peaks for Her? So the first peak, which is precisely what I'm working on, is self-supervised learning. How do we get machines to learn models of the world by observation, kind of like babies and like young animals? So we've been working with, you know, cognitive scientists. So this Emmanuelle Dupou, who's at FAIR in Paris, is half-time, is also a researcher in French University. And he has this chart that shows how many months of life baby humans can learn different concepts. And you can measure this in sort of various ways. So things like distinguishing animate objects from inanimate inanimate objects, you can tell the difference at age two, three months. Whether an object is going to stay stable, is going to fall, you know, about four months, you can tell. You know, there are various things like this. And then things like gravity, the fact that objects are not supposed to float in the air, but are supposed to fall, you run this around the age of eight or nine months. If you look at a lot of, you know, eight-month-old babies, you give them a bunch of toys on their high chair. First thing they do is they throw them on the ground when you look at them. It's because, you know, they're learning about, actively learning about gravity. Gravity, yeah. Okay, so they're not trying to annoy you, but they, you know, they need to do the experiment, right? So, you know, how do we get machines to learn like babies? Mostly by observation with a little bit of interaction and learning those models of the world, because I think that's really a crucial piece of an intelligent autonomous system. So if you think about the architecture of an intelligent autonomous system, it needs to have a predictive model of the world. So something that says, here is a world at time T, here is a state of the world at time T plus one if I take this action. And it's not a single answer, it can be a- Yeah, it can be a distribution, yeah. Well, but we don't know how to represent distributions in high-dimensional continuous spaces, so it's gotta be something weaker than that, okay? But with some representation of uncertainty. If you have that, then you can do what optimal control theorists call model predictive control, which means that you can run your model with a hypothesis for a sequence of action and then see the result. Now, what you need, the other thing you need is some sort of objective that you want to optimize. Am I reaching the goal of grabbing this object? Am I minimizing energy? Am I, whatever, right? So there is some sort of objective that you have to minimize. And so in your head, if you have this model, you can figure out the sequence of action that will optimize your objective. That objective is something that ultimately is rooted in your basal ganglia, at least in the human brain, that's what it is, basal ganglia, computes your level of contentment, or miscontentment, I don't know if that's a word, unhappiness, okay? Yeah, yeah. Discontentment. Discontentment, maybe. And so your entire behavior is driven towards kind of minimizing that objective, which is maximizing your contentment, computed by your basal ganglia. And what you have is an objective function, which is basically a predictor of what your basal ganglia is gonna tell you. So you're not gonna put your hand on fire because you know it's gonna burn, and you're gonna get hurt, and you're predicting this because of your model of the world and you're sort of predictor of this objective, right? So if you have those three components, you have four components, you have the hardwired contentment objective computer, if you want, calculator, and then you have the three components, one is the objective predictor, which basically predicts your level of contentment, one is the model of the world, and there's a third module I didn't mention, which is the module that will figure out the best course of action to optimize an objective given your model. Okay? Yeah. Callista Policy Network, or something like that, right? Now, you need those three components to act autonomously intelligently, and you can be stupid in three different ways. You can be stupid because your model of the world is wrong, you can be stupid because your objective is not aligned with what you actually want to achieve. Okay? In humans, that would be a psychopath. Right. And then the third way you can be stupid is that you have the right model, you have the right objective, but you're unable to figure out a course of action to optimize your objective given your model.

https://youtu.be/maAJXNDjIcQ

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Garry Kasparov: Magnus Carlsen is a Lethal Combination of Fischer and Karpov | Lex Fridman Podcast

Where do you put Magnus Carlsen, the current world champion, in the list of all-time greats? In terms of style, moments of brilliance, consistency? It's a tricky question. You know, the moment you start ranking world champions, I think it's not fair because any new generation knows much more about the game than the previous one. So when people say, oh, Gary was the greatest, Fischer was the greatest, Magnus was the greatest, it disregards the fact that the great players of the past, the last year, Cabo Blanc, López, I mean, they knew so little about chess by today's standards. I mean, today, just any kid, you know, that spent a few years with his or her chess computer knows much more about the game simply just because you have access to this information. And it has been discovered generation after generation. We added more and more knowledge to the game of chess. It's about the gap between the world champion and the rest of the field. So it's the... Now, if you look at the gap, then probably Fischer, you know, could be on top, but very short period of time. Then you should also add a time factor. I was on top not as big as Fischer, but much longer. So and also, unlike Fischer, I succeeded in beating next generation. Here's the question. Yeah. Let's see if you still got the fire. Speaking of the next generation, because you did succeed beating the next generation. It's close. Okay. Anand, short Anand, the sheer of... Kramnik is already 12 years younger. So that's a neck. But still yet, I competed with them and I just beat most of them. And I was still dominant when I left at age 41. So back to Magnus. Magnus, I mean, consistency is phenomenal. The reason Magnus is on top and it seems unbeatable today, Magnus is a lethal combination of Fischer and Karpov, which is very unusual because Fischer's style was very dynamic, just fighting to the last point, just using every resource available. Karpov was very different. It's just he had an unparalleled ability to use every piece with a maximum effect, just means minimal resources always produce maximum effect. So now imagine that you merge these two styles. So it's like squeezing every stone for a drop of water, but doing it just for 50, 60, 70, 80 moves. I mean, Magnus could go on as long as Fischer with all his passion and energy, and at the same time being as meticulous and deadly as Karpov by just using every little advantage. So, and he has good, very good health. It's important. I mean, physical conditions are, by the way, very important. So a lot of people don't recognize it. There are latest studies shows that chess players burn thousands of calories during the game. So that puts him on the top of this field of the world champions. But again, it's the discussion that I saw recently in internet, whether Garry Kasparov of his peak, let's say late 80s, could beat Magnus Carlsen today, I mean, it's totally irrelevant because Garry Kasparov in 1989, okay, he's played great chess, but still, I knew very little about chess compared to Magnus Carlsen in 2019, who by the way, learned from me as well. So that's why, yeah. I'm extremely cautious in making any judgment that involves time gaps. You ask soccer fans, so who is your favorite? Pelé, Maradona or Messi? Yeah. Who's your favorite? Messi. Messi. Why? Because- Maybe Maradona, maybe. No, because you're younger, but that's simple. Your instinctive answer is correct because you didn't see Maradona in action. I saw all of them in action, so that's why. But since when I was just following it, it's Pelé and Maradona, they were big stars and it's, Messi's already just, I was gradually losing interest in just other things. So I remember Pelé in 1970, the final match Brazil-Italy. So that's the first World Cup soccer I watched. So that's the, and actually my answer when I just, because I was asked this question as well. So I say that it's just, while it's impossible to make a choice, I would still probably go with Maradona for a simple reason. The Brazilian team in 1970 could have won without Pelé. It was absolutely great. Still could have won. But Argentina team in 1986 without Maradona would not be unified. So this is, and Messi, he still hasn't won a title. That's- Could argue for that for an hour, but you could say if you ask Maradona, if you look in his eyes, especially let's say Garry Kasparov in 1989, he would have said, I was sure as hell would beat Magnus Carlsen. Just simply because- The confidence, the fire. Simply because, simply because again, it's just, they saw me in action. So this, again, it's the age factor that's important. Therefore with the passion and energy and being equipped with all modern ideas. But again, then you make a very just important assumption that you could empower Garry Kasparov in 89 with all ideas that have been accumulated over 30 years. That would not be Garry Kasparov. That would be someone else. Because again, I belong to 1989. I was way ahead of the field and I beat Karpov several times in the world championship matches and I crossed 2,800, which by the way, if you look at the rating, which is just, it's even today, so this is the rating that I retired. So it's still, it's just, it's a top two, two, three. So that's, it's Caruana and Deag. It's about the same rating now. And I crossed 2,800 in 1990. Well, just you look at the inflation. When I crossed 2,800 in 1990, there was only one player in 2,700 category, Anatoly Karpov. Now we had more than 50. So just when you see this, so if you add inflation, so I think my 2,851, it could probably, could be more valuable as Magnus 2,882, which was his highest rating. But anyway, again, too many hypotheticals.

https://youtu.be/Np1zODg5cqc

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AI Simulating Humans to Understand Itself (Joscha Bach) | AI Podcast Clips

Let me ask a romanticized question. What is the most beautiful to you, silly ape, the most beautiful or surprising idea in the development of artificial intelligence, whether in your own life or in the history of artificial intelligence that you've come across? If you built an AI, it probably can make models at an arbitrary degree of detail, right, of the world. And then it would try to understand its own nature. It's tempting to think that at some point when we have general intelligence, we have competitions where we will let the AIs wake up in different kinds of physical universes, and we measure how many movements of the Rubik's cube it takes until it's figured out what's going on in its universe and what it is in its own nature and its own physics and so on, right? So what if we exist in the memory of an AI that is trying to understand its own nature and remembers its own genesis and remembers Lex and Yosha sitting in a hotel room, sparking some of the ideas off that led to the development of general intelligence? So we're a kind of simulation that's running in an AI system that's trying to understand itself. Maybe. It's not that I believe that, but I think it's a beautiful idea. It's a, yeah. Yeah. Yeah. Yeah. I mean, yeah, you kind of return to this idea with the Turing test of intelligence being, of intelligence being the process of asking and answering what is intelligence. I mean, what, why, do you think there's an answer? Why is there such a search for an answer? So does there have to be like an answer? You just said an AI system that's trying to understand the why of what, you know, understand itself. Is that a fundamental process of greater and greater complexity, greater and greater intelligence? Is the continuous trying of understanding itself? No, I think you will find that most people don't care about that because they're well-adjusted enough to not care. And the reason why people like you and me care about it probably has to do with the need to understand ourselves. It's because we are in fundamental disagreement with the universe that we wake up in. What's the disagreement? I look down on me and I see, oh my God, I'm caught in a monkey. What's that? Some people are unhappy with the government and I'm unhappy with the entire universe that I find myself in. So you don't think that's a fundamental aspect of human nature that some people are just suppressing? That they wake up shocked they're in the body of a monkey? No, there is a clear adaptive value to not be confused by that and by. Well, no, that's not what I asked. So yeah, if there's clear adaptive value, then there's clear adaptive value to, while fundamentally your brain is confused by that, by creating an illusion, another layer of the narrative that says, that tries to suppress that and instead say that what's going on with the government right now is the most important thing and what's going on with my football team is the most important thing. But it seems to me, for me it was a really interesting moment reading Ernest Becker's Denial of Death. This kind of idea that we're all, the fundamental thing from which most of our human mind springs is this fear of mortality and being cognizant of your mortality and the fear of that mortality. And then you construct illusions on top of that. I guess you being, just to push on it, you really don't think it's possible that this worry of the big existential questions is actually fundamental as the existentialist thought to our existence. I think that the fear of death only plays a role as long as you don't see the big picture. The thing is that minds are software states, right? Software doesn't have identity. Software in some sense is a physical law. But if, hold on a second, but if, yeah. Right, software. But it feels like there's an identity. I thought that was for this particular piece of software and the narrative it tells, that's a fundamental property of it, of assigning an identity. The maintenance of the identity is not terminal. It's instrumental to something else. You maintain your identity so you can serve your meaning. So you can do the things that you're supposed to do before you die. And I suspect that for most people, the fear of death is the fear of dying before they're done with the things that they feel they have to do even though they cannot quite put their finger on it, what that is. Right, but in the software world, to return to the question, then what happens after we die? Because. Why would you care? You will not be longer there. The point of dying is that you are gone. Well, maybe I'm not. This is what, you know, it seems like there's so much, in the idea that this is just, the mind is just a simulation that's constructing a narrative around some particular aspects of the quantum mechanical wave function world that we can't quite get direct access to. Then the idea of mortality seems to be fuzzy as well. Maybe there's not a clear end. Fuzzy idea is the one of continuous existence. We don't have continuous existence. How do you know that? Like that. Because it's not computable. Because you're saying it's gonna be direct. There is no continuous process. The only thing that binds you together with the Lex Friedman from yesterday is the illusion that you have memories about him. So if you want to upload, it's very easy. You make a machine that thinks it's you. Because it's the same thing that you are. You are a machine that thinks it's you. But that's immortality. Yeah, but it's just a belief. You can create this belief very easily once you realize that the question whether you are immortal or not depends entirely on your beliefs and your own continuity. But then you can be immortal by the continuity of the belief. You cannot be immortal, but you can stop being afraid of your mortality because you realize you were never continuously existing in the first place. Well, I don't know if I'd be more terrified or less terrified by that. It seems like the fact that I existed. Also, you don't know this state in which you don't have a self. You can turn off yourself, you know? I can't turn off myself. You can't turn it off. You can't turn it off. I can. So you can basically meditate yourself in a state where you are still conscious, where still things are happening, where you know everything that you knew before, but you're no longer identified with changing anything. And this means that your self, in a way, dissolves. There is no longer this person. You know that this person construct exists in other states and it runs on this brain of Lex Friedman, but it's not a real thing. It's a construct. It's an idea. And you can change that idea. And if you let go of this idea, if you don't think that you are special, you realize it's just one of many people and it's not your favorite person even, right? It's just one of many. And it's the one that you are doomed to control for the most part. And that is basically informing the actions of this organism as a control model. This is all there is. And you are somehow afraid that this control model gets interrupted or loses the identity of continuity. Yeah, so I'm attached, I mean, yeah, it's a very popular, it's a somehow compelling notion that being attached, like there's no need to be attached to this idea of an identity. But that in itself could be an illusion that you construct. So the process of meditation, while popularly thought of as getting under the concept of identity, it could be just putting a cloak over it, just telling it to be quiet for the moment. I think that meditation is eventually just a bunch of techniques that let you control attention. And when you can control attention, you can get access to your own source code, hopefully not before you understand what you're doing. And then you can change the way it works, temporarily or permanently. So yeah, meditation is to get a glimpse at the source code, get under, so basically control or turn off the attention. The thing is that you learn to control attention. So everything else is downstream from controlling attention. And control the attention that's looking at the attention. Normally we only get attention in the parts of our mind that create heat, where you have a mismatch between model and the results that are happening. And so most people are not self-aware because their control is too good. If everything works out roughly the way you want, and the only things that don't work out is whether your football team wins, then you will mostly have models about these domains. And it's only when, for instance, your fundamental relationships to the world around you don't work, because the ideology of your country is insane and the other kids are not nerds and don't understand why you understand physics and you don't, why you want to understand physics and you don't understand why somebody would not want to understand physics.

https://youtu.be/aRdUqKtbgsY

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Elon Musk: Understanding the Human Brain at Neuralink

We currently understand very little about the human brain. Do you also hope that the work at Neuralink will help us understand more about the human mind, about the brain? Yeah, I think the work at Neuralink will definitely shed a lot of insight into how the brain and the mind works. Right now, just the data we have regarding how the brain works is very limited. We've got fMRI, which is kind of like putting a stethoscope on the outside of a factory wall and then putting it all over the factory wall and you can sort of hear the sounds, but you don't know what the machines are doing, really. You can infer a few things, but it's very broad brushstroke. In order to really know what's going on in the brain, you have to have high-precision sensors, and then you want to have stimulus and response. If you trigger a neuron, how do you feel? What do you see? How does it change your perception of the world? You're speaking to physically just getting close to the brain, being able to measure signals from the brain will open the door inside the factory. Yes, exactly. Being able to have high-precision sensors that tell you what individual neurons are doing, and then being able to trigger a neuron and see what the response is in the brain. So you can see the consequences of if you fire this neuron, what happens? How do you feel? What does it change? It'll be really profound to have this in people because people can articulate their change, like if there's a change in mood, or if they can tell you if they can see better or hear better, or be able to form sentences better or worse, or their memories are jogged, or that kind of thing.

https://youtu.be/6CTJMx64Vbw

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Donald Knuth: P=NP | AI Podcast Clips

You've mentioned over the past few years that you believe P may be equal to NP, but that it's not really, you know, if somebody does prove that P equals NP, it will not directly lead to an actual algorithm to solve difficult problems. Can you explain your intuition here? Has it been changed? And in general, on the difference between easy and difficult problems of P and NP and so on? So the popular idea is if an algorithm exists, then somebody will find it. And it's just a matter of writing it down. But many more algorithms exist than anybody can understand or ever make use of. Or discover, yeah. Because they're just way beyond human comprehension. The total number of algorithms is more than mind-boggling. So we have situations now where we know that algorithms exist, but we don't know, we don't have the foggiest idea what the algorithms are. There are simple examples based on game playing where you have, where you say, well, there must be an algorithm that exists to win in the game of hex, because, for the first player to win in the game of hex, because hex is always either a win for the first player or the second player. Well, what's the game of hex? There's a game of hex which is based on putting pebbles onto a hexagonal board, and the white player tries to get a white path from left to right, and the black player tries to get a black path from bottom to top. And how does capture occur? And there's no capture. You just put pebbles down one at a time. But there's no draws, because after all the white and black are played, there's either going to be a white path across from east to west or a black path from bottom to top. So there's always, you know, it's the perfect information game, and people take turns, like tic-tac-toe. And the hex board can be different sizes, but there's no possibility of a draw, and players move one at a time. And so it's got to be either a first player win or a second player win. Mathematically, you follow out all the trees, and there's always a win for the first player, second player, okay. And it's finite. The game is finite. But there's an algorithm that will decide—you can show it has to be one or the other, because the second player could mimic the first player with kind of a pairing strategy. And so you can show that it has to be one way or the other. But we don't know any algorithm anyway. We don't know—there are cases where you can prove the existence of a solution, but nobody knows any way how to find it. More like the algorithm question, there's a very powerful theorem in graph theory by Robinson and Seymour that says that every class of graphs that is closed under taking minors has a polynomial time algorithm to determine whether it's in this class or not. Now, a class of graphs, for example, planar graphs, these are graphs that you can draw in a plane without crossing lines. And a planar graph, taking minors means that you can shrink an edge into a point, or you can delete an edge. And so you start with a planar graph, shrink any edge to a point, it's still planar. Delete an edge, it's still planar. But there are millions of different ways to describe a family of graphs that still remains the same under taking minor. And Robinson and Seymour proved that any such family of graphs, there's a finite number of minimum graphs that are obstructions, so that if it's not in the family, then it has to contain, then there has to be a way to shrink it down until you get one of these bad minimum graphs that's not in the family. In the case of a planar graph, the minimum graph is a five-pointed star where everything points to another, and the minimum graph consisting of trying to connect three utilities to three houses without crossing lines. And so there are two bad graphs that are not planar. And every non-planar graph contains one of these two bad graphs by shrinking and removing edges. Sorry, can you say that again? So he proved that there's a finite number of these bad graphs. There's always a finite number. So somebody says, here's a family of- It's hard to believe. It's very surprising. And they proved it in a sequence of 20 papers, I mean, and it's deep work. Because that's for any arbitrary class. So it's for any- Any arbitrary class that's closed under taking minors. Closed under, maybe I'm not understanding, because it seems like a lot of them are closed under taking minors. Almost all the important classes of graphs are. There are tons of such graphs, but also hundreds of them that arise in applications. I have a book over here called Classes of Graphs, and it's amazing how many different classes of graphs that people have looked at. So why do you bring up this theorem, or this proof? So now, there's lots of algorithms that are known for special classes of graphs. For example, if I have a chordal graph, then I can color it efficiently. If I have some kind of graphs, it'll make a great network. So you'd like to test it. Somebody gives you a graph, and says, oh, is it in this family of graphs? If so, then I can go to the library and find an algorithm that's going to solve my problem on that graph. So we want to have a graph that says—an algorithm that says, you give me a graph, I'll tell you whether it's in this family or not. And so all I have to do is test whether or not—does this given graph have a minor that's one of the bad ones? A minor is everything you can get by shrinking and removing it. And given any minor, there's a polynomial time algorithm saying I can tell whether this is a minor of you. And there's a finite number of bad cases. So I just try, you know, does it have this bad case? Polynomial time, I got the answer. Does it have this bad case? Polynomial time, I got the answer. Total polynomial time. And so I've solved the problem. However, all we know is that the number of minors is finite. We don't know what—we might only know one or two of those minors, but we don't know that if we've got 20 of them, we don't know there might be 21, 25. All we know is that it's finite. So here we have a polynomial time algorithm that we don't know. That's a really great example of what you worry about or why you think P equals NP won't be useful. But still, why do you hold the intuition that P equals NP? Because you have to rule out so many possible algorithms as being not working. You know, you can take the graph and you can represent it as in terms of certain prime numbers and then you can multiply those together and then you can take the bitwise and and construct some certain constant in polynomial time and then that's a perfectly valid algorithm. And there are so many algorithms of that kind. A lot of times we see random—you take data and we get coincidences that some fairly random looking number actually is useful because it happens to solve a problem just because there's so many hairs on your head. But it seems like unlikely that two people are going to have the same number of hairs on their head. But you can count how many people there are and how many hairs on their head. So there must be people walking around in the country that have the same number of hairs on their head. Well, that's a kind of a coincidence that you might say also, you know, this particular combination of operations just happens to prove that a graph has a Hamiltonian path. I see lots of cases where unexpected things happen when you have enough possibilities. Because the space of possibility is so huge, your intuition just says— You have to rule them all out. And so that's the reason for my intuition. It's by no means a proof. Some people say, well, P can't equal NP because you've had all these smart people. The smartest designers of algorithms have been wracking their brains for years and years and there's million-dollar prizes out there. Nobody has thought of the algorithm, so there must be no such algorithm. On the other hand, I can use exactly the same logic and I can say, well, P must be equal to NP because there's so many smart people out here been trying to prove it unequal to NP and they've all failed. This kind of reminds me of the discussion about the search for aliens. We've been trying to look for them and we haven't found them yet, therefore they don't exist but you can show that there's so many planets out there that they very possibly could exist. Yeah, right. And then there's also the possibility that they exist but they all discovered machine learning or something and then blew each other up.

https://youtu.be/XDTOs8MgQfg

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Ava's Smile: Ex Machina's Most Important Moment (Alex Garland) | AI Podcast Clips

For an entire generation of AI researchers, 2001, a space odyssey, put an image, the idea of human level, super human level intelligence into their mind. Do you ever, sort of jumping back to Ex Machina and talk a little bit about that, do you ever consider the audience of people who build the systems, the roboticists, the scientists that build the systems based on the stories you create? Which I would argue, I mean, there's literally most of the top researchers, about 40, 50 years old and plus, you know, that's their favorite movie, 2001, Space Odyssey. It really is in their work, their idea of what ethics is, of what is the target, the hope, the dangers of AI, is that movie, right? Do you ever consider the impact on those researchers when you create the work you do? Certainly not with Ex Machina in relation to 2001, because I'm not sure, I mean, I'd be pleased if there was, but I'm not sure, in a way, there isn't a fundamental discussion of issues to do with AI that isn't already and better dealt with by 2001. 2001 does a very, very good account of the way in which an AI might think and also potential issues with the way the AI might think. And also, then a separate question about whether the AI is malevolent or benevolent. And 2001 doesn't really, it's a slightly odd thing to be making a film when you know there's a pre-existing film, which is not a really superb job. But there's questions of consciousness, embodiment, and also the same kinds of questions. Because those are my two favorite AI movies. So can you compare HAL 9000 and EVA, HAL 9000 from 2001 Space Odyssey and EVA from Ex Machina, the, in your view, from a philosophical perspective. But they've got different goals. The two AIs have completely different goals. I think that's really the difference. So in some respects, Ex Machina took as a premise, how do you assess whether something else has consciousness? So it was a version of the Turing test, except instead of having the machine hidden, you put the machine in plain sight, in the way that we are in plain sight of each other and say, now assess the consciousness. And the way it was illustrating the way in which you'd assess the state of consciousness of a machine is exactly the same way we assess the state of consciousness of each other. And in exactly the same way that in a funny way, your sense of my consciousness is actually based primarily on your own consciousness, that is also then true with the machine. And so it was actually about how much of the sense of consciousness is a projection rather than something that consciousness is actually containing. And has Plato's cave, I mean, this, you really explored, you could argue that HAL sort of Space Odyssey explores idea of the Turing test for intelligence. No, not test, there's no test, but it's more focused on intelligence. And Ex Machina kind of goes around intelligence and says the consciousness of the human to human, human to robot interaction is more interesting, more important, more, at least the focus of that particular movie. Yeah, it's about the interior state and what constitutes the interior state and how do we know it's there. And actually in that respect, Ex Machina is as much about consciousness in general as it is to do specifically with machine consciousness. And it's also interesting, you know that thing you started asking about, the dream state, and I was saying, well, I think we're all in a dream state because we're all in a subjective state. One of the things that I became aware of with Ex Machina is that the way in which people reacted to the film was very based on what they took into the film. So many people thought Ex Machina was the tale of a sort of evil robot who murders two men and escapes and she has no empathy, for example, because she's a machine. Whereas I felt, no, she was a conscious being with a consciousness different from mine, but so what, imprisoned and made a bunch of value judgments about how to get out of that box. And there's a moment which it sort of slightly bugs me, but nobody ever has noticed it and it's years after, so I might as well say it now, which is that after Ava has escaped, she crosses a room and as she's crossing a room, this is just before she leaves the building, she looks over her shoulder and she smiles. And I thought after all the conversation about tests, in a way, the best indication you could have of the interior state of someone is if they are not being observed and they smile about something, where they're smiling for themselves. And that, to me, was evidence of Ava's true sentience, whatever that sentience was. But that's really interesting. We don't get to observe Ava much or something like a smile in any context except through interaction, trying to convince others that she's conscious, that's beautiful. Exactly, yeah. But it was a small, in a funny way, I think maybe people saw it as an evil smile, like, ha, you know, I fooled them. But actually, it was just a smile. And I thought, well, in the end, after all the conversations about the test, that was the answer to the test, and then off she goes. So if we align, if we just to linger a little bit longer on Hal and Ava, do you think in terms of motivation, what was Hal's motivation? Is Hal good or evil? Is Ava good or evil? Ava's good, in my opinion. And Hal is neutral, because I don't think Hal is presented as having a sophisticated emotional life. He has a set of paradigms, which is that the mission needs to be completed. I mean, it's a version of the paperclip. Yeah. The idea that it's a super intelligent machine, but it's just performed a particular task. Yeah. And in doing that task, may destroy everybody on Earth, or may achieve undesirable effects for us humans. Precisely, yeah. But what if, okay. At the very end, he says something like, I'm afraid, Dave. But that maybe he is on some level experiencing fear, or it may be this is the terms in which it would be wise to stop someone from doing the thing they're doing, if you see what I mean. Yes, absolutely. So actually, that's funny. So that's such a small, short exploration of consciousness that I'm afraid. And then you just with X-Mach gonna say, okay, we're gonna magnify that part, and then minimize the other part. So that's a good way to sort of compare the two. But if you could just use your imagination, and if Ava sort of, I don't know, I don't know, was president of the United States, so had some power. So what kind of world would she want to create? If we, as you kind of say, good. And there is a sense that she has a really, like there's a desire for a better human to human interaction, human to robot interaction in her. But what kind of world do you think she would create with that desire? So that's a really, that's a very interesting question. I'm gonna approach it slightly obliquely, which is that if a friend of yours got stabbed in a mugging, and you then felt very angry at the person who'd done the stabbing, but then you learned that it was a 15 year old, and the 15 year old, both their parents were addicted to crystal meth, and the kid had been addicted since he was 10, and he really never had any hope in the world, and he'd been driven crazy by his upbringing, and did the stabbing, that would hugely modify, and it would also make you wary about that kid then becoming president of America. And Ava has had a very, very distorted introduction into the world. So although there's nothing, as it were, organically within Ava that would lean her towards badness, it's not that robots or sentient robots are bad. She did not, her arrival into the world was being imprisoned by humans. So I'm not sure she'd be a great president. Yeah, the trajectory through which she arrived at her moral views have some dark elements. But I like Ava, personally I like Ava. Would you vote for her? I'm having difficulty finding anyone to vote for in my country, or if I lived here in yours. So that's a yes, I guess, because the competition. She could easily do a better job than any of the people we've got around at the moment. I'd vote for her over Boris Johnson. So what is a good test of consciousness? We talk about consciousness a little bit more. If something appears conscious, is it conscious? You mentioned the smile, which seems to be something done. I mean, that's a really good indication because it's a tree falling in the forest with nobody there to hear it. But does the appearance from a robotics perspective of consciousness mean consciousness to you? No, I don't think you could say that fully because I think you could then easily have a thought experiment which said, we will create something which we know is not conscious, but is going to give a very, very good account of seeming conscious. And also it would be a particularly bad test where humans are involved because humans are so quick to project sentience into things that don't have sentience. So someone could have their computer playing up and feel as if their computer is being malevolent to them when it clearly isn't. And so of all the things to judge consciousness, us, we're empathy machines. So the flip side of that, the argument there is because we just attribute consciousness to everything almost, anthropomorphize everything, including Roombas, that maybe consciousness is not real, that we just attribute consciousness to each other. So you have a sense that there is something really special going on in our mind that makes us unique and gives us subjective experience. There's something very interesting going on in our minds. I'm slightly worried about the word special because it nudges towards metaphysics and maybe even magic. I mean, in some ways, something magic-like, which I don't think is there at all. I mean, if you think about, so there's an idea called panpsychism that says consciousness is in everything. Yeah, I don't buy that. I don't buy that. Yeah, so the idea that there is a thing that it would be like to be the sun. Yeah, no, I don't buy that. I think that consciousness is a thing. My sort of broad modification is that usually the more I find out about things, the more illusory our instinct is and is leading us into a different direction about what that thing actually is. That happens, it seems to me, in modern science, that happens a hell of a lot, whether it's to do with even how big or small things are. So my sense is that consciousness is a thing, but it isn't quite the thing, or maybe very different from the thing that we instinctively think it is. So it's there, it's very interesting, but we may be in sort of quite fundamentally misunderstanding it for reasons that are based on intuition.

https://youtu.be/RuSDbIcFgbo

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Elon Musk: It's Game, Set, Match - Tesla is Vastly Ahead of Everyone | AI Podcast Clips

It's amazing how people can't differentiate between say the narrow AI that allows a car to figure out what a lane line is and navigate streets versus general intelligence. Like these are just very different things. Like your toaster and your computer are both machines but one is much more sophisticated than another. You're confident with Tesla you can create the world's best toaster? The world's best toaster, yes. The world's best self-driving... I'm... yes. To me right now this seems game set match. I don't want to be complacent or overconfident but that is just literally how it appears right now. I could be wrong but it appears to be the case that Tesla is vastly ahead of everyone.

https://youtu.be/dpqLy-3cHmc

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Elon Musk: Perception vs Control - What's Harder?

What's harder, perception or control for these problems? So being able to perfectly perceive everything or figuring out a plan once you perceive everything, how to interact with all the agents in the environment? In your sense, from a learning perspective, is perception or action harder in that giant, beautiful, multitask learning neural network? The hardest thing is having accurate representation of the physical objects in vector space. So taking the visual input, primarily visual input, some sonar and radar, and then creating the accurate vector space representation of the objects around you. Once you have an accurate vector space representation, the planning and control is relatively easier. That is relatively easy. Basically once you have accurate vector space representation, then you're kind of like a video game. Cars in Grand Theft Auto or something, they work pretty well. They drive down the road, they don't crash pretty much unless you crash into them. That's because they've got an accurate vector space representation of where the cars are, and then rendering that as the output.

https://youtu.be/1soLVufJWLU

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Ray Dalio: Work-Life Balance and the Arc of Life | AI Podcast Clips

Much of your passions in life has been through something you might be able to call work. Alan Watts has this quote, he said that the real key to life, secret to life, is to be completely engaged with what you're doing in the here and now, and instead of calling it work, realize it is play. So I'd like to ask, what is the role of work in your life's journey, or in a life's journey? And what do you think about this modern idea of kind of separating work and work-life balance? I have a principle that I believe in, is make your work and your passion the same thing. Okay. So that's similar view. In other words, if you can make your work and your passion, it's just going to work out great. And then of course, people have different purposes of work. And I don't want to be theoretical about that. People have to take care of their family. So money at a certain point is an important component of that work. So you look beyond that, what is the money going to get you and what are you trying to achieve? But the most important thing, I agree, is meaningful work and meaningful relationships. Like if you can get into the thing that you're, your mission that you're on, and you are excited about that mission that you're on, and then you can do that with people who you have the meaningful relationships with. You have meaningful work and meaningful relationships. I mean, that is fabulous for most people. And it seems that many people struggle to get there, not out of, not necessarily because they're constrained by the fact that they have the financial constraints of having to provide for their family and so on. And it's, I mean, you know, this idea is out there that there needs to be a work-life balance, which means that most people, we're going to return to the same thing as most doesn't mean optimal, but most people seem to not be doing their life's passion, not be, not unifying work and passion. Why do you think that is? Well the work-life balance, there's a life arc that you go through. Starts at zero and ends somewhere in the vicinity of 80, and there is a phase, and there's a, and you could look at the different degrees of happiness that happen in those phases. I can go through that if that was interesting, but we don't have time probably for it. But you get in the part of the life, that part of the life which has the lowest level of happiness is age 45 to 55, and because as you move into this second phase of your life, now the first phase of your life is when you're learning dependent on others. Second phase of your life is when you're working and others are dependent on you and you're trying to be successful. And in that phase of one's life, you encounter the work-life balance challenge because you're trying to be successful at work and successful at parenting and successful and successful in all those things that take your demand. And they get into that, and I understand that problem in the work-life balance. The issue is primarily to know how to approach that, okay? So I understand it's stressful, it produces stress, and it produces bad results, and it produces the lowest level of happiness in one's life. What's interesting is you get later in life, the levels of happiness rise, and the highest level of happiness is between ages 70 and 80, which is interesting for other reasons. But in that spot, and the key to work-life balance is to realize and to learn how to get more out of an hour of life, okay? Because an hour of work, what people are thinking is that they have to make a choice between one thing and another, and of course they do, but they don't realize that if they develop the skill to get a lot more out of an hour, it's the equivalent of having many more hours in your life. And so that's why in the book Principles, I try to go into, okay, now how can you get a lot more out of an hour? That allows you to get more life into your life, and it reduces the work-life balance. And that's the primary struggle in that 35 to 45. If you could linger on that, what are the ups and downs of life in terms of happiness in general, and perhaps in your own life when you look back at the moments, the peaks? It's pretty much the same pattern. Usually in one's life tends to be a very happy period all the way up, and 16 is like a really great happy... I think, like myself, you start to get elements of freedom, you get your driver's license, whatever, but 16 is there. Junior year in high school quite often can be a stressful period to try to get things about the high school. You go into college, tends to be very high happiness, generally speaking. And then freedom, friendships, all of that. Freedom is a big thing. And then 23 is a peak point in happiness, that freedom. Then sequentially, one has a great time, they date, they go out, and so on. You find the love of your life, you begin to develop a family. And then with that, as time happens, you have more of your work-life balance challenges that come and your responsibilities. And then as you get there in that mid part of your life, that is the biggest struggle. Chances are you will crash in that period of time. You'll have your series of failures, that's that. That's when you go into the abyss. You learn, you hopefully learn from those mistakes, you have the metamorphosis, you come out, you change, you hopefully become better and you take more responsibilities and so on. And then when you get to the later part, as you are starting to approach the transition in that late part of the second phase of your life, before you go into the third phase of your life, second phase is you're working, trying to be successful. Third phase of your life is you want people to be successful without you. You want your kids to be successful without you because when you're at that phase, they're at making their transition from the first phase to the second phase and they're trying to be successful and you want them to be successful without you. And you have, your parents are gone and then you have freedom and then you have freedom again and that with that freedom and then you have these, history has shown with this, you have friendships, you have perspective on life, you have different things. And that's one of the reasons that that later part of the life can be real. On average actually, it's the highest, very interesting thing. If they, there are surveys and say, how good do you look and how good do you feel? And that's the highest survey. The person, now they're not looking the best and they're not feeling the best, right? Maybe it's 35 that they're actually looking the best and feeling the best, but they rank the highest at that point, survey results of being the highest in that 70 to 80 period of time, because it has to do with an attitude on life. Then you start to have grandkids, oh, grandkids are great. And you start to experience that transition well. So that's what the arc of life pretty much looks like. And I'm experiencing it.

https://youtu.be/9mL26U3GGcc

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Elon Musk: First Principles

First principles is kind of a physics way of looking at the world. You boil things down to the most fundamental truths and say, okay, what are we sure is true and then reason up from there. Somebody could say, in fact people do, that battery packs are really expensive and that's just the way they'll always be because that's the way they've been in the past. No, that's pretty dumb. If you apply that reasoning to anything new, you wouldn't be able to ever get to that new thing. So first principles would be to say, okay, what are the material constituents of the batteries? What is the spot market value of the material constituents? So you can say, okay, it's got cobalt, nickel, aluminum, carbon, and some polymers for separation and a steel can. If we bought that in London Metal Exchange, what would each of those things cost? Like, oh, it's like $80 per kilowatt hour. So clearly you just need to think of clever ways to take those materials and combine them into the shape of a battery cell and you can have batteries that are much, much cheaper than anyone realizes.

https://youtu.be/bLv9MGsUt6g

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Best hidden feature of Python | Chaining comparison operators

This is a hidden feature of Python that I recently came across, the chaining of comparison operators, that is not available in almost any mainstream programming language. I think it's elegant and intuitive and doesn't make any sense to me why it's not available in most languages. So what is it? Say we assign the values 2 and 3 to x and y, and then look at a single statement that includes several comparison operators chained together, 1 less than x less than y less than 4. In Python this evaluates to true. The way Python evaluates the statement is the same way that we would intuitively or mathematically look at the statement, which is as a chain of binary comparison operators. 1 is less than x and x is less than y and y is less than 4, which again evaluates to true. Now you can use any comparison operator, less than, greater than, less than or equal to, greater than or equal to, and mix and match them together in a single arbitrarily long chain of comparison operators. Now if we change the original statement to include a greater than operator as the last comparison, then the entire statement returns false, because y, which is equal to 3, is not greater than 4. And then finally again we can flip the 4 and the y to make the statement return true, and all the individual comparisons are true. 1 is less than x, which is equal to 2, x is less than 4, and 4 is greater than y, y being equal to 3. Now this feature is available in a few other languages, not many, like Perl 6, or Reiku, I think it's been renamed to, not sure how to pronounce it, and Julia, and as shown here it's also a first class citizen in some functional languages, like Scheme, Common Lisp, and Closure, with the added constraint that the chaining of the operator includes only the same operator, so you can't mix and match. So shown here, the greatest language of all time, which is Lisp, the equals operator applied to a list of numbers, 3 and 3 returns true, 3 and 5 returns false, all 3's returns true, all 3's except one of them being 5 returns false. So again, that's chaining the equality comparison operator across the entire list. And the same is true for the less than operator applied to the entire list, below, 3 less than 5 is true, and then a long sequence returning true if it's in strictly increasing order, and false if it's not in strictly increasing order. I put some links in the description, one of the more interesting ones is in the software engineering stack exchange, where I discuss this from a semi-philosophical perspective, why most mainstream languages do not include this feature. You should check out some of the answers on that page, but to summarize some of the discussion, the reason to do it is, despite the initial intuition about this feature being difficult to implement, it's actually very easy to implement, and as I said, it's a mathematically intuitive and just elegant statement, which I think makes it one of the best hidden features, at least to me, of Python. In the discussion, the reasons that come up not to do it is fundamentally just laziness, in that its importance versus other features is quite low, and it doesn't seem to be the kind of feature that pops up as an intuitive first feature to implement when a language is first born. And as with certain other features, this can potentially break backward compatibility, if this kind of chaining operators was allowed previously, syntactically speaking, meaning it was allowed but didn't do the intuitive thing, it can certainly break in quite painful ways backward compatibility. But still, as I said in the previous video, list comprehensions I think is the best feature of Python, and the chaining of comparison operators I think is the best hidden feature, or not well-known feature of Python. Quick shout-out to ExpressVPN, click their link in the description, it's the best way to support the podcast I host and these videos that I make. If you enjoy these, subscribe, and remember, try to learn something new every day.

https://youtu.be/HPfPFM1wNmE

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David Chalmers: What is Consciousness? | AI Podcast Clips

Let's try to go to the very simplest question that you've answered many a time, but perhaps the simplest things can help us reveal, even in time, some new ideas. So what, in your view, is consciousness? What is qualia? What is the hard problem of consciousness? Consciousness, I mean, the word is used many ways, but the kind of consciousness that I'm interested in is basically subjective experience. What it feels like from the inside to be a human being or any other conscious being. I mean, there's something it's like to be me. Right now, I have visual images that I'm experiencing. I'm hearing my voice. I've got maybe some emotional tone. I've got a stream of thoughts running through my head. These are all things that I experience from the first person point of view. I've sometimes called this the inner movie in the mind. It's not a perfect metaphor. It's not like a movie in every way, and it's very rich. But yeah, it's just direct, subjective experience. And I call that consciousness, or sometimes philosophers use the word qualia, which you suggested. People tend to use the word qualia for things like the qualities of things like colors, redness, the experience of redness versus the experience of greenness, the experience of one taste or one smell versus another, the experience of the quality of pain. And yeah, a lot of consciousness is the experience of those qualities. But consciousness is bigger, the entirety of any kinds of experience. I mean, consciousness of thinking is not obviously qualia. It's not like specific qualities like redness or greenness. But still, I'm thinking about my hometown. I'm thinking about what I'm gonna do later on. Maybe there's still something running through my head, which is subjective experience. Maybe it goes beyond those qualities or qualia. Philosophers sometimes use the word phenomenal consciousness for consciousness in this sense. I mean, people also talk about access consciousness, being able to access information in your mind, reflective consciousness, being able to think about yourself. But it looks like the really mysterious one, the one that really gets people going is phenomenal consciousness. The fact that there's subjective experience and all this feels like something at all. And then the hard problem is, how is it that, why is it that there is phenomenal consciousness at all? And how is it that physical processes in a brain could give you subjective experience? It looks like on the face of it, you'd have all this big complicated physical system in a brain running without it giving subjective experience at all. And yet we do have subjective experience. So the hard problem is just explain that. Explain how that comes about. We haven't been able to build machines where a red light goes on that says it's not conscious. So how do we actually create that? Or how do humans do it and how do we ourselves do it? We do every now and then create machines that can do this. We create babies that are conscious. They've got these brains. That brain does produce consciousness. But even though we can create it, we still don't understand why it happens. Maybe eventually we'll be able to create machines which as a matter of fact, AI machines which as a matter of fact are conscious. But that won't necessarily make the hard problem go away any more than it does with babies. Because we still want to know how and why is it that these processes give you consciousness. You know, you just made me realize for a second, maybe it's a totally dumb realization, but nevertheless, that it's a useful way to think about the creation of consciousness is looking at a baby. So that there's a certain point at which that baby is not conscious. The baby starts from maybe, I don't know, from a few cells, right? There's a certain point at which it becomes consciousness arrives, it's conscious. Of course we can't know exactly that line. But it's a useful idea that we do create consciousness. Again, a really dumb thing for me to say, but not until now did I realize we do engineer consciousness. We get to watch the process happen. We don't know which point it happens or where it is. But we do see the birth of consciousness. Yeah, I mean, there's a question of course is whether babies are conscious when they're born. And it used to be, it seems, at least some people thought they weren't, which is why they didn't give anesthetics to newborn babies when they circumcised them. And so now people think, oh, that's incredibly cruel. Of course, babies feel pain. And now the dominant view is that the babies can feel pain. Actually, my partner, Claudia, works on this whole issue of whether there's consciousness in babies and of what kind. And she certainly thinks that newborn babies come into the world with some degree of consciousness. Of course, then you can just extend the question backwards to fetuses, and suddenly you're into politically controversial territory. But the question also arises in the animal kingdom. Where does consciousness start or stop? Is there a line in the animal kingdom where the first conscious organisms are? It's interesting, over time, people are becoming more and more liberal about ascribing consciousness to animals. People used to think, maybe only mammals could be conscious. Now most people seem to think, sure, fish are conscious, they can feel pain, and now we're arguing over insects. You'll find people out there who say plants have some degree of consciousness. So who knows where it's gonna end? The far end of this chain is the view that every physical system has some degree of consciousness. Philosophers call that panpsychism. I take that view. I mean, that's a fascinating way to view reality. So if you could talk about, if you can linger on panpsychism for a little bit, what does it mean? So it's not just plants are conscious. I mean, it's that consciousness is a fundamental fabric of reality. What does that mean to you? How are we supposed to think about that? Well, we're used to the idea that some things in the world are fundamental, right? In physics, we take things like space or time or space-time, mass, charge as fundamental properties of the universe, you don't reduce them to something simpler. You take those for granted, you've got some laws that connect them, here is how mass and space and time evolve, theories like relativity or quantum mechanics or some future theory that will unify them both. But everyone says you gotta take some things as fundamental, and if you can't explain one thing in terms of the previous fundamental things, you have to expand. Maybe something like this happened with Maxwell. Ended up with fundamental principles of electromagnetism and took charge as fundamental, because it turned out that was the best way to explain it. So I at least take seriously the possibility something like that could happen with consciousness. Take it as a fundamental property like space, time, and mass, and instead of trying to explain consciousness wholly in terms of the evolution of space, time, and mass, and so on, take it as a primitive and then connect it to everything else by some fundamental laws. Because there's this basic problem that the physics we have now looks great for solving the easy problems of consciousness, which are all about behavior. They give us a complicated structure and dynamics, they tell us how things are gonna behave, what kind of observable behavior they'll produce, which is great for the problems of explaining how we walk and how we talk and so on. Those are the easy problems of consciousness. But the hard problem was this problem about subjective experience just doesn't look like that kind of problem about structure, dynamics, how things behave. So it's hard to see how existing physics is gonna give you a full explanation of that. Certainly trying to get a physics view of consciousness, yes, there has to be a connecting point, and it could be at the very axiomatic, at the very beginning level. But, I mean, first of all, there's a crazy idea that sort of everything has properties of consciousness. At that point, the word consciousness is already beyond the reach of our current understanding, like far, because it's so far from, at least for me, maybe you can correct me, it's far from the experiences that we have, that I have as a human being. To say that everything is conscious, that means that basically, another way to put that, if that's true, then we understand almost nothing about that fundamental aspect of the world. How do you feel about saying an ant is conscious? Do you get the same reaction to that, or is that something you can understand? I can understand ant, I can't understand an atom. A plant. A planticle. So I'm comfortable with living things on Earth being conscious, because there's some kind of agency where they're similar size to me, and they can be born and they can die, and that is understandable intuitively. Of course, you anthropomorphize, you put yourself in the place of the plant, but I can understand it. I mean, I'm not like, I don't believe, actually, that plants are conscious or that plants suffer, but I can understand that kind of belief, that kind of idea. How do you feel about robots? Like the kind of robots we have now? If I told you, like, that a Roomba had some degree of consciousness, or some deep neural network? I could understand that a Roomba has consciousness. I just had spent all day at iRobot. And I mean, I personally love robots and have a deep connection with robots, so I also probably anthropomorphize them. There's something about the physical object. So there's a difference than a neural network, a neural network running a software. To me, the physical object, something about the human experience allows me to really see that physical object as an entity. And if it moves, it moves in a way that it, there's a, like I didn't program it, where it feels that it's acting based on its own perception, and yes, self-awareness and consciousness, even if it's a Roomba, then you start to assign it some agency, some consciousness. So, but to say that panpsychism, that consciousness is a fundamental property of reality is a much bigger statement. That it's like turtles all the way, it's like every, it doesn't end. The whole thing is, so like how, I know it's full of mystery, but if you can linger on it, like how would it, how do you think about reality if consciousness is a fundamental part of its fabric? The way you get there is from thinking, can we explain consciousness given the existing fundamentals? And then if you can't, as at least right now it looks like, then you've got to add something. It doesn't follow that you have to add consciousness. Here's another interesting possibility is, well, we'll add something else. Let's call it proto-consciousness, or X. And then it turns out space, time, mass, plus X will somehow collectively give you the possibility for consciousness. Why don't we allow that view? Either I call that pan-proto-psychism, because maybe there's some other property, proto-consciousness at the bottom level. And if you can't imagine there's actually genuine consciousness at the bottom level, I think we should be open to the idea there's this other thing, X. Maybe we can't imagine that somehow gives you consciousness. But if we are playing along with the idea that there really is genuine consciousness at the bottom level, of course, this is going to be way out and speculative. But at least in, say, if it was classical physics, then you'd end up saying, well, every little atom, with a bunch of particles in space-time, each of these particles has some kind of consciousness whose structure mirrors maybe their physical properties, like its mass, its charge, its velocity, and so on. The structure of its consciousness would roughly correspond to that. And the physical interactions between particles, I mean, there's this old worry about physics, I mentioned this before in this issue about the manifest image. We don't really find out about the intrinsic nature of things. Physics tells us about how a particle relates to other particles and interacts. It doesn't tell us about what the particle is in itself. That was Kant's thing in itself. So here's a view. The nature in itself of a particle is something mental. A particle is actually a little conscious subject with properties of its consciousness that correspond to its physical properties. The laws of physics are actually ultimately relating these properties of conscious subjects. So in this view, a Newtonian world actually would be a vast collection of little conscious subjects at the bottom level, way, way simpler than we are without free will or rationality or anything like that. But that's what the universe would be like. Now, of course, that's a vastly speculative view. No particular reason to think it's correct. Furthermore, non-Newtonian physics, say quantum mechanical wave function, suddenly it starts to look different. It's not a vast collection of conscious subjects. Maybe there's ultimately one big wave function for the whole universe. Corresponding to that might be something more like a single conscious mind whose structure corresponds to the structure of the wave function. People sometimes call this cosmo-psychism. And now, of course, we're in the realm of extremely speculative philosophy. There's no direct evidence for this. But yeah, but if you want a picture of what that universe would be like, think yeah, giant cosmic mind with enough richness and structure among it to replicate all the structure of physics. I think therefore I am at the level of particles and with quantum mechanics at the level of the wave function. It's kind of an exciting, beautiful possibility, of course, way out of reach of physics currently. It is interesting that some neuroscientists are beginning to take panpsychism seriously. You find consciousness even in very simple systems. So for example, the integrated information theory of consciousness, a lot of neuroscientists are taking it seriously. Actually, I just got this new book by Christoph Koch. Just came in, The Feeling of Life Itself, Why Consciousness is Widespread but Can't Be Computed. He basically endorses a panpsychist view where you get consciousness with the degree of information processing or integrated information processing in a system, and even very, very simple systems, like a couple of particles, will have some degree of this. So he ends up with some degree of consciousness in all matter. And the claim is that this theory can actually explain a bunch of stuff about the connection between the brain and consciousness. Now, that's very controversial. I think it's very, very early days in the science of consciousness. It's interesting that it's not just philosophy that might lead you in this direction, but there are ways of thinking quasi-scientifically that lead you there, too. But maybe it's different than panpsychism. What do you think? So Alan Watts has this quote that I'd like to ask you about. The quote is, through our eyes, the universe is perceiving itself. Through our ears, the universe is listening to its harmonies. We are the witnesses to which the universe becomes conscious of its glory, of its magnificence. So that's not panpsychism. Do you think that we are essentially the tools, the senses the universe created to be conscious of itself? It's an interesting idea. Of course, if you went for the giant cosmic mind view, then the universe was conscious all along. It didn't need us. We're just little components of the universal consciousness. Likewise, if you believe in panpsychism, then there was some little degree of consciousness at the bottom level all along, and we were just a more complex form of consciousness. So I think maybe the quote you mentioned works better. If you're not a panpsychist, you're not a cosmopsychist, you think consciousness just exists at this intermediate level. And of course, that's the orthodox view. That, you would say, is the common view? So is your own view of panpsychism a rarer view? I think it's generally regarded, certainly, as a speculative view held by a fairly small minority of at least theorists, philosophers, most philosophers and most scientists who think about consciousness are not panpsychists. There's been a bit of a movement in that direction the last 10 years or so. Seems to be quite popular, especially among the younger generation, but it's still very definitely a minority view. Many people think it's totally batshit crazy to use the technical term. But... It's a philosophical term. So the orthodox view, I think, is still consciousness is something that humans have, and some good number of non-human animals have, and maybe AIs might have one day, but it's restricted. On that view, then, there was no consciousness at the start of the universe. There may be none at the end, but it is this thing which happened at some point in the history of the universe, consciousness developed. And yes, that's a very amazing event on this view because many people are inclined to think consciousness is what somehow gives meaning to our lives. Without consciousness, there'd be no meaning, no true value, no good versus bad, and so on. So with the advent of consciousness, suddenly the universe went from meaningless to somehow meaningful. Why did this happen? I guess the quote you mentioned was somehow, this was somehow destined to happen because the universe needed to have consciousness within it, to have value and have meaning. And maybe you could combine that with a theistic view or a teleological view. The universe was inexorably evolving towards consciousness. Actually, my colleague here at NYU, Tom Nagel, wrote a book called Mind and Cosmos a few years ago where he argued for this teleological view of evolution toward consciousness, saying this led to problems for Darwinism. It's got him on, you know, this was very, very controversial. Most people didn't agree. I don't myself agree with this teleological view, but it is at least a beautiful speculative view of the cosmos.

https://youtu.be/uKIk5AL16Bg

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Biological versus Artificial Neural Networks (John Hopfield) | AI Podcast Clips

What difference between biological neural networks and artificial neural networks is most captivating and profound to you? At the higher philosophical level, let's not get technical just yet. One of the things that very much intrigues me is the fact that neurons have all kinds of components, properties to them. In evolutionary biology, if you have some little quirk in how a molecule works or how a cell works, and it can be made use of, evolution will sharpen it up and make it into a useful feature rather than a glitch. And so you expect in neurobiology for evolution to have captured all kinds of possibilities of getting neurons, of how you get neurons to do things for you. And that aspect has been completely suppressed in artificial neural networks. Do the glitches become features in the biological neural network? They can. Look, let me take one of the things that I used to do research on. If you take things which oscillate, they have rhythms which are sort of close to each other, under some circumstances, these things will have a phase transition and suddenly the rhythm will, everybody will fall into step. There was a marvelous physical example of that in the Millennium Bridge across the Thames River about, built about 2001. And pedestrians walking across, pedestrians don't walk, synchronize, they don't walk in lockstep, but they're all walking about the same frequency. And the bridge could sway at that frequency and the slight sway made pedestrians tend a little bit to lock into step. And after a while, the bridge was oscillating back and forth and the pedestrians were walking in step to it. And you could see it in the movies made out of the bridge. And the engineers made a simple-minded mistake. They had assumed when you walk, it's step, step, step, and it's back and forth motion. But when you walk, it's also right foot, left foot, side to side motion. It's the side to side motion for which the bridge was strong enough, but it wasn't stiff enough. And as a result, you would feel the motion and you'd fall into step with it. And people were very uncomfortable with it. They closed the bridge for two years while they built stiffening for it. Now, nerves, look, nerve cells produce action potentials. You have a bunch of cells which are loosely coupled together producing action potentials of the same rate. There'll be some circumstances under which these things can lock together. Other circumstances in which they won't. Well, they fire together. You can be sure that other cells are gonna notice it. So you can make a computational feature out of this in an evolving brain. Most artificial neural networks don't even have action potentials, let alone have the possibility for synchronizing them. And you mentioned the evolutionary process. So the evolutionary process that builds on top of biological systems leverages that the weird mess of it somehow. So how do you make sense of that ability to leverage all the different kinds of complexities in the biological brain? Well, look, at the biological molecule level, you have a piece of DNA which encodes for a particular protein. You could duplicate that piece of DNA and now one part of it can code for that protein but the other one could itself change a little bit and thus start coding for a molecule which is slightly different. Now that molecule was just slightly different, had a function which helped any old chemical reaction was as important to the cell. You would go ahead and let that try and evolution would slowly improve that function. And so you have the possibility of duplicating and then having things drift apart. One of them retain the old function, the other one do something new for you. And there's evolutionary pressure to improve. Look, there is in computers too, but it's improvement has to do with closing some companies and opening some others. The evolutionary process looks a little different. Yeah, similar time scale perhaps. No. Much shorter in time scale. Companies close, yeah, go bankrupt and are born. Yeah, shorter, but not much shorter. Some companies last a century, but yeah, you're right. I mean, if you think of companies as a single organism that builds and you all know, yeah, it's a fascinating dual correspondence there between biological and- And companies have difficulty having a new product competing with an old product. When IBM built its first PC, you probably read the book. They made a little isolated internal unit to make the PC. And for the first time in IBM's history, they didn't insist that you build it out of IBM components, but they understood that they could get into this market, which is a very different thing by completely changing their culture. And biology finds other markets in a more adaptive way. Yeah, it's better at it. It's better at that kind of integration. So maybe you've already said it, but what to use the most beautiful aspect or mechanism of the human mind? Is it the adaptive, the ability to adapt as you've described or is there some other little quirk that you particularly like? Adaptation is everything when you get down to it. But the difference, there are differences between adaptation where you're learning goes on only over generations and over evolutionary time, or your learning goes on at the timescale of one individual who must learn from the environment during that individual's lifetime. And biology has both kinds of learning in it. And the thing which makes neurobiology hard is that it's a mathematical system, as it were, built on this other kind of evolutionary system. What do you mean by mathematical system? Where is the math in the biology? Well, when you talk to a computer scientist about neural networks, it's all math. The fact that biology actually came about from evolution and the fact that biology is about a system which you can build in three dimensions. If you look at computer chips, computer chips are basically two-dimensional structures, maybe 2.1 dimensions, but they really have difficulty doing three-dimensional wiring. Biology is, the neocortex is actually also sheet-like and it sits on top of the white matter, which is about 10 times the volume of the gray matter and contains all what you might call the wires. But there's a huge, the effect of computer structure on what is easy and what is hard is immense. So- And biology does, it makes some things easy that are very difficult to understand how to do computationally. On the other hand, you can't do simple floating-point arithmetic because it's awfully stupid. Yeah, and you're saying this kind of three-dimensional complicated structure makes, it's still math. It's still doing math. The kind of math it's doing enables you to solve problems of a very different kind. That's right, that's right. So you mentioned two kinds of adaptation, the evolutionary adaptation and the adaptation or learning at the scale of a single human life. Which do you, which is particularly beautiful to you and interesting from a research and from just a human perspective? And which is more powerful? I find things most interesting that I begin to see how to get into the edges of them and tease them apart a little bit and see how they work. And since I can't see the evolutionary process going on, I'm in awe of it. But I find it just a black hole as far as trying to understand what to do. And so in a certain sense, I'm in awe of it, but I couldn't be interested in working on it. So the human life's time scale is however thing you can tease apart and study. Yeah, you can do, there's developmental neurobiology which understands how the connections and how the structure evolves from a combination of what the genetics is like and the real, the fact that you're building a system in three dimensions. In just days and months, those early days of a human life are really interesting. They are, and of course, there are times of immense cell multiplication. There are also times of the greatest cell death in the brain is during infancy. It's turnover. So what is not effective, what is not wired well enough to use the moment, throw it out. It's a mysterious process. From, let me ask, from what field do you think the biggest breakthroughs in understanding the mind will come in the next decades? Is it neuroscience, computer science, neurobiology, psychology, physics? Maybe math, maybe literature? Well, of course, I see the world always through a lens of physics. I grew up in physics and the way I pick problems is very characteristic of physics and of an intellectual background, which is not psychology, which is not chemistry and so on and so on. And both of your parents are physicists. Both of my parents were physicists and the real thing I got out of that was a feeling that the world is an understandable place. And if you do enough experiments and think about what they mean and structure things so you can do the mathematics of the relevant to the experiments, you also be able to understand how things work. But that was a few years ago. Did you change your mind at all through many decades of trying to understand the mind, of studying in different kinds of ways? Not even the mind, just biological systems. You still have hope that physics, that you can understand? There's a question of what do you mean by understand? Of course. When I taught freshman physics, I used to say, I wanted to get physics to understand the subject, to understand Newton's laws. I didn't want them simply to memorize a set of examples to which they knew the equations to write down to generate the answers. I had this nebulous idea of understanding so that if you looked at a situation, you could say, oh, I expect the ball to make that trajectory. Or I expect some intuitive notion of understanding. And I don't know how to express that very well. I've never known how to express it well. And you run smack up against it when you look at these simple neural nets, feedforward neural nets, which do amazing things, and yet you know contain nothing of the essence of what I would have felt was understanding. Understanding is more than just an enormous lookup table. Let's linger on that. How sure you are of that? What if the table gets really big? So, I mean, ask another way, these feedforward neural networks, do you think they'll ever understand? Could answer that in two ways. I think if you look at real systems, feedback is an essential aspect of how these real systems compute. On the other hand, if I have a mathematical system with feedback, I know I can unlayer this and do it. But I have an exponential expansion in the amount of stuff I have to build if I can solve the problem that way. So feedback is essential. So we can talk even about recurrent neural nets, so recurrence. But do you think all the pieces are there to achieve understanding through these simple mechanisms? Like, back to our original question, what is the fundamental, is there a fundamental difference between artificial neural networks and biological? Or is it just a bunch of surface stuff? Suppose you ask a neurosurgeon, when is somebody dead? Yeah. They'll probably go back to saying, well, I can look at the brain rhythms and tell you this is a brain which is never gonna function again. This one is, this other one is one which if we treat it well, is still recoverable. And then just do that by some electrodes and looking at simple electrical patterns which don't look in any detail at all at what individual neurons are doing. These rhythms are utterly absent from anything which goes on at Google. Yeah, but the rhythms. But the rhythms what? So, well, that's like comparing, okay, I'll tell you, it's like you're comparing the greatest classical musician in the world to a child first learning to play. The question I'm at, but they're still both playing the piano. I'm asking, is there, will it ever go on at Google? Do you have a hope? Because you're one of the seminal figures in both launching both disciplines, both sides of the river. I think it's going to go on generation after generation the way it has where, what you might call the AI computer science community says, let's take the following. This is our model of neurobiology at the moment. Let's pretend it's good enough and do everything we can with it. And it does interesting things. And after the while it sort of grinds into the sand and you say, ah, something else is needed for neurobiology and some other grand thing comes in and enables you to go a lot further. But we'll go into the sand again. And I think it's going to be generations of this evolution. I don't know how many of them and each one is going to get you further into what our brain does. In some sense, past the Turing test, longer and more broad aspects. And how many of these are good there are going to have to be before you say, I've made something, I've made a human. I don't know. But your sense is it might be a couple. My sense is it might be a couple more. Yeah. And going back to my brain waves as it were. From the AI point of view, they would say, ah, maybe these are an heavy phenomenon and not important at all. The first car I had, a real wreck of a 1936 Dodge, go above 45 miles an hour and the wheels would shimmy. Yeah. Good speedometer that. Now, nobody designed the car that way. The car is malfunctioning to have that. But in biology, if it were useful to know when are you going more than 45 miles an hour, you just capture that and you wouldn't worry about where it came from. Yeah. It's going to be a long time before that kind of thing, which can take place in large complex networks of things is actually used in the computation. Look, how many transistors are there in your laptop these days? Actually, I don't know the number. It's- It's on the scale of 10 to the 10. I can't remember the number either. Yeah. And all the transistors are somewhat similar. And most physical systems with that many parts, all of which are similar, have collective properties. Yes. Sound waves in air, earthquakes, what have you, have collective properties. Whether, there are no collective properties used in artificial neural networks, in AI. Yeah, it's very- If biology uses them, it's going to take us to more generations of things for people to actually dig in and see how they are used and what they mean. See, you're very right. I might have to return several times to your biology and try to make our transistors more messy. Yeah, yeah. At the same time, the simple ones will conquer big aspects. And I think one of the most biggest surprises to me was how well learning systems, which are manifestly non-biological, how important they can be actually and how important and how useful they can be in AI.

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Starting a Business is a Rough Ride (Stephen Schwarzman) | AI Podcast Clips

I'm now personally taking a step into building a startup, first time, hoping to change the world of course. There are thousands, maybe more, maybe millions of other first time entrepreneurs like me. What advice, you've gone through this process, you've talked about the suffering, the emotional turmoil it all might entail, what advice do you have for those people taking that step? I'd say it's a rough ride and you have to be psychologically prepared for things going wrong with frequency. You have to be prepared to be put in situations where you're being asked to solve problems you didn't even know those problems existed. You know, for example, renting space, it's not really a problem unless you've never done it. You have no idea what a lease looks like, right? You don't even know the relevant rent in a market. So everything is new, everything has to be learned. What you realize is that it's good to have other people with you who've had some experience in areas where you don't know what you're doing. Unfortunately an entrepreneur starting doesn't know much of anything, so everything is something new. And I think it's important not to be alone because it's sort of overwhelming and you need somebody to talk to other than a spouse or a loved one because even they get bored with your problems. And so, you know, getting a group, you know, if you look at Alibaba, you know, Jack Ma was telling me they basically were like a financial death's door at least twice. And you know, the fact that it wasn't just Jack, I mean, people think it is because he became the sort of public face and the driver, but a group of people who can give advice, share situations to talk about, that's really important. And that's not just referring to the small details like renting space. No. It's also the psychological burden. Yes, yeah. And you know, because most entrepreneurs at some point question what they're doing because it's not going so well or they're screwing it up and they don't know how to unscrew it up because we're all learning. And it's hard to be learning, you know, when there are like 25 variables going on. If you're missing four big ones, you can really make a mess. And so, the ability to in effect have either an outsider who's really smart that you can rely on for certain type of things or other people who are working with you on a daily basis. Most people who haven't had experience believe in the myth of the one person, one great person, you know, makes outcomes, creates outcomes that are positive. Most of us, it's not like that. If you look back over a lot of the big successful tech companies, it's not typically one person. You know, and you will know these stories better than I do because it's your world, not mine. But even I know that almost every one of them had two people. I mean, if you look at Google, you know, that's what they had and that was the same at Microsoft at the beginning. And, you know, it was the same at Apple. You know, people have different skills and they need to play off of other people. So, you know, the advice that I would give you is make sure you understand that so you don't head off in some direction as a lone wolf and find that either you can't invent all the solutions or you make bad decisions on certain types of things. This is a team sport. Team sport means you're alone, in effect, and that's the myth. But it's mostly a myth. Yeah, I think, and you talk about this in your book, and I could talk to you about it forever, the harshly self-critical aspect to your personality and to mine as well in the face of failure. It's a powerful tool, but it's also a burden. It's very interesting, very interesting to walk that line. But let me ask in terms of people around you, in terms of friends, in the bigger picture of your own life, where do you put the value of love, family, friendship in the big picture journey of your life? Well, ultimately all journeys are alone. It's great to have support. And when you go forward and say your job is to make something work and that's your number one priority, and you're going to work at it to make it work, it's like superhuman effort. People don't become successful as part-time workers. Doesn't work that way. And if you're prepared to make that 100 to 120% effort, you're going to need support. And you're going to have to have people involved with your life who understand that that's really part of your life. Sometimes you're involved with somebody and they don't really understand that, and that's a source of conflict and difficulty. But if you're involved with the right people, whether it's a dating relationship or a spousal relationship, you have to involve them in your life, but not burden them with every minor triumph or mistake. They actually get bored with it after a while. And so you have to set up different types of ecosystems. You have your home life, you have your love life, you have children, and that's like the enduring part of what you do. And then on the other side, you've got the sort of unpredictable nature of this type of work. What I say to people at my firm who are younger, usually, well, everybody's younger, but people who are of an age where they're just having their first child, or maybe they have two children, that it's important to make sure they go away with their spouse at least once every two months to just some lovely place where there are no children, no issues. Sometimes once a month if they're sort of energetic and clever. And that... Escape the craziness of it all. Yeah, and reaffirm your values as a couple. And you have to have fun. If you don't have fun with the person you're with, and all you're doing is dealing with issues, then that gets pretty old. And so you have to protect the fun element of your life together. And the way to do that isn't by hanging around the house and dealing with sort of more problems. It... You have to get away and reinforce and reinvigorate your relationship. And whenever I tell one of our younger people about that, they sort of look at me and it's like the scales are falling off of their eyes and they're saying, geez, I hadn't thought about that. I'm so enmeshed in all these things, but that's a great idea. And that's something as an entrepreneur you also have to do. You just can't let relationships slip because you're half overwhelmed.

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DeepMind solves protein folding | AlphaFold 2

I think it's fair to say that this year, 2020, has thrown quite a few challenges at human civilization. So it's really nice to get some positive news about truly marvelous accomplishments of engineering and science. One was SpaceX, I would argue, launching a new era of space exploration. And now, a couple of days ago, DeepMind has announced that its second iteration of the AlphaFold system has, quote unquote, solved the 50-year-old grand challenge problem of protein folding. Solved here means that these computational methods were able to achieve prediction performance similar to much slower, much more expensive experimental methods like X-ray crystallography. In 2018, which is the previous iteration of the CASP competition, AlphaFold achieved a score of 58 on the hardest class of proteins. And this year, it achieved a score of 87, which is a huge improvement, and it's still 26 points better than the closest competition. So this is definitely a big leap, but it's also fair to say that the internet is full of hype about this breakthrough. And so let me indulge in the fun a bit. Some of it is definitely a little bit subjective, but I think the case could be made on the life science side that this is the biggest advancements in structural biology of the past one or two decades. And in my field of artificial intelligence, I think a strong case could be made that this is one of the biggest advancements in recent history of the field. So of course, the competition is pretty steep, and I talk with excitement about each of these entries. Of course, the ImageNet moment itself or the AlexNet moment that launched a deep learning revolution in the space of computer vision. So many people are comparing now this breakthrough of AlphaFold2 to the ImageNet moment, but now in the life sciences field. I think the good old argument over beers about which is the biggest breakthrough comes down to the importance you place on how much real world direct impact a breakthrough has. Of course, AlexNet was ultimately on a toy dataset of very simplistic image classification problem, which does not have a direct application to the real world, but it did demonstrate the ability of deep neural networks to learn from a large amount of data in a supervised way. But anyway, this is probably a very long conversation over many beers of AlphaZero with reinforcement learning self-play, obviously in contention for the biggest breakthrough. The recent breakthroughs in the application of transformers in the natural language processing space with GPT-3 being the most kind of recent iteration of state-of-the-art performance. The actual deployment of robots in the field used by real humans, which is Tesla Autopilot. You know, deployment of massive fleet learning, of massive machine learning in safety-critical systems. And then other kinds of robots like the Google self-driving car, Waymo systems that are taking even a further leap of removing the human from the picture, being able to drive the car autonomously without human supervision. Smart speakers in the home. There's a lot of actual in the wild natural language processing that I think doesn't get enough credit from the artificial intelligence community, how much amazing stuff is there. And depending how much value you put in engineering achievements, especially in the hardware space, Boston Dynamics with its SpotManySpot robot is just, one could argue, is one of the great accomplishments in the artificial intelligence field, especially when you maybe look 20 and 50 years down the line when the entire world is populated by robot dogs and the humans have gone extinct. Anyway, I say all that for fun, but really this is one of the big breakthroughs in our field and something to truly be excited about. And I'll talk about some of the possible future impact I see here from this breakthrough in just a couple of slides here. Anyway, my prediction is that there'll be at least one, potentially several Nobel prizes that will result in derivative work launched directly with these computational methods. It's kind of exciting to think that it's possible also that we'll see a first Nobel prize that is awarded where much of the work is done by a machine learning system. Of course, the Nobel prize is awarded to the humans behind the system, but it's exciting to think that a computational approach or machine learning system will play a big role in a Nobel prize level discovery in the field like medicine and physiology or chemistry or even physics. Okay, let's talk a bit about proteins and protein folding, why this whole space is really fascinating. First of all, there's amino acids, which are the basic building blocks of life in eukaryotes, which is what we're talking about here with humans, there's 21 of them. Proteins are chains of amino acids and are the workhorses of living organisms of cells. And they do all kinds of stuff from structural to functional they serve as catalysts for chemical reactions, they move stuff around, they do all kinds of things. So they're both the building blocks of life and the doers and movers of life. Hopefully I'm not being too poetic. So protein folding is the fascinating process of going from the amino acid sequence to a 3D structure. There's a lot that could be said here, there's a lot of lectures on this topic, but let me quickly say some of the more fascinating and important things that I remember from a few biology classes I took in high school and college. Okay, so first is there's a fascinating property of uniqueness that a particular sequence usually maps one-to-one to a 3D structure, not always, but usually. To me from an outsider's perspective, that's just weird and fascinating. The other thing to say is that the 3D structure determines the function of the protein. So one of the correlators of that is that the underlying cause of many diseases is the misfolding of proteins. Now back to the weirdness of the uniqueness of the folding, there's a lot of ways for a protein to fold based on the sequence of amino acids. There's I think 10 to the power of 80 atoms in the universe, so 10 to the power of 143 is a lot. And you can look at Leventhal's paradox, which is one of the early formulations of just how hard this problem is and why it's really weird that a protein is able to do it so quickly. As a completely irrelevant side note, I wonder how many possible chess games there are. I think I remember it being 10 to the power of 100, something like that. I think that would also necessitate removing certain kinds of infinite games. Anyway, off the top of my head, I would venture to say that the protein folding problem just in the number of possible combinations is much, much harder than the game of chess, but it's also much weirder. You know, they say that life imitates chess, but I think that from a biological perspective, life is way weirder than chess. Anyway, to say once again what I said before is that the misfolding of proteins is the underlying cause of many diseases. And again, I'll talk about the implications of that a little bit later. From a computational, from a machine learning, from a dataset perspective, what we're looking at currently is 200 million proteins that have been mapped and 170,000 protein 3D structures, so much, much fewer. And that's our training data for the learning-based approaches for the protein folding problem. Now, the way those 3D structures were determined is through experimental methods. One of the most accurate being X-ray crystallography, which I saw a University of Toronto study showing that it costs about $120,000 per protein. It takes about one year to determine the 3D structure. So because it costs a lot and it's very slow, that's why you only have 170,000 3D structures determined. Now, that's one of the big things that the AlphaFold2 system might be able to provide is at least for a large class of proteins be able to determine the 3D structure with a high accuracy, enough to be able to sort of open up the structural biology field entirely with sort of several orders of magnitude more protein 3D structures to play with. There's not currently a paper out that describes the details of the AlphaFold2 system, but I think it's clear that it's heavily based on the AlphaFold1 system from two years ago. So I think it's useful to look at how that system works. And then we can hypothesize, speculate about the kind of methodological improvements in the AlphaFold2 system. Okay, so for AlphaFold1 system, there's two steps in the process. The first includes machine learning, the second does not. The first step includes a convolutional neural network that takes as input the amino acid residue sequences plus a ton of different features that their paper describes, including the multiple sequence alignment of evolutionary related sequences. And the output of the network is this distance matrix with the rows and columns being the amino acid residues. They're giving a confidence distribution of the distance between the two amino acids in the final geometric 3D structure of the protein. Then once you have the distance matrix, then you have a non-learning based gradient descent optimization of folding this 3D structure to figure out how you can as closely as possible match the distances between the amino acid residues that are specified by the distance matrix. Okay, that's it at a high level. Now, how does AlphaFold2 work? First of all, we don't know for sure. There's only a blog post and some little speculation here and there. But one thing is clear that there's attentional mechanisms. So I think convolutional neural networks are out and transformers are in. The same kind of process that's been happening in the natural language processing space and really most of the deep learning space, it's clear that attention mechanisms are going to be taking over every aspects of machine learning. So I think the big change is ComNet is out, transformers are in. The rest is more in the speculation space. It does seem that the MSA, the multiple sequence alignment, is part of the learning process now, as opposed to part of the feature engineering, which it was in the original step. I believe it was only a source of features. Please correct me if I'm wrong on that. But it does seem like here it's now part of the learning process. And there's something iterative about it, at least in the blog post, where there's a constant passing of learned information between the sequence residue representation, which is the evolution related sequence side of things. And then the amino acid residue to residue distances that are more akin to the alpha fold one system. How that iterative process works, it's unclear, whether it's part of one giant neural network or whether several neural networks evolved, I don't know. But it does seem that the evolution related sequences are now part of the learning process. It does seem that there's some kind of iterative passing information. And of course, attention being involved into the entire picture. Now, at least in the blog post, the term spatial graph is used as opposed to sort of a distance matrix or adjacency matrix. So I don't know if there's some magical tricks involved in some interesting generalization of an adjacency matrix that's involved in a spatial graph representation, or if it's simply just using the term spatial graph because there is more than just pairwise distances involved in this version of the learning architecture. I think the two lessons of the recent history of deep learning, if you involve attention, if you involve transformers, you're gonna get a big boost. And the other lesson is that if you make as much of the problem learnable as possible, you're often going to see quite significant benefits. This is something I've definitely seen in the computer vision especially the semantic segmentation side of things. Okay, why is this breakthrough important? Allow this computer scientist AI person to wax poetic about some biology for a bit. So because the protein structure gives us the protein function, figuring out the structure for maybe millions of proteins might allow us to learn unknown functions of genes encoded in DNA. Also, as I mentioned before, it might allow us to understand the cause of many diseases that are the result of misfolded proteins. Other application will stem from the ability to quickly design new proteins that in some way alter the function of other proteins. So for treatments, for drugs, that means designing proteins that fix other misfolded proteins. Again, those are the causes of many diseases. I read a paper that was talking about agriculture applications of being able to engineer insecticidal proteins or frost protective coating, stuff I know nothing about. I read it, it's out there. Tissue regeneration through self-assembling proteins, supplements for improved health and anti-aging, and all kinds of biomaterials, for textiles and just materials in general. Now in the long-term or the super long-term future, impact of this breakthrough might be just the advancement of end-to-end learning of really complicated problems in the life sciences. So protein folding is looking at the folding of a single protein. So being able to predict multi-protein interaction or protein complex formation, which even in my limited knowledge of biology, I think is a much, much, much harder problem, as far as I understand. And just being able to incorporate the environment into the modeling of the folding of the protein and also seeing how the function of that protein might change given the environment. All those kinds of things, incorporating that into the end-to-end learning problem. Then taking a step even further is this is physics, biophysics. So being able to accurately do physics-based simulation of biological systems. So if we think of a protein as one of the most basic biological systems, so then taking a step out further and further and increasing the complexity of the biological systems, you can start to think of something crazy like being able to do accurate physics-based simulation of cells, for example, or entire organs. Or maybe one day being able to do an accurate physics-based simulation of the very over-caffeinated organ that's producing this very video. In fact, how do we know this is not a physics-based simulation of a biological system whose assigned name happens to be Lex? I guess we'll never know. And of course, we can go farther out into super long-term sci-fi kind of ideas of biological life and artificial life, which are fascinating ideas of being able to play with simulation of prediction of organisms that are biologically based or non-biologically based. I mean, that's the exciting future of end-to-end learning systems that step outside the game-playing world of StarCraft, of Chess and Go, and go into the life sciences of real-world systems that operate in the real world. That's where Tesla autopilot is really exciting. That's where any robots that use machine learning are really exciting. And that's where this big breakthrough in the space of structural biology is super exciting. And truly, to me, as one humble human, inspiring beyond words. Speaking of words, for me, these quick videos are fun and easy to make, and I hope it's at least somewhat useful to you. If it is, I'll make more. It's fun, I enjoy it. I love it, really. Quick shout-out to podcast sponsors. Vincero Watches, the maker of classy, well-performing watches. I'm wearing one now. And Four Sigmatic, the maker of delicious mushroom coffee. I drink it every morning and all day, as you can probably tell from my voice now. Please check out these sponsors in the description to get a discount and to support this channel. All right, love you all. And remember, try to learn something new every day.

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Beauty Quarks (Harry Cliff) | AI Podcast Clips

So I work on a detector called LHCb, which is one of these four big detectors that are spaced around the ring. We do slightly different stuff to the big guys. There's two big experiments called ATLAS and CMS, 3,000 physicists and scientists and computer scientists on them each. They are the ones that discovered the Higgs and they look for supersymmetry and dark matter and so on. What we look at are standard model particles called bquarks, which depending on your preferences, either bottom or beauty, we tend to say beauty because it sounds sexier. But these particles are interesting because we can make lots of them. We make billions or hundreds of billions of these things. You can therefore measure their properties very precisely. So you can make these really lovely precision measurements. And what we are doing really is a sort of complementary thing to the other big experiments, which is, if you think of the sort of analogy they often use is, if you imagine you're in the jungle and you're looking for an elephant, say, and you are a hunter and you're kind of like, let's say there's the elephant's very rare, you don't know where in the jungle, the jungle's big. So there's two ways you go about this. Either you can go wandering around the jungle and try and find the elephant. The problem is if there's only one elephant and the jungle's big, the chances of running into it are very small. Or you could look on the ground and see if you see footprints left by the elephant. And if the elephant's moving around, you've got a chance, your better chance maybe of seeing the elephant's footprints. If you see the footprints, you go, okay, there's an elephant. I maybe don't know what kind of elephant it is, but I got a sense there's something out there. So that's sort of what we do. We are the footprint people. We are, we're looking for the footprints, the impressions that quantum fields that we haven't managed to directly create the particle of, the effects these quantum fields have on the ordinary standard model fields that we already know about. So these, these B particles, the way they behave can be influenced by the presence of say super fields or dark matter fields or whatever you like. And then the way they decay and behave can be altered slightly from what our theory tells us they ought to behave. And it's easier to collect huge amounts of data on B quarks. We get billions and billions of these things. You can make very precise measurements. And the only place really at the LHC or in really in high energy physics at the moment where there's fairly compelling evidence that there might be something beyond the standard model is in these B, these beauty quarks decays. Just to clarify, which is the difference between the different, the four experiments, for example, that you mentioned, is it the kind of particles that are being collided? Is it the energies of which they're collided? What's the fundamental difference between the different experiments? The collisions are the same. What's different is the design of the detectors. So Atlas and CMS are called, they're called what are called general purpose detectors. And they are basically barrel shaped machines and the collisions happen in the middle of the barrel and the barrel captures all the particles that go flying out in every direction. So in a sphere effectively that can flying out and it can record all of those particles. And what's the, sorry to be interrupting, but what's the, what's the mechanism of the recording? So these detectors, if you've seen pictures of them, they're huge, like Atlas is 25 meters high and 45 meters long. They're vast machines, instruments, I guess you should call them really. They are, they're kind of like onions. So they have layers, concentric layers of detector detectors, different sorts of detectors. So close into the beam pipe, you have what are called usually made of silicon, they're tracking detectors. So they're little made of strips of silicon or pixels of silicon. And when a particle goes through the silicon, it gives a little electrical signal and you get these dots, you know, electrical dots through your detector, which allows you to reconstruct the trajectory of the particle. So that's the middle. And then the outsides of these detectors, you have things called calorimeters, which measure the energies of the particles. And then very edge, you have things called muon chambers, which basically met these muon particles, which are the heavy version of the electron. They are, they're like high velocity bullets and they can get right to the edge of the detectors. If you see something at the edge, that's a muon. So that's broadly how they work. And all of that is being recorded. That's all being fed out to, you know, computers. That data must be awesome. Okay. So LHCb is different. So we, because we're looking for these be quarks, be quarks tend to be produced along the beam line. So in a collision, the be quarks tend to fly sort of close to the beam pipe. So we built a detector that sort of pyramid cone shaped basically, that just looks in one direction. So we ignore, if you have your collision stuff goes everywhere, we ignore all the stuff over here and going off sideways. We're just looking in this little region close to the beam pipe where most of these be quarks are made. So is there a different aspect of the sensors involved in the collection of the be quark? Yeah, trajectories. There are some differences. So one of the differences is that one of the ways, you know, you've seen a be quark is that be quarks are actually quite long lived by particle standards. So they live for 1.5 trillionths of a second, which is if you're, if you're a fundamental particle is a very long time. Because you know, the Higgs boson, I think lives for about a trillionth of a trillionth of a second, or maybe even less than that. So these are quite long lived things, and they will actually fly a little distance before they decay. So they will fly, you know, a few centimetres, maybe if you're lucky, then they'll decay into other stuff. So what we need to do in the middle of the detector, you want to be able to see, you have your place where the protons crash into each other, and that produces loads of particles that come flying out. So you have loads of lines, loads of tracks that point back to that proton collision. And then you're looking for a couple of other tracks, maybe two or three that point back to a different place that's maybe a few centimetres away from the proton collision. And that's the sign that little be particle has flown a few centimetres and decayed somewhere else. So we need to be able to very accurately resolve the proton collision from the be particle decay. So we are the middle of our detector is very sensitive, and it gets very close to the collision. So you have this really beautiful delicate silicon detector that sits, I think it's seven millimetres from the beam. And the LHC beam has as much energy as a jumbo jet at takeoff. So it's enough to melt a tonne of copper. So you have this furiously powerful thing sitting next to this tiny delicate, you know, silicon sensor. So those aspects of our detector that are specialised to measure these particular be quarks that we're interested in. And is there, I mean, I remember seeing somewhere that there's some mention of matter and antimatter connected to the be, these beautiful quarks. Is that, what's the connection? Yeah, what's the connection there? Yeah, so there is a connection, which is that when you produce these be particles, these particles can, because you don't see the be quark, you see the thing that be quark is inside. So they're bound up inside what we call beauty particles, where the be quark is joined together with another quark or two, maybe two other quarks, depending on what it is. There are a particular set of these be particles that exhibit this property called oscillation. So if you make a, for the sake of argument, a matter version of one of these be particles, as it travels, because of the magic of quantum mechanics, it oscillates backwards and forwards between its matter and antimatter versions. So it does this weird flipping about backwards and forwards. And what we can use this for is a laboratory for testing the symmetry between matter and antimatter. So if the symmetry between antimatter and antimatter is precise, it's exact, then we should see these be particles decaying as often as matter as they do as antimatter, because this oscillation should be even. It should spend as much time in each state. But what we actually see is that one of the states it spends more time in, it's more likely to decay in one state than the other. So this gives us a way of testing this fundamental symmetry between matter and antimatter.

https://youtu.be/oxRnBkI7r68

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What is Deep Reinforcement Learning? (David Silver, DeepMind) | AI Podcast Clips

If it's okay, can we take a step back and kind of ask the basic question of what is, to you, reinforcement learning? So reinforcement learning is the study and the science and the problem of intelligence in the form of an agent that interacts with an environment. So the problem you're trying to solve is represented by some environment, like the world in which that agent is situated. And the goal of RL is clear, that the agent gets to take actions. Those actions have some effect on the environment, and the environment gives back an observation to the agent saying, you know, this is what you see or sense. And one special thing which it gives back is called the reward signal, how well it's doing in the environment. And the reinforcement learning problem is to simply take actions over time so as to maximize that reward signal. So a couple of basic questions. What types of RL approaches are there? So I don't know if there's a nice, brief, inwards way to paint a picture of sort of value-based, model-based, policy-based reinforcement learning. Yeah. So now if we think about, okay, so there's this ambitious problem definition of RL. It's really, you know, it's truly ambitious. It's trying to capture and encircle all of the things in which an agent interacts with an environment and say, well, how can we formalize and understand what it means to crack that? Now let's think about the solution method. Well, how do you solve a really hard problem like that? Well, one approach you can take is to decompose that very hard problem into pieces that work together to solve that hard problem. And so you can kind of look at the decomposition that's inside the agent's head, if you like, and ask, well, what form does that decomposition take? And some of the most common pieces that people use when they're kind of putting this system, the solution method together, some of the most common pieces that people use are whether or not that solution has a value function. That means, is it trying to predict, explicitly trying to predict how much reward it will get in the future? Does it have a representation of a policy? That means something which is deciding how to pick actions. Is that decision-making process explicitly represented? And is there a model in the system? Is there something which is explicitly trying to predict what will happen in the environment? And so those three pieces are to me, some of the most common building blocks. And I understand the different choices in RL as choices of whether or not to use those building blocks when you're trying to decompose the solution. Should I have a value function represented? Should I have a policy represented? Should I have a model represented? And there are combinations of those pieces. And of course, other things that you could add into the picture as well. But those three fundamental choices give rise to some of the branches of RL with which we're very familiar. And so those, as you mentioned, there is a choice of what's specified or modeled explicitly. And the idea is that all of these are somehow implicitly learned within the system. So it's almost a choice of how you approach a problem. Do you see those as fundamental differences or are these almost like small specifics, like the details of how you solve the problem, but they're not fundamentally different from each other? I think the fundamental idea is maybe at the higher level. The fundamental idea is the first step of the decomposition is really to say, well, how are we really going to solve any kind of problem where you're trying to figure out how to take actions and just from this stream of observations, you've got some agent situated in its sensory motor stream and getting all these observations in, getting to take these actions and what should it do? How can you even broach that problem? Maybe the complexity of the world is so great that you can't even imagine how to build a system that would understand how to deal with that. And so the first step of this decomposition is to say, well, you have to learn. The system has to learn for itself. And so note that the reinforcement learning problem doesn't actually stipulate that you have to learn. You could maximize your rewards without learning. It would just wouldn't do a very good job of it. So learning is required because it's the only way to achieve good performance in any sufficiently large and complex environment. So that's the first step. So that step gives commonality to all of the other pieces because now you might ask, well, what should you be learning? What does learning even mean? You know, in this sense, learning might mean, well, you're trying to update the parameters of some system, which is then the thing that actually picks the actions. And those parameters could be representing anything. They could be parameterizing a value function or a model or a policy. And so in that sense, there's a lot of commonality in that whatever is being represented there is the thing which is being learned and it's being learned with the ultimate goal of maximizing rewards. But the way in which you decompose the problem is really what gives the semantics to the whole system. Are you trying to learn something to predict well, like a value function or a model? Are you learning something to perform well, like a policy? And the form of that objective is kind of giving the semantics to the system. And so it really is at the next level down a fundamental choice. And we have to make those fundamental choices as system designers or enabler our algorithms to be able to learn how to make those choices for themselves. So then the next step you mentioned, the very first thing you have to deal with is, can you even take in this huge stream of observations and do anything with it? So the natural next basic question is, what is deep reinforcement learning? And what is this idea of using neural networks to deal with this huge incoming stream? So amongst all the approaches for reinforcement learning, deep reinforcement learning is one family of solution methods that tries to utilize powerful representations that are offered by neural networks to represent any of these different components of the solution, of the agent, like whether it's the value function or the model or the policy. The idea of deep learning is to say, well, here's a powerful toolkit that's so powerful that it's universal in the sense that it can represent any function and it can learn any function. And so if we can leverage that universality, that means that whatever we need to represent for our policy or for our value function or for our model, deep learning can do it. So that deep learning is one approach that offers us a toolkit that has no ceiling to its performance, that as we start to put more resources into the system, more memory and more computation and more data, more experience, more interactions with the environment, that these are systems that can just get better and better and better at doing whatever the job is they've asked them to do. Whatever we've asked that function to represent, it can learn a function that does a better and better job of representing that knowledge, whether that knowledge be estimating how well you're going to do in the world, the value function, whether it's going to be choosing what to do in the world, the policy, or whether it's understanding the world itself, what's going to happen next, the model. Nevertheless, the fact that neural networks are able to learn incredibly complex representations that allow you to do the policy, the model, or the value function is, at least to my mind, exceptionally beautiful and surprising. Was it surprising to you? Can you still believe it works as well as it does? Do you have good intuition about why it works at all and works as well as it does? I think, let me take two parts to that question. I think it's not surprising to me that the idea of reinforcement learning works because in some sense, I feel it's the only thing which can, ultimately. I feel we have to address it and there must be success is possible because we have examples of intelligence. It must at some level be possible to acquire experience and use that experience to do better in a way which is meaningful to environments of the complexity that humans can deal with. It must be. Am I surprised that our current systems can do as well as they can do? I think one of the big surprises for me and a lot of the community is really the fact that deep learning can continue to perform so well despite the fact that these neural networks that they're representing have these incredibly nonlinear kind of bumpy surfaces, which to our kind of low dimensional intuitions make it feel like surely you're just going to get stuck and learning will get stuck because you won't be able to make any further progress. And yet, the big surprise is that learning continues and these, what appear to be local optima turn out not to be because in high dimensions when we make really big neural nets, there's always a way out and there's a way to go even lower. And then you're still not in a local optima because there's some other pathway that will take you out and take you lower still. And so no matter where you are, learning can proceed and do better and better and better without bound. And so that is a surprising and beautiful property of neural nets, which I find elegant and beautiful and somewhat shocking that it turns out to be the case. As you said, which I really like, to our low dimensional intuitions, that's surprising. Yeah. We're very tuned to working within a three dimensional environment. And so to start to visualize what a billion dimensional neural network surface that you're trying to optimize over, what that even looks like, is very hard for us. And so I think that really, if you try to account for the essentially the AI winter, where people gave up on neural networks, I think it's really down to that lack of ability to generalize from low dimensions to high dimensions. Because back then we were in the low dimensional case. People could only build neural nets with 50 nodes in them or something. And to imagine that it might be possible to build a billion dimensional neural net, and it might have a completely different, qualitatively different property, was very hard to anticipate. And I think even now, we're starting to build the theory to support that. And it's incomplete at the moment, but all of the theory seems to be pointing in the direction that indeed, this is an approach which truly is universal, both in its representational capacity, which was known, but also in its learning ability, which is surprising. It makes one wonder what else we're missing due to our low dimensions intuitions that will seem obvious once it's discovered. I often wonder, when we one day do have AIs, which are superhuman in their abilities to understand the world, what will they think of the algorithms that we developed back now? Will it be looking back at these days and thinking that, will we look back and feel that these algorithms were naive first steps, or will they still be the fundamental ideas which are used even in a hundred thousand, 10,000 years? It's hard to know. They'll watch back to this conversation with a smile, maybe a little bit of a laugh. My sense is, I think just like when we used to think that the sun revolved around the earth, they'll see our systems of today, reinforcement learning as too complicated. That the answer was simple all along. There's something, just like you said in the game of Go, I mean, I love the systems of like cellular automata, that there's simple rules from which incredible complexity emerges. So it feels like there might be some very simple approaches, just like where Sutton says, right? These simple methods with compute over time seem to prove to be the most effective. I 100% agree. I think that if we try to anticipate what will generalize well into the future, I think it's likely to be the case that it's the simple, clear ideas which will have the longest legs and which will carry us furthest into the future. Nevertheless, we're in a situation where we need to make things work today. And sometimes that requires putting together more complex systems where we don't have the full answers yet as to what those minimal ingredients might be.

https://youtu.be/MrIFte_rOh0

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Simon Sinek: Leadership, Hard Work, Optimism and the Infinite Game | Lex Fridman Podcast #82

The following is a conversation with Simon Sinek, author of several books, including Start With Why, Leaders Eat Last, and his latest, The Infinite Game. He's one of the best communicators of what it takes to be a good leader, to inspire, to build businesses that solve big, difficult challenges. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcasts, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do one or two minutes of ads now, and never any ads in the middle that can break the flow of the conversation. I hope that works for you, and doesn't hurt the listening experience. Quick summary of the ads. Two sponsors, Cash App and Masterclass. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST, and signing up to Masterclass at masterclass.com slash LEX. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as one dollar. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency in the context of the history of money is fascinating. I recommend Ascent of Money as a great book on this history. Debits and credits on ledgers started around 30,000 years ago. The US dollar created over 200 years ago, and Bitcoin, the first decentralized cryptocurrency, released just over 10 years ago. So given that history, cryptocurrency's still very much in its early days of development, but it's still aiming to and just might redefine the nature of money. So again, if you get Cash App from the App Store or Google Play, and use the code LEXPODCAST, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. This show is sponsored by Masterclass. Sign up at masterclass.com slash LEX to get a discount and to support this podcast. When I first heard about Masterclass, I honestly thought it was too good to be true. For $180 a year, you get an all-access pass to watch courses from experts at the top of their field. To list some of my favorites, Chris Hatfield on space exploration, Neil deGrasse Tyson on scientific thinking and communication, Will Wright, the creator of SimCity, and Sims on game design. I love that game. Jane Goodall on conservation, Carlos Santana, one of my favorite guitarists on guitar, Garry Kasparov on chess. Obviously I'm Russian. I love Garry. Daniel Negrano on poker, one of my favorite poker players. Also Phil Ivey gives a course as well, and many, many more. Chris Hatfield explaining how rockets work and the experience of being launched into space alone is worth the money. By way of advice, for me, the key is not to be overwhelmed by the abundance of choice. Pick three courses you want to complete, watch each all the way through from start to finish. It's not that long, but it's an experience that will stick with you for a long time, I promise. It's easily worth the money. You can watch it on basically any device. Once again, sign up at masterclass.com slash Lex to get a discount and to support this podcast. And now here's my conversation with Simon Sinek. In the Infinite Game, your most recent book, you describe the finite game and the infinite game. So from my perspective of artificial intelligence and game theory in general, I'm a huge fan of finite games from the broad philosophical sense is something that in the robotics, artificial intelligence space, we know how to deal with. And then you describe the infinite game, which has no exact static rules, has no well-defined static objective, the players are known, unknown, they change, there's a dynamic element. So this is something that applies to business, politics, life itself. So can you try to articulate the objective function here of the infinite game or in the cliche, broad philosophical sense, what is the meaning of life? Go for the start with the softballs. Yeah, easy question first. So James Kars was the philosopher who originally articulated this concept of finite and infinite games. And when I learned about it, it really challenged my view of how the world works, right? Because I think we all think about winning and being the best and being number one. But if you think about it, only in a finite game can that exist, a game that has fixed rules, agreed upon objectives and known players like football or baseball. There's always a beginning, middle and end. And if there's a winner, there has to be a loser. Infinite games, as Kars describes them, as you said, have known and unknown players, which means anyone can join. It has a changeable rules, which means you can play however you want. And the objective is to perpetuate the game, to stay in the game as long as possible. In other words, there's no such thing as being number one or winning in a game that has no finish line. And what I learned is that when we try to win in a game that has no finish line, we try to be number, we try to be the best in a game that has no agreed upon objectives or agreed upon metrics or timeframes. There's a few consistent and predictable outcomes, the decline of trust, the decline of cooperation, the decline of innovation. And I find this fascinating because so many of the ways that we run most organizations is with a finite mindset. So trying to reduce the beautiful complex thing that is life or politics or business into something very narrow, and in that process, the reductionist process, you lose something fundamental that makes the whole thing work in the long term. So returning, I'm not gonna let you off the hook easy, what is the meaning of life? So what is the objective function that is worthwhile to pursue? Well, if you think about our tombstones, they have the date we were born and the date we died, but really it's what we do with the gap in between. There's a poem called the dash. It's the dash that matters. It's what we do between the time we're born and the time we die that gives our life meaning. And if we live our lives with a finite mindset, which means to accumulate more power or money than anybody else, to outdo everyone else, to be number one, to be the best, we don't take any of us with us. We don't take any of it with us. We just die. The people who get remembered, the way we wanna be remembered is what kind of people we were, right? Devoted mother, loving father, what kind of person we were to other people. Jack Welch just died recently. And the Washington Post, when it wrote the headline for his obit, it wrote, he pleased Wall Street and distressed employees. And that's his legacy. A finite player who is obsessed with winning, who leaves behind a legacy of short-term gains for a few and distress for many. That's his legacy. And every single one of us gets the choice of the kind of legacy we wanna have. Do we wanna be remembered for our contributions or our detractions? To live with a finite mindset, to live a career with a finite mindset, to be number one, be the best, be the most famous, you live a life like Jack Welch. You know, to live a life of service, to see those around us rise, to contribute to our communities, to our organizations, to leave them in better shape than we found them. That's the kind of legacy most of us would like to have. So day-to-day, when you think about what is the fundamental goals, dreams, motivations of an infinite game, of seeing your life, your career as an infinite game, what does that look like? I mean, I guess I'm sort of trying to stick on this personal ego, personal drive, the thing that, the fire, the reason we wanna wake up in the morning and the reason we can't go to bed because we're so excited. What is that? So for me, it's about having a just cause. It's about a vision that's bigger than me, that my work gets to contribute to something larger than myself. That's what drives me every day. I wake up every morning with a vision of a world that does not yet exist, a world in which the vast majority of people wake up every single morning inspired, feel safe at work, and return home fulfilled at the end of the day. It is not the world we live in. And so that we still have work to do is the thing that drives me. I know what my underlying values are. I wake up to inspire people to do the things that inspire them. And these are the things that, these are the things that I, these are my go-tos, my touch points that inspire me to keep working. I think of a career like an iceberg. If you have a vision for something, you're the only one who can see the iceberg underneath the ocean. But if you start working at it, a little bit shows up. And now a few other people can see what you imagine, be like, oh, right, yeah, no, I wanna help build that as well. And if you have a lot of success, then you have a lot of iceberg and people can see this huge iceberg and they say, you've accomplished so much. But what I see is all the work still yet to be done. Yet I still see the huge iceberg underneath the ocean. And so the growth, you talk about momentum. So the incremental revealing of the iceberg is what drives you. Well, it necessarily is incremental. What drives me is that, is the realization, is realizing the iceberg, bringing more of the iceberg from the unknown to the known, bringing more of the vision from the imagination to reality. And you have this fundamental vision of optimism. You call yourself an optimist. I mean, in this world, I have a sort of, I see myself a little bit as the main character from the Idiot by Dostoevsky, who is also kind of seen by society as a fool because he was optimistic. So one, can you maybe articulate where that sense of optimism comes from? And maybe also try to articulate your vision of the future where people are inspired, where optimism drives us. It's easy to forget that when you look at social media and so on, with the word toxicity and negativity can often get more likes, that optimism has a sort of a beauty to it. And I do hope it's out there. So can you try to articulate that vision? Yeah, so, I mean, for me, optimism and being an optimist is just seeing the silver lining in every cloud. Even in tragedy, it brings people together. And the question is, can we see that? Can you see the beauty that is in everything? I don't think optimism is foolishness. I don't think optimism is blindness, though it probably involves some naivete, the belief that things will get better, the belief that we tend towards the good, even in times of struggle or bad. You can't sustain war, but you can sustain peace. I think things that are stable are more sustainable, things that are optimistic are more sustainable than things that are chaotic. So you see people as fundamentally good. I mean, some people may disagree that you can't sustain peace, you can't sustain war. I mean, you don't have to, I think war is costly. It involves life and money, and peace does not involve those things. It requires work. I'm not saying it doesn't require work, but it doesn't drain resources, I think, the same way that war does. The people that would say that we will always have war, and I just talked to the historian of Stalin, is, would say that conflict and the desire for power and conflict is central to human nature. I concur. But something in your words also, perhaps it's the naive aspect that I also share, is that you have an optimism that people are fundamentally good. I'm an idealist, you know, and I think idealism is good. I'm not a fool to believe that the ideals that I imagine can come true. Of course, there'll never be world peace, but shouldn't we die trying? You know, I think that's the whole point. That's the whole point of vision. Vision should be idealistic, and it should be, for all practical purposes, impossible. But that doesn't mean we shouldn't try, and it's the milestones that we reach that take us closer to that ideal that make us feel that our life and our work have meaning, and we're contributing to something bigger than ourselves. You know, just because it's impossible doesn't mean we shouldn't try. As I said, we're still moving the ball down the field. We're still making progress. Things are still getting better, even if we never get to that ideal state. So I think idealism is a good thing. You know, in the word infinite game, one of the beautiful and tragic aspects of life, human life at least, at least from the biological perspective, is that it ends. So sadly, it's- To some people, yeah. Fine, it's tragic to some people, or is it ends, it ends- I think some people believe that it ends on the day you die, and some people think it continues on. There's, and there's a lot of different ways to think what continues on even looks like. But let me drag it back to the personal. Sure. Which is, how do you think about your own mortality? Are you afraid of death? How do you think about your own death? I definitely haven't accomplished everything I want to contribute to. I would like more time on this earth to keep working towards that vision. Do you think about the fact that it ends for you? Are you cognizant of- Of course I'm cognizant of it. I mean, aren't we all? I don't dwell on it. I'm aware of it. I know that my life is finite, and I know that I have a certain amount of time left on this planet, and I'd like to make that time be valuable. You know, some people would think that ideas kind of allow you to have a certain kind of immortality. Yeah. Maybe to linger on this kind of question, so first to push back on the, you said that everyone's cognizant of their mortality. There's a guy named Ernest Becker who would disagree that you basically say that most of human cognition is created by us trying to create an illusion and try to hide the fact from ourselves the fact that we're gonna die, to try to think that it's all gonna go on forever. But the fact that we know that it doesn't. Yes, but this mix of denial. I mean, I think the book's called Denial of Death. It's this constant denial that we're running away from. In fact, some would argue that the inspiration, the incredible ideas you've put out there, your TED Talk has been seen by millions and millions of people, right? It's just you trying to desperately fight the fact that you are biologically mortal. Your creative genius comes from the fact that you're trying to create ideas that live on long past you. Well, that's very nice of you. I mean, I would like my ideas to live on beyond me because I think that is a good test that those ideas have value in the lives of others. I think that's a good test that others would continue to talk about or share the ideas long after I'm gone, I think is perhaps the greatest compliment one can get for one's own work. But I don't think it's my awareness of my mortality that drives me to do it. It's my desire to contribute that drives me to do it. It's the optimist vision. It's the pleasure and the fulfillment you get from inspiring others. It's as pure as that. Let me ask, listen, I'm rushing. I'm trying to get you to- You're good, you're good. I'm enjoying it. Get you into these dark areas. You're good, I'm enjoying it. Is the ego tied up into it somehow? So your name is extremely well known. If your name wasn't attached to it, do you think you would act differently? I mean, for years I hated that my name was attached to it. I had a rule for years that I wouldn't have my face on the front page of the website. I had a fight with the publisher because I didn't want my name big on the book. I wanted it tiny on the book because I kept telling them it's not about me, it's about the ideas. They wanted to put my name on the top of my book, I refused. None of my books have my names on the top because I won't let them. They would like very much to put my name on the top of the book, but the idea has to be bigger than me. I'm not bigger than the idea. That's beautifully put. Do you think ego- But I also am aware that I've become, I've become recognized as the messenger. And even though I still think the message is bigger than me, I recognize that I have a responsibility as the messenger. And whether I like it or not is irrelevant. I accept the responsibility. I am happy to do it. I'm not sure how to phrase this, but there's a large part of the culture right now that emphasizes all the things that nobody disagrees with, which is health, sleep, diet, relaxation, meditation, vacation, are really important. And there's no, you know, it's like you can't really argue against that. In fact, people- Less sleep. Less- I'm just, I'm joking. Yes, well, that's the thing. I often speak to the fact that passion and love for what you're doing and the two words hard work, especially in the engineering fields, are more important than, are more important to prioritize than sleep. Even though sleep is really important, your mind should be obsessed with the hard work, with the passion, and so on. And then I get some pushback, of course, from people. What do you make sense of that? Is that just me, the crazy Russian engineer, really pushing hard work? Probably. I think that's a short-term strategy. I think if you sacrifice your health for the work, at some point it catches up with you. And at some point, it's like going, going, going, and you get sick. Your body will shut down for you if you refuse to take care of yourself. You know, you get sick. It's what happens. Sometimes, you know, more severe illness than something that just slows you down. So I think taking, like getting sleep, I mean, there've been studies on this that, you know, executives, for example, who get a full night's sleep and stop at a reasonable hour actually accomplish more, are more productive than people who work and burn the midnight oil because their brains are working better because they're well-rested. So, you know, working hard, yes, but when that works smart, I think that giving our minds and our bodies rest makes us more efficient. I think just driving, driving, driving, driving is a short-term strategy. So, but to push back on that a little bit, the annoying thing is you're like 100% right in terms of science, right? But the thing is, it's because you're 100% right, that weak part of your mind uses that fact to convince you, like what, so, you know, I get all kinds of, my mind comes up with all kinds of excuses to try to convince me that I shouldn't be doing what I'm doing. To rationalize. To rationalize. And so, what I have a sense, I think what you said about executives and leaders is absolutely right, but there's the early days. The early days of madness and passion. For sure. Then I feel like emphasizing sleep, thinking about sleep as giving yourself a way out from the fact that those early days, especially, can be suffering. As long, it's not sustainable. You know, it's not sustainable. Sure, if you're investing all that energy in something at the beginning to get it up and running, then at some point, you're gonna have to slow down. Or your body will slow you down for you. Like, you can choose or your body can choose. I mean. So, okay, so you don't think, from my perspective, it feels like people have gotten a little bit soft. But you're saying no. I think that there seems evidence that working harder and later have taken a back seat. I think we have to be careful with broad generalizations. But I think if you go into the workplace, there are people who would complain that more people now than before, you know, look at their watches and say, oh, it's five o'clock, go bye, right? Now, is that a problem with the people? You're saying it's the people giving themselves excuses and people don't work hard. Or is it the organizations aren't giving them something to believe in, something to be passionate about? We can't manufacture passion. You can't just tell someone be passionate. You know, that's not how it works. Passion's an output, not an input. Like if I believe in something and I wanna contribute all that energy to do it, we call that passion. You know, working hard for something we love is passion. Working hard for something we don't care about is called stress. But we're working hard either way. So I think the organizations bear some accountability and our leaders bear some accountability, which is if they're not offering a sense of purpose, if they're not offering us a sense of cause, if they're not telling us that our work is worth more than simply the money it makes, then yeah, I'm gonna come at five o'clock because I don't really care about making you money. Remember, we live in a world right now where a lot of people, rather a few people, are getting rich on the hard work of others. And so I think when people look up and say, well, why would I do that? If you're not gonna look after me and then you're gonna lay me off at the end of the year because you missed your arbitrary projections, you're gonna lay me off because you missed your arbitrary projections, then why would I offer my hard work and loyalty to you? So I don't think we can immediately blame people for going soft. I think we can blame leaders for their inability or failure to offer their people something bigger than making a product or making money. Yeah, so that's brilliant and start with why leaders last. Your books, you basically talk about what it takes to be a good leader. And so some of the blame should go on the leader, but how much of it is on finding your passion? How much is it on the individual? And allowing yourself to pursue that passion, pushing yourself to your limits to really take concrete steps along your path towards that passion. Yeah, there's mutual responsibility. There's mutual accountability. I mean, we're responsible as individuals to find the organizations and find the leaders that inspire us. And organizations are responsible for maintaining that flame and giving people who believe what they believed a chance to contribute. So to linger on it, have you by chance seen the movie Whiplash? Yes. Again, maybe I'm romanticizing suffering. Again. I'm not, it's the Russian. Yeah, the Russians love suffering. But people who haven't seen, it's the movie Whiplash as a drum instructor that pushes the drum musician to his limits to bring out the best in him. And there's a toxic nature to it. There's suffering in it. You've worked with a lot of great leaders, a lot of great individuals. Is that toxic relationship as toxic as it appears in the movie? Or is that fundamental? I've seen that relationship, especially in the past with Olympic athletes, especially in athletics, extreme performers seem to do wonders. It does wonders for me. There's some of my best relationships. Now, I'm not representative of everyone, certainly. But some of my best relationships for mentee and mentor have been toxic from an external perspective. What do you make of that movie? What do you make of that kind of relationship? That's not my favorite movie. Oh, okay. So you don't think that's a healthy, you don't think that kind of relationship is a great example of a great leader? I think it's a short-term strategy. I mean, look, being hard on someone is not the same as toxicity. If you go to the Marine Corps, a drill instructor will be very hard on their Marines. And then, but still even on the last day of bootcamp, they'll take their hat off and they'll become a human. But of all the drill instructors, the three or four main drill instructors assigned to a group of recruits, the one that they all want the respect of is the one that's the hardest on them. That's true. And you hear, there's plenty of stories of people who wanna earn the respect of a hard parent or a hard teacher. But fundamental, that parent, that teacher, that drill instructor has to believe in that person, has to see potential in them. It's not a formula, which is if I'm hard on people, they'll do well, which is there has to still be love. It has to be done with absolute love and it has to be done responsibly. I mean, some people can take a little more pressure than others, but it's not, I don't, I think it's irresponsible to think of it as a formula that if I'm just toxic at people, they will do well. It depends on their personalities. First of all, that works for some, but not all. And second of all, it can't be done willy-nilly. It has to still be done with care and love. And sometimes you can get equal or better results without all of the toxicity. So one of the, I guess toxicity on my part was a really bad word to use, but if we talk about what makes a good leader and just look at an example in particular, looking at Elon Musk, he's known to push people to their limits in a way that I think really challenges people in a way they've never been challenged before to do the impossible, but it can really break people. And jobs was hard and Amazon is hard. And, you know, but the thing that's important is none of them lie about it. You know, people ask me about Amazon all the time. Like Jeff Bezos never lied about it. You know, even the ones who like Amazon don't last more than a couple of years before they burn out. But when we're honest about the culture, then it gives people the opportunity who like to work in that kind of culture to choose to work in that kind of culture as opposed to pretending and saying, oh no, this is all, you know, it's all lovey-lovey here. And then you show up and it's the furthest thing from it. So, I mean, you know, I think the reputations of putting a lot of pressure on people to, you know, jobs was not an easy man to work for. He pushed people, but everyone who worked there was given the space to create and do things that they would not have been able to do anywhere else and work at a level that they didn't work anywhere else. And jobs didn't have all the answers. I mean, he pushed his people to come up with answers. He wasn't just looking for people to execute his ideas. And people did, people accomplished more than they thought they were capable of, which is wonderful. How do you, you're talking about the infinite game and not thinking about too short term, and yet you see some of the most brilliant people in the world being pushed by Ilan Musk to accomplish some of the most incredible things. When we're talking about autopilot, we're talking about some of the hardware engineering, they do some of the best work of their life and then leave. How do you balance that in terms of what it takes to be a good leader, what it takes to accomplish great things in your life? Yeah, so I think there's a difference between someone who can get a lot out of people in the short term and building an organization that can sustain beyond any individual. There's a difference. When you say beyond any individual, you mean beyond, beyond like if the leader dies. Correct, like could Tesla continue to do what it's doing without Ilan Musk? And you're perhaps implying, which is a very interesting question, that it cannot. I don't know. The argument you're making of this person who pushes everyone arguably is not a repeatable model. Is Apple the same without Steve Jobs or is it slowly moving in a different direction? Or has he established something that could be resurrected with the right leader? That was his dream, I think, is to build an organization that lives on beyond him. At least I remember reading that somewhere. I think that's what a lot of leaders desire, which is to create something that was bigger than them. Most businesses, most entrepreneurial ventures could not pass the school bus test, which is if the founder was hit by a school bus, would everyone continue the business without them or would they all just go find jobs? And the vast majority of companies would fail that test, especially in the entrepreneurial world, that if you take the inspired visionary leader away, the whole thing collapses. So is that a business or is that just a force of personality? And a lot of entrepreneurs face that reality, which is they have to be in every meeting, make every decision, come up with every idea, because if they don't, who will? And the question is, well, what have you done to build your bench? Sometimes it's ego, the belief that only I can. Sometimes it's just things did so well for so long that just forgot. And sometimes it's a failure to build the training programs or hire the right people that could replace you, who are maybe smarter and better. And browbeating people is only one strategy. I don't think it's necessarily the only strategy, nor is it always the best strategy. I think people get to choose the cultures they wanna work in. So this is why I think companies should be honest about the kind of culture that they've created. I heard a story about Apple where somebody came in from a big company. He had accomplished a lot and his ego was very large and he was going on about how he did this and he did that and he did this and he did that. And somebody from Apple said, we don't care what you've done. The question is, what are you gonna do? And that's, for somebody who wants to be pushed, that's the place you go because you choose to be pushed. Now, we all wanna be pushed to some degree. Anybody who wants to accomplish anything in this world wants to be pushed to some degree, whether it's through self-pressure or external pressure or public pressure, whatever it is. But I think this whole idea of one size fits all is a false narrative of how leadership works. But what all leadership requires is creating an environment in which people can work at their natural best. But you have a sense that it's possible to create a business where it lives on beyond you. So if we look at now, if we just look at this current moment, I just recently talked to Jack Dorsey, CEO of Twitter, and he's under a lot of pressure now. I don't know if you're aware of the news that he's being pushed out as a potential CEO of Twitter because he's the CEO already of an incredibly successful company. Plus he wants to go to Africa to live a few months in Africa to connect with the world that's outside of the Silicon Valley. And sort of there's this idea, well, can Twitter live without Jack? We'll find out. But you have a general, as a student of great leadership, you have a general sense that it's possible. Yeah, of course it's possible. I mean, what Bill Gates built with Microsoft may not have survived Steve Ballmer if the company weren't so rich, but Satya Nardala is putting it back on track again. It's become a visionary company again. It's attracting great talent again. It went through a period where they couldn't get the best talent and the best talent was leaving. Now people want to work for Microsoft again. Well, that's not because of pressure. Ballmer put more pressure on people, mainly to hit numbers than anything else. That didn't work. Yes. Right? And so the question is, what kind of pressure are we putting on people? We're putting on pressure people to hit numbers or hit arbitrary deadlines, or putting on pressure on people because we believe that they can do better work. And the work that we're trying to do is to advance a vision that's bigger than all of us. And if you're gonna put pressure on people, it better be for the right reason. Like if you're gonna put pressure on me, it better be for a worthwhile reason. If it's just to hit a goal, if it's just to hit some arbitrary data or some arbitrary number or make a stock price hit some target, you can keep it. I'm out of here. Yes. But if you want to put pressure on me because we are brothers and sisters in arms, working to advance a cause bigger than ourselves, that we believe whatever we're gonna build will significantly contribute to the greater good of society, then go ahead, I'll take the pressure. And if you look at the apples and if you look at the Elon Musk's, you know, the jobs in the Elon Musk, they fundamentally believe that what they were doing would improve society and it was for the good of humankind. And so the pressure, in other words, what they were doing was more important, more valuable than any individual on the team. And so the pressure they put on people served a greater good. And so we looked to the left and we looked to the right to each other and said, we're in this together. We accept this. We want this. But if it's just pressure to hit a number or make the widget move a little faster, that's soul sucking. That's not passion. That's stress. And I think a lot of leaders confuse that making people work hard is not what makes them passionate. Giving them something to believe in and work on is what drives passion. And when you have that, then turning up the pressure only brings people together, drives them further. If done the right way. Done the right way. Speaking of pressure, I'm gonna give you 90 seconds to answer the last question, which is if I told you that tomorrow was your last day to live, you talked about mortality, sunrise to sunset, can you tell me, can you take me through the day? What do you think that day would involve? You can't spend it with your family. I told you as well. I would probably want to fill all of my senses with things that excite my senses. I'd want to look at beautiful art. I'd want to listen to beautiful music. I'd want to taste incredible food. I'd want to smell amazing tastes. I'd want to touch, you know, something that's beautiful to touch. I'd want all of my senses to just be consumed with things that I find beautiful. And you talked about this idea of, we don't do it often these days, of just listening to music, turning off all the devices and actually taking in and listening to music. So as an addendum, if we were to talk about music, what song would you be blasting in this last day you're alive? Is it Led Zeppelin? What are we talking about? That I love. No, no. There's probably gonna be a Beatles song in there. There'll definitely be some Beethoven in there. The classics. The classics. Yeah, exactly. Thank you so much for talking today. Thank you for making time for it. Under pressure, we made it happen. It was great. Thanks for listening to this conversation with Simon Sinek. And thank you to our sponsors, Cash App and Masterclass. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST and signing up to Masterclass at masterclass.com slash LEX. If you enjoy this podcast, subscribe on YouTube, review it with five stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter, at Lex Friedman. And now let me leave you with some words from Simon Sinek. There are only two ways to influence human behavior. You can manipulate it, or you can inspire it. Thank you for listening. I hope to see you next time.

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Toward a Fundamental Theory of Physics (Stephen Wolfram) | AI Podcast Clips

What kind of computation do you think the fundamental laws of physics might emerge from? Just to clarify, so you've done a lot of fascinating work with kind of discrete kinds of computation that you know, you could sell your automata and we'll talk about it, have this very clean structure. It's a nice way to demonstrate that simple rules can create immense complexity. But what kind, you know, is that actually, are cellular automata sufficiently general to describe the kinds of computation that might create the laws of physics? Just to give, can you give a sense of what kind of computation do you think would create the laws of physics? So this is a slightly complicated issue because as soon as you have universal computation, you can in principle simulate anything with anything, but it is not a natural thing to do. And if you're asking, were you to try to find our physical universe by looking at possible programs in the computational universe of all possible programs, would the ones that correspond to our universe be small and simple enough that we might find them by searching that computational universe? We got to have the right basis, so to speak, we have got to have the right language in effect for describing computation for that to be feasible. So the thing that I've been interested in for a long time is what are the most structuralist structures that we can create with computation? So in other words, if you say a cellular automaton has a bunch of cells that are arrayed on a grid and it's very, you know, and every cell is updated in synchrony at a particular, you know, when there's a click of a clock, so to speak, and it goes a tick of a clock and every cell gets updated at the same time. That's a very specific, very rigid kind of thing. But my guess is that when we look at physics and we look at things like space and time, that what's underneath space and time is something as structureless as possible, that what we see, what emerges for us as physical space, for example, comes from something that is sort of arbitrarily unstructured underneath. And so I've been for a long time interested in kind of what are the most structuralist structures that we can set up? And actually what I had thought about for ages is using graphs, networks, where essentially so let's talk about space, for example. So what is space? It's a kind of a question I might ask. Back in the early days of quantum mechanics, for example, people said, oh, for sure, space is going to be discrete because all these other things we're finding are discrete, but that never worked out in physics. And so space and physics today is always treated as this continuous thing, just like you could have imagined it. I mean, the very first thing Euclid says in his sort of common notions is, you know, a point is something which has no part. In other words, there are points that are arbitrarily small and there's a continuum of possible positions of points. And the question is, is that true? And so, for example, if we look at, I don't know, a fluid like air or water, we might say, oh, it's a continuous fluid. We can pour it, we can do all kinds of things continuously. But actually we know, because we know the physics of it, that it consists of a bunch of discrete molecules bouncing around and only in the aggregate is it behaving like a continuum. And so the possibility exists that that's true of space too. People haven't managed to make that work with existing frameworks and physics. But I've been interested in whether one can imagine that underneath space and also underneath time is something more structureless. And the question is, is it computational? So there are a couple of possibilities. It could be computational, somehow fundamentally equivalent to a Turing machine. Or it could be fundamentally not. So how could it not be? It could not be, so a Turing machine essentially deals with integers, whole numbers, at some level. And, you know, it can do things like it can add one to a number. It can do things like this. It can also store whatever the heck it did. Yes. It has an infinite storage. But when one thinks about doing physics or sort of idealized physics or idealized mathematics, one can deal with real numbers, numbers with an infinite number of digits, numbers which are absolutely precise. And one can say, we can take this number and we can multiply it by itself. Are you comfortable with infinity in this context? Are you comfortable in the context of computation? Do you think infinity plays a part? I think that the role of infinity is complicated. Infinity is useful in conceptualizing things. It's not actualizable. Almost by definition, it's not actualizable. But do you think infinity is part of the thing that might underlie the laws of physics? I think that, no. I think there are many questions that you ask about, you might ask about physics, which inevitably involve infinity. Like when you say, you know, is faster than light travel possible? You could say, given the laws of physics, can you make something even arbitrarily large, even quote, infinitely large, that will make faster than light travel possible? Then you're thrown into dealing with infinity as a kind of theoretical question. But I mean, talking about, you know, sort of what's underneath space and time and how one can make a computational infrastructure. One possibility is that you can't make a computational infrastructure in a Turing machine sense, that you really have to be dealing with precise real numbers. You're dealing with partial differential equations, which have precise real numbers at arbitrarily closely separated points. You have a continuum for everything. Could be that that's what happens, that there's sort of a continuum for everything and precise real numbers for everything. And then the things I'm thinking about are wrong. You know, that's the risk you take if you're, you know, if you're trying to sort of do things about nature, is you might just be wrong. It's not, it's for me personally, it's kind of a strange thing. I've spent a lot of my life building technology where you can do something that nobody cares about, but you can't be sort of wrong in that sense, in the sense you build your technology and it does what it does. But I think, you know, this question of what, you know, what the sort of underlying computational infrastructure for the universe might be, it's, so it's sort of inevitable it's going to be fairly abstract, because if you're going to get all these things, like there are three dimensions of space, there are electrons, there are muons, there are quarks, there are this, you don't get to, if the model for the universe is simple, you don't get to have sort of a line of code for each of those things. You don't get to have sort of the muon case, the tau lepton case and so on. All of those things have to be emergent somehow. Right. So. Something deeper. Right. So that means it's sort of inevitable that it's a little hard to talk about what the sort of underlying structuralist structure actually is. Do you think human beings have the cognitive capacity to understand, if we're to discover it, to understand the kinds of simple structure from which these laws can emerge? Like do you think that's a hopeless pursuit? Well here's what I think. I think that, I mean I'm right in the middle of this right now. I'm telling you that I think this human, yeah, I mean this human has a hard time understanding, you know, a bunch of the things that are going on. But what happens in understanding is one builds waypoints. I mean if you said understand modern 21st century mathematics, starting from, you know, counting back in, you know, whenever counting was invented 50,000 years ago, whatever it was, right. That will be really difficult. But what happens is we build waypoints that allow us to get to higher levels of understanding. And we see the same thing happening in language. You know, when we invent a word for something, it provides kind of a cognitive anchor, a kind of a waypoint that lets us, you know, like a podcast or something. You could be explaining, well, it's a thing which works this way, that way, the other way. But as soon as you have the word podcast and people kind of societally understand it, you start to be able to build on top of that. And so I think, and that's kind of the story of science actually too. I mean, science is about building these kind of waypoints where we find this sort of cognitive mechanism for understanding something. Then we can build on top of it. You know, we have the idea of, I don't know, differential equations. We can build on top of that. We have this idea or that idea. So my hope is that if it is the case that we have to go all the way sort of from the sand to the computer and there's no waypoints in between, then we're toast. We won't be able to do that. Well eventually we might. So if we're, us clever apes are good enough at building those abstractions, eventually from sand we'll get to the computer, right? And it just might be a longer journey. The question is whether it is something that you asked, whether our human brains will quote understand what's going on. And that's a different question because for that it requires steps that are for, that are sort of from which we can construct a human understandable narrative. And that's something that I think I am somewhat hopeful that that will be possible. Although, you know, as of literally today, if you ask me, I'm confronted with things that I don't understand very well. And so this is a small pattern in a computation trying to understand the rules under which the computation functions. And it's an interesting possibility under which kinds of computations such a creature can understand itself. My guess is that within, so we didn't talk much about computational irreducibility, but it's a consequence of this principle of computational equivalence. And it's sort of a core idea that one has to understand, I think, which is, question is you're doing a computation, you can figure out what happens in the computation just by running every step in the computation and seeing what happens. Or you can say, let me jump ahead and figure out, you know, have something smarter that figures out what's going to happen before it actually happens. And a lot of traditional science has been about that act of computational reducibility. It's like, we've got these equations and we can just solve them and we can figure out what's going to happen. We don't have to trace all of those steps. We just jump ahead because we solved these equations. Okay, so one of the things that is a consequence of the principle of computational equivalence is you don't always get to do that. Many, many systems will be computationally irreducible in the sense that the only way to find out what they do is just follow each step and see what happens. Why is that? Well, if you have, if you're saying, well, we, with our brains, we're a lot smarter. We don't have to mess around like the little cellular automaton going through and updating all those cells. We can just, you know, use the power of our brains to jump ahead. But if the principle of computational equivalence is right, that's not going to be correct because it means that there's us doing our computation in our brains. There's a little cellular automaton doing its computation. And the principle of computational equivalence says these two computations are fundamentally equivalent. So that means we don't get to say we're a lot smarter than the cellular automaton and jump ahead because we're just doing computation that's of the same sophistication as the cellular automaton itself. That's computational reducibility. It's fascinating. But the, and that's a really powerful idea. I think that's both depressing and humbling and so on that while we in a cellular automaton are the same, but the question we're talking about, the fundamental laws of physics is kind of the reverse question. You're not predicting what's going to happen. You have to run the universe for that. But saying, can I understand what rules likely generated me? I understand, but the problem is to know whether you're right, you have to have some computational reducibility because we are embedded in the universe. If the only way to know whether we get the universe is just to run the universe, we don't get to do that because it just ran for 14.6 billion years or whatever. And we don't, you know, we can't rerun it, so to speak. So we have to hope that there are pockets of computational reducibility sufficient to be able to say, yes, I can recognize those are electrons there. And I think that it is a, it's a feature of computational irreducibility. It's sort of a mathematical feature that there are always an infinite collection of pockets of reducibility. The question of whether they land in the right place and whether we can sort of build a theory based on them is unclear. But to this point about, you know, whether we as observers in the universe built out of the same stuff as the universe can figure out the universe, so to speak, that relies on these pockets of reducibility. Without the pockets of reducibility, it won't work, can't work. But I think this question about how observers operate, it's one of the features of science over the last hundred years, particularly, has been that every time we get more realistic about observers, we learn a bit more about science. So for example, relativity was all about observers don't get to say when, you know, what's simultaneous with what. They just wait for the light signal to arrive to decide what's simultaneous. Or for example, in thermodynamics, observers don't get to say the position of every single molecule in a gas. They can only see the kind of large scale features. And that's why the second law of thermodynamics, law of entropy increase, and so on works. If you could see every individual molecule, you wouldn't conclude something about thermodynamics. You would conclude, oh, these molecules just all doing these particular things. You wouldn't be able to see this aggregate fact. So I strongly expect that, in fact, in the theories that I have, that one has to be more realistic about the computation and other aspects of observers in order to actually make a correspondence between what we experience. In fact, my little team and I have a little theory right now about how quantum mechanics may work, which is a very wonderfully bizarre idea about how the sort of thread of human consciousness relates to what we observe in the universe. But there's several steps to explain what that's about. What do you make of the mess of the observer at the lower level of quantum mechanics? Sort of the textbook definition with quantum mechanics kind of says that there's two worlds. One is the world that actually is, and the other is that's observed. What do you make sense of that kind of observing? Well, I think, actually, the ideas we've recently had might actually give away into this. And that's, I don't know yet. I mean, I think that's, it's a mess. I mean, the fact is there is a, one of the things that's interesting, and when people look at these models that I started talking about 30 years ago now, they say, oh, no, that can't possibly be right. You know, what about quantum mechanics? Right? You say, okay, tell me what is the essence of quantum mechanics? What do you want me to be able to reproduce to know that I've got quantum mechanics, so to speak? Well, and that question comes up, comes up very operationally, actually, because we've been doing a bunch of stuff with quantum computing. And there are all these companies that say, we have a quantum computer. We say, let's connect to your API and let's actually run it. And they're like, well, maybe you shouldn't do that yet. We're not quite ready yet. And one of the questions that I've been curious about is, if I have five minutes with a quantum computer, how can I tell if it's really a quantum computer or whether it's a simulator at the other end? Right? And turns out it's really hard. It turns out there isn't, it's like a lot of these questions about sort of what is intelligence, what's life. It's a boring test for quantum computing. That's right. That's right. It's like, are you really a quantum computer? And I think the simulation. Yes, exactly. Is it just a simulation or is it really a quantum computer? Same issue all over again. So this whole issue about the sort of mathematical structure of quantum mechanics and the completely separate thing that is our experience in which we think definite things happen, whereas quantum mechanics doesn't say definite things ever happen. Quantum mechanics is all about the amplitudes for different things to happen. But yet our thread of consciousness operates as if definite things are happening. To linger on the point, you've kind of mentioned the structure that could underlie everything and this idea that it could perhaps have something like a structure of a graph. Can you elaborate why your intuition is that there's a graph structure of nodes and edges and what it might represent? Right. Okay. So the question is, what is in a sense the most structuralist structure you can imagine? Right? And in fact, what I've recently realized in the last year or so, I have a new most structuralist structure. By the way, the question itself is a beautiful one and a powerful one in itself. So even without an answer, just the question is a really strong question. Right. But what's your new idea? Well it has to do with hypergraphs. Actually what is interesting about the sort of model I have now is, it's a little bit like what happened with computation. Everything that I think of as, oh, well maybe the model is this, I discover it's equivalent. And that's quite encouraging because it's like I could say, well, I'm going to look at trivalent graphs with three edges for each node and so on. Or I could look at this special kind of graph. Or I could look at this kind of algebraic structure. And it turns out that the things I'm now looking at, everything that I've imagined that is a plausible type of structuralist structure is equivalent to this. So what is it? Well, a typical way to think about it is, well, so you might have some collection of tuples, collection of, let's say numbers. So you might have 1, 3, 5, 2, 3, 4, little, just collections of numbers, triples of numbers, let's say, quadruples of numbers, pairs of numbers, whatever. And you have all these sort of floating little tuples. They're not in any particular order. And that sort of floating collection of tuples, and I told you this was abstract, represents the whole universe. The only thing that relates them is when a symbol is the same, it's the same, so to speak. So if you have two tuples and they contain the same symbol, let's say at the same position of the tuple, the first element of the tuple, then that represents a relation. Okay, so let me try and peel this back. Wow, okay. I told you it's abstract, but this is the... So the relationship is formed by some aspect of sameness. Right. So think about it in terms of a graph. So a graph, a bunch of nodes, let's say you number each node, okay? Then what is a graph? A graph is a set of pairs that say this node has an edge connecting it to this other node. So that's the... And a graph is just a collection of those pairs that say this node connects to this other node. So this is a generalization of that, in which instead of having pairs, you have arbitrary n-tuples. That's it. That's the whole story. And now the question is, okay, so that might represent the state of the universe. How does the universe evolve? What does the universe do? And so the answer is that what I'm looking at is transformation rules on these hypergraphs. In other words, you say this, whenever you see a piece of this hypergraph that looks like this, turn it into a piece of a hypergraph that looks like this. So on a graph, it might be when you see the subgraph, when you see this thing with a bunch of edges hanging out in this particular way, then rewrite it as this other graph. And so that's the whole story. So the question is, what... So now you say, I mean, as I say, this is quite abstract. And one of the questions is, where do you do those updating? So you've got this giant graph. What triggers the updating? What's the ripple effect of it? Is it... Yes. And I suspect everything's discrete, even in time. So... Okay, so the question is, where do you do the updates? Yes. And the answer is, the rule is, you do them wherever they apply. And you do them, the order in which the updates is done is not defined. That is, you can do them, so there may be many possible orderings for these updates. Now the point is, imagine you're an observer in this universe. So and you say, did something get updated? Well, you don't in any sense know until you yourself have been updated. So in fact, all that you can be sensitive to is essentially the causal network of how an event over there affects an event that's in you. That doesn't even feel like observation. That's like, that's something else. You're just part of the whole thing. Yes, you're part of it. But even to have... So the end result of that is all you're sensitive to is this causal network of what event affects what other event. I'm not making a big statement about sort of the structure of the observer. I'm simply saying, I'm simply making the argument that what happens, the microscopic order of these rewrites is not something that any observer, any conceivable observer in this universe can be affected by. Because the only thing the observer can be affected by is this causal network of how the events in the observer are affected by other events that happen in the universe. So the only thing you have to look at is the causal network. You don't really have to look at this microscopic rewriting that's happening. So these rewrites are happening wherever they... They happen wherever they feel like. Causal network, you said that there's not really... so the idea would be an undefined, like what gets updated, the sequence of things is undefined. That's what you mean by the causal network, but then the... No, the causal network is given that an update has happened, that's an event. Then the question is, is that event causally related to? Does that event... If that event didn't happen, then some future event couldn't happen yet. And so you build up this network of what affects what. And so what that does, so when you build up that network, that's kind of the observable aspect of the universe in some sense. And so then you can ask questions about how robust is that observable network of what's happening in the universe. Okay, so here's where it starts getting kind of interesting. So for certain kinds of microscopic rewriting rules, the order of rewrites does not matter to the causal network. And so this is, okay, mathematical logic moment, this is equivalent to the Church-Rossa property or the confluence property of rewrite rules. And it's the same reason that if you are simplifying an algebraic expression, for example, you can say, oh, let me expand those terms out, let me factor those pieces. Doesn't matter what order you do that in, you'll always get the same answer. And that's, it's the same fundamental phenomenon that causes for certain kinds of microscopic rewrite rules, that causes the causal network to be independent of the microscopic order of rewritings. Why is that property important? Because it implies special relativity. I mean, the reason it's important is that that property, special relativity says you can look at these sort of, you can look at different reference frames, you can have different, you can be looking at your notion of what space and what time can be different, depending on whether you're traveling at a certain speed, depending on whether you're doing this, that and the other. But nevertheless, the laws of physics are the same. That's what the principle of special relativity says, is laws of physics are the same independent of your reference frame. Well, it turns out this sort of change of the microscopic rewriting order is essentially equivalent to a change of reference frame, or at least there's a sub part of how that works that's equivalent to change of reference frame. So, somewhat surprisingly, and sort of for the first time in forever, it's possible for an underlying microscopic theory to imply special relativity, to be able to derive it. It's not something you put in as a, this is a, it's something where this other property, causal invariance, which is also the property that implies that there's a single thread of time in the universe. It might not be the case that that's, that is the, that's what would lead to the possibility of an observer thinking that definite stuff happens. Otherwise, you've got all these possible rewriting orders, and who's to say which one occurred. But with this causal invariance property, there's a notion of a definite thread of time. It sounds like that kind of idea of time, even space, would be emergent from the system. Oh yeah. No, I mean- So it's not a fundamental part of the system. No, no. At a fundamental level, all you've got is a bunch of nodes connected by hyper edges or whatever. So there's no time, there's no space. That's right. And, but the thing is that it's just like imagining, imagine you're just dealing with a graph, and imagine you have something like a, you know, like a honeycomb graph, where you have a bunch of hexagons. You know, that graph at a microscopic level, it's just a bunch of nodes connected to other nodes. But at a macroscopic level, you say that looks like a honeycomb, you know, lattice. It looks like a two-dimensional, you know, manifold of some kind. It looks like a two-dimensional thing. If you connect it differently, if you just connect all the nodes one to another, and kind of a sort of linked list type structure, then you'd say, well, that looks like a one-dimensional space. But at the microscopic level, all these are just networks with nodes. The macroscopic level, they look like something that's like one of our sort of familiar kinds of space. And it's the same thing with these hyper graphs. Now, if you ask me, have I found one that gives me three-dimensional space? The answer is not yet. So we don't know, you know, this is one of these things we're kind of betting against nature, so to speak. And I have no way to know. So there are many other properties of this, this kind of system that have a very beautiful actually and very suggestive. And it will be very elegant if this turns out to be right, because it's very clean. I mean, you start with nothing and everything gets built up. Everything about space, everything about time, everything about matter, it's all just emergent from the properties of this extremely low-level system. And that will be pretty cool if that's the way our universe works. Now, do I, on the other hand, the thing that I find very confusing is, let's say we succeed. Let's say we can say this particular sort of hyper graph rewriting rule gives the universe. Just run that hyper graph rewriting rule for enough times and you'll get everything. You'll get this conversation we're having. You'll get everything. It's that if we get to that point and we look at what is this thing, what is this rule that we just have that is giving us our whole universe? How do we think about that thing? Let's say, turns out the minimal version of this, and this is kind of cool thing for a language designer like me, the minimal version of this model is actually a single line of orphan language code. Which I wasn't sure was going to happen that way, but it's kind of, no, we don't know what, that's just the framework to know the actual particular hyper graph that might be a longer, the specification of the rules might be slightly longer. How does that help you accept marveling in the beauty and the elegance of the simplicity that creates the universe? Does that help us predict anything? Not really because of the irreducibility. That's correct. That's correct. But so the thing that is really strange to me, and I haven't wrapped my brain around this yet, is one keeps on realizing that we're not special in the sense that we don't live at the center of the universe. We don't blah, blah, blah. And yet if we produce a rule for the universe and it's quite simple and we can write it down in a couple of lines or something, that feels very special. How did we come to get a simple universe when many of the available universes, so to speak, are incredibly complicated? It might be a quintillion characters long. Why did we get one of the ones that's simple? And so I haven't wrapped my brain around that issue yet. If indeed we are in such a simple, the universe is such a simple rule, is it possible that there is something outside of this that we are in a kind of what people call the simulation, right? That we're just part of a computation that's being explored by a graduate student in an alternate universe? Well, you know, the problem is we don't get to say much about what's outside our universe because by definition our universe is what we exist within. Now can we make a sort of almost theological conclusion from being able to know how our particular universe works? Interesting question. I don't think that if you ask the question, could we, and it relates again to this question about extraterrestrial intelligence, you know, we've got the rule for the universe. Was it built in on purpose? Hard to say. That's the same thing as saying we see a signal from, you know, that we're, you know, receiving from some, you know, random star somewhere and it's a series of pulses and, you know, it's a periodic series of pulses, let's say. Was that done on purpose? Can we conclude something about the origin of that series of pulses? Just because it's elegant does not necessarily mean that somebody created it or that we can even comprehend what would create it. Yeah, I think it's the ultimate version of the sort of identification of the techno signature question. I think the ultimate version of that is was our universe a piece of technology, so to speak, and how on earth would we know? Because but I mean, it'll be, it's, I mean, you know, in the kind of crazy science fiction thing you could imagine, you could say, oh, somebody is going to have, you know, there's going to be a signature there, it's going to be, you know, made by so and so. But there's no way we could understand that, so to speak. And it's not clear what that would mean. Because the universe simply, you know, this, if we find a rule for the universe, we're not we're simply saying that rule represents what our universe does. We're not saying that that rule is something running on a big computer and making our universe. It's just saying that represents what our universe does in the same sense that, you know, laws of classical mechanics, differential equations, whatever they are, represent what mechanical systems do. It's not that the mechanical systems are somehow running solutions to those differential equations, those differential equations just representing the behavior of those systems. So what's the gap in your sense to linger on the fascinating, perhaps slightly sci-fi question? What's the gap between understanding the fundamental rules that create a universe and engineering a system, actually creating a simulation ourselves? You've talked about sort of, you've talked about, you know, nanoengineering kind of ideas that are kind of exciting, actually creating some ideas of computation in the physical space. How hard is it as an engineering problem to create the universe once you know the rules that create it? Well, that's an interesting question. I think the substrate on which the universe is operating is not a substrate that we have access to. I mean, the only substrate we have is that same substrate that the universe is operating in. So if the universe is a bunch of hypergraphs being rewritten, then we get to attach ourselves to those same hypergraphs being rewritten. We don't get to, and if you ask the question, you know, is the code clean? You know, can we write nice, elegant code with efficient algorithms and so on? Well, that's an interesting question. How, you know, that's this question of how much computational reducibility there is in the system. I mean, I've seen some beautiful cellular automata that basically create copies of itself within itself, right? That's the question, whether it's possible to create, like whether you need to understand the substrate or whether you can just- Yeah, well, right. I mean, so one of the things that is sort of one of my slightly sci-fi thoughts about the future, so to speak, is, you know, right now, if you poll typical people, you say, do you think it's important to find the fundamental theory of physics? You get, because I've done this poll informally at least, it's curious, actually, you get a decent fraction of people saying, oh yeah, that would be pretty interesting. I think that's becoming, surprisingly enough, more, I mean, a lot of people are interested in physics in a way that, like without understanding it, just kind of watching scientists, a very small number of them, struggle to understand the nature of our reality. Right. And I think that's somewhat true, and in fact, in this project that I'm launching into to try and find the fundamental theory of physics, I'm going to do it as a very public project. I mean, it's going to be live streamed and all this kind of stuff, and I don't know what will happen. It'll be kind of fun. I mean, I think that it's the interface to the world of this project. I mean, I figure one feature of this project is, you know, unlike technology projects that basically are what they are, this is a project that might simply fail, because it might be the case that it generates all kinds of elegant mathematics that has absolutely nothing to do with the physical universe that we happen to live in. Well, okay, so we're talking about kind of the quest to find the fundamental theory of physics. The first point is, you know, it's turned out it's kind of hard to find the fundamental theory of physics. People weren't sure that that would be the case. Back in the early days of applying mathematics to science, 1600s and so on, people were like, oh, in 100 years we'll know everything there is to know about how the universe works. It turned out to be harder than that. And people got kind of humble at some level, because every time we got to sort of a greater level of smallness and studying the universe, it seemed like the math got more complicated and everything got harder. Basically, when I was a kid, basically, I started doing particle physics, and when I was doing particle physics, I always thought finding the fundamental, fundamental theory of physics, that's a kooky business, we'll never be able to do that. But we can operate within these frameworks that we built for doing quantum field theory and general relativity and things like this, and it's all good and we can figure out a lot of stuff. Did you even at that time have a sense that there's something behind that too? Sure, sure. I just didn't expect that. I thought in some rather un... It's actually kind of crazy, thinking back on it, because it's kind of like there was this long period in civilization where people thought the ancients had it all figured out and we'll never figure out anything new. And to some extent, that's the way I felt about physics when I was in the middle of doing it, so to speak, was, you know, we've got quantum field theory, it's the foundation of what we're doing. And there's, you know, yes, there's probably something underneath this, but we'll sort of never figure it out. But then I started studying simple programs in the computational universe, things like cellular automata and so on. And I discovered that they do all kinds of things that were completely at odds with the intuition that I had had. And so after that, after you see this tiny little program that does all this amazingly complicated stuff, then you start feeling a bit more ambitious about physics and saying, maybe we could do this for physics too. And so that's, that got me started years ago now, in this kind of idea of could we actually find what's underneath all of these frameworks like quantum field theory, general relativity and so on. And people perhaps don't realize as clearly as they might, that, you know, the frameworks we're using for physics, which is basically these two things, quantum field theory, sort of the theory of small stuff and general relativity, theory of gravitation and large stuff. Those are the two basic theories and they're a hundred years old. I mean, general relativity was 1915, quantum field theory, well 1920s. So basically a hundred years old and they've, it's been a good run. There's a lot of stuff been figured out, but what's interesting is the foundations haven't changed in all that period of time. Even though the foundations had changed several times before that in the 200 years earlier than that. And I think the kinds of things that I'm thinking about, which are sort of really informed by thinking about computation and the computational universe, it's a different foundation. It's a different set of foundations and might be wrong, but it is at least, you know, we have a shot. And I think it's, you know, to me, it's, you know, my personal calculation for myself is, is you know, if it turns out that the finding the fundamental theory of physics, it's kind of low hanging fruit, so to speak, it'd be a shame if we just didn't think to do it. You know, if people just said, oh, you'll never figure that stuff out. Let's, you know, and it takes another 200 years before anybody gets around to doing it. You know, I think it's, I don't know how low hanging this fruit actually is. It may be, you know, it may be that it's kind of the wrong century to do this project. I mean, I think the, the, the cautionary tale for me, you know, I think about things that I've tried to do in technology where people thought about doing them a lot earlier. My favorite example is probably Leibniz who, who thought about making essentially encapsulating the world's knowledge in a computational form in the late 1600s and did a lot of things towards that and basically, you know, we finally managed to do this, but he was 300 years too early and that's the, that's kind of the, in terms of life planning, it's kind of like avoid things that can't be done in your, in your century, so to speak. Yeah. Timing, timing is everything. So you think if we kind of figure out the underlying rules that can create from which quantum field theory and general relativity can emerge, do you think that'll help us unify it at that level of abstraction? Oh, we'll know it completely. We'll know how that all fits together. Yes, without a question. And I mean, it's already, even the things I've already done, they're very, you know, it's very, very elegant actually, how, how things seem to be fitting together. Now, you know, is it right? I don't know yet. It's awfully suggestive. If it isn't right, it's then the designer of the universe should feel embarrassed, so to speak, because it's a really good way to do it. And your intuition in terms of designing universe, does God play dice? Is there, is there randomness in this thing or is it deterministic? So the kind of graph- That's a little bit of a complicated question because when you're dealing with these things that involve these rewrites that have, okay. Even randomness is an emergent phenomenon perhaps? Yes. I mean, it's a, yeah, well, randomness in many of these systems, pseudo-randomness and randomness are hard to distinguish. In this particular case, the current idea that we have about measurement and quantum mechanics is something very bizarre and very abstract. And I don't think I can yet explain it without kind of yakking about very technical things. Eventually I will be able to. But if that's right, it's kind of a, it's a weird thing because it slices between determinism and randomness in a weird way that hasn't been sliced before, so to speak. So like many of these questions that come up in science, where it's like, is it this or is it that? Turns out the real answer is it's neither of those things. It's something kind of different and sort of orthogonal to those categories. And so that's the current, this week's idea about how that might work. But we'll see how that unfolds. I mean, there's this question about a field like physics and sort of the quest for fundamental theory and so on. And there's both the science of what happens and there's the sort of the social aspect of what happens. Because in a field that is basically as old as physics, we're at, I don't know what it is, fourth generation, I don't know, fifth generation, I don't know what generation it is of physicists. And like, I was one of these, so to speak. And for me, the foundations were like the pyramids, so to speak. You know, it was that way and it was always that way. It is difficult in an old field to go back to the foundations and think about rewriting them. It's a lot easier in young fields where you're still dealing with the first generation of people who invented the field. And it tends to be the case that the nature of what happens in science tends to be, you know, you'll get, typically the pattern is some methodological advance occurs. And then there's a period of five years, 10 years, maybe a little bit longer than that, where there's lots of things that are now made possible by that methodological advance, whether it's, you know, I don't know, telescopes or whether that's some mathematical method or something. It's, you know, there's a something, something happens, a tool gets built, and then you can do a bunch of stuff. And there's a bunch of low hanging fruit to be picked. And that takes a certain amount of time. After that, all that low hanging fruit is picked, then it's a hard slog for the next however many decades or century or more to get to the next sort of level at which one can do something. And it tends to be the case that in fields that are in that kind of, I wouldn't say cruise mode because it's really hard work, but it's very hard work for very incremental progress.

https://youtu.be/VPaBRjSrq2A

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Arguing Machines: Tesla Autopilot vs Neural Network

Our group at MIT is studying semi-autonomous vehicles. Now that includes both inward-facing sensors for driver state sensing and outward-facing sensors for scene perception and the control planning, motion planning task. Now today we'll look at the second part of that, at the perception and the control of the vehicle. On the dashboard of the Tesla, there's a Jetson TX2 with a camera sitting on top of it. We have a neural network end-to-end running on the Jetson that's detecting the forward roadway, taking it as a sequence of images and producing steering commands. We also have here a Tesla that has a perception control system on it in the form of Autopilot. It's using a monocular camera, this is the hardware version 1. It's making decisions based on this single video stream producing steering commands. And we'll look at two systems arguing today, Autopilot arguing against a neural network and we'll see what comes out. In this concept, Tesla Autopilot is the primary AI system and the end-to-end neural network is the secondary AI system. And the disagreement between the two is used to detect challenging situations and seek human driver supervision. It is important to clarify that this is not a criticism of Autopilot. Of the two, it is by far the superior perception control system. The question is whether the argument between the two systems can create transparency that leverage the human driver as a supervisor of challenging driving scenarios. Scenarios that may have not otherwise been caught by Autopilot alone. This is a general framework for supervision of black box AI systems that we hope can help save human lives. In the paper accompanying this video, we show that we can predict driver-initiated disengagement of Autopilot with a simple threshold on the disagreement of steering decisions. We believe this is a very surprising and powerful result that hopefully may be useful for human supervision of any kind of AI system that operates in the real world and makes decisions where errors may result in loss of human life. A quick note that we use the intensity of red color on the disagreement detected text as the visualization of disagreement magnitude. In retrospect, this is not an effective visualization because visually it looks like the two systems are constantly disagreeing. They are not. The intent of the on-road demo is to show successful real-time operation of the Argue Machines framework. The paper that goes along with this approach, on the other hand, is where we show the predictive power of this approach on large-scale naturalistic data. Inside the car, we have a screen over the center stack and a Jetson TX2 with a camera on top of it. The camera is feeding a video stream into the Jetson. On the Jetson is a neural network that's predicting the steering command, taking in end-to-end the video stream from the forward roadway and as an output for the neural network giving a steering command. That's being shown as pink on this display. The pink line is the steering suggested by the neural network. Cyan line is the steering of the car, of the Tesla that we're getting from the CAN bus. When I move the steering wheel around, we see that live in real-time mapped on this graphic here showing in cyan the steering position of the car. Up top is whenever the two disagree significantly, the disagreement detected red sign appears showing that there's a disagreement. I'll demonstrate that on road. We're now driving on the highway with the Tesla being controlled by autopilot. The Jetson TX2 on the dashboard with a camera plugged in has a neural network running on it end-to-end. The input to the neural network is a sequence of images and the output is steering commands. Now there's two perception control systems working here. One is autopilot, the other one is an end-to-end neural network. Both the steering commands from both are being visualized on the center stack here. In pink is the output from the neural network, in cyan is the output from autopilot. And whenever there is some disagreement or a lot of disagreement, up on top there's a disagreement detected text that becomes more intensely red the greater the disagreement. At the bottom of the screen is the input to the neural network that is a sequence of images that are subtracted from each other capturing the temporal dynamics of the scene. All right, so why is this interesting? There's two perception control systems, two AI systems taking in the external world using a monocular camera and making a prediction, making steering commands to control the vehicle. Now whenever those two systems disagree, that's interesting for many reasons. One, the disagreement is an indicator that from a visual perspective, from a perception perspective the situation is challenging for those systems. Therefore you might want to bring the driver's attention to the situation so they take control back from the vehicle. It's also interesting for validating systems. So if you propose a new perception control system, you can imagine putting it into a car to go along with autopilot or with other similar systems to see how well that new system works with autopilot when it disagrees, when it doesn't. And the disagreement from the computer vision aspect is also really interesting for detecting edge cases. So the challenging thing about driving or for building autonomous vehicles is that most of the driving is really boring. The interesting bits happen rarely. So one of the ways to detect those interesting bits, the edge cases, is to look at the disagreement between these perception systems, to look at cases when the two perception systems diverge and therefore they struggle with that situation. Finally, when the driver is controlling and takes control of the vehicle, which I am doing now, and when my steering decisions, my turning of the steering wheel is such that the neural network disagrees, it perhaps means that I am either distracted or the situation is visually challenging, therefore I should pay extra attention. So it makes sense for the system to warn you about that situation. Now the interesting thing about Tesla and the autopilot system is that if we instrument a lot of these vehicles, as we have, we've instrumented 20 Teslas as part of the MIT Autonomous Vehicle Study and are collecting month after month, year after year now, data, video in and video out, we can use that data to train better systems, to train perception systems, control, motion planning, and the end-to-end network that we're showing today. We have the large-scale data to train the learning-based perception and control algorithms. Now an important thing to mention is that these systems were designed to work on the highway, at highway speeds. So the kind of disagreement it's trained to detect is disagreement between autopilot and the neural network in highway situations. So the visual characteristics of lane markings deteriorating or construction zones and so on. Now the details, and if you're interested in more, can be found in a paper titled Arguing Machines.

https://youtu.be/YBvcKtLKNAw

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Exponential Progress of AI: Moore's Law, Bitter Lesson, and the Future of Computation

This video is looking at exponential progress for artificial intelligence from a historical perspective and anticipating possible future trajectories that may or may not lead to exponential progress of AI. At the center of this discussion is a blog post called The Bitter Lesson by Rich Sutton, which ties together several different concepts, specifically looking at the role of computation in the progress of artificial intelligence and computer science in general. This blog post and the broader discussion is part of the AI Paper Club on our Discord server. If you want to join the discussion, everyone is welcome. Link is in the description. So I'd like to first discuss the argument made in The Bitter Lesson by Rich Sutton that discusses the role of computation in the progress of artificial intelligence, and then I'd like to look into the future and see what are the possible ideas that will carry the flag of exponential improvement in AI, whether it is in computation with the continuation of Moore's Law or a bunch of other ideas in both hardware and software. So, The Bitter Lesson. The basic argument contains several ideas. The central idea is that most of the improvement in artificial intelligence over the past 70 years has occurred due to the improvement of computation versus improvement in algorithms. And when I say improvement of computation, I mean Moore's Law, transistor count doubling every two years. And so it wasn't the innovation in the algorithms, but instead the same brute force algorithms that were sufficiently general and were effective at leveraging computation were the ones associated with successful progress of AI. So, put another way, general methods that are automated and can leverage big compute are better than specialized, fine-tuned, human expertise injected methods that leverage small compute. And when I say small compute, I'm referring to any computational resources available today, because with the exponential growth of computational resources over the past many decades with Moore's Law, basically anything you have today is much smaller than anything you'll have tomorrow. That's how exponential growth works. And looking from yet another perspective of human expertise, human knowledge injection, AI that discovers a solution by itself is better than AI that encodes human expertise and human knowledge. Rich Sutton also in his blog post argues that the two categories of techniques that were most capable of leveraging massive amounts of computation are learning techniques and search techniques. Now, by way of example, you can think of search techniques as the ones that were used to beat Garry Kasparov, IBM Deep Blue in the game of chess. These are these brute force search techniques that were criticized at the time for being for their brute force nature. And the same, I would say, is the brute force learning techniques of Google Deep Mind that beat the world champion at the game of Go. Now, the reason I call self-play mechanism brute force is because the reinforcement learning methods of today are fundamentally wasteful in terms of how efficient they are at learning. And that's the critical thing about brute force methods that Rich Sutton argues, that these methods are able to leverage computation. So they may not be efficient or they may not have the kind of cleverness that human expertise might provide, but they're able to leverage computation. And therefore, as computation exponentially grows, they're able to outperform everything else. And the blog post provides a few other examples of speech recognition that started with heuristics that went to the statistical methods of HMMs. And finally, now the recent big successes in speech recognition and natural language processing in general with neural networks. And the same in the computer vision world, the fine-tuned human expertise feature selection of everything that led up to SIFT. And then finally, with the big image net moment and showed that neural networks able to discover automatically the hierarchy of features required to successfully complete different computer vision tasks. I think this is a really thought-provoking blog post because it suggests that when we develop methods, whether it's in the software or the hardware, we should be thinking about long-term progress, the impact of our ideas, not for this year, but in five years, 10 years, 20 years from now. So when you look at the progress of the field from that perspective, there's certain things that are not gonna hold up. And Rich argues that actually majority of things that we work on in the artificial intelligence community, especially in the academic circles, is too focused on the injection of human expertise, because that is how you're able to get incremental improvement that you can publish on and then sort of add publications to your resume. You have career success and progress, and you feel better because you're injecting your own expertise into the system as opposed to having these, quote-unquote, dumb brute force approaches. I think there is something from a human psychologist's perspective about brute force methods just not being associated with innovative, brilliant thinking. In fact, if you look at the brute force search or the brute force learning approaches, I think at the time, if we look at it today, the publications and the science associated with these methods, I think, did not get the recognition they deserve. They got a huge amount of recognition because of the publicity of the actual matches they were involved in, but the scientific community, I don't think, gave enough respect to the scientific contribution of these general methods. And it's an interesting, thought-provoking idea. I would love to see that when people publish papers today, maybe almost have like a section where they describe if computation was able to be scaled by 10x, by 100x, looking five, 10 years down the future, will this method hold up to that scaling? Is it scalable? Is this method fundamentally scalable? I think that's a really good question to ask. Is this something that would benefit, at least scale linearly with compute? That to me is a really interesting and provocative question that all graduate students and faculty and researchers should be asking themselves about the methods they propose. Overall, I think this blog post serves as a really good thought experiment because I think we often give a disproportionate amount of respect, I think, to algorithmic improvement and not enough respect when we look at the big arc of progress in artificial intelligence to computation, to the improvement of computation, whether that's talking about just the raw transistor count or other aspects of improving the computational process. If we look at this blog post as it is, you can, of course, raise some contentions and some opposing views. First, the blog post doesn't mention anything about data. And in terms of learning, if we look at the kind of learning that's been really successful for real-world applications, it's supervised learning, meaning it's learning that uses human annotation of data. And so, the scalability of learning methods with computation also needs to be coupled with the scalability of being able to annotate data. And it's unclear to me how the scalability with computation is naturally scaled with annotation of data. Now, I'll propose some ideas there later on. I think they're super exciting in the space of active learning, but in general, those two are not directly linked, at least in the argument of the blog post. So, to be fair, the blog post is looking at the historical context of progress in AI. And so, in that way, it's looking at methods that leverage the exponential improvement in raw computation power as observed by Moore's law. But of course, you can also generalize this blog post to say, really, any methods that hook onto any kind of exponential improvement, so computational improvement at any level of abstraction, including, as we'll later talk about, at the highest level of abstraction of deep learning or even meta-learning. As long as these methods can hook onto the exponential improvement in these contexts, it's able to ride the wave of exponential improvement. It's just that the main exponential improvement we've seen in the past 70 years is that of Moore's law. Another contention that I personally don't find very convincing is when you say that learning or search methods don't require much human expertise, well, they kind of do. You still need to do some fine-tuning. There's still a bunch of tricks, even though it's at the higher level. And the reason I don't find that very convincing is because I think the amount and the quality of human expertise required for deep learning methods is just much smaller and much more directed than in classical machine learning methods, or especially in heuristic-based methods. Now, one big, I don't know if it's a contention, but it's an open question for me. It's often useful when we try to chase the creation of intelligent systems to think about the existence proof that we have before us, which is our own brain. And I think it's fair to say that the process that created the intelligence of our brain is the evolutionary process. Now, the question as it relates to the blog post, to me, is whether evolution falls under the category of search methods or of learning methods, or some mix of the two. Is it a subset, a combination of the two, or is it a superset? Or is it a completely different kind of thing? I think that's a really interesting and really difficult question for me that I think about often. What is the evolutionary process in terms of our best performing methods of today? Of course, there's genetic algorithms, there's genetic programming. These are very kind of specialized evolution-inspired methods. But the actual evolutionary process that created life on Earth, that created intelligent life on Earth, how does that relate to the search and the learning methods that leverage computation so well? It does seem from a 10,000 foot level that the evolutionary process, whether it relates to search or learning, is the kind of process that would leverage computation very well. In fact, from a human-centric perspective of a human that values his life, the evolutionary process seems to be very brute force, very wasteful. So in that way, perhaps it does have similarities to the brute force search and the brute force learning self-play mechanisms that we see so successfully like successfully leveraging computation. So to summarize the argument made in the bitter lesson, the exponential progress of AI over the past 60, 70 years was coupled to the exponential progress of computation with Moore's law and the doubling of transistors. And as we stand today, the open question then is, if we look at the possibility of future exponential improvement of artificial intelligence, will that be due to human ingenuity, so invention of new, better, clever algorithms, or will it be due to improvement increase in raw computational power? Or I think a distinct option is both. I'll talk about my bets for this open question at the end of the video, but at this time let's talk about some possible flag bearers of exponential improvement in AI in the coming years and decades. First, let's look at Moore's law, which is an observation, it's not a law. It has two meanings, I would say. One is the precise technical meaning or the actual meaning, which is the doubling of transistor count every two years. Or you can look at it from a financial perspective and look at dollars per flop decreasing exponentially. This allows you to compare CPUs and GPUs and different kinds of processes together on the same plot. And the second meaning, I think that's very commonly used in general public discourse, is the general sense that there's an exponential improvement of computational capabilities. And I'm actually personally okay with that use of Moore's law as we generalize across different technologies and different ideas to use Moore's law to mean the general observation of the exponential improvement of computational capabilities. So the question that's been asked many times over the past several decades, is Moore's law dead? I think has two camps. Majority of the industry says yes, and then there's a few folks like Jim Keller of now Intel. I did a podcast with him, I highly recommend it. Says no, because actually when we look at the size of transistors, we have not yet hit the theoretical physics limit of how small we can get with the transistors. Now it gets extremely difficult for many reasons to get a transistor that starts approaching the size of a single nanometer in terms of power, in terms of error correction, in terms of what's required for actual fabrication of that kind of scale of thing. But the theoretical physics limit hasn't been reached, so Moore's law can continue. But also if we look at the broader definition of just exponential improvement of computational capabilities, there's a lot of other candidates, flag bearers, as I mentioned, that could carry that exponential flag forward. Let's look at them now. One is the global compute capacity. Now this one is really interesting, and I actually had trouble finding good data to answer the very basic question. I don't think that data exists. The question being, how much total compute capacity is there in the world today? And looking historically, how has it been increasing? There's a few kind of speculative studies, some of them I cite here. They're really interesting, but I do wish there was a little bit more data. I'm actually really excited by the potential of this in a way that is completely unexpected potentially in the future. Now what are we talking about? We're talking about the actual number of general compute capable devices in the world. One of the really powerful compute devices that appeared over the past 20 years is gaming consoles. The other one, I mean past maybe 10 years, is smartphone devices. Now if we look into the future, the possibility, first of all, smartphone devices growing exponentially, but also the compute surface across all types of devices. So if we think of Internet of Things, every object in our day-to-day life gaining computational capabilities means that that computation can be then leveraged in some distributed way. And then we can look at an entirely other dimension of devices that could explode exponentially in the near or the long-term future of virtual reality and augmented reality devices. So currently both of those type of devices are not really gaining ground, but it's very possible that in the future a huge amount of computational resources become available for these virtual worlds, for augmented worlds. So I'm actually really excited by the potential things that we can't yet expect in terms of the exponential growth of actual devices which are able to do computation. The exponential expansion of compute surfaces in our world. That's really interesting. That might force us to rethink the nature of computation, to push it more and more towards distributed computation. So speaking of distributed computation, another possibility of exponential growth of AI is just massively parallel computation. So increasing CPUs, GPUs, stacking them on top of each other and increasing that stack exponentially. Now you run up against Amdahl's Law and all kinds of challenges that characterize that as you increase the number of processors it becomes more and more difficult. There's a diminishing return in terms of the compute speedup you gain when you add more processors. Now if we can overcome that Amdahl's Law, if we can successfully design algorithms that are perfectly parallelizable across thousands, maybe millions, maybe billions of processors, then that changes the game. That changes the game and allows us to exponentially improve the AI algorithms by exponentially increasing the number of processors involved. Another dimension of approaches that contribute to exponential growth of AI is devices that are at their core parallelizable. More general devices like the GPUs, graphic processing units, or ones that are actually specific to neural networks or whatever the algorithm is, which is ASICs, application-specific integrated circuits. The TPU by Google being an excellent example of that where there's a bunch of hardware design decisions made that are specialized in machine learning allowing it to be much more efficient in terms of both energy use and the actual performance of the algorithm. Now another big space that I could probably divide in many slides of flag bearers for exponential AI growth is changing the actual nature of computation. So a completely different kind of computation. So two exciting candidates shown here. One is quantum computing and the other is neuromorphic computing. You're probably familiar with quantum computers with qubits versus classical computers that only represent zeros and ones. Qubits also represent zero ones and the superposition of zero ones. So there is a lot of excitement and development in this space, but it's I would say very early days, especially considering general methods that are able to leverage computation. First, it's really hard to build large quantum computers, but even if you can, second, it's very hard to build algorithms that significantly outperform the algorithms on classical computers, especially in the space of artificial intelligence with machine learning. Then there's another space of computing called neuromorphic computing that draws a lot of inspiration, a lot more inspiration from the human brain. Specifically, it models spiking networks. Now, the idea I think with neuromorphic computing is it's able to perform computation in a much more efficient way. One of the characteristic things about the human brain versus our computers today is it's much more energy efficient than our computers for the same amount of computation. So neuromorphic computing is trying to achieve the same kind of performance. Again, very early days, and it's unclear how you can design general algorithms that reach even close to the same performance of machine learning algorithms, for example, run on classical computers of today with GPUs or ASICs. But of course, if you want to have a complete shift, like a phase shift in terms of the way we approach computation and artificial intelligence, a computer which functions in a completely different way than our classical computers is something that might be able to achieve that kind of phase shift. Now, another really exciting space of methodologies is brain-computer interfaces. In the short term, it's exciting because it may help us understand and treat neurological diseases. But in the long term, the possibility of leveraging human brains for computation, now that's a weird way to put it, but we have a lot of compute power in our brains. We're actually doing a lot of computation, each one of us, every living moment of our lives. And the unfortunate thing is we're not able to share the outcome of that computation with the world. We share it with a very low bandwidth channel. So not from an individual perspective, but from a perspective of society, it's interesting to consider if we can create a high bandwidth connection between a computer and a human brain, then we're able to leverage the computation the human brain already provides to be able to add to the global compute capacity available to the world. That's a really interesting possibility. The way I put it is a little bit ineloquent, but I think oftentimes when you talk about brain-computer interfaces, the way, for example, Elon Musk talks about Neuralink, it's often talked about from an individual perspective of increasing your ability to communicate with the world and receive information from the world. But if you look from a society perspective, you're now able to leverage the computational power of human brains, either the empty cycles or just the actual computation we'll perform to survive in our daily lives, able to leverage that to add to the global compute surface, the global capacity available in the world. And the human brain is quite an incredible computing machine. So if you can connect into that and share that computation, I think incredible exponential growth can be achieved without significant innovation on the algorithm side. Now, a lot of the previous things we talked about was more on the hardware side, or at least very low-level software side of exponential improvement. I really like the recent paper from Danny Hernandez and others at OpenAI called Measuring the Algorithmic Efficiency of Neural Networks that looks at different kind of domains of machine learning and deep learning and shows that the efficiency of the algorithms involved has increased exponentially, actually far outpacing the improvement of Moore's law. So if we look at sort of the main one, starting from the ImageNet moment with AlexNet neural network on the computer vision task, if we look at AlexNet in 2012, and then EfficientNet in 2019, and all the networks that led up to it, the improvement is, it takes 44 times less computation to train a neural network to the level of AlexNet. So if we look at Moore's law in the same kind of span of time, Moore's law would only observe a 11 times decrease in the cost. And the paper highlights also the same kind of exponential improvements in natural language, even in reinforcement learning. So the open question raises is, maybe with deep learning, when we look at these learning methods, that the algorithmic process may yield more gains than hardware efficiency improvements. That's a really exciting possibility, especially for people working in the field, because that means human ingenuity will be essential for the continuation exponential improvement of AI. All that said, whether AI will continue to improve exponentially is an open question. I want to sort of place a flag down. I don't know, I change my mind every day on most things, but today I feel AI will continue to improve exponentially. Now, exponential improvement is always just a stack of S-curves. It's not a single sort of nice exponential improvement. It's always kind of big breakthrough innovation on top of each other that level out, and then a new innovation comes along. So the other open question is, where will the S-curves that feed the exponential come from, most likely, out of the candidates that we discussed? So for me, the innovation in algorithms and innovation in supervised learning in how data is organized and leveraged in that learning process. So the efficiency of learning and search processes, especially with active learning. There's a lot of terminology swimming around that's a little bit loose. So folks like Yann LeCun is really excited by self-supervised learning. And you can think of it, you can define it however the heck you want, but you can think of self-supervised learning as leveraging human annotation very little, leveraging human expertise very little. So that's looking at mechanisms that are extremely powerful, like self-play and reinforcement learning, or in a video computer vision context, you have the idea would be that you would have an algorithm just watches YouTube videos all day. And from that is able to figure out the common sense reasoning, the physics of the world, and so on in an unsupervised way, just by observing the world. Now, for me, I'm excited by active learning much more, which is the optimization of the way you select the data from which you learn from. You say, I'm going to learn, I'm going to become increasingly efficient, I'm going to learn from smaller and smaller data sets, but I'm going to be extremely selective about which part of the data I look at and annotate or ask human supervision over. I think a really simple, but exciting example of that in the real world is what the Tesla Autopilot team is doing by creating this pipeline, where there's a multitask learning framework, where there's a bunch of different tasks. And there's a pipeline for discovering edge cases for each of the tasks, and you keep feeding back the edge cases discovered, and then you keep feeding those edge cases back and retraining the network over and over for each of the different tasks. And then there's a shared part of the network that keeps learning over time. And so there's this active learning framework that just keeps looping over and over and gets better and better over time as it continually discovers and learns from the edge cases. I think that's a very simple example of what I'm talking about, but I'm really excited by that possibility. So innovation and learning in terms of its ability to discover just the right data to improve its performance. And I believe the performance of active learning can increase exponentially in the coming years. Another source of ESCO is that I'm really excited about, but it's very unpredictable. Is the general expansion of the compute surfaces in the world. So it's unclear, but it's very possible that the Internet of Things, IoT eventually will come around where there's smart devices just everywhere. And we're not talking about Alexa here or there. We're talking about just everything is a compute surface. I think that's a really exciting possibility of the future. It may be far away, but I certainly hope to be part of the people that tries to create some of that future. So it's an exciting out there possibility. To me, the total game changer that we don't expect that seems crazy, especially when Elon Musk talks about in the context of Neuralink is brain computer interfaces. I think that's a really exciting technology for helping understand and treat neurological diseases. But if you can make it work to where a computer can communicate in a high bandwidth way with a brain, a two-way communication, that's going to change the nature of computation and the nature of artificial intelligence completely. If an AI system can communicate with the human brain and each leveraging each other's computation, I don't think we can even imagine the kind of world that that would create. That's a really exciting possibility. But at this time, it's shrouded in uncertainty. It seems impossible and crazy. But if anyone can do it, it's the folks working on brain computer interfaces and certainly folks like Elon Musk and the brilliant engineers working at Neuralink. When you talk about exponential improvement in AI, the natural question that people ask is, when is the singularity coming? Is it 2030, 2045, 2050, a century from now? Again, I don't have firm beliefs on this, but from my perspective, I think we're living through the singularity. I think the smoothness of the exponential improvement that we've been a part of in artificial intelligence is sufficiently smooth to where we don't even sense the madness of the curvature of the improvement that we've been living through. I think it's been just incredible. Every new stage, we just so quickly take for granted. I think we're living through the singularity, and I think we'll continue adapting incredibly well to the exponential improvement of AI. I can't wait to what the future holds. That was my simple attempt to discuss some of the ideas by Rich Sutton in his blog post, The Bitter Lesson, and the broader context of exponential improvement in AI and the role of computation and algorithmic improvement in that exponential improvement. This has been part of the AI Paper Club on our Discord server. You're welcome to join anytime. It's not just AI. It's people from all walks of life, all levels of expertise, from artists to musicians to neuroscientists to physicists. It's kind of an incredible community, and I really enjoyed being part of it. It's, I think, something special. So join us anytime. If you have suggestions for papers we should cover, let me know. Otherwise, thanks for watching, and I'll see you next time.

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Chris Urmson: Is Lidar a Crutch? | AI Podcast Clips

You said LiDAR came into the game early on and it's really the primary driver of autonomous vehicles today as a sensor. So how important is the role of LiDAR in the sensor suite in the near term? So I think it's, I think it's essential. You know, I believe, but I also believe the cameras are essential and I believe the radar is essential. I think that you really need to use the composition of data from these different sensors if you want the thing to really be robust. The question I want to ask, let's see if we can untangle it, is what are your thoughts on the Elon Musk provocative statement that LiDAR is a crutch? That is a kind of, I guess, growing pains and that much of the perception task can be done with cameras. So I think it is undeniable that people walk around without lasers in their foreheads and they can get into vehicles and drive them. And so there's an existence proof that you can drive using passive vision. No doubt, can't argue with that. In terms of sensors. Yeah. So there's proof. In terms of sensors, right. There's an example that we all go do it, many of us every day. In terms of LiDAR being a crutch, sure. But in the same way that the combustion engine was a crutch on the path to an electric vehicle, in the same way that any technology ultimately gets replaced by some superior technology in the future. And really the way that I look at this is that the way we get around on the ground, the way that we use transportation is broken. And that we have this, what was, I think the number I saw this morning, 37,000 Americans killed last year on our roads. And that's just not acceptable. And so any technology that we can bring to bear that accelerates this self-driving technology, coming to market and saving lives is technology we should be using. And it feels just arbitrary to say, well, I'm not okay with using lasers because that's whatever, but I am okay with using an eight megapixel camera or a 16 megapixel camera. These are just bits of technology and we should be taking the best technology from the tool bin that allows us to go and solve a problem. The question I often talk to, well, obviously you do as well, to the automotive companies. And if there's one word that comes up more often than anything, it's cost and trying to drive costs down. So while it's true that it's a tragic number, the 37,000, the question is what, and I'm not the one asking this question because I hate this question, but we want to find the cheapest sensor suite that creates a safe vehicle. So in that uncomfortable trade-off, do you foresee LIDAR coming down in cost in the future or do you see a day where level four autonomy is possible without LIDAR? I see both of those, but it's really a matter of time. And I think really, maybe I would talk to the question you asked about, you know, the cheapest sensor. I don't think that's actually what you want. What you want is a sensor suite that is economically viable. And then after that, everything is about margin and driving cost out of the system. What you also want is a sensor suite that works. And so it's great to tell a story about how it would be better to have a self-driving system with a $50 sensor instead of a $500 sensor. But if the $500 sensor makes it work and the $50 sensor doesn't work, who cares? So long as you can actually have an economic, there's an economic opportunity there. And the economic opportunity is important because that's how you actually have a sustainable business and that's how you can actually see this come to scale and be out in the world. And so when I look at LIDAR, I see a technology that has no underlying fundamental expense to it. It's going to be more expensive than an imager because CMOS processes or FAB processes are dramatically more scalable than mechanical processes, but we still should be able to drive cost down substantially on that side. And then I also do think that with the right business model, you can absorb more, you know, certainly more cost on the bill of materials. Yeah. If the sensor suite works, extra value is provided, thereby you don't need to drive cost down to zero. That's basic economics.

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Stuart Russell: The Control Problem of Super-Intelligent AI | AI Podcast Clips

Let's just talk about maybe the control problem. So this idea of losing ability to control the behavior in our AI system. So how do you see that? How do you see that coming about? What do you think we can do to manage it? Well so it doesn't take a genius to realize that if you make something that's smarter than you, you might have a problem. You know, Alan Turing wrote about this and gave lectures about this in 1951. He did a lecture on the radio and he basically says, you know, once the machine thinking method starts, very quickly they'll outstrip humanity. And you know, if we're lucky we might be able to, I think he says, we may be able to turn off the power at strategic moments, but even so our species would be humbled. And actually he was wrong about that, right? If it's a sufficiently intelligent machine, it's not going to let you switch it off. It's actually in competition with you. So what do you think is meant, just for a quick tangent, if we shut off this superintelligent machine that our species will be humbled? I think he means that we would realize that we are inferior, right? That we only survive by the skin of our teeth because we happen to get to the off switch. You know, just in time, you know, and if we hadn't, then we would have lost control over the earth. So do you, are you more worried when you think about this stuff about superintelligent AI or are you more worried about super powerful AI that's not aligned with our values? So the paperclip scenarios kind of. I think, so the main problem I'm working on is the control problem, the problem of machines pursuing objectives that are, as you say, not aligned with human objectives. And this has been the way we've thought about AI since the beginning. You build a machine for optimizing and then you put in some objective and it optimizes, right? And, you know, we can think of this as the King Midas problem, right? Because if, you know, so King Midas put in this objective, right? Everything I touch should turn to gold and the gods, you know, that's like the machine, they said, okay, done. You now have this power. And of course his food and his drink and his family all turned to gold and then he dies of misery and starvation. And this is, you know, it's a warning, it's a failure mode that pretty much every culture in history has had some story along the same lines. You know, there's the genie that gives you three wishes and, you know, third wish is always, you know, please undo the first two wishes because I messed up. And you know, when Arthur Samuel wrote his chess, his checker playing program, which learned to play checkers considerably better than Arthur Samuel could play and actually reached a pretty decent standard. Norbert Wiener, who was one of the major mathematicians of the 20th century, he's sort of the first father of modern automation control systems. He saw this and he basically extrapolated, you know, as Turing did and said, okay, this is how we could lose control. And specifically that we have to be certain that the purpose we put into the machine is the purpose which we really desire. And the problem is, we can't do that. You mean it's very difficult to encode, to put our values on paper is really difficult, or you're just saying it's impossible? I hope the line is right between the two. So theoretically it's possible, but in practice it's extremely unlikely that we could specify correctly in advance the full range of concerns of humanity. You talked about cultural transmission of values, I think is how humans to human transmission of values happens, right? Well we learn, yeah, I mean, as we grow up we learn about the values that matter, how things should go, what is reasonable to pursue and what isn't reasonable to pursue. You think machines can learn in the same kind of way? Yeah, so I think that what we need to do is to get away from this idea that you build an optimizing machine and then you put the objective into it. Because if it's possible that you might put in a wrong objective, and we already know this is possible because it's happened lots of times, right? That means that the machine should never take an objective that's given as gospel truth. Because once it takes the objective as gospel truth, then it believes that whatever actions it's taking in pursuit of that objective are the correct things to do. So you could be jumping up and down and saying, no, no, no, no, you're going to destroy the world, but the machine knows what the true objective is and is pursuing it, and tough luck to you. And this is not restricted to AI, right? This is, I think, many of the 20th century technologies, right? So in statistics, you minimize a loss function. The loss function is exogenously specified. In control theory, you minimize a cost function. In operations research, you maximize a reward function, and so on. So in all these disciplines, this is how we conceive of the problem. And it's the wrong problem, because we cannot specify with certainty the correct objective, we need uncertainty, we need the machine to be uncertain about what it is that it's supposed to be maximizing. It's objective. It's my favorite idea of yours. I've heard you say somewhere, well, I shouldn't pick favorites, but it just sounds beautiful of we need to teach machines humility. Yeah, I mean, that's... That's a beautiful way to put it. I love it. That they're humble, in that they know that they don't know what it is they're supposed to be doing, and that those objectives, I mean, they exist. They're within us, but we may not be able to explicate them. We may not even know how we want our future to go. Right? Exactly. So a machine that's uncertain is going to be deferential to us. So if we say, don't do that, well, now the machine's learned something a bit more about our true objectives, because something that it thought was reasonable in pursuit of our objective turns out not to be, so now it's learned something. So it's going to defer, because it wants to be doing what we really want. And that point, I think, is absolutely central to solving the control problem. And it's a different kind of AI when you take away this idea that the objective is known, then, in fact, a lot of the theoretical frameworks that we're so familiar with, you know, Markov decision processes, goal-based planning, you know, standard games research, all of these techniques actually become inapplicable. And you get a more complicated problem, because now the interaction with the human becomes part of the problem, because the human, by making choices, is giving you more information about the true objective, and that information helps you achieve the objective better. And so that really means that you're mostly dealing with game-theoretic problems, where you've got the machine and the human and they're coupled together, rather than a machine going off by itself with a fixed objective. Which is fascinating on the machine and the human level, that when you don't have an objective, means you're together coming up with an objective. I mean, there's a lot of philosophy that, you know, you could argue that life doesn't really have meaning. We together agree on what gives it meaning, and we kind of culturally create things that give why the heck we are on this earth anyway. We together as a society create that meaning, and you have to learn that objective. And one of the biggest, I thought that's where you were going to go for a second, one of the biggest troubles we run into outside of statistics and machine learning and AI, in just human civilization, is when you look at, I came from, I was born in the Soviet Union, and the history of the 20th century, we ran into the most trouble, us humans, when there was a certainty about the objective. And you do whatever it takes to achieve that objective, whether you're talking about Germany or communist Russia. You get into trouble with humans. Yeah, and I would say with, you know, corporations, in fact, some people argue that, you know, we don't have to look forward to a time when AI systems take over the world. They already have, and they're called corporations. Right, that corporations happen to be using people as components right now. But they are effectively algorithmic machines, and they're optimizing an objective, which is quarterly profit that isn't aligned with overall well-being of the human race, and they are destroying the world. They are primarily responsible for our inability to tackle climate change. So I think that's one way of thinking about what's going on with corporations. But I think the point you're making is valid, that there are many systems in the real world where we've sort of prematurely fixed on the objective and then decoupled the machine from those that it's supposed to be serving. And I think you see this with government, right, government is supposed to be a machine that serves people. But instead it tends to be taken over by people who have their own objective and use government to optimize that objective regardless of what people want.

https://youtu.be/bHPeGhbSVpw

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Training for David Goggins - 4x4x48 Challenge | Lex Fridman

I just finished a six mile run in good old below freezing Boston weather. A bit too dark, a bit too icy, but probably good for the mind and soul. So I thought it'd be a good time to make this video and say that for the second year now, Mr. David Goggins is doing the 4x4x48 challenge at 8 p.m. Pacific on Friday, March 5th. That's running 48 miles in 48 hours by doing 4 miles every 4 hours. But this time, friends, him and I are doing it together, in person. Just him and I, probably in the middle of a desert somewhere, probably with just one of us returning home alive. And I think you know which one it is. We'll do a podcast before and after. Also, he'll go live on Instagram at the beginning of every four hour leg. I've not been training much at all, to be honest, and this video is a quick explanation of how I'm training for this challenge, starting today, in a way that gives me a reasonable fitness base, while still letting me be productive in all the different things I have going on. I took on this challenge with David on a bit of a leap of faith and a bit of madness in order to test myself mentally and physically. But also because I often take this kind of leap into things that seem very stupid at the time. But when all is said and done, I almost always become a better person because of it. So if you're out there a little bit out of shape, like me, I'm hoping you join me in getting back to exercising this month and perhaps taking on the challenge along with me, along with David, along with us. If you're not a runner, you can just do some sort of exercise for 40 to 60 minutes every four hours instead. If you want to get involved, check links in the description for more information, I think. But mostly just tag me and David if you're stepping your fitness up in any kind of way this month as you train, and if you're participating in the challenge. I know it'll be inspiring to me to see anybody who's just getting out there, since, to be honest, this would be a ridiculously big challenge for me with everything I have going on. So I can probably use all the inspiration you got. Okay, so training-wise, check out the Google sheet of my training in the description, but it's pretty basic. The focus, as usual, is to establish a ritual, a habit of daily exercise, and then increasing duration a little bit every week. So maybe let me first speak to the principle of that. I know that for muscle building and for increasing race performance, it's good to mix up workouts from long to short sprints, that kind of thing, with rest days, and just mixing it up throughout the week. But I don't know about anyone else, but for me, that has only really worked when I'm already in really good shape. What for me has been more beneficial, more effective, is to focus on building up the habit of exercise. Every day, the same thing. The habit and ritual of it lessens the need and the reliance on motivation, on day-to-day motivation. So for me, the training is easily integrated into the day. It has two parts. One is cardio, one is bodyweight exercises, and the schedule is pretty basic. I run a medium distance every day, Monday through Friday, and a long distance run on Saturday, and then rest on Sunday. So specifically for me, that means week one, what I'm doing now, six miles each day. Then week two is seven miles, week three is eight miles, week four is nine miles. So we're about four and a half weeks out from the challenge. I think two or three days before the challenge, I'll take complete rest days. So my recommendation to you for what it's worth is to pick a cardio exercise that you can stick to on a daily basis. So running, cycling, swimming, even walking, and just build the habit. And do an intensity and duration that doesn't break your body down, but it's still challenging. Just keeps challenging you, but not too much. Not causing injury, not causing over exertion, over exhaustion. On the bodyweight exercise side, for me, that's six days of exercise. That includes push-ups, pull-ups, bodyweight squats, and these ab roller things for the abs, for the core. I do it in rounds of 20 push-ups, 10 pull-ups, 10 ab rollers, and 10 squats. My recommendation, again, take it with a grain of salt, is if you do bodyweight exercises, pick numbers within the round that allows you to do timed rounds without much rest in between. Maybe no more than one minute's rest. And do essentially a full body workout, but not to exhaustion. And I know a lot of people are going to say, you know, rest days are really essential. You want to alternate upper body, lower body, push-pull, all those kinds of things. All of that is true when you're trying to achieve maximum performance. What I find for me, in a busy life, when I have a million things going on, building the habit, building the ritual of exercise, and not pushing myself to exhaustion, is the most effective way to stay healthy and just to feel good, and make sure that exercise stays part of my life. You probably didn't ask me, but that's my recommendation if you're starting from being kind of out of shape to building up shape for doing something like that 48 mile challenge. But you should also definitely read a lot of different advice that's out there and integrate it in a way that works for your own schedule, for your own body, all that kind of stuff. On the diet side, I'm eating clean as usual, just meat and veggies. The veggies are mostly cauliflower and green beans, my two favorites. And on the meat side is ground beef, actually from Belcampo Farms. They sent me a ton of meat and it's delicious. On the supplement side, I'm doing the usual athletic greens every morning, plus fish oil and electrolytes before and after the run. You should definitely check out Athletic Greens and Belcampo Farms. They are both somehow amazingly now sponsors of the podcast that I host. After I posted about how much I love their stuff. And also check out cauliflower, especially in rice form. It's a game changer. So at least my training regimen is pretty simple. Run basically every day, body weight exercises every day. Don't overexert and gradually increase the duration of the exercise. And the rest is just in the mind. And I'm hoping I am mentally tough enough to not die with Dave Calkins. I thought to post this video, you know, hopefully to inspire others to step up their exercise game this month, to run, to cycle, all that kind of stuff. And maybe even join in on this crazy challenge. I think it's a really perfect balance of testing the body and mind, just being able to persevere through this 48 hour period. It's just long enough to where it's not this kind of shorter marathon run of suffering. You kind of have to suffer just a little bit to get through it. I mean, you kind of have to suffer just a little bit every four hours. It's honestly just a huge honor to be able to do this kind of thing with David Goggins. We were just supposed to do the podcast, but of course, as he does with everybody he meets, he pulls you in and challenges you to push yourself to your own limits to discover yourself. And I think that's kind of what this whole life is about, is to do difficult things and in the process, be able to discover something about yourself that you wouldn't be able to discover in any kind of way. There's some kind of magic in the challenge that allows you to put a mirror to yourself, to meet your demons, to overcome them, and then the rest of life becomes easy, or at least easier. The training in Boston is definitely a bit rough right now. It's been below freezing for many days in a row. So it's starting to feel a lot like Rocky IV, except in this version, the Russian is the out of shape underdog training in the snow, and it's the American who says, if he dies, he dies. So we'll see what happens. All of you all.

https://youtu.be/x02fjnpqiyA

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Occam's Razor (Marcus Hutter) | AI Podcast Clips

What is Occam's Razor? So Occam's Razor says that you should not multiply entities beyond necessity, which sort of if you translate it to proper English means, and you know, in the scientific context means that if you have two theories or hypotheses or models which equally well describe the phenomenon you're studying or the data, you should choose the more simple one. So that's just the principle? Yes. So that's not like a provable law perhaps? Perhaps we'll kind of discuss it and think about it, but what's the intuition of why the simpler answer is the one that is likelier to be more correct descriptor of whatever we're talking about? I believe that Occam's Razor is probably the most important principle in science. I mean, of course we lead logical deduction and we do experimental design, but science is about understanding the world, finding models of the world, and we can come up with crazy complex models which explain everything but predict nothing, but the simple model seem to have predictive power and it's a valid question why. And there are two answers to that. You can just accept it, that is the principle of science, and we use this principle and it seems to be successful. We don't know why, but it just happens to be. Or you can try, you know, find another principle which explains Occam's Razor. And if we start with the assumption that the world is governed by simple rules, then there's a bias to our simplicity and applying Occam's Razor is the mechanism to finding these rules. And actually in a more quantitative sense, and we come back to that later in case of somnolent deduction, you can rigorously prove that. You assume that the world is simple, then Occam's Razor is the best you can do in a certain sense. So I apologize for the romanticized question, but why do you think, outside of its effectiveness, why do you think we find simplicity so appealing as human beings? Why does E equals MC squared seem so beautiful to us humans? I guess mostly, in general, many things can be explained by an evolutionary argument. And, you know, there's some artifacts in humans which are just artifacts and not evolutionary necessary. But with this beauty and simplicity, it's, I believe, at least the core, is about, like science, finding regularities in the world, understanding the world, which is necessary for survival, right? You know, if I look at a bush, right, and I just see noise, and there is a tiger, right, and eats me, then I'm dead. But if I try to find a pattern, and we know that humans are prone to find more patterns in data than they are, you know, like the Mars face and all these things, but this bias towards finding patterns, even if they are non, but, I mean, it's best, of course, if they are, yeah, helps us for survival. Yeah, that's fascinating. I haven't thought really about the, I thought I just loved science, but indeed, in terms of just for survival purposes, there is an evolutionary argument for why we find the work of Einstein so beautiful. Maybe a quick, small tangent. Could you describe what Solomonov induction is? Yeah, so that's a theory which I claim, and Marcel Solomonov sort of claimed a long time ago that this solves the big philosophical problem of induction, and I believe the claim is essentially true, and what it does is the following. So, okay, for the picky listener, induction can be interpreted narrowly and widely. Narrow means inferring models from data, and widely means also then using these models for doing predictions, so prediction is also part of the induction. So I'm a little sloppy sort of with the terminology, and maybe that comes from Ray Solomonov being sloppy. Maybe I shouldn't say that. He can't complain anymore. So let me explain a little bit this theory in simple terms. So assume you have a data sequence. Make it very simple, the simplest one, say 1, 1, 1, 1, 1, and you see 100 1s. What do you think comes next? The natural answer, I'm gonna speed up a little bit. The natural answer is, of course, 1, okay? And the question is why, okay? Well, we see a pattern there, yeah? Okay, there's a 1, and we repeat it, and why should it suddenly after 100 1s be different? So what we're looking for is simple explanations or models for the data we have, and now the question is a model has to be presented in a certain language, in which language do we use? In science, we want formal languages, and we can use mathematics, or we can use programs on a computer, so abstractly on a Turing machine, for instance, or it can be a general-purpose computer. And there are, of course, lots of models. You can say maybe it's 100 1s, and then 100 0s, and 100 1s, that's a model, right? But there are simpler models. There's a model print1 loop that also explains the data, and if you push that to the extreme, you are looking for the shortest program, which, if you run this program, reproduces the data you have. It will not stop. It will continue, naturally, and this you take for your prediction, and on the sequence of 1s, it's very plausible, right, that print1 loop is the shortest program. We can give some more complex examples, like 1, 2, 3, 4, 5. What comes next? The short program is, again, you know, counter, and so that is, roughly speaking, how the Lomoff induction works. The extra twist is that it can also deal with noisy data, so if you have, for instance, a coin flip, say a biased coin which comes up head with 60% probability, then it will predict. It will learn and figure this out, and after a while, it predicts, oh, the next coin flip will be head with probability 60%, so it's the stochastic version of that. But the goal is, the dream is, always the search for the short program. Yes, yeah. Well, in Solomonoff induction, precisely what you do is, so you combine, so looking for the shortest program is like applying Opach's razor, like looking for the simplest theory. There's also Epicurus' principle, which says, if you have multiple hypotheses which equally well describe your data, don't discard any of them. Keep all of them around. You never know. And you can put that together and say, okay, I have a bias towards simplicity, but I don't rule out the larger models, and technically what we do is, we weigh the shorter models higher and the longer models lower, and you use a Bayesian technique. So you have a prior, and which is precisely two to the minus the complexity of the program, and you weigh all this hypothesis and take this mixture, and then you get also the stochasticity in. Yeah, like many of your ideas, that's just a beautiful idea of weighing based on the simplicity of the program. I love that. That seems to me maybe a very human-centric concept. It seems to be a very appealing way of discovering good programs in this world. You've used the term compression quite a bit. I think it's a beautiful idea. Sort of, we just talked about simplicity, and maybe science or just all of our intellectual pursuits is basically the attempt to compress the complexity all around us into something simple. So what does this word mean to you, compression? I essentially have already explained it. So compression means for me, finding short programs for the data or the phenomenon at hand. You could interpret it more widely as finding simple theories which can be mathematical theories, or maybe even informal, like just in words. Compression means finding short descriptions, explanations, programs for the data. Do you see science as a kind of our human attempt at compression? So we're speaking more generally, because when you say programs, you're kind of zooming in on a particular sort of, almost like a computer science, artificial intelligence focus. But do you see all of human endeavor as a kind of compression? Well, at least all of science I see as an endeavor of compression, not all of humanity, maybe. And well, there are also some other aspects of science like experimental design, right? I mean, we create experiments specifically to get extra knowledge. And that is then part of the decision-making process. But once we have the data, to understand the data is essentially compression. So I don't see any difference between compression, understanding, and prediction. So we're jumping around topics a little bit, but returning back to simplicity, a fascinating concept of Kolmogorov complexity. So in your sense, do most objects in our mathematical universe have high Kolmogorov complexity? And maybe what is, first of all, what is Kolmogorov complexity? Okay, Kolmogorov complexity is a notion of simplicity or complexity. And it takes the compression view to the extreme. So I explained before that if you have some data sequence, just think about a file on a computer and best sort of, you know, just a string of bits. And if you, and we have data compressors, like we compress big files into, say, zip files with certain compressors. And you can also produce self-extracting archives. That means as an executable, if you run it, it reproduces your original file without needing an extra decompressor. It's just the decompressor plus the archive together in one. And now there are better and worse compressors, and you can ask, what is the ultimate compressor? So what is the shortest possible self-extracting archive you could produce for a certain dataset, yeah, which reproduces the dataset? And the length of this is called the Kolmogorov complexity. And arguably, that is the information content in the dataset. I mean, if the dataset is very redundant or very boring, you can compress it very well so the information content should be low. And, you know, it is low according to this definition. So it's the length of the shortest program that summarizes the data? Yes, yeah. And what's your sense of our sort of universe when we think about the different objects in our universe, that we, concepts or whatever, at every level, do they have high or low Kolmogorov complexity? So what's the hope? Do we have a lot of hope in being able to summarize much of our world? That's a tricky and difficult question. So as I said before, I believe that the whole universe, based on the evidence we have, is very simple. So it has a very short description. Sorry, to linger on that, the whole universe, what does that mean? Do you mean at the very basic fundamental level in order to create the universe? Yes, yeah. So you need a very short program, and you run it. To get the thing going. To get the thing going, and then it will reproduce our universe. There's a problem with noise. We can come back to that later, possibly. Is noise a problem, or is it a bug or a feature? I would say it makes our life as a scientist really, really much harder. I mean, think about without noise, we wouldn't need all of the statistics. But that may be, we wouldn't feel like there's a free will. Maybe we need that for the... This is an illusion that noise can give you free will. At least in that way, it's a feature. But also, if you don't have noise, you have chaotic phenomena, which are effectively like noise. So we can't get away with statistics even then. I mean, think about rolling a dice, and forget about quantum mechanics, and you know exactly how you throw it. But I mean, it's still so hard to compute the trajectory that effectively, it is best to model it as coming out with a number, with probability one over six. But from this set of philosophical, Kolmogorov complexity perspective, if we didn't have noise, then arguably you could describe the whole universe as, well, as a standard model plus generativity. I mean, we don't have a theory of everything yet, but sort of assuming we are close to it or have it, yeah? Plus the initial conditions, which may hopefully be simple. And then you just run it, and then you would reproduce the universe. But that's spoiled by noise or by chaotic systems, or by initial conditions, which may be complex. So now, if we don't take the whole universe, but just a subset, just take planet Earth. Planet Earth cannot be compressed into a couple of equations. This is a hugely complex system. So interesting. So when you look at the window, like the whole thing might be simple, but when you just take a small window, then it may become complex. And that may be counterintuitive, but there's a very nice analogy. The book, the library of all books. So imagine you have a normal library with interesting books, and you go there, great. Lots of information and quite complex, yeah? So now I create a library, which contains all possible books, say, of 500 pages. So the first book just has A, A, A, A, A over all the pages. The next book, A, A, A, and ends with B, and so on. I create this library of all books. I can write a super short program, which creates this library. So this library which has all books has zero information content. And you take a subset of this library, and suddenly you have a lot of information in there. So that's fascinating. I think one of the most beautiful object, mathematical objects that, at least today, seems to be understudied or under-talked about is cellular automata. What lessons do you draw from sort of the game of life for cellular automata, where you start with the simple rules, just like you're describing with the universe, and somehow complexity emerges? Do you feel like you have an intuitive grasp on the fascinating behavior of such systems, where, like you said, some chaotic behavior could happen, some complexity could emerge, it could die out in some very rigid structures? Do you have a sense about cellular automata that somehow transfers maybe to the bigger questions of our universe? Yeah, the cellular automata, and especially the converse game of life, is really great, because the rules are so simple, you can explain it to every child, and even by hand, you can simulate a little bit. And you see these beautiful patterns emerge, and people have proven that it's even Turing-complete. You cannot just use a computer to simulate game of life, but you can also use game of life to simulate any computer. That is truly amazing. And it's the prime example, probably, to demonstrate that very simple rules can lead to very rich phenomena. And people sometimes, you know, how is chemistry and biology so rich? I mean, this can't be based on simple rules, yeah? But no, we know quantum electrodynamics describes all of chemistry. And we come later back to that. I claim intelligence can be explained or described in one single equation, this very rich phenomenon. You asked also about whether, you know, I understand this phenomenon. It's probably not. And there's this saying, you never understand really things, you just get used to them. And I think I got pretty used to cellular automata. So you believe that you understand now why this phenomenon happens. But I give you a different example. I didn't play too much with this converse game of life, but a little bit more with fractals and with the Mandelbrot set, and in this beautiful patterns, just look Mandelbrot set. And well, when the computers were really slow and I just had a black and white monitor and programmed my own programs in assembler too. Assembler, wow. Wow, you're legit. To get these fractals on the screen, and it was mesmerized and much later. So I returned to this, you know, every couple of years, and then I tried to understand what is going on. And you can understand a little bit. So I tried to derive the locations, you know, there are these circles and the apple shape. And then you have smaller Mandelbrot sets recursively in this set. And there's a way to mathematically, by solving high order polynomials, to figure out where these centers are and what size they are approximately. And by sort of mathematically approaching this problem, you slowly get a feeling of why things are like they are. And that sort of is, you know, first step to understanding why this rich phenomena. Do you think it's possible? What's your intuition? Do you think it's possible to reverse engineer and find the short program that generated these fractals sort of by looking at the fractals? Well, in principle, yes. So, I mean, in principle, what you can do is you take any data set, you know, you take these fractals or you take whatever your data set, whatever you have, say a picture of Conway's Game of Life. And you run through all programs. You take a program size one, two, three, four, and all these programs, run them all in parallel in so-called dovetailing fashion, give them computational resources, first one 50%, second one half resources, and so on, and let them run, wait until they hold, give an output, compare it to your data. And if some of these programs produce the correct data, then you stop and then you have already some program. It may be a long program because it's faster. And then you continue and you get shorter and shorter programs until you eventually find the shortest program. The interesting thing, you can never know whether it's the shortest program because there could be an even shorter program, which is just even slower. And you just have to wait, yeah? But asymptotically, and actually after finite time, you have the shortest program. So this is a theoretical but completely impractical way of finding the underlying structure in every data set. And that is what Solomon of induction does and Kolmogorov complexity. In practice, of course, we have to approach the problem more intelligently. And then if you take resource limitations into account, there's, for instance, the field of pseudo random numbers, and these are random numbers. So these are deterministic sequences, but no algorithm which is fast, fast means runs in polynomial time, can detect that it's actually deterministic. So we can produce interesting, I mean, random numbers, maybe not that interesting, but just an example. We can produce complex looking data, and we can then prove that no fast algorithm can detect the underlying pattern. Which is unfortunately, that's a big challenge for our search for simple programs in the space of artificial intelligence, perhaps. Yes, it definitely is for artificial intelligence, and it's quite surprising that it's, I can't say easy. I mean, physicists worked really hard to find these theories, but apparently it was possible for human minds to find these simple rules in the universe. It could have been different, right? It could have been different. It's awe-inspiring.

https://youtu.be/DCjeM3Sei-s

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Donut-shaped C code that generates a 3D spinning donut

Here, on the left, is a spinning ASCII donut, and on the right is a donut-shaped C code by Andy Salone that generates it. Now with syntax highlighting. Now I recommend you check out Andy's blog post on the mathematics behind a flying spinning torus, aka donut. The link to the post is in the description. The basic steps are create a circle, then create a torus by rotating the circle about the Y axis, then using rotation matrices, spin the donut around the X and Z axes. Finally, project the donut onto the 2D screen, adding illumination by calculating the surface normal after picking a particular light source. The cool thing is because this is ASCII world, there's different characters associated with different levels of luminance. We can go back to the de-obfuscated version of the code that I generated, adding a microsecond sleep function to aid in the animation. Compiling and running the code, we get our spinning donut. There's a lot of parameters that you can control with this donut, including the field of view and the distance of the donut from the viewer. I spend at least an hour every day learning and exploring outside my main line of work, so I thought it'd be cool to start throwing together quick little videos about things that I find beautiful, whether they're basic or advanced in the world of machine learning, math, computer science, programming, psychology, whatever, even biology, physics, history, and philosophy. So, hope this is of value, fun, and something you would enjoy.

https://youtu.be/DEqXNfs_HhY

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Jim Keller: Elon Musk and Tesla Autopilot | AI Podcast Clips

All the cost is in the equipment to do it. And the trend on equipment is, once you figure out how to build the equipment, the trend of cost is zero. Elon said, first you figure out what configuration you want the atoms in, and then how to put them there. Right? Because, well, here's the, you know, his great insight is, people are how constrained. I have this thing, I know how it works, and then little tweaks to that will generate something, as opposed to what do I actually want, and then figure out how to build it. It's a very different mindset. And almost nobody has it, obviously. Well, let me ask on that topic, you were one of the key early people in the development of autopilot, at least in the hardware side. Elon Musk believes that autopilot and vehicle autonomy, if you just look at that problem, can follow this kind of exponential improvement. In terms of the how question that we're talking about, there's no reason why it can't. What are your thoughts on this particular space of vehicle autonomy, and your part of it, and Elon Musk's and Tesla's vision for vehicle autonomy? Well, the computer you need to build was straightforward. And you could argue, well, does it need to be two times faster, or five times, or 10 times? But that's just a matter of time. Or price, in the short run. So that's not a big deal. You don't have to be especially smart to drive a car. So it's not like a super hard problem. I mean, the big problem with safety is attention, which computers are really good at, not skills. Well, let me push back on one, you see, everything you said is correct, but we as humans tend to take for granted how incredible our vision system is. So you can drive a car with 20, 50 vision, and you can train a neural network to extract the distance of any object and the shape of any surface from a video and data. It's really simple. No, it's not simple. That's a simple data problem. It's not simple. Because it's not just detecting objects, it's understanding the scene, and it's being able to do it in a way that doesn't make errors. So the beautiful thing about the human vision system, and our entire brain around the whole thing, is we're able to fill in the gaps. It's not just about perfectly detecting cars. It's inferring the occluded cars. It's understanding the physics. I think that's mostly a data problem. So you think what data, with compute, with improvement of computation, with improvement in collection. Well, there is a, you know, when you're driving a car and somebody cuts you off, your brain has theories about why they did it. You know, they're a bad person, they're distracted, they're dumb. You know, you can listen to yourself. Right. So, you know, if you think that narrative is important to be able to successfully drive a car, then current autopilot systems can't do it. But if cars are ballistic things with tracks and probabilistic changes of speed and direction, and roads are fixed and given, by the way, they don't change dynamically. Right, you can map the world really thoroughly. You can place every object really thoroughly. Right, you can calculate trajectories of things really thoroughly. Right. But everything you said about really thoroughly has a different degree of difficulty. So. And you could say at some point, computer autonomous systems will be way better at things that humans are lousy at. Like, they'll be better at attention. They'll always remember there was a pothole in the road that humans keep forgetting about. They'll remember that this set of roads has these weirdo lines on it that the computers figured out once. And especially if they get updates, so if somebody changes a given. Right. Like, the key to robots and stuff, somebody said, is to maximize the givens. Right. So, having a robot pick up this bottle cap is way easier if you put a red dot on the top. Because then you don't have to figure out, you know, if you want to do a certain thing with it, you know, maximize the givens is the thing. And autonomous systems are happily maximizing the givens. Like, humans, when you drive someplace new, you remember it because you're processing it the whole time. And after the 50th time you drove to work, you get to work, you don't know how you got there. Right, you're on autopilot. Right. Autonomous cars are always on autopilot. But the cars have no theories about why they got cut off or why they're in traffic. So they also never stopped paying attention. Right, so I tend to believe you do have to have theories, mental models of other people, especially with pedestrian and cyclists, but also with other cars. So everything you said is, like, is actually essential to driving. Driving is a lot more complicated than people realize, I think, so sort of to push back slightly, but to- So to cut into traffic, right? You can't just wait for a gap. You have to be somewhat aggressive. You'd be surprised how simple a calculation for that is. I may be on that particular point, but there's a, maybe I should have to push back. I would be surprised. You know what, yeah, I'll just say where I stand. I would be very surprised, but I think it's, you might be surprised how complicated it is. I tell people, like, progress disappoints in the short run and surprises in the long run. It's very possible, yeah. I suspect in 10 years it'll be just, like, taken for granted. Yeah, probably. But you're probably right, and I'll look like- It's gonna be a $50 solution that nobody cares about. It's like GPS is like, wow, GPS, we have satellites in space that tell you where your location is. It was a really big deal, and now everything has a GPS in it. Yeah, that's true, but I do think that systems that involve human behavior are more complicated than we give them credit for. So we can do incredible things with technology that don't involve humans, but when you- I think humans are less complicated than people, you know, frequently ascribed. Maybe I have false- We tend to operate out of large numbers of patterns and just keep doing it over and over. But I can't trust you because you're a human. That's something a human would say. But my hope is on the point you've made is, even if, no matter who's right, I'm hoping that there's a lot of things that humans aren't good at that machines are definitely good at, like you said, attention and things like that, where they'll be so much better that the overall picture of safety and autonomy will be obviously cars will be safer, even if they're not as good at understanding- I'm a big believer in safety. I mean, there are already the current safety systems like cruise control that doesn't let you run into people and lane keeping. There are so many features that you just look at the Pareto of accidents and knocking off like 80% of them is, you know, super doable. Just to linger on the autopilot team and the efforts there, it seems to be that there's a very intense scrutiny by the media and the public in terms of safety, the pressure, the bar put before autonomous vehicles. What are your, sort of as a person there working on the hardware and trying to build a system that builds a safe vehicle and so on, what was your sense about that pressure? Is it unfair? Is it expected of new technology? Yeah, it seems reasonable. I was interested, I talked to both American and European regulators, and I was worried that the regulations would write into the rules technology solutions, like modern brake systems imply hydraulic brakes. So if you read the regulations to meet the letter of the law for brakes, it sort of has to be hydraulic, right? And the regulator said they're interested in the use cases, like a head-on crash, an offset crash, don't hit pedestrians, don't run into people, don't leave the road, don't run a red light or a stoplight. They were very much into the scenarios. And, you know, and they had all the data about which scenarios injured or killed the most people. And for the most part, those conversations were like, what's the right thing to do to take the next step? Now, Elon's very interested also in the benefits of autonomous driving or freeing people's time and attention as well as safety. And I think that's also an interesting thing, but, you know, building autonomous systems so they're safe and safer than people seemed, since the goal is to be 10x safer than people, having the bar to be safer than people and scrutinizing accidents seems philosophically, you know, correct. So I think that's a good thing. What are, it's different than the things you worked at, the Intel, AMD, Apple, with autopilot chip design and hardware design. What are interesting or challenging aspects of building this specialized kind of computing system in the automotive space? I mean, there's two tricks to building like an automotive computer. One is the software team, the machine learning team is developing algorithms that are changing fast. So as you're building the accelerator, you have this, you know, worry or intuition that the algorithms will change enough that the accelerator will be the wrong one, right? And there's a generic thing, which is if you build a really good general purpose computer say it's performance is one, and then GPU guys will deliver about 5x to performance for the same amount of silicon, because instead of discovering parallelism, you're given parallelism. And then special accelerators get another two to 5x on top of a GPU, because you say, I know the math is always eight bit integers into 32 bit accumulators, and the operations are the subset of mathematical possibilities. So auto, you know, AI accelerators have a claim performance benefit over GPUs, because in the narrow mass space, you're nailing the algorithm. Now, you still try to make it programmable, but the AI field is changing really fast. So there's a, you know, there's a little creative tension there of, I want the acceleration afforded by specialization without being over specialized so that the new algorithm is so much more effective that you would have been better off on a GPU. So there is a tension there. To build a good computer for an application like automotive, there's all kinds of sensor inputs and safety processors and a bunch of stuff. So one of Elon's goals to make it super affordable. So every car gets an autopilot computer. So some of the recent startups you look at, and they have a server in the trunk, because they're saying, I'm going to build this autopilot computer to replace the driver. So their cost budget's 10 or $20,000. And Elon's constraint was, I'm going to put one in every car, whether people buy autonomous driving or not. So the cost constraint he had in mind was great. Right, and to hit that, you had to think about the system design. That's complicated. It's fun. You know, it's like, it's like, it's Crestman's work. Like, you know, a violin maker, right? You can say Stradivarius is this incredible thing. The musicians are incredible. But the guy making the violin, you know, picked wood and sanded it, and then he cut it, you know, and he glued it, you know, and he waited for the right day so that when he put the finish on it, it didn't, you know, do something dumb. That's craftsman's work, right? You may be a genius craftsman because you have the best techniques and you discover a new one, but most engineers are craftsman's work. And humans really like to do that. You know, it's like- Smart humans. No, everybody. All humans. I don't know. I used to, I dug ditches when I was in college. I got really good at it. Satisfying. Yeah. So- Digging ditches is also craftsman work. Yeah, of course. So there's an expression called complex mastery behavior. So when you're learning something, that's fun because you're learning something. When you do something and it's rote and simple, it's not that satisfying. But if the steps that you have to do are complicated and you're good at them, it's satisfying to do them. And then if you're intrigued by it all, as you're doing them, you sometimes learn new things that you can raise your game. But craftsman's work is good. And engineers, like engineering is complicated enough that you have to learn a lot of skills. And then a lot of what you do is then craftsman's work, which is fun. Autonomous driving, building a very resource constrained computer. So a computer has to be cheap enough that you can put it in every single car. That's essentially boils down to craftsman's work. It's engineering, it's- Yeah, you know, there's thoughtful decisions and problems to solve and trade-offs to make. You need 10 camera in ports or eight, you know, you're building for the current car or the next one, you know, how do you do the safety stuff? You know, there's a whole bunch of details, but it's fun, but it's not like I'm building a new type of neural network, which has a new mathematics and a new computer to work. You know, that's like, there's more invention than that. But the rejection to practice, once you pick the architecture, you look inside and what do you see, adders and multipliers and memories and, you know, the basics. So computers is always this weird set of abstraction layers of ideas and thinking that reduction to practice is transistors and wires and, you know, pretty basic stuff. And that's an interesting phenomenon. By the way, like factory work, like lots of people think factory work is road assembly stuff. I've been on the assembly line. Like the people who work there really like it. It's a really great job. It's really complicated. Putting cars together is hard, right? And the car is moving and the parts are moving and sometimes the parts are damaged and you have to coordinate putting all the stuff together and people are good at it. They're good at it. And I remember one day I went to work and the line was shut down for some reason. And some of the guys sitting around were really bummed because they had reorganized a bunch of stuff and they were going to hit a new record for the number of cars built that day. And they were all gung-ho to do it. And these were big, tough buggers. And, you know, but what they did was complicated and you couldn't do it. Yeah, and I mean. Well, after a while you could, but you'd have to work your way up because, you know, like putting a bright, what's called the brights, the trim on a car on a moving assembly line where it has to be attached 25 places in a minute and a half is unbelievably complicated. And human beings can do it. It's really good. I think that's harder than driving a car, by the way. Putting together, working on a factory. Too smart people can disagree. Yeah. I think driving a car. Well, we'll get you in the factory someday and then we'll see how you do. No, not for us humans driving a car is easy. I'm saying building a machine that drives a car is not easy. Okay, driving a car is easy for humans because we've been evolving for billions of years. To drive cars. Yeah, I noticed that. To do. The paleolithic cars are super cool. No, now you join the rest of the internet in mocking me. Okay. I wasn't mocking you, I was just, you know, intrigued by your anthropology. Yeah. I'll have to go dig into that. There's some inaccuracies there, yes. Okay, but in general, what have you learned in terms of, thinking about passion, craftsmanship, tension, chaos, you know, the whole mess of it, what have you learned, have taken away from your time working with Elon Musk, working at Tesla, which is known to be a place of chaos, innovation, craftsmanship, and all those things. I really like the way you thought. Like, you think you have an understanding about what first principles of something is, and then you talk to Elon about it, and you didn't scratch the surface. You know, he has a deep belief that no matter what you do, it's a local maximum. And I had a friend, he invented a better electric motor, and it was like a lot better than what we were using. And one day he came by, he said, you know, I'm a little disappointed, because, you know, this is really great, and you didn't seem that impressed. And I said, you know, when the super intelligent aliens come, are they gonna be looking for you? Like, where is he? The guy, he built the motor. Probably not, you know. But doing interesting work that's both innovative, and let's say craftsman's work on the current thing, is really satisfying, and it's good. And that's cool. And then Elon was good at taking everything apart. Like, what's the deep first principle? Oh, no, what's really, no, what's really? You know, that ability to look at it without assumptions, and how constraints is super wild. You know, he built a rocket ship, and electric car, and everything. And that's super fun, and he's into it, too. Like, when they first landed two SpaceX rockets to Tesla, we had a video projector in the big room, and like 500 people came down, and when they landed, everybody cheered, and some people cried. It was so cool. All right, but how did you do that? Well, it was super hard. And then people say, well, it's chaotic. Really? To get out of all your assumptions? You think that's not gonna be unbelievably painful? And is Elon tough? Yeah, probably. Do people look back on it and say, boy, I'm really happy I had that experience to go take apart that many layers of assumptions? Sometimes super fun, sometimes painful. So it could be emotionally and intellectually painful, that whole process of just stripping away assumptions? Yeah, imagine 99% of your thought process is protecting your self-conception. And 98% of that's wrong. Now you got the math right. How do you think you're feeling when you get back into that one bit that's useful? And now you're open and you have the ability to do something different. I don't know if I got the math right. It might be 99.9, but it ain't 50. Imagining that 50% is hard enough. Yeah. Now, for a long time, I've suspected you could get better. Like you can think better, you can think more clearly, you can take things apart. And there's lots of examples of that, people who do that. And Nilan is an example of that. Apparently. You are an example. I don't know if I am. I'm fun to talk to. Certainly. I've learned a lot of stuff. Right. Well, here's the other thing is, like I joke, like I read books. And people think, oh, you read books? Well, no, I've read a couple of books a week for 55 years. Well, maybe 50, because I didn't learn to read until I was eight or something. And it turns out when people write books, they often take 20 years of their life where they passionately did something, reduce it to 200 pages. That's kind of fun. And then you go online and you can find out who wrote the best books and who like, you know, that's kind of wild. So there's this wild selection process and then you can read it and for the most part, understand it. And then you can go apply it. Like I went to one company, I thought, I haven't managed much before. So I read 20 management books and I started talking to them and basically compared to all the VPs running around, I'd read 19 more management books than anybody else. It wasn't even that hard. And half the stuff worked, like first time. It wasn't even rocket science. But at the core of that is questioning the assumptions or sort of entering the thinking, first principles thinking, sort of looking at the reality of the situation and using that knowledge, applying that knowledge. So I mean, that's- So I would say my brain has this idea that you can question first assumptions. But I can go days at a time and forget that and you have to kind of like circle back to that observation. Because it is emotionally challenging. Well, it's hard to just keep it front and center because you operate on so many levels all the time and getting this done takes priority or being happy takes priority or screwing around takes priority. Like how you go through life is complicated. And then you remember, oh yeah, I could really think first principles. Oh shit, that's tiring. But you do for a while and that's kind of cool. So just as a last question in your sense from the big picture, from the first principles, do you think, you kind of answered it already, but do you think autonomous driving is something we can solve on a timeline of years? So one, two, three, five, 10 years as opposed to a century? Yeah, definitely. Just to linger on it a little longer, where's the confidence coming from? Is it the fundamentals of the problem, the fundamentals of building the hardware and the software? As a computational problem, understanding ballistics, roles, topography, it seems pretty solvable. I mean, and you can see this, like speech recognition for a long time, people are doing frequency and domain analysis and all kinds of stuff. And that didn't work for at all, right? And then they did deep learning about it and it worked great. And it took multiple iterations. And autonomous driving is way past the frequency analysis point. Use radar, don't run into things. And the data gathering is going up and the computation is going up and the algorithm understanding is going up and there's a whole bunch of problems getting solved like that. The data side is really powerful, but I disagree with both you and Elon. I'll tell Elon once again, as I did before, that when you add human beings into the picture, it's no longer a ballistics problem. It's something more complicated, but I could be very well proven wrong. Cars are hardly damped in terms of rate of change. Like the steering system's really slow compared to a computer. The acceleration of the acceleration is really slow. Yeah, on a certain time scale, on a ballistics time scale, but human behavior, I don't know. I shouldn't say- Human beings are really slow too. Weirdly, we operate half a second behind reality. Nobody really understands that one either. It's pretty funny. Yeah, yeah. We very well could be surprised. And I think with the rate of improvement in all aspects on both the compute and the software and the hardware, there's gonna be pleasant surprises all over the place.

https://youtu.be/ymcOLL2qEg8

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Bjarne Stroustrup: C++ Standards - C++03, C++11, C++14, C++17, C++20

But get back to the standardization. We are standardizing C++ under ISO rules, which are very open process. People come in, there's no requirements for education or experience. So you've started to develop C++ and there's a whole, what was the first standard established? What is that like? The ISO standard, is there a committee that you're referring to? There's a group of people. What is that like? How often do you meet? What's the discussion like? I'll try and explain that. So sometime in early 1989, two people, one from IBM, one from HP, turned up in my office and told me I would like to standardize C++. This was a new idea to me and I pointed out that it wasn't finished yet and it wasn't ready for formal standardization and such. And they said, no, Bjarne, you haven't gotten it. You really want to do this. Our organizations depend on C++. We cannot depend on something that's owned by another corporation that might be a competitor. Of course we could rely on you, but you might get run over by a bus. We really need to get this out in the open. It has to be standardized under formal rules and we are going to standardize it under ISO rules and you really want to be part of it because basically otherwise we'll do it ourselves. And we know you can do it better. So through a combination of arm twisting and flattery, it got started. So in late, in late 89, there was a meeting in DC at the, actually no, it was not ISO then, it was ANSI, the American National Standard, doing. We met there, we were lectured on the rules of how to do an ANSI standard. There was about 25 of us there, which apparently was a new record for that kind of meeting. And some of the old C guys that has been standardizing C was there. So we got some expertise in. So the way this works is that it's an open process. Everybody can sign up if they pay the minimal fee, which is about a thousand dollars, though less than, it's a little bit more now. And I think it's $1,280. It's not going to kill you. And we have three meetings a year. This is fairly standard. We tried two meetings a year for a couple of years that didn't work too well. So three one week meetings a year, and you meet and you have technical discussions, and then you bring proposals forward for votes. The votes are done one person per, one vote per organization. So you can't have, say IBM come in with 10 people and dominate things, that's not allowed. And these are organizations that extensively use C++? Yes. Or individuals. Or individuals. I mean, it's a bunch of people in a room deciding the design of a language based on which a lot of the world's systems run. Right. Well, I think most people would agree it's better than if I decided it, or better than if a single organization like AT&T decided it. I don't know if everyone agrees to that, by the way. Bureaucracies have their critics too. Yes, they're the... Look, standardization is not pleasant. It's horrifying. It's like democracy. But we, exactly. As Churchill says, democracy is the worst way except for all the others, right? And it's, I would say, the same with formal standardization. But anyway, so we meet and we have these votes and that determines what the standard is. A couple of years later, we extended this so it became worldwide. We have standard organizations that are active in currently 15 to 20 countries. And another 15 to 20 are sort of looking and voting based on the rest of the work on it. And we meet three times a year. Next week I'll be in Cologne, Germany, spending a week doing standardization. And we will vote out the committee draft of C++20, which goes to the National Standards Committee for comments and requests for changes and improvements. Then we do that and there's a second set of votes where hopefully everybody votes in favor. This has happened several times. First time we finished, we started in... The first technical meeting was in 1990. The last was in 98. We voted it out. That was the standard that people used till 11 or a little bit past 11. And it was an international standard. All the countries voted in favor. It took longer with 11. I'll mention why. But all the nations voted in favor. And we work on the basis of consensus. That is, we do not want something that passes 60-40 because then we're going to get dialects and opponents and people complain too much. They all complain too much, but basically it has no real effect. The standards have been obeyed. They have been working to make it easier to use many compilers, many computers, and all of that kind of stuff. And so the first... it was traditional with ISO standards to take 10 years. We did the first one in eight. Brilliant. And we thought we were going to do the next one in six because now we're good at it. It took 13. Yeah, it was named OX. It was named OX. Hoping that you would at least get it within the single, within the odds, the single digits. I thought we would get, I thought we would get six, seven or eight. The confidence of youth. That's right. Well, the point is that this was sort of like a second system effect. That is, we now knew how to do it. And so we're going to do it much better. And we got more ambitious. And it took longer. Furthermore, there is this tendency because it's a 10 year cycle or eight, doesn't matter. Just before you're about to ship, somebody has a bright idea. And so we really, really must get that in. We did that successfully with the STL. We got the standard library that gives us all the STL stuff. That basically, I think it saved C++. It was beautiful. And then people tried it with other things and it didn't work so well. They got things in, but it wasn't as dramatic and it took longer and longer and longer. So after C++ 11, which was a huge improvement and what basically what most people are using today, we decided never again. And so how do you avoid those slips? And the answer is that you ship more often so that if you have a slip on a 10 year cycle, by the time you know it's a slip, there's 11 years till you get it. Now with a three year cycle, there is about three, four years till you get it. Like the delay between feature freeze and shipping. So you always get one or two years more. And so we shipped 14 on time. We shipped 17 on time and we ship, we will ship 20 on time. It'll happen. And furthermore, this allow, this gives a predictability that allows the implementers, the compiler implementers, the library implementers, they have a target and they deliver on it. 11 took two years for most compilers were good enough. 14, most compilers actually getting pretty good in 14. 17, everybody shipped in 17. We are going to have at least almost everybody ship almost everything in 20. And I know this because they're shipping in 19. Delivery is good, delivery on time is good. And so, yeah. That's great. It works.

https://youtu.be/w7gIClKZ85s

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Barry Barish: Gravitational Waves and the Most Precise Device Ever Built | Lex Fridman Podcast #213

The following is a conversation with Barry Barish, a theoretical physicist at Caltech, and the winner of the Nobel Prize in Physics for his contributions to the LIGO detector and the observation of gravitational waves. LIGO, or the Laser Interferometer Gravitational Wave Observatory, is probably the most precise measurement device ever built by humans. It consists of two detectors with four kilometer long vacuum chambers situated 3,000 kilometers apart, operating in unison to measure a motion that is 10,000 times smaller than the width of a proton. It is the smallest measurement ever attempted by science, a measurement of gravitational waves caused by the most violent and cataclysmic events in the universe, occurring over tens of millions of light years away. To support this podcast, please check out our sponsors in the description. This is the Lex Friedman Podcast, and here is my conversation with Barry Barish. You've mentioned that you were always curious about the physical world, and that an early question you remember stood out where you asked your dad, why does ice float on water? And he couldn't answer, and this was very surprising to you. So you went on to learn why. Maybe you can speak to what are some early questions in math and physics that really sparked your curiosity? Yeah, that memory is kind of something I use to illustrate something I think that's common in science, that people that do science somehow have maintained something that kids always have. A small kid, eight years old or so, asks you so many questions usually, typically, that you consider them pests, you know, tell them to stop asking so many questions. And somehow, our system manages to kill that in most people. So in school, we make people study and do their things, but not to pester them by asking too many questions. And I think, not just myself, but I think it's typical of scientists like myself that have somehow escaped that. Maybe we're still children, or maybe we somehow didn't get it beaten out of us. But I think it's, I teach in college level, and it's, to me, one of the biggest deficits is the lack of curiosity, if you want, that we've beaten out of them, because I think it's an innate human quality. Is there some advice or insights you can give to how to keep that flame of curiosity going? I think it's a problem of both parents, and the parents should realize that's a great quality we have, that you're curious, and that's good. Instead, we have expressions like curiosity killed the cat, and more. But I mean, basically, it's not thought to be a good thing. You get it, curiosity killed the cat means if you're too curious, you get in trouble. And you can lead to trouble. I don't like cats anyway, so maybe it's a good thing. Yeah, that, to me, needs to be solved, really, in education and in homes. That realization that there's certain human qualities that we should try to build on and not destroy, one of them is curiosity. Anyway, back to me and curiosity. I was a pest and asked a lot of questions. My father generally could answer them, at that age. And the first one I remember that he couldn't answer was not a very original question, but basically that ice is made out of water, and so why does it float on water? And he couldn't answer it. And it may not have been the first question. It's the first one that I remember. And that was the first time that I realized that to learn and answer your own curiosity or questions, there's various mechanisms. In this case, it was going to the library or asking people who know more and so forth, but eventually you do it by what we call research. But it's driven by, hopefully you ask good questions. If you ask good questions and you have the mechanism to solve them, then you do what I do in life, basically. Not necessarily physics, but, and it's a great quality in humans, and we should nurture it. Do you remember any other kind of, in high school, maybe early college, more basic physics ideas that sparked your curiosity, or mathematics or science in general? I wasn't really into science until I got to college, to be honest with you. But just staying with water for a minute, I remember that I was curious why, what happens to water? It rains and there's water in a wet pavement, and then the pavement dries out. What happened to this water that came down? And I didn't know that much. And then eventually I learned in chemistry or something, water's made out of hydrogen and oxygen. Those are both gases. So how the heck does it make this substance, this liquid? Yeah, so that has to do with states of matter. I know perhaps LIGO and the thing for which you've gotten the Nobel Prize and the things, much of your life work, perhaps was a happy accident in some sense in the early days. But is there a moment where you looked up to the stars, and also the same way you wondered about water, wondered about some of the things that are out there in the universe? Oh yeah, I think everybody's looks and is interested in the universe. Oh yeah, I think everybody's looks and is in awe and is curious about what it is out there. And as I learned more, I learned, of course, that we don't know very much about what's there. And the more we learn, the more we know we don't know. I mean, we don't know what the majority of anything is out there. It's all what we call dark matter, dark energy. And that's one of the big questions. When I was a student, those weren't questions. So we even know less, in a sense, the more we look. So of course, I think that's one of the areas that almost it's universal. People see the sky, they see the stars, and they're beautiful, and see it looks different on different nights. And it's a curiosity that we all have. What are some questions about the universe that in the same way that you felt about the ice, that today, you mentioned to me offline, you're teaching a course on the frontiers of science, frontiers of physics. What are some questions outside the ones we'll probably talk about that it kind of, yeah, fill you with, get your flame of curiosity up and firing up, fill you with awe? Well, first, I'm a physicist, not an astronomer. So I'm interested in the physical phenomenon, really. So the question of dark matter and dark energy, which we probably won't talk about, are recent, they're in the last 20, 30 years, or certainly dark energy. Dark energy is a complete puzzle. It goes against what you will ask me about, which is general relativity and Einstein's general relativity. It basically takes something that he thought was what he called a constant, which isn't, and if that's even the right theory, and it represents most of the universe. And then we have something called dark matter, and there's good reason to believe it might be an exotic form of particles. And that is something I've always worked on, on particle accelerators and so forth. And it's a big puzzle what it is. It's a bit of a cottage industry in that there's lots and lots of searches, but it may be a little bit like looking for a treasure under rocks or something. We don't have really good guidance except that we have very, very good information that it's pervasive and it's there, and that it's probably particles, small, that evidences all of those things. But then the most logical solution doesn't seem to work, something called supersymmetry. And do you think the answer could be something very complicated? You know, I like to hope that, think that most things that appear complicated are actually simple if you really understand them. I think we just don't know at the present time, and it isn't something that affects us. It does affect, it affects how the stars go around each other and so forth, because we detect that there's missing gravity, but it doesn't affect everyday life at all. I tend to think and expect maybe that the answers will be simple, and we just haven't found it yet. Do you think those answers might change the way we see other sources of gravity, black holes, the way we see the parts of the universe that we do study? It's conceivable. The black holes that we've found in our experiment, and we're trying now to understand the origin of those, it's conceivable, but doesn't seem the most likely that they were primordial, that is, they were made at the beginning. And in that sense, they could represent at least part of the dark matter. So there can be connections, dark black holes, or how many there are, how much of the mass they encompass is still pretty primitive, we don't know. So before I talk to you more about black holes, let me take a step back to, I actually went to high school in Chicago, and would go to take classes at Fermilab, watch the buffalo and so on. Yeah. So let me ask about, you mentioned that Enrico Fermi was somebody who was inspiring to you in a certain kind of way. Why is that? Can you speak to that? Sure. He was amazing, actually. He's the last, this is not the, I'll come to the reason in a minute, but he had a big influence on me at a young age. But he was the last physicist of note that was both an experimental physicist and a theorist at the same time. And he did two amazing things within months. In 1933, we didn't really know what the nucleus was, what radioactive decay was, what beta decay was, when electrons come out of a nucleus. And near the end of 1933, the neutron had just been discovered. And that meant that we knew a little bit more about what the nucleus is, that it's made out of neutrons and protons. The neutron wasn't discovered until 1932. And once we discovered that there was a neutron and proton, and they made the nucleus, and then there are electrons that go around, the basic ingredients were there. And he wrote down not only just the theory, a theory, but a theory that lasted decades and has only been improved on, of beta decay, that is, the radiation. He did this, came out of nowhere, and it was a fantastic theory. He submitted it to Nature magazine, which was the primary best place to publish even then. And it got rejected as being too speculative. And so, he went back to his drawing board in Rome where he was, added some to it, made it even longer, because it's really a classic article, and then published it in the local Italian journal for physics and the German one. At the same time, in January of 1932, Giulio and Curie, for the first time, saw artificial radioactivity. This was an important discovery because radioactivity had been discovered much earlier. They had x-rays, and you shouldn't be using them, but there was radioactivity. People knew it was useful for medicine. But radioactive materials are hard to find, and so it wasn't prevalent. But if you could make them, then they had great use. And Giulio and Curie were able to bombard aluminum or something with alpha particles and find that they excited something that decayed and had some half-life and so forth, meaning it was an artificial version, or let's call it not a natural version, an induced version of radioactive materials. And Fermi somehow had the insight, and I still can't see where he got it, that the right way to follow that up was not using charged particles like alphas and so forth, but use these newly discovered neutrons as the bombarding particle. It seemed impossible. They barely had been seen. It was hard to get very many of them, but it had the advantage that they're not charged, so they go right into the nucleus. And that turned out to be the experimental work that he did that won him the Nobel Prize, and it was the first step in fission, the discovery of fission. And he did two completely different things, an experiment that was a great idea and a tremendous implementation, because how do you get enough neutrons? And then he learned quickly that not only do you want neutrons, but you want really slow ones. He learned that experimentally, and he learned how to make slow ones, and then they were able to go through the periodic table and make lots of particles. He missed on fission at the moment, but he had the basic information, and then fission follows soon after that. Forgive me for not knowing, but is the birth of the idea of bombarding neutrons, is that an experimental idea? Was it born out of an experiment? He just observed something, or is this an Einstein-style idea where you come up from basic intuition? I think it took a combination, because he realized that neutrons had a characteristic that would allow them to go all the way into the nucleus when we didn't really understand what the structure was of all this. So that took an understanding or recognition of the physics itself of how a neutron interacts compared to, say, an alpha particle that Giulio and Curie had used. And then he had to invent a way to have enough neutrons, and he had a team of associates, and he pulled it off quite quickly. So it was pretty astounding. And probably, maybe you can speak to it, his ability to put together the engineering aspects of great experiments and doing the theory, they probably fed each other. I wonder, can you speak to why we don't see more of that? Is that just really difficult to do? It's difficult to do. Yeah, I think in both theory and experiment, in physics anyway, it was conceivable if you had the right person to do it, and no one's been able to do it since. So I had the dream that that was what I was going to be like Fermi. So you loved both sides of it, the theory and the experiment. Yeah, yeah. I never liked the idea that you did experiments without really understanding the theory, or the theory should be related very closely to experiments. And so I've always done experimental work that was closely related to the theoretical ideas. I think I told you I'm Russian, so I'm going to ask some romantic questions. Yeah. Is it tragic to you that he's seen as the architect of the nuclear age, that some of his creations led to potentially, some of his work has led to potentially still the destruction of the human species, some of the most destructive weapons? Yeah. I think even more general than him, I gave you all the virtues of curiosity a few minutes ago. There's an interesting book called The Ratchet of Curiosity. A ratchet is something that goes in one direction. And that is written by a guy who's probably a sociologist or philosopher or something. And he picks on this particular problem, but other ones. And that is the danger of knowledge, basically. You're curious, you learn something. So it's a little bit like curiosity killed the cat. You have to be worried about whether you can handle new information that you get. So in this case, the new information had to do with really understanding nuclear physics. And that information, maybe we didn't have the sophistication to know all the details how to keep it under control. And Fermi himself was a very apolitical person. So he wasn't very driven by, or at least he appears in all of his writing, the writing of his wife, the interactions that others had with him as either he avoided it all, or he was pretty apolitical. I mean, he just saw the world through kind of the lens of a scientist. But he asked if it's tragic. The bomb was tragic, certainly on Japan. And he had a role in that. So I wouldn't want it as my legacy, for example. I mean, but brought it to the human species that it's the ratchet of curiosity that we do stuff just to see what happens. That curiosity, that in sort of my area of artificial intelligence, that's been a concern. On a small scale, on a silly scale, perhaps currently, there's constantly unintended consequences. You create a system, and you put it out there, and you have intuitions about how it will work. You have hopes how it will work, but you put it out there just to see what happens. And in most cases, because artificial intelligence is currently not super powerful, it doesn't create large-scale negative effects. But that same curiosity, as it progresses, might lead to something that destroys the human species. And the same may be true for bioengineering. There's people that engineer viruses to protect us from viruses, to see how close is this to mutating so it can jump to humans, or engineering defenses against those. And it seems exciting, and the positive applications are really exciting at this time. But we don't think about how that runs away in decades to come. Yeah. And I think it's the same idea as this little book, The Ratchet of Science, The Ratchet of Curiosity. I mean, whether you pursue, take curiosity and let artificial intelligence or machine learning run away with having its solutions to whatever you want, or we do it, it's, I think, a similar consequence. I think, from what I've read about Enrico Fermi, he became a little bit cynical about the human species towards the end of his life, about having observed what he observed. Well, he didn't write much. I mean, he died young. He died soon after the World War. There was already the work by Teller to develop the hydrogen bomb, and I think he was a little cynical of that, pushing it even further, and rising tensions between the Soviet Union and the US, and it looked like an endless thing. But he didn't say very much, but a little bit, as you said. Yeah, there's a few clips to sort of maybe pick on a bad mood, but in a sense that, almost like a sadness, a melancholy sadness, a hope that waned a little bit about that perhaps we can do, like this curious species can find the way out. Well, especially, I think, people who worked like he did at Los Alamos and spent years of their life somehow had to convince themselves that dropping these bombs would bring lasting peace. Yes, and it did. And that it didn't, yeah. As a small interesting aside, it'd be interesting to hear if you have opinions on this, his name is also attached to the Fermi Paradox, which asks if there is a, you know, it's a very interesting question, which is, it does seem, if you sort of reason, basically, that there should be a lot of alien civilizations out there. If the human species, if Earth is not that unique by basic, no matter the values you pick, it's likely that there's a lot of alien civilizations out there. And if that's the case, why have they not at least obviously visited us or sent us loud signals that everybody can hear? Fermi's quoted as saying, sitting down at lunch, I think it was with Teller and Herb York, who was kind of one of the fathers of the atomic bomb. And he sat down and he says something like, where are they? Which meant, where are these other? And then he did some numerology where he calculated, you know, how many, what they knew about how many galaxies there are, and how many stars, and how many planets there are like the Earth, and blah, blah, blah. That's been done much better by somebody named Drake. And so, people usually refer to the, I don't know whether it's called the Drake formula or something, but it has the same conclusion. The conclusion is it would be a miracle if there weren't other, you know, the statistics are so high that how can we be singular and separate? So, probably there is, but there's almost certainly life somewhere. Maybe there was even life on Mars a while back, but intelligent life, probably white. So, you know, the statistics say that. Communicating with us, I think that it's harder than people think. We might not know the right way to expect the communication, but all the communication that we know about travels at the speed of light. And we don't think anything can go faster than the speed of light. That limits the problem quite a bit. And it makes it difficult to have any back and forth communication. You could send signals like we try to or look for, but to have any communication, it's pretty hard when it has to be close enough that the speed of light would mean we could communicate with each other. And we didn't even understand that. I mean, we're an advanced civilization, but we didn't even understand that a little more than 100 years ago. So, are we just not advanced enough, maybe, to know something about that's the speed of light? Maybe there's some other way to communicate that isn't based on electromagnetism? I don't know. Gravity seems to have the same speed. That was a principle that Einstein had and something we've measured, actually. So, is it possible? I mean, so we'll talk about gravitational waves. And in some sense, there's a brainstorming going on, which is like, how do we detect the signal? Like, what would a signal look like and how would we detect it? And that's true for gravitational waves. That's true for basically any physics phenomena. You have to predict that that signal should exist. You have to have some kind of theory and model why that signal should exist. I mean, is it possible that aliens are communicating with us via gravity? Like, why not? Well, yeah, it's true. Why not? For us, it's very hard to detect these gravitational effects. They have to come from something that has a lot of gravity, like black holes. But we're pretty primitive at this stage. There's very reputable physicists that look for a fifth force, one that we haven't found yet. Maybe it's the key. So, you know, it's possible. What would that look like? What would a fifth force of physics look like exactly? Well, usually they think it's probably a longer-range force than we have now. But there are reputable colleagues of mine that spend their life looking for a fifth force. So, longer range than gravity? Yeah. It doesn't fall off like one over r squared, but maybe separately. Gravity, Newton taught us, goes like inversely, one over the square of the distance apart you are. So, it falls pretty fast. That's okay. So, now we have a theory of what consciousness is. It's just the fifth force of physics. There we go. That's a good hypothesis. Speaking of gravity, what are gravitational waves? Let's maybe start from the basics. We learned gravity from Newton, right? When you were young, you were told that if you jumped up, the earth pulled you down. And when the apple falls out of the tree, the earth pulls it down. And maybe you even asked your teacher why. But most of us accepted that. That was Newton's picture, the apple falling out of the tree. But Newton's theory never told you why the apple was attracted to the earth. That was missing in Newton's theory. Newton's theory also, Newton recognized at least one of the two problems I'll tell you. One of them is, there's more than those, but one is why does the earth, what's the mechanism by which the earth pulls the apple or holds the moon when it goes around, whatever it is. That's not explained by Newton, even though he has the most successful theory of physics ever, went 200 and some years with nobody ever seeing a violation. But he accurately describes the movement of an object falling down to earth, but he's not answering why that, what's the, because it's a distance, right? He gives a formula, which it's a product of the earth's mass, the apple's mass, inversely proportional to the square of the distance between, and then the strength, he called capital G, the strength he couldn't determine, but it was determined 100 years later. But no one ever saw a violation of this until a possible violation, which Einstein fixed, which was very small, that has to do with mercury going around the sun, the orbit being slightly wrong if you calculate it by Newton's theory. But so like most theories then in physics, you can have a wonderful one like Newton's theory, it isn't wrong, but you have to have an improvement on it to answer things that it can't answer. And in this case, Einstein's theory is the next step. We don't know if it's anything like a final theory or even the only way to formulate it either. But he formulated this theory, which he released in 1915. He took 10 years to develop it, even though in 1905, he solved three or four of the most important problems in physics in a matter of months, and then he spent 10 years on this problem before he let it out. And this is called general relativity, it's a new theory of gravity, 1915. In 1916, Einstein wrote a little paper where he did not do some fancy derivative of gravity, did not do some fancy derivation, instead he did what I would call, he used his intuition, which he was very good at too. And that is he noticed that if he wrote the formulas for general relativity in a particular way, they looked a lot like the formulas for electricity and magnetism. Being Einstein, he then took the leap that electricity and magnetism, we discovered only 20 years before that in the 1880s, have waves. Of course, that's light and electromagnetic waves, radio waves, everything else. So he said if the formulas look similar, then gravity probably has waves too. That's such a big leap, by the way. I mean, maybe you can correct me, but that just seems... That seems like a heck of a leap. Yeah, and it was considered to be a heck of a leap. So first that paper was, except for this intuition, was poorly written, had a serious mistake. It had a factor of two wrong in the strength of gravity, which meant if we use those formulas, we would... And two years later, he wrote a second paper. And in that paper, it turns out to be important for us because in that paper, he not only fixed his factor of two mistake, which he never admitted, he just wrote it, fixed it like he always did. And then he told us how you make gravitational waves, what makes gravitational waves. And you might recall in electromagnetism, we make electromagnetic waves in a simple way. You take a plus charge and minus charge, you oscillate like this, and that makes an electromagnetic waves. And a physicist named Hertz made a receiver that could detect the waves and put it in the next room. He saw them and moved forward and backward and saw that it was wave-like. So Einstein said it won't be a dipole like that, it'll be a four-pole thing. And that's what it's called a quadrupole moment that gives the gravitational waves. So he saw that again by insight, not by derivation. That set the table for what you needed to do to do it. At the same time, in the same year, Schwarzschild, not Einstein, said there were things called black holes. So it's interesting that that came the same. So what year was that? 1915. So that was in parallel with... I should probably know this, but did Einstein not have an intuition that there should be such things as black holes? That came from Schwarzschild. Oh, interesting. Yeah. So Schwarzschild, who was a German theoretical physicist, he got killed in the war, I think, in the First World War, two years later or so. He's the one that proposed black holes, that there were black holes. It feels like a natural conclusion of general relativity, no? Or is that not? Well, it may seem like it, but I don't know about a natural conclusion. It is a result of curved space-time, though. Right. But it's such a weird result that you might have to... It's a special... Yeah, it's a special case. Yeah. So I don't know. Anyway, Einstein then, an interesting part of the story is that Einstein then left the problem. Most physicists, because it really wasn't derived, he just made this, didn't pick up on it, or general relativity much, because quantum mechanics became the thing in physics. And Einstein only picked up this problem again after he immigrated to the US. So he came to the US in 1932, and I think in 1934 or 5, he was working with another physicist called Rosen, who he did several important works with, and they revisited the question. And they had a problem that most of us as students always had, that studied general relativity. General relativity is really hard, because it's four-dimensional instead of three-dimensional. And if you don't set it up right, you get infinities, which don't belong there. We call them coordinate singularities as a name. But if you get these infinities, you don't get the answers you want. And he was trying to derive now from general relativity gravitational waves. And in doing it, he kept getting these infinities. And so he wrote a paper with Rosen that he submitted to our most important journal, Physical Review Letters. And when it was submitted to Physical Review Letters, it was entitled, Do Gravitational Waves Exist? A very funny title to write 20 years after he proposed they exist. But it's because he had found these singularities, these infinities. And so the editor at that time, and part of it that I don't know, is peer review. We live and die by peer review as scientists send our stuff out. And I don't know when peer review actually started or what peer review Einstein ever experienced before this time. But the editor of Physical Review sent this out for review. He had a choice. He could take any article and just accept it. He could reject it, or he could send it for review. I believe the editors used to have much more power. Yeah, yeah. And he was a young man. His name was Tate. And he ended up being editor for years. But so he sent this for review to a theoretical physicist named Robertson, who was also in this field of general relativity, who happened to be on sabbatical at that moment at Yale at that moment at Caltech. Otherwise, his institution was Princeton, where Einstein was. And he saw that the way they set up the problem, the infinities were like I make it as a student, because if you don't set it up right in general relativity, you get these infinities. And so he reviewed the article and gave an illustration that if they set it up on what are called cylindrical coordinates, these infinities went away. He's the editor of physical review was obviously intimidated by Einstein. He wrote this really not a letter back like I would get saying, you know, you're screwed up in your paper. Instead, it was kind of what do you think of the comments of our referee? Einstein wrote back. It's a well-documented letter, wrote back a letter to physical review saying, I didn't send you the paper to send it to one of your so-called experts. I sent it to you to publish. I now I withdraw the paper. And he never published again in that journal. That was 1936. Instead, he rewrote it with the fixes that were made, changed the title and published it in what was called the Franklin Review, which is the Franklin Institute in Philadelphia, which is Benjamin Franklin Institute, which doesn't have a journal now, but did at that time. So the article is published. It's the last time he ever wrote about it. It remained controversial. So it wasn't until close to 1960, 1958, where there was a conference which brought that brought together the experts in general relativity to try to sort out whether there was whether it was true that there were gravitational waves or not. And there was a very nice derivation by a British theorist from the heart of the theory that gets gravitational waves. And that was number one. The second thing that happened at that meeting is Richard Feynman was there and Feynman said, well, if there's typical Feynman, if there's gravitational waves, they need to be able to do something. Otherwise, they don't exist. So they have to be able to transfer energy. So he made a idea of a Gedanken experiment that is just a bar with a couple of rings on it. And then if a gravitational wave goes through, it distorts the bar. And that creates friction on these little rings. Yeah. And that's heat and that's energy. So that meant. Is that a good idea? It sounds like a good idea. Yeah. It means that he showed that with the distortion of space time, you could transfer energy just by this little idea. And it was shown theoretically. So at that point, it was believed theoretically then by people that gravitational waves should exist. No, we should be able to detect them. We should be able to detect them, except that they're very, very small. And so what kind of, there's a bunch of questions here, but what kind of events would generate gravitational waves? You have to have this, what I call quadrupole moment. That comes about if I have, for example, two objects that go around each other like this, like the earth around the sun or the moon around the earth, or in our case, it turns out to be two black holes going around each other like this. So how's that different than basic oscillation back and forth? Is it just more common in nature to have? Oscillation is a dipole moment. So it has to be in three-dimensional space kind of oscillation. So you have to have something that's three-dimensional that'll give what I call a quadrupole moment that's just built into this. And luckily in nature, you have stuff. And luckily things exist, and it is luckily because the effect is so small that you could say, look, I can take a barbell and spin it, right, and detect the gravitational waves. But unfortunately, no matter how much I spin it, how fast I spin it, so I know how to make gravitational waves, but they're so weak, I can't detect them. So we have to take something that's stronger than I can make. Otherwise, we would do what Hertz did for electromagnetic waves, go in our lab, take a barbell, put it on something, spin it. Can I ask a dumb question? So a single object that's weirdly shaped, does that generate gravitational waves? So if it's rotating? Sure. But it's just much weaker signal. It's weaker. Well, we didn't know what the strongest signal would be that we would see. We targeted seeing something called neutron star. Actually, because black holes, we don't know very much about. It turned out we were a little bit lucky. There was a stronger source, which was the black holes. Well, another ridiculous question. So you say waves. What does a wave mean? Like the most ridiculous version of that question is, what does it feel like to ride a wave as you get closer to the source or experience it? Well, if you experience a wave, imagine that this is what happens to you. I don't know what you mean about getting close. It comes to you. So it's like this light wave or something that comes through you. So when the light hits you, it makes your eyes detect it. I flashed it. What does this do? It's like going to the amusement park, and they have these mirrors. You look in this mirror, and you look short and fat. And the one next to you makes you tall and thin. Imagine that you went back and forth between those two mirrors once a second. That would be a gravitational wave with a period of once a second. If you did it 60 times a second, go back and forth. And then that's all that happens. It makes you taller and shorter and fatter back and forth as it goes through you at the frequency of the gravitational wave. So the frequencies that we detect are higher than one a second, but that's the idea. And the amount is small. Amount is small. But if you're closer to the source of the wave, is it the same amount? Yeah, it doesn't dissipate. It doesn't dissipate. Okay, so it's not that fun of an amusement ride, a park ride. Well, it does dissipate, but it's proportional to the distance. Right, it's not a big power. Right, gotcha. So it would be a fun ride if you get a little bit closer or a lot closer. I mean, I wonder what the, okay, this is a ridiculous question, but I have you here. I mean, like the getting fatter and taller, I mean, that experience, for some reason that's mind-blowing to me because it brings the distortion of space-time to you. I mean, space-time is being morphed, right? Like this is a wave. That's right. That's so weird. And we're in space, so we're affected by it. Yeah, we're in space and now it's moving. And we're part of space. I don't know what to do with it. I mean, does it, okay. How much do you think about the philosophical implications of general relativity? Like that we're in space-time and it can be bent by gravity. Like, is that just what it is? Are we supposed to be okay with this? Because like Newton, even Newton is a little weird, right? But that at least like makes sense. That's our physical world. You know, when an apple falls, it makes sense. But like the fact that entirety of the space-time we're in can bend. Well, that's really mind-blowing. Well, let me make another analogy. This is a therapy session for me at this point. Yeah, right, another analogy. Thank you. So imagine you have a trampoline. Yes. Okay. What happens if you put a marble on a trampoline? It doesn't do anything, right? No. Maybe a little bit, but not much. Yeah. I mean, just if I drop it, it's not going to go anywhere. Now imagine I put a bowling ball at the center of the trampoline. Now I come up to the trampoline and I put a marble on, what happens? It'll roll towards the bowling ball. All right. So what's happened is the presence of this massive object distorted the space that the trampoline did. This is the same thing that happens to the presence of the earth, the earth and the apple. The presence of the earth affects the space around it just like the bowling ball on the trampoline. Yeah, this doesn't make me feel better. I'm referring from the perspective of an ant walking around on that trampoline. Then some guy just dropped a ball and not only dropped the ball, right? It's not just dropping a bowling ball. It's making the ball go up and down or doing some kind of oscillation thing where it's like waves. And that's so fundamentally different from the experience on being on flatland and walking around and just finding delicious sweet things as ant does. And it just feels like to me from a human experience perspective, completely, it's humbling. It's truly humbling. It's humbling, but we see that kind of phenomenon all the time. Let me give you another example. Imagine that you walk up to a still pond. Yes. Okay. Now I throw, you throw a rock in it, what happens? The rock goes in, sinks to the bottom, fine. And these little ripples go out and they travel out. That's exactly what happens. I mean, there's a disturbance, which is these safe, the bowling ball or black holes. And then the ripples, they go out in the water. They don't have any, they don't have the rock, any pieces of the rock. The thing is, I guess what's not disturbing about that is it's a, I mean, I guess a flat two-dimensional surface that's being disturbed. Like for a three-dimensional surface, three-dimensional space to be disturbed feels weird. It's even worse. It's four-dimensional because it's space and time. Time, yeah. So that's why you need Einstein is to make it four-dimensional. To make it okay? No. To make it four-dimensional. Yeah, to take the same phenomenon and look at it in all of space and time. Anyway, luckily for you and I and all of us, the amount of distortion is incredibly small. So it turns out that if you think of space itself, now this is gonna blow your mind too. If you think of space as being like a material like this table, it's very stiff. You know, we have materials that are very pliable, materials that are very stiff. So space itself is very stiff. So when gravitational waves come through it, luckily for us, it doesn't distort it so much that it affects our ordinary life very much. No, I mean, that's great. That's great. I thought there was something bad coming. No, this is great. That's great news. So I mean, that, I mean, perhaps we evolved as life on Earth. To be such that for us, this particular set of effects of gravitational waves is not that significant. Maybe that's why. You probably used this effect today or yesterday. To do what? So it's pervasive. You mean gravity or the way, or external? Because I only- Curvature of space. Curvature of space. How? I only care about the curvature of space. How, I only care personally as a human, right? The gravity of Earth. But you use it every day almost. Oh, it's curving. Because, no, no, no. It's in this thing. Every time it tells you where you are. Yeah. How does it tell you where you are? It tells you where you are because we have 24 satellites or some number that are going around in space and it asks how long it takes the being to go to the satellite. And come back the signal to different ones. And then it triangulates and tells you where you are. And then if you go down the road, it tells you where you are. Do you know that if you did that with the satellites and you didn't use Einstein's equations- Oh, no. You won't get the right answer. That's right. And in fact, if you take a road that's say 10 meters wide, I've done these numbers, and you ask how long you'd stay on the road if you didn't make the correction. For general relativity, this thing you're poo-pooing, because you're using every day, you'd go off the road. You'd go off the road. Well, actually, that might be my problem. So, you use it. So, don't poo-poo it. Well, I think I'm using an Android, and the GPS doesn't work that well, so maybe I'm using Newton's physics. So, I need to upgrade to general relativity. So, gravitational waves and Einstein had- wait, Feynman really does have a part in the story? Yeah. Was that one of the first kind of experimental proposed to detect gravitational waves? Well, he did what we call a Godankan experiment. That's a thought experiment. Okay. Not a real experiment. But then after that, then people believe gravitational waves must exist. You can kind of calculate how big they are. There's tiny. And so, people started searching. The first idea that was used was Feynman's idea, and the- oh, the very end of it. And it was to take a great big, huge bar of aluminum, and then put around- and it's made like a cylinder, and then put around it some very, very sensitive detectors so that if a gravitational wave happened to go through it, it would go- and you detect the extra strain that was there. And that was this method that was used until we came along. It wasn't a very good method to use. And what was the- so, we're talking about a pretty weak signal here. Yeah, that's why that method didn't work. So, what- can you tell the story of figuring out what kind of method would be able to detect this very weak signal of gravitational waves? So, remembering what happens when you go to the amusement park. Yeah. That it's going to do something like stretch this way and squash that way, squash this way and stretch this way. We do have an instrument that can detect that kind of thing. It's called an interferometer. And what it does is it just basically takes, usually, light. And the two directions that we're talking about, you send light down one direction and the perpendicular direction. And if nothing changes, it takes the same- and the arms are the same length. It just goes down, bounces back. And if you invert one compared to the other, they cancel. So, nothing happens. But if it's like the amusement park and one of the arms got- you know, it got shorter and fatter. So, it took longer to go horizontally than it did to go vertically. Then when they come back- when the light comes back, it comes back somewhat- it comes back somewhat out of time. And that basically is the scheme. The only problem is that that's not done very accurately in general, and we had to do it extremely accurately. So, what's the difficulty of doing so accurately? Okay. So, the measurement that we have to do is a distortion in time. How big is it? One- it's a distortion that's one part in 10 to the 21. That's 21 zeros and a one. Okay. Wow. And this- so, this is like a delay in the thing coming back? It's one of them coming back after the other one, but the difference is just one part in 10 to the 21. So, for that reason, we make it big. Let it- let the arms be long. Okay. So, one part in 10 to the 21. In our case, it's kilometers long. So, we have an instrument that's kilometers in one direction, kilometers in the other. How many kilometers are we talking about? Four kilometers? Four. Four kilometers in each direction. If you take then one part in 10 to the 21, we're talking about measuring something to 10 to the minus 18 meters. Okay. Now, to tell you how small that is, the proton thing we're made of that you can't go and grab so easily is 10 to the minus 15 meters. So, this is one one thousandth the size of a proton. That's the effect- size of the effect. Einstein himself didn't think this could be measured. Have you ever seen? Actually, he said that, but that's because he didn't- he didn't have the ability to measure that, but that's because he didn't anticipate modern lasers and techniques that we developed. Okay. So, maybe can you tell me a little bit what you're referring to as LIGO, the Laser Interferometer Gravitational-Wave Observatory. What is LIGO? Can you just elaborate kind of the big picture view here before I ask you specific questions about it? Yeah, so in the same idea that I just said, we have two long vacuum pipes, ten to- four kilometers long. Okay. We start with a laser beam and we divide the beam going down the two arms and we have a mirror at the other end, reflects it back. It's more subtle, but we bring it back. If there's no distortion in space-time and the lengths are exactly the same, which we calibrate them to be, then when it comes back, if we just invert one signal compared to the other, they'll just cancel. So, we see nothing. Okay. But if one arm got a little bit longer than the other, then they don't come back at exactly the same time, they don't exactly cancel, that's what we measure. So, to give a number to it, we have to do that to- we have the change of length to be able to do this 10 to the minus 18 meters to one part in 10 to the 12th. And that was the big experimental challenge that required a lot of innovation to be able to do. What- you gave a lot of credit to, I think, Caltech and MIT for some of the technical developments within this project. Is there some interesting things you can speak to, like, at the low level of some cool stuff that had to be solved? Like, what do we- I'm a software engineer, so all of this- I have so much more respect for everything done here than anything I've ever done. So, it's just code. So, I'll give you an example of doing mechanical engineering. At a better- at a- basically mechanical engineering and geology, maybe at a level. So, what are we- what's the problem? The problem is the following, that I've given you this picture of an instrument that by some magic I can make good enough to measure this very short distance. But then I put it down here, it won't work. And the reason it doesn't work is that the earth itself is moving all over the place all the time. You don't realize it, it seems pretty good to you. Yeah, I get it. But it's moving all the time. So, somehow it's moving so much that we can't deal with it. We happen to be trying to do the experiment here on earth, but we can't deal with it. So, we have to make the instrument isolated from the earth. Oh, no. At the frequencies we're at, we've got to float it. That's a mechanical- that's an engineering problem, not a physics problem. So, when you actually- like we're doing- we're having a conversation on a podcast right now, there's- and people who record music work with this, you know, how to create an isolated room. And they usually build a room within a room, but that's still not isolated. In fact, they say it's impossible to truly isolate from sound, from noise and stuff like that. But that's like one step of millions that you took, is building a room inside a room. You basically have to isolate all- No, this is actually an easier problem. You just have to do it really well. So, making a clean room is really a tough problem because you have to put a room inside a room. Yeah. You have to- So, this is- This is really simple engineering, or physics. Uh-huh. Okay, so what do you have to do? How do you isolate yourself from the Earth? Yes. First, we work at- we're not looking at all frequencies for gravitational waves, we're looking at particular frequencies that you can deal with here on Earth. So, what frequencies would those be? You were just talking about frequencies. I mean, I don't- We know by evolution, our bodies know. It's the audio band, okay? The reason our ears work where they work is that's where the Earth isn't going, making too much noise. Okay, so the reason our ears work the way they work is because this is where it's quiet. That's right. So, if you go to one hertz instead of 10 hertz, the Earth is really moving around. So, somehow, we live in what we call the audio band. It's tens of hertz to thousands of hertz. That's where we live. That's where we live, okay? If we're going to do an experiment on the Earth- Might as well do it in the- It's the same frequency. That's where the Earth is quiet. So, we have to work in that frequency. So, we're not looking at all frequencies, okay? So, the solution for the shaking of the Earth to get rid of it is pretty mundane. If we do the same thing that you do to make your car drive smoothly down the road. So, what happens when your car goes over a bump? Early cars did that. They bounced. Right. Okay, but you don't feel that in your car. So, what happened to that energy? You can't just disappear energy. So, we have these things called shock absorbers in the car. What they do is they absorb, they take the thing that went like that, and they basically can't get rid of the energy, but they move it to very, very low frequency. So, what you feel isn't- you feel it go smoothly, okay? All right. So, we also work at this frequency. So, we basically- why don't we have to do anything other than shock absorbers? So, we made the world's fanciest shock absorbers, okay? Not just like in your car where there's one layer of them. They're just the right squishiness and so forth. They're better than what's in the cars. And we have four layers of it. So, whatever shakes and gets through the first layer, we treat it in a second, third, fourth layer. So, it's a mechanical engineering problem. Yeah, that's what I said. So, it's a real- So, there's no weird tricks to it, like a chemistry type thing or- No, no. Just, well, the right squishiness, so you need the right material inside. And ours look like little springs, but they're- Springs? They're springs? They look like- So, legitimately like shock absorbers. Yeah. What? Okay. Okay. And this is now experimental physics at its limit. Okay, so you do this and we make the world's fanciest shock absorbers, just mechanical engineering. Just mechanical engineering, this is hilarious. But we didn't test- we weren't good enough to discover gravitational waves. So, we did another, we added another feature, and it's something else that you're aware of, probably have one, and that is to get rid of noise. You've probably noise, which is you don't like, and that's the same principle that's in these little Bose earphones. Noise cancelling? Noise cancelling. So, how do they work? They basically, you go on an airplane and they sense the ambient noise from the engines and cancel it, because it's just the same over and over again. They cancel it. And when the stewardess comes and asks you whether you want coffee or tea or a drink or something, you hear her, fine, because she's not ambient, she's a signal. So- Are we talking about active cancelling? Like where they actually- Active cancelling. So- This is, okay. So, another- Don't tell me you have active cancelling on this, besides the shock absorbers. Yeah, so we add this, so inside this array of shock absorbers, you asked for some interesting- This is awesome. So, inside this, it's harder than the earphone problem, but it's just engineering. We have to see, measure not just that the engine still made noise, but the earth is shaking, it's moving in some direction. So, we have to actually tell not only that there's noise and cancel it, but what direction it's from. So, we put this array of seismometers inside this array of shock absorbers and measure the residual motion and its direction. And we put little actuators that push back against it and cancel it. This is awesome. So, you have the actuators and you have the thing that is sensing the vibrations and then you have the actuators that adjust to that and do so in perfect synchrony. Yeah. What- If it all works right. And so, how much do we reduce the shaking of the earth? I mean- One part in 10 to the 12th. One part in 10- What gets through us is one part in 10 to the 12th. That's a pretty big reduction. You don't need that in your car, but that's what we do. And so, that's how isolated we are from the earth. And that was the biggest, I'd say, technical problem outside of the physics instrument, the interferometer. Can I ask you a weird question here? You make it very poetically and humorously. You're saying it's just a mechanical engineering problem. But is this one of the biggest precision mechanical engineering efforts ever? I mean, this seems exceptionally difficult. It is. And so, it took a long time. And I think nobody seems to challenge the statement that this is the most precision, precise instrument that's ever been built, LIGO. I wonder what listening to Led Zeppelin sounds on this thing. I don't know. No background noise. Wow. Wow. Wow. So, when you were first conceiving this, I would probably, if I was knowledgeable enough, kind of laugh off the possibility that this is even possible. I'm sure, like, how many people believe that this is possible? I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. But I would probably laugh off the possibility that this is possible. Did you believe this was possible? Oh, oh, I did. I didn't know for sure that we needed it active when we started. We did just passive, but we were doing the tests to develop the active to add as a second stage, which we ended up needing. But there was a lot of, you know, now there was a lot of skepticism. felt that money was being wasted, as we were all so expensive. Doing what I told you is not cheap. So it was kind of controversial. It was funded by the National Science Foundation. Can you just linger on this just for a little longer? The actuator thing, the act of canceling. Do you remember little experiments that were done along the way to prove to the team, to themselves that this is even possible? So from our, because I work with quite a bit of robots, and to me the idea that you could do it this precisely is humbling and embarrassing, frankly. Because like, this is another level of precision that I can't even, because robots are a mess. And this is basically one of the most precise robots ever. So, right. So like, is there, do you have any like small scale experiments that were done that just made this as possible? Yeah, and larger scale. We made a test, that also has to be in vacuum too, but we made test chambers that had this system in it, our first mock of this system, so we could test it. And optimize it and make it work. But it's just a mechanical engineering problem. Okay. Humans are just ape descendants, I gotcha. I gotcha. Is there any video of this? Like some kind of educational purpose visualizations of this active canceling? I don't think so. I mean, is this, does this live on? Well, we worked for parts of it, for the active canceling, we worked with, for the instruments, for the sensor and instruments, we worked with a small company near where you are, because it was our MIT people that got them, that were interested in the problem because they thought they might be able to commercialize it for making stable tables to make microelectronics, for example, which are limited by how stable the table is. I mean, at this point, it's a little expensive. So you never know, you never know where this leads. So maybe on the, let me ask you just, sticking at it a little longer, this silly old mechanical engineering problem, what was to you kind of the darkest moment of what was the hardest stumbling block to get over on the engineering side? Like, was there any time where there was a doubt, where it's like, I'm not sure we would be able to do this, a kind of a engineering challenge that was hit? Do you remember anything like that? I think the one that, that my colleague at MIT, Ray Weiss, worked on so hard and was much more of a worry than this, this is only a question if you're not doing well enough, you have to keep making it better somehow. But this whole huge instrument has to be in vacuum. And the vacuum tanks are this big around. And so it's the world's biggest high vacuum system. And so how do you make it, first of all? How do you make this four meter long sealed vacuum system? It has to be made out of- Four kilometers long. Four kilometers long, would I say something else? Meters. Four kilometers long. Big difference. Yeah, and so, but to make it, we started with a roll of stainless steel and then we roll it out like a spiral so that there's a spiral weld on it. Okay, so the engineering was fine, we did that, we worked through very good companies and so forth to build it. But the big worry was, what if you develop a leak? This is a high vacuum, not just vacuum system. Typically in a laboratory, if there's a leak, you put helium around the thing you have and then you detect where the helium is coming in. But if you have something as big as this, you can't surround it with helium. So you might not actually even know that there's a leak and it will be affecting- Well, we can measure how good the vacuum is. So we can know that, but a leak can develop and then we don't, how do we fix it or how do we find it? And so that was, you asked about a worry, that was always a really big worry. What's the difference between a high vacuum and a vacuum? What is high vacuum? That's like some delta close to vacuum? Is it some threshold? Well, there's a unit, high vacuum is when the vacuum and the units that are used, which are TORs, 10 to the minus nine, and there's high vacuum is usually used in small places. The biggest vacuum system period is at CERN in this big particle accelerator, but the high vacuum where they need really good vacuum so particles don't scatter in it is smaller than ours. So ours is a really large high vacuum system. I don't know, this is so cool. I mean, this is basically by far the greatest listening device ever built by human. The fact that like descendants of apes could do this, that evolution started with single cell organisms. I mean, is there any more, I'm a huge, theory is like, yeah, yeah. But like bridges, when I look at bridges from a civil engineering perspective, it's one of the most beautiful creations by human beings. It's physics, you're using physics to construct objects that can support huge amount of mass. And it's like structural, but it's also beautiful in that humans can collaborate to create that throughout history. And then you take this on another level. This is like, this is like exciting to me beyond measure that humans can create something so precise. But another concept lost in this, you just said, you started talking about single cell. Yeah. Okay. You have to realize this discovery that we made that everybody's bought off on, happened 1.3 billion years ago, somewhere. And then the signal came to us. 1.3 billion years ago, we were just converting on the earth from single cell to multi-cell life. So when this actually happened, this collision of two black holes, we weren't here. We weren't even close to being here. And we're both developing slowly. There were single, yeah, we were going from single cell to multi-cell life at that point. All to meet up at this point. Yeah. Wow, that's like, that's almost romantic. It is. Okay, so on the human side of things, it's kind of fascinating because you're talking about over a thousand people team for LIGO. Yeah. They started out with, you know, around a hundred and you've for parts of the time at least led this team. What does it take to lead a team like this of incredibly brilliant theoreticians and engineers and just a lot of different parties involved, a lot of egos, a lot of ideas. You had this funny example, I forget where, where in publishing a paper, you have to all agree on like, you know, the phrasing of a certain sentence or the title of the paper and so on. That's a very interesting, simple example. I'd love you to speak to that, but just in general, how, what does it take to lead this kind of team? Okay, I think the general idea is one we all know. You want to get where the sum of something is more than the individual parts is what we say, right? Yeah. So that's what you're trying to achieve. Yes. Okay, how do you do that actually? Mostly if we take multiple objects or people, I mean, you put them together, the sum is less. Yes. Why? Because they overlap. So you don't have individual things that, you know, this person does that, this person does that, then you get exactly the sum. But what you want is to develop where you get more than what the individual contributions are. We know that's very common. People use that expression everywhere. And it's the expression that has to be kind of built into how people feel it's working. Because if you're part of a team and you realize that somehow the team is able to do more than the individuals could do themselves, then they buy on kind of in terms of the process. So that's the goal that you have to have is to achieve that. And that means that you have to realize parts of what you're trying to do that require, not that one person couldn't do it, it requires the combined talents to be able to do something that neither of them could do themselves. And we have a lot of that kind of thing. And I think, I mean, build into some of the examples that I gave you. And so how do you then, so the key almost in anything you do is the people themselves, right? So in our case, the first and most important was to attract, to spend years of their life on this, and the best possible people in the world to do it. So the only way to convince them is that somehow it's better and more interesting for them than what they could do themselves. And so that's part of this idea. I got you, yeah, that's powerful. But nevertheless, there's best people in the world, there's egos. Is there something to be said about managing egos? Oh, that's, the human problem is always the hardest. And so that's an art, not a science, I think. I think the fact here that combined, there's a romantic goal that we had to do something that people hadn't done before, which was important scientifically and a huge challenge, enabled us to say, take and get, I mean, what we did, just to take an example, we used the light to go in this thing, comes from lasers. We need a certain kind of laser. So the kind of laser that we used, there were three different institutions in the world that had the experts that do this, maybe in competition with each other. So we got all three to join together and work with us to work on this, as an example. So that you had, and they had the thing that they were working together on a kind of object that they wouldn't have otherwise, and were part of a bigger team where they could discover something that isn't even engineers. These are engineers that do lasers, and they're part of our laser physicists. So could you describe the moment or the period of time when finally this incredible creation of human beings led to a detection of gravitational waves? It's a long story, unfortunately. This is a part that we started. Failures along the way kind of thing, or? All failures, that's all, it's built into it. Okay. If you're not a, if you're not. It's just mechanical engineering. You build on your failures, that's expected. So we're trying things that no one's done before. So it's technically not just gravitational waves. And so it's built on failures. But anyway, we did, before me, even the people did R&D on the concepts. But starting in 1994, we got money from the National Science Foundation to build this thing. It took about five years to build it. So by 1999, we had built the basic unit. It did not have active seismic isolation at that stage. It didn't have some other things that we have now. What we did at the beginning was stick to technologies that we had at least enough knowledge that we could make work or had tested in our own laboratories. And so then we put together the instrument. We made it work. It didn't work very well, but it worked. And we didn't see any gravitational waves. And then we figured out what limited us. And we went through this every year for almost 10 years, never seeing gravitational waves. We would run it, looking for gravitational waves for months, learn what limited us, fix it for months, and then run it again. Eventually, we knew we had to take another big step. And that's when we made several changes, including adding these active seismic isolation, which turned out to be a key. And we fortunately got the National Science Foundation to give us another couple hundred million dollars, a hundred million more, and we rebuilt it or fixed or improved it. And then in 2015, we turned it on, and we almost instantly saw this first collision of two black holes. And then we went through a process of, do we believe what we've seen? Yeah, I think you're one of the people that went through that process. It sounds like some people immediately believed it. Yeah. And then you were like, oh, it's disgusting. So as human beings, we all have different reactions to almost anything. So quite a few of my colleagues had a eureka moment immediately. I mean, it's the- Amazing. The figure that we put in our paper, first is just data. We didn't have to go through fancy computer programs to do anything. And we showed next to it the calculations of Einstein's equations. It looks just like what we detected. Wow. And we did it in two different detectors halfway across the US. So it was pretty convincing, but you don't wanna fool yourself. So we had, being a scientist, we had, for me, we had to go through and try to understand that the instrument itself, which was new, I said we had rebuilt it, couldn't somehow generate things that look like this. That took some tests. And then the second, you'll appreciate more, we had to somehow convince ourselves we weren't hacked in some clever way. Cybersecurity question. Yeah. Even though we're not on the internet. No, it can be physical access too. Yeah, that's fascinating. It's fascinating that you would think about that. I mean, not enough. I mean, because it matches prediction. So the chances of it actually being manipulated is very, very low. But nevertheless. We still could have disgruntled old graduate students who had worked with us earlier. I don't know how that's supposed to embarrass you. I suppose, yeah, I suppose I see. But about what I think you said, within a month you kind of convinced yourself. Within a month we convinced ourselves. We kept 1,000 collaborators quiet during that time. Then we spent another month or so trying to understand what we'd seen so that we could do the science with it instead of just putting it out to the world and let somebody else understand that it was two black holes and what it was. The fact that 1,000 collaborators were quiet is a really strong indication that this is a really close-knit team. Yeah, and they're around the world. Or either strong-knit or tight-knit or a strong dictatorship or something. Yeah, either fear or love. You can rule by fear or love. Yeah, right. Or you can go back to Machu Belly. All right, well, I mean, this is really exciting that that's a success story because it didn't have to be a success story, right? I mean, eventually, perhaps you could say it'll be an event, but it could have taken it over a century to get there. Oh, yeah, yeah. It's, and it's only downhill now, kind of. What do you mean it's only, you mean with gravitational waves? Well, yeah, we've now, we now, well, now we're off because of the pandemic, but when we turned off, we were seeing some sort of gravitational wave event each week. Now we're fixing, we're adding features where it'll probably be, when we turn back on next year, it'll probably be one every couple days. And they're not all the same, so it's learning about what's out there in gravity instead of just optics. So it's all great. We're only limited by, the fantastic thing, other than that this is a great field and it's all new and so forth, is that experimentally, the great thing is that we're limited by technology and technical limitations, not by science. So the, another, a really important discovery that was made before ours was what's called the Higgs boson, made on the big accelerator at CERN. You know, this huge accelerator, they discovered a really important thing. It's, you know, we have Einstein's equation, E equals MC squared. So energy makes mass or mass can make energy, and that's the bomb. But the mechanism by which that happens, not fission, but how do you create mass from energy, was never understood until there was a theory of it about 70 years ago now. And so they discovered it's named after a man named Higgs. It's called the Higgs boson. And so it was discovered, but since that time, and I worked on those experiments, since that time, they haven't been able to progress very much further, a little bit, but not a lot further. And the difference is that we're really lucky we're in what we're doing, in that there you see this Higgs boson, but there's tremendous amount of other physics that goes on, and you have to pick out the needle in the haystack kind of physics. You can't make the physics go away, it's there. In our case, we have a very weak signal, but once we get good enough to see it, it's weak compared to where we've reduced the background, but the background is not physics, it's just technology. It's getting ourselves better isolated from the earth or getting a more powerful laser. And so since 2015, when we saw the first one, we continually can make improvements that are enabling us to turn this into a real science to do astronomy, a new kind of astronomy. It's a little like astronomy. I mean, Galileo started the field. I mean, he basically took lenses that were made for classes and he didn't invent the first telescope, but made a telescope, looked at Neptune and saw that it had four moons. That was the birth of not just using your eyes to understand what's out there. And since that time, we've made better and better telescopes obviously, and astronomy thrives. And in a similar way, we're starting to be able to crawl, but we're starting to be able to do that with gravitational waves. And it's gonna be more and more that we can do as we can make better and better instruments. Because as I say, it's not limited by- Picking it out of others. Yeah, it's not limited by the physics. So you have an optimism about engineering. As human progress marches on, engineering will always find a way to build a large enough device, accurate enough device to detect the- As long as it's not limited by physics, yeah, they'll do it. So you, two other folks, and the entire team won the Nobel Prize for this big effort. There's a million questions I can ask for, but looking back, where does the Nobel Prize fit into all of this? You know, if you think hundreds of years from now, I venture to say that people will not remember the winners of a prize, but they'll remember creations like these. Maybe I'm romanticizing engineering. But I guess I wanna ask, how important is the Nobel Prize in all of this? Well, that's a complicated question. As a physicist, it's something, if you're trying to win a Nobel Prize, forget it, because they give one a year. So there's been 200 physicists who have won the Nobel Prize since 1900. Yeah. And so that's, you know, so things just have to fall right. So your goal cannot be to win a Nobel Prize. It wasn't my dream. It's tremendous for science. I mean, why the Nobel Prize for a guy that made dynamite and stuff is what it is, it's a long story. But it's the one day a year where actually the science that people have done is all over the world and so forth. Forget about the people again. You know, it is really good for science. Celebrating science. It celebrates science for several days, different fields, you know, chemistry, medicine, and so forth. And everybody doesn't understand everything about these. They're generally fairly abstract, but then it's, you know, it's on the front page of newspapers around the world. So it's really good for science. It's not easy to get science on the front page of the New York Times. It's not there. Should be, but it's not. And so the Nobel Prize is important in that way. It's otherwise, you know, I have a certain celebrity that I didn't have before. And now you get to be a celebrity that advertises science. It's a mechanism to remind us how incredible, how much credit science deserves in everything we have. Well, it has a little bit more. One thing I didn't expect, which is good, is that, you know, we have a government. I'm not picking on ours necessarily, but it's true of all governments, are not run by scientists. In our case, it's run by lawyers and businessmen. Okay. And at best, they may have an aide or something that knows a little science. So our country is, and all countries, are hardly to hardly take into account science in making decisions. Yes. Okay. And having a Nobel Prize, the people in those positions actually listen. So you have more influence. I don't care whether it's about global warming or what the issue is. There's some influence which is lacking otherwise. And people pay attention to what I say. If I talk about global warming, they wouldn't have before I had the Nobel Prize. Yeah, this is very true. You're like the celebrities who talk. Yeah. Celebrity has power. Celebrity has power. And that's important. And that's a good thing. That's a good thing, yeah. Singling out people, I mean, on the other side of it, singling out people has all kinds of, you know, whether it's for Academy Awards or for this, have unfairness and arbitrariness and so forth and so on. So, you know, that's the other side of the coin. Just like you said, especially with the huge experimental projects like this, you know, it's a large team and it does the nature of the Nobel Prize is singles out a few individuals to represent the team. Nevertheless, it's a beautiful thing. What are ways to improve LIGO in the future, increase the sensitivity? I've seen a few ideas that are kind of fascinating. Is, are you interested in them? Sort of looking, I'm not speaking about five years. Perhaps you could speak to the next five years, but also the next hundred years. Yeah, so let me talk to both the instrument and the science. Sure. So they go hand in hand. I mean, the thing that I said is if we make it better, we see more kinds of weaker objects and we do astronomy. Okay. We're very motivated to make a new instrument, which will be a big step, the next step, like making a new kind of telescope or something. And the ideas of what that instrument should be, haven't converged yet. There's different ideas in Europe. They've done more work to kind of develop the ideas, but they're different from ours and we have ideas. So, but I think over the next few years, we'll develop those. The idea is to make an instrument that's at least 10 times better than what we have, what we can do with this instrument, 10 times better than that. 10 times better means you can look 10 times further out. 10 times further out is a thousand times more volume. So you're seeing much, much more of the universe. The big change is that if you can see far out, you see further back in history. Yeah, you're traveling back in time. Yeah. And so we can start to do what we call cosmology instead of astronomy or astrophysics. Cosmology is really the study of the evolution of the- Oh, interesting, yeah. And so then you can start to hope to get to the important problems having to do with how the universe began, how it evolved and so forth, which we really only study now with optical instruments or electromagnetic waves. And early in the universe, those were blocked because basically it wasn't transparent. So the photons couldn't get out when everything was too dense. What do you think, sorry, on this tangent, what do you think an understanding of gravitational waves from earlier in the universe can help us understand about the Big Bang and all that kind of stuff? Yeah, yeah, that's, so- But it's a non, it's another perspective on the thing. Is there some insights you think could be revealed just to help a layman understand? Sure. First, we don't understand, we use the word Big Bang, we don't understand the physics of what the Big Bang itself was. So I think my, and in the early stage, there were particles and there was a huge amount of gravity and mass being made. And so the big, so I'll say two things. One is, how did it all start? How did it happen? And I'll give you at least one example that we don't understand, but we should understand. We don't know why we're here. Yes, no, we do not. I don't mean it philosophically. I mean it in terms of physics, okay? Now, what do I mean by that? If I go into my laboratory at CERN or somewhere and I collide particles together or put energy together, I make as much antimatter as matter. Right. Antimatter then annihilates matter and makes energy. So in the early universe, you made somehow, somehow a lot of matter and antimatter, but there was an asymmetry. Somehow there was more matter and antimatter. The matter and antimatter annihilated each other, at least that's what we think. And there was only matter left over, and we live in a universe that we see this all matter. We don't have any idea. We have an ideas, but we don't have any, we don't have any way to understand that at the present time with the physics that we know. Can I ask a dumb question? Does antimatter have anything like a gravitational field to send signals? So how does this asymmetry of matter and antimatter could be investigated or further understood by observing gravitational fields or weirdnesses in gravitational fields? I think that in principle, if there were, you know, anti-neutron stars instead of just neutron stars, we would see different kinds of signals, but it didn't get to that. We live in a universe that we've done enough looking, because we don't see matter, antiprotons anywhere, no matter what we look at, that it's all made out of matter. There is no antimatter except when we go in our laboratories. But when we go in our laboratories, we make as much antimatter as matter. So there's something about the early universe that made this asymmetry. So we can't even explain why we're here. That's what I meant. Physics-wise, not in terms of how we evolved and all that kind of stuff. So- So there might be inklings of the physics that gravitational waves- So gravitational waves don't get obstructed like light. So I said light only goes to 300,000 years. So it goes back to the beginning. So if you could study the early universe with gravitational waves, we can't do that yet. Then it took 400 years to be able to do that with optical, but then you can really understand the very, maybe understand the very early universe. So in terms of questions like why we're here or what the Big Bang was, we should be, we can in principle study that with gravitational waves. So to keep moving in this direction, it's a unique kind of way to understand our universe. So you think there's more Nobel Prize level ideas to be discovered in relation to- I'd be shocked if there- Gravitational waves. If there isn't, not even going to that, which is a very long range problem, but I think that we only see with electromagnetic waves, 4% of what's out there. So there must be, we looked for things that we knew should be there. There should be, I would be shocked if there wasn't physics, objects, science, and with gravity that doesn't show up in everything we do with telescopes. So I think we're just limited by not having powerful enough instruments yet to do this. Do you have a preference? I keep seeing this E-LISA idea. Yeah. Do you have a preference for earthbound or spacefaring mechanisms for- They're complementary. It's a little bit like- Measuring signal. It's completely analogous to what's been done in astronomy. So astronomy from the time of Galileo was done with visible light. Yeah. The big advances in astronomy in the last 50 years are because we have instruments that look at the infrared, microwave, ultraviolet, and so forth. So looking at different wavelengths has been important. Basically going into space means that we'll look at, instead of the audio band, which we look at, as we said, on the earth's surface, we'll look at lower frequencies. So it's completely complementary and it starts to be looking at different frequencies just like we do with astronomy. It seems almost incredible to me, engineering-wise, just like on earth, to send something that's kilometers across into space. Is that harder to engineer? It actually is a little different. It's three satellites separated by hundreds of thousands of kilometers. And they send a laser beam from one to the other. And if the triangle changes shape a little bit, they detect that from a passage. Did you say hundreds of thousands of kilometers? Yeah. Sending lasers to each other. Okay. It's just engineering. Yeah. It's possible though? Yes. It's doable? Yes. Okay. That's just incredible, because they have to maintain, I mean, the precision here is probably, there might be some more, what is it? Maybe noise is a smaller problem. I guess there's no vibration to worry about, like seismic stuff. So getting away from earth, maybe you get away from the seismic stuff. Yeah, those parts are easier. They don't have to measure it as accurately at low frequencies but they have a lot of tough engineering problems. In order to detect that the gravitational waves affect things, the sensors have to be what we call free masses, just like ours, are isolated from the earth. They have to isolate it from the satellite. And that's a hard problem. They have to do that pretty, not as well as we have to do it, but very well. And they've done a test mission and the engineering seems to be, at least in principle, in hand. This'll be in the 2030s when it floats. 2030s? Yeah. This is incredible. This is incredible. Let me ask about black holes. Yeah. So what we're talking about is observing and orbiting black holes. I saw the terminology of binary black hole systems. Binary black holes. That's when they're dancing? Okay. They're both going around each other just like the earth around the sun. Okay, is that weird that there's black holes going around each other? So finding binary systems of stars is similar to finding binary systems of- Of black holes. Well, they were once stars. So we haven't said what a black hole is physically yet. Yeah, what's a black hole? So black hole is, first, it's a mathematical concept or a physical concept, and that is a region of space. So it's simply a region of space where the curvature of space-time, meaning the gravitational field, is so strong that nothing can get out, including light. And there's light gets bent in gravitation, if the space-time is warped enough. And so even light gets bent around and stays in it. So that's the concept of a black hole. So it's not a, and maybe you can make, maybe that's a concept that didn't say how they come about. And there could be different ways they come about. The ones that we are seeing, there's a, we're not sure. That's what we're trying to learn now is what they, but the general expectation is that they come, these black holes happen when a star dies. So what does that mean that a star dies? What happens? A star like our sun basically makes heat and light by fusion. It's made up. And as it burns, it burns up the hydrogen and then the helium, and then, and slowly works its way up to the heavier and heavier elements that are in the star. And when it gets up to iron, the fusion process doesn't work anymore. And so the stars die, and that happens to stars. And then they do what's called a supernova. What happens then is that a star is a delicate, delicate balance between an outward pressure from fusion and light and burning, and an inward pressure of gravity trying to pull the masses together. Once it burns itself out, it goes, and it collapses, and that's a supernova. When it collapses, all the mass that was there is in a very much smaller space. And if a star, if you do the calculations, if a star is big enough, that can create a strong enough gravitational field to make a black hole. Our sun won't. It's too small. Too small. And we don't know exactly what it, but it's usually thought that a star has to be at least three times as big as our sun to make a black hole. But that's the physical way that you can make black holes. That's the first explanation that one would give for what we see, but it's not necessarily true. We're not sure yet. What we see in terms of, for the origins of black holes? No, the black holes that we see in gravitational waves. So, but you're also looking for the ones who are binary solar systems. So, they're binary systems, but they could have been made from binary stars, so there's binary stars around. So, that's. Gotcha. So, the first explanation is that that's what they are. Gotcha. Other, but what we see has some puzzles. This is kind of the way science works, I guess. Yeah. We see heavier ones than up to, we've seen one system that was 140 times the mass of our own sun already. Wow, yeah. That's not believed to be possible with the parent being a big star, because big stars can only be so big, or they are unstable. It's just the fact that they live in an environment that makes them unstable. So, the fact that we see bigger ones, they maybe come from something else. It's possible that they were made in a different way by little ones eating each other up, or maybe they were made, or maybe they came with the Big Bang, what we call primordial, which means they're really different. They came from that. We don't know at this point. If they came with the Big Bang, then maybe they account for what we call dark matter or some of it. Like there was a lot of them, if they came with, and because there's a lot of dark matter. But will gravitational waves give you any kind of intuition about the origin of these oscillating? We think that if we see the distributions enough of them, the distributions of their masses, the distributions of how they're spinning, so we can actually measure when they're going around each other, whether they're spinning like this. The direction of the spin? Or no, the orientation. Whether the whole system has any wobbles. What? So this is now, okay. We're doing that. And then you're constantly kind of crawling back and back in time. And we're crawling back in time and seeing how many there are as we go back. And so do they point back? So you're like, what is that discipline called? Cartography or something? You're like mapping the early universe via the lens of gravitational waves. Not yet the early universe, but at least back in time. Earlier, right. So black holes are this mathematical phenomenon, but they come about in different ways. We have a huge black hole at the center of our galaxy and other galaxies. Those probably were made some other way. We don't know. When the galaxies themselves had to do with the formation of galaxies, we don't really know. So the fact that we use the word black hole, the origin of black holes might be quite different depending on how they happen. They just have to, in the end, have a gravitational field that will bend everything in. How do you feel about black holes as a human being? There's this thing that's nearly infinitely dense, doesn't let light escape. Isn't that kind of terrifying? Feels like the stuff of nightmares. I think it's an opportunity. To do what exactly? So like the early universe is an opportunity. In fact, we can study the early universe. We can learn things like I told you. And here again, we have an embarrassing situation in physics. We have two wonderful theories of physics. One based on quantum mechanics, quantum field theory. And we can go to a big accelerator like at CERN and smash particles together and almost explain anything that happens beautifully using quantum field theory and quantum mechanics. Then we have another theory of physics called general relativity, which is what we've been talking about most of the time, which is fantastic at describing things at high velocities, long distances, and so forth. So that's not the way it's supposed to be. We're trying to create a theory of physics, not two theories of physics. So we have an embarrassment that we have two different theories of physics. People have tried to make a unified theory, what they call a unified theory. You've heard those words for decades. They still haven't. That's been primarily done theoretically or people actively do that. My personal belief is that like much of physics, we need some clues. So we need some experimental evidence. So where is there a place? If we go to CERN and do those experiments, gravitational waves or general relativity don't matter. If we go to study our black holes, elementary particle physics doesn't matter. We're studying these huge objects. So where might we have a place where both phenomenon have to be satisfied? An example is black holes. Inside black holes. Yeah. So we can't do that today. But when I think of black hole, it's a potential treasure chest of understanding the fundamental problems of physics and maybe can give us clues to how we bring the embarrassment of having two theories of physics together. That's my own romantic idea. What's the worst that could happen? It's so enticing. Just go in and look. Do you think, how far are we away from figuring out the unified theory of physics, a theory of everything? What's your sense? Who will solve it? Like what discipline will solve it? Yeah. I think so little progress has been made without more experimental clues, as I said, that we're just not able to say that we're close without some clues. The most popular theory these days that might lead to that is called string theory. Yeah. The problem with string theory is it works, it solves a lot of beautiful mathematical problems we have in physics. It's very satisfying theoretically, but it has almost no predictive, maybe no predictive ability because it is a theory that works in 11 dimensions. We live in a physical world of three space and one time dimension. In order to make predictions in our world with string theory, you have to somehow get rid of these other seven dimensions. That's done mathematically by saying they curl up on each other on scales that are too small to affect anything here. But how you do that, and that's okay, that's an okay argument, but how you do that is not unique. So that means if I start with that theory and I go to our world here, I can't uniquely go to it. Which means it's not predictive. It's not predictive. And that's actually- And that's a killer, that's a killer. And string theory is, it seems like from my outsider's perspective, has lost favor over the years, perhaps because of this very idea. Yeah, it's a lack of predictive power. I mean, that science has to connect to something where you make predictions as beautiful as it might be. So I don't think we're close. I think we need some experimental clues. It may be that information on something we don't understand presently at all, like dark energy, or probably not dark matter, but dark energy or something might give us some ideas. But I don't think we're, I can't envision right now in the short term, meaning the horizon that we can see how we're gonna bring these two theories together. A kind of two-part question, maybe just asking the same thing in two different ways. One question is, do you have hope that humans will colonize the galaxy, so expand out, become a multi-planetary species? Another way of asking that, from a gravitational and a propulsion perspective, do you think we'll come up with ways to travel closer to the speed of light, or maybe faster than the speed of light, which would make it a whole heck of a lot easier to expand out into the universe? Yeah. Well, I think we're not, that's very futuristic. I think we're not that far from being able to make a one-way trip to Mars. That's then a question of whether people are willing to send somebody on a one-way trip. Oh, I think they are. There's a lot of, the Explorer's burned bright within their hearts. Yeah, exactly. There's a lot of people willing to die for the opportunity to explore new territory. Yeah. So, you know, this recent landing on Mars is pretty impressive. They have a little helicopter, they're gonna fly around. You can imagine, you can imagine in the not-too-distant future that you could have, I don't think civilization's colonizing. I can envision, but I can envision something more like the South Pole. We haven't colonized Antarctica, because it's all ice and cold and so forth, but we have stations. So, we have a station that's self-sustaining at the South Pole. I've been there. It has- Wow, really? Yeah. What's that like? Because there's parallels there to go to Mars. It's fantastic. What's the journey like? The journey involves going, the South Pole station is run in the US by the National Science Foundation. I went because I was on the National Science Board that runs the National Science Foundation. And so, you get a VIP trip if you're healthy enough to the South Pole to see it, which I took. You fly from the US to Australia, to Christ Church in Australia, in Southern Australia. And from there, you fly to McMurdo Station, which is on the coast. And it's the station with about 1,000 people right on the coast of Antarctica. It's about a seven or eight hour flight, and they can't predict the weather. So, when I flew from Christ Church to McMurdo Station, they tell you in advance, you do it in a military aircraft, they tell you in advance that they can't predict whether they can land, because they have to land on ice. That's reassuring. Yeah, and so, about halfway, the pilot got on and said, sorry, this is, they call it a boomerang flight. You know, a boomerang goes out and comes back. So, we had to stay a little while in Christ Church, but then we eventually went to McMurdo Station and then flew to the South Pole. The South Pole itself is, when I was there, it was minus 51 degrees. That was summer. It has zero humidity, and it's about 11,000 feet altitude, because it's never warm enough for anything to melt, so it doesn't snow very much, but it's about 11,000 feet of snowpack. So, you land in a place that's high altitude, cold as could be, and incredibly dry, which means you have a physical adjustment. The place itself is fantastic. They have this great station there. They do astronomy at the South Pole. Nature-wise, is it beautiful? What's the experience like? Or is it like visiting any town? No, it's very small. There's only less than 100 people there, even when I was there. There were about 50 or 60 there, and in the winter, there's less, half of that. Their winter. It gets real cold. It gets really cold, yeah. But it's a station, and I think, and that's, I mean, we haven't gone beyond that. On the coast of Antarctica, they have greenhouses, and they're self-sustaining in McMurdo Station, but we haven't really settled more than that kind of thing in Antarctica, which is a big country, or big plot, a big piece of land. So, I can't envision colonizing it, people living so much, as much as I can see the equivalent of the South Pole Station. Well, in the computing world, there's an idea of backing up your data, and then you wanna do off-site backup to make sure that if the whole thing, if your whole house burns down, that you can have a backup off-site of the data. I think the difference between Antarctica and Mars is Mars is an off-site backup, that if we have nuclear war, whatever the heck might happen here on Earth, it'd be nice to have a backup elsewhere. And it'd be nice to have a large enough colony where we sent a variety of people, except a few silly astronauts in suits, have an actual vibrant, get a few musicians and artists up there, get a few, maybe one or two computer scientists, those are essential, maybe even a physicist, but I'm not sure. Yeah, maybe not. So that comes back to something you talked about earlier, which is the Fermi's paradox, because you talked about having to escape. And so the missing, one number you don't know how to use in Fermi's calculation or Drake, who's done it better, is how long do civilizations last? We've barely gotten to where we can communicate with electricity and magnetism, and maybe we'll wipe ourselves out pretty soon. Are you hopeful in general? Like you think we've got another couple hundred years at least, or are you worried? Well, no, I'm hopeful, but I don't know if I'm hopeful in the longterm. If you say, are we able to go for another couple thousand years? I'm not sure. I think we have where we started, the fact that we can do things that don't allow us to kind of keep going, or there can be, whether it ends up being a virus that we create or ends up being the equivalent of nuclear war or something else. It's not clear that we can control things well enough. So speaking of really cold conditions and not being hopeful and eventual suffering and destruction of the human species, let me ask you about Russian literature. You mentioned, how's that for a transition? I'm doing my best here. You mentioned that you used to love literature when you were younger and you were even, or hoping to be a writer yourself. That was the motivation. And some of the books I've seen that you listed that were inspiring to you was from Russian literature, like I think Tolstoy, Dostoevsky, Solzhenitsyn. Yeah, right. Maybe in general, you can speak to your fascination with Russian literature or in general, what you picked up from those. I'm not surprised you picked up on the Russian literature. I'm sorry. Your background, but that's okay. It's the, when I- You should be surprised that I didn't make the entire conversation about this. That's the real surprise. I didn't really become a physicist or want to go in science until I started college. So when I was younger, I was good at math and that kind of stuff, but I didn't really, I came from a family, nobody went to college and I didn't have any mentors. But I'd like to read when I was really young. And so when I was very young, I read, I always carried around a pocketbook and read it. And my mother read these mystery stories and I got bored by those eventually. And then I discovered real literature. I don't know at what age, but about 12 or 13. And so then I started reading good literature and there's nothing better than Russian literature, of course, in reading good literature. So I read quite a bit of Russian literature at that time. And so you asked me about, well, I don't know, I'll say a few words. Dostoevsky, so what about Dostoevsky? For me, Dostoevsky was important in, I mean, I've read a lot of literature because it's kind of the other thing I do with my life. And he made two incredible, in addition to his own literature, he influenced literature tremendously by having, I don't know how to pronounce, polyphony. So he's the first real serious author that had multiple narrators. And that's, he absolutely is the first. And he also was the first, he began existential literature. So the most important book that I've read in the last year when I've been forced to be isolated was existential literature. I decided to reread Camus' The Plague. Oh yeah, that's a great book. It's a great book, and it's right now to read it. It's fantastic. I think that book is about love, actually. Love for humanity. It is, but it has all the, it has all the, if you haven't read it in recent years, I had read it before, of course, but to read it during this, because it's about a plague, so it's really fantastic to read now. But that reminds me of, he was a great existentialist, but the beginning of existential literature was Dostoevsky. So in addition to his own great novels, he had a tremendous impact on literature. And there's also, for Dostoevsky, unlike most other existentialists, he was, at least in part, religious. I mean, religiosity permeated his idea. I mean, one of my favorite books of his is The Idiot, which is a Christ-like figure in there. Well, there's Prince Mishkin, is that his name? Prince Mishkin, yeah. Yeah, Mishkin. Yeah, Mishkin. Yeah. That's one thing about, you read it in English, I presume. Yeah, yeah. Yeah, so that's the names. That's what gets a lot of people, is there's so many names, so hard to pronounce. You have to remember all of them. It's like you have the same problem. But he was a great character, so that, yeah. I kind of, I have a connection with him, because I often, the title of the book, Idiot, The Idiot, is, I kind of, I often call myself an idiot, because that's how I feel. I feel so naive about this world, and I'm not sure, I'm not sure why that is. Maybe it's genetic, or so on, but I, I have a connection, a spiritual connection to that character. To Mishkin. To Mishkin, yeah. That you're just, in the- But he was far from an idiot. No, in some sense, in some sense. But in another sense, maybe not of this kind. In another sense, he was. Yeah. I mean, he was a bumbler, a bunker. Yeah. But you also mentioned Solzhenitsyn. Yes. Very interesting. Yes. Did- And he always confused me. Of course, he was really, really important in writing about the Stalin, and first getting in trouble, and then he, later, he wrote about Stalin in a way, I forget what it was, what the book was, in a way that was very critical of Lenin. Yeah, he's evolved through the years, and he actually showed support for Putin eventually. It was a very interesting transition he took, no, journey he took through thinking about Russia and the Soviet Union. But I think what I get from him is basic, it's like Viktor Frankl has this man's search for meaning. I have a similar kind of sense of of the cruelty of human nature. Yeah. Cruelty of indifference. Yeah. But also the ability to find happiness in the small joys of life. That's something, there's nothing like a prison camp that makes you realize you could still be happy with a very, very little. Well, yeah, he was, his description of how to make, how to go through a day and actually enjoy it in a prison camp is pretty amazing. Yeah. Oh, and some prison camp. I mean, it's the worst of the worst. The worst of the worst. And also just, you do think about the role of authoritarian states, and in hopeful idealistic systems somehow leading to the suffering of millions. And I, this might be arguable, but I think a lot of people believe that Stalin, I think genuinely believed that he's doing good for the world. And he wasn't. This is a very valuable lesson that even evil people think they're doing good. Otherwise it's too difficult to do the evil. The best way to do evil is to believe, frame it in a way like you're doing good. And then this is a very clear picture of that, which is the Gulags. And Solzhenitsyn is one of the best people to reveal that. Yeah. The most recent thing I read, it isn't actually fiction, was the woman, I can't remember her name, who got the Nobel Prize about, within the last five years. I don't know whether she's Ukrainian or Russian, but there are interviews. Have you read that? Interview of Ukrainian survivors of? Well, I think she may be originally Ukrainian. The book's written in Russian and translated into English, and many of the interviews are in Moscow and places. But she won the Nobel Prize within the last five years or so. But what's interesting is that these are people of all different ages, all different occupations and so forth, and they're reflecting on their reaction to basically the present Soviet system, the system they lived with before. There's a lot of looking back by a lot of them with, well, it being much better before. Yeah. I don't know what, in America, we think we know the right answer, what it means to build a better world. I'm not so sure. I think we're all just trying to figure it out. Yeah, there's- We're doing our best. I think you're right. Is there advice you can give to young people today besides reading Russian literature at a young age about how to find their way in life, how to find success in career or just life in general? I just, my own belief, it may not be very deep, but I believe it. I think you should follow your dreams, and you should have dreams, and follow your dreams if you can to the extent that you can. We spend a lot of our time doing something with ourselves, in my case, physics, in your case, I don't know, whatever it is, machine learning and this. We should, yeah, should have fun. What was, wait, wait, wait, wait, follow your dreams, what dream did you have? Because there's- Well, originally, I was- Because you didn't follow your dream. I thought you were supposed to be a writer. Well, I changed along the way. I was gonna be, but I changed. What happened? That was what happened? Oh, I decided to take the most serious literature course in my high school, which was a mistake. I'd probably be a second-rate writer now. Could be a Nobel Prize-winning writer. And the book that we read, the book that we read, even though I had read Russian novels, I was 15, I think, cured me from being a novelist. Destroyed your dream? Yes. Cured you, okay, what was the book? Moby Dick. Okay. So why Moby Dick? Yeah, why? And so I've read it since, and it's a great novel. Maybe it's as good as the Russian novels. I've never made it through. I lost, it was too boring, it was too long. Okay, your words are gonna mesh with what I say. Excellent. And you may have the same problem at a older age. Maybe that's why I'm not a writer. It may be. So the problem is, Moby Dick is, what I remember was there was a chapter that was maybe 100 pages long, all describing this, why there was Ahab and the white whale. And it was the battle between Ahab with his wooden peg leg and the white whale. And there was a chapter that was 100 pages long in my memory, I don't know how long it really was, that described in detail the great white whale and what he was doing and what his fins were like and this and that. And it was so incredibly boring, the word you used, that I thought if this is great literature, screw it. How fascinating. Okay, now why did I have a problem? I know now in reflection, because I still read a lot, and I read that novel after I was 30 or 40 years old, and the problem was simple. I diagnosed what the problem was. That novel, in contrast to the Russian novels, which are very realistic and point of view, is one huge metaphor. Oh yeah. At 15 years old, I probably didn't know the word, and I certainly didn't know the meaning of a metaphor. Yeah, like why do I care about a fish? Why are you telling me all about this fish? Yeah, exactly. It's one big metaphor, so reading it later as a metaphor, I could really enjoy it. But the teacher gave me the wrong book, or maybe it was the right book because I went into physics. But it was truly, I think, I may oversimplify, but it was really that I was too young to read that book. Not too young to read the Russian novels, interestingly, but too young to read that because I probably didn't even know the word, and I certainly didn't understand it as a metaphor. Well, in terms of fish, I recommend people read Old Man and the Sea, much shorter, much better. It's still a metaphor, though, but you can read it just as a story about a guy catching a fish, and it's still fun to read. I had the same experience as you, not with Moby Dick, but later in college, I took a course on James Joyce. Don't ask me why. I was majoring in computer science. I took a course on James Joyce, and I kept being told that he is widely considered, by many considered, to be the greatest literary writer of the 20th century. And I kept reading, I think, so his short story is The Dead, I think it's called. It was very good. Well, not very good, but pretty good. And then Ulysses. It's actually very good. It is very good. I mean, The Dead, the final story, still rings with me today. But then Ulysses was, I got through Ulysses with the help of some Cliff Notes and so on, but, and so I did Ulysses and then Finnegan's Wake. The moment I started Finnegan's Wake, I said, this is stupid. That's when I went full into, I don't know. That's when I went full Kafka, Bukowski, like people who just talk about the darkness of the human condition in the fewest words possible, and without any of the music of language. So it was a turning point as well. I wonder when is the right time to do the, to appreciate the beauty of language. Like even Shakespeare. I was very much off-put by Shakespeare in high school, and only later started to appreciate its value in the same way. Let me ask you a ridiculous question. I mean, because you've read Russian literature, let me ask this one last question. I might be lying, there might be a couple more, but what do you think is the meaning of this whole thing? You got a Nobel Prize for looking out into the, trying to reach back into the beginning of the universe, listening to the gravitational waves, but that still doesn't answer the why. Why are we here? Beyond just the matter and antimatter. The philosophical question. The philosophical question about the meaning of life I'm probably not really good at. I think that the individual meaning, the individual meaning, I would say rather simplistically is whether you've made a difference, positive difference I'd say, for anything besides yourself. Meaning you could have been important to other people, or you could have discovered gravitational waves that matters to other people or something, but something beyond just existing on the earth as an individual. So your life has meaning if you have affected either knowledge or people or something beyond yourself. That's a simplistic statement, but it's about as good as I can have. That may, in all of its simplicity, it may be very true. Do you think about, does it make you sad that this ride ends? Do you think about your mortality? Yeah. Are you afraid of it? I'm not exactly afraid of it, but saddened by it. And I'm old enough to know that I've lived most of my life, and I enjoy being alive. I can imagine being sick and not wanting to be alive, but I'm not. And so I'm not- It's been a good ride. Yeah, and I'm not happy to see it come to an end. I'd like to see it prolong. But I don't fear the dying itself or that kind of thing. It's more I'd like to prolong what is, I think, a good life that I'm living and still living. It's kind of, it's sad to think that the fineness of it is the thing that makes it special. And also sad to, to me, at least, it's kind of, I don't think I'm using too strong of a word, but it's kind of terrifying, the uncertainty of it, the mystery of it. The mystery of death. The mystery of it, yeah, of death. When we're talking about the mystery of black holes, that's somehow distant, that's somehow out there, and the mystery of our own. But even life, the mystery of consciousness, I find so hard to deal with, too. I mean, it's not as painful. I mean, we're conscious, but the whole magic of life, we can understand, but consciousness, where we can actually think and so forth, it's pretty. It seems like such a beautiful gift that it really sucks that we get to let go of it, we have to let go of it. What do you hope your legacy is? As I'm sure they will. Aliens, when they visit, and humans have destroyed all of human civilization. Aliens read about you in an encyclopedia that we'll leave behind. What do you hope it says? Well, I would hope they, if, to the extent that they evaluated me, felt that I helped move science forward as a tangible contribution, and that I served as a good role model for how humans should live their lives. And we're part of creating one of the most incredible things humans have ever created. So yes, there's the science, that's the Fermi thing, right? And the instrument, I guess. And the instrument. Instrument is a magical creation, not just by a human, by a collection of humans. The collaboration is, that's humanity at its best. I do hope we last quite a bit longer, but if we don't, this is a good thing to remember humans by. At least they built that thing. That's pretty impressive. Barry, this was an amazing conversation. Thank you so much for wasting your time in explaining so many things so well. I appreciate your time today. Thank you. Thanks for listening to this conversation with Barry Barish. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Werner Heisenberg, a theoretical physicist and one of the key pioneers of quantum mechanics. Not only is the universe stranger than we think, it is stranger than we can think. Thank you for listening and hope to see you next time.

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Daniel Kahneman: Deep Learning (System 1 and System 2) | AI Podcast Clips

So we're not talking about humans, but if we think about building artificial intelligence systems, robots, do you think all the features and bugs that you have highlighted in human beings are useful for constructing AI systems? So both systems are useful for perhaps instilling in robots? What is happening these days is that actually what is happening in deep learning is more like a system one product than like a system two product. I mean, deep learning matches patterns and anticipate what's going to happen. So it's highly predictive. But what deep learning doesn't have, and many people think that this is the critical, it doesn't have the ability to reason, so there is no system two there. But I think very importantly, it doesn't have any causality or any way to represent meaning and to represent real interaction. So until that is solved, what can be accomplished is marvelous and very exciting, but limited. That's actually really nice to think of current advances in machine learning as essentially system one advances. So how far can we get with just system one? If we think of deep learning and artificial intelligence systems? It's very clear that deep mind has already gone way beyond what people thought was possible. I think the thing that has impressed me most about the developments in AI is the speed. It's that things, at least in the context of deep learning, and maybe this is about to slow down, but things moved a lot faster than anticipated. The transition from solving chess to solving Go, that's bewildering how quickly it went. The move from alpha Go to alpha zero is sort of bewildering the speed at which they accomplished that. Now, clearly, there are many problems that you can solve that way, but there are some problems for which you need something else. Something like reasoning. Well, reasoning and also, you know, one of the real mysteries, psychologist Gary Marcus, who is also a critic of AI, I mean, what he points out, and I think he has a point, is that humans learn quickly. Human don't need a million examples, they need two or three examples. So clearly, there is a fundamental difference. And what enables a machine to learn quickly, what you have to build into the machine, because it's clear that you have to build some expectations or something in the machine to make it ready to learn quickly, that at the moment seems to be unsolved. I'm pretty sure that DeepMind is working on it, but if they have solved it, I haven't heard yet. They're trying to actually, them and OpenAI are trying to start to get to use neural networks to reason. So assemble knowledge, of course, causality is, temporal causality is out of reach to most everybody. You mentioned the benefits of System 1 is essentially that it's fast, allows us to function in the world. Fast and skilled, yeah. It's skilled. And it has a model of the world. You know, in a sense, I mean, there was the earlier phase of AI attempted to model reasoning, and they were moderately successful, but, you know, reasoning by itself doesn't get you much. Deep learning has been much more successful in terms of, you know, what they can do. But now, it's an interesting question, whether it's approaching its limits. What do you think? I think absolutely. So I just talked to Gian Lacune, you mentioned, you know, so he thinks that the limits, we're not going to hit the limits with neural networks, that ultimately this kind of System 1 pattern matching will start to start to look like System 2 without significant transformation of the architecture. So I'm more with the majority of the people who think that yes, neural networks will hit a limit in their capability. He, on the one hand, I have heard him tell the Mises-Sabis essentially that, you know, what they have accomplished is not a big deal, that they have just touched, that basically, you know, they can't do unsupervised learning in an effective way. But you're telling me that he thinks that the current, within the current architecture, you can do causality and reasoning? So he's very much a pragmatist in a sense that's saying that we're very far away, that there's still, I think there's this idea that he says is we can only see one or two mountain peaks ahead, and there might be either a few more after or thousands more after. So that kind of idea. I heard that metaphor. Right, but nevertheless, it doesn't see a, the final answer not fundamentally looking like one that we currently have. So neural networks being a huge part of that. Yeah, I mean, that's very likely because, because pattern matching is so much of what's going on. And you can think of neural networks as processing information sequentially. Yeah, I mean, you know, there is, there is an important aspect to, for example, you get systems that translate and they do a very good job, but they really don't know what they're talking about. And for that, I'm really quite surprised. For that, you would need, you would need an AI that has sensation, an AI that is in touch with the world. Yes, self-awareness, and maybe even something that resembles consciousness kind of ideas. Certainly awareness of, you know, awareness of what's going on so that the words have meaning or can get, are in touch with some perception or some action. Yeah, so that's a big thing for Jan, and what he refers to as grounding to the physical space. So that's what, we're talking about the same thing. Yeah, so, but so how, how you ground? I mean the grounding, without grounding, then you get, you get a machine that doesn't know what it's talking about, because it is talking about the world, ultimately. The question, the open question is what it means to ground. I mean, we're very human-centric in our thinking, but what does it mean for a machine to understand what it means to be in this world? Does it need to have a body? Does it need to have a finiteness like we humans have? All of these elements, it's a very, it's an open question. You know, I'm not sure about having a body, but having a perceptual system, having a body would be very helpful too. I mean, if, if you think about human, mimicking human, but having a perception, that seems to be essential, so that you can build, you can accumulate knowledge about the world. So if, you can imagine a human completely paralyzed, and there is a lot that the human brain could learn, you know, with a paralyzed body. So if we got a machine that could do that, that would be a big deal. And then the flip side of that, something you see in children, and something in machine learning world is called active learning, maybe it is also, is being able to play with the world. How important for developing system one or system two, do you think it is to play with the world? To be able to interact with the world? Well, certainly a lot, a lot of what you learn is you learn to anticipate the outcomes of your actions. I mean, you can see that how babies learn it, you know, with their hands, how they, how they learn, you know, to connect, you know, the movements of their hands with something that clearly is something that happens in the brain, and the ability of the brain to learn new patterns. So you know, it's the kind of thing that you get with artificial limbs, that you connect it and then people learn to operate the artificial limb, you know, really impressively quickly, at least from what I hear. So we have a system that is ready to learn the world through action. At the risk of going into way too mysterious of land, what do you think it takes to build a system like that? Obviously, we're very far from understanding how the brain works, but how difficult is it to build this mind of ours? You know, I mean, I think that Jan LeCun's answer that we don't know how many mountains there are, I think that's a very good answer. I think that, you know, if you look at what Ray Kurzweil is saying, that strikes me as off the wall. But I think people are much more realistic than that, where actually Demis Hassabis is and Jan is, and so the people are actually doing the work fairly realistic, I think. To maybe phrase it another way, from a perspective not of building it, but from understanding it, how complicated are human beings in the following sense? You know, I work with autonomous vehicles and pedestrians, so we try to model pedestrians. How difficult is it to model a human being, their perception of the world, the two systems they operate under, sufficiently to be able to predict whether the pedestrian's going to cross the road or not? I'm fairly optimistic about that, actually, because what we're talking about is a huge amount of information that every vehicle has and that feeds into one system, into one gigantic system. And so anything that any vehicle learns becomes part of what the whole system knows. And with a system multiplier like that, there is a lot that you can do. So human beings are very complicated, and the system is going to make mistakes, but humans make mistakes. I think that they'll be able to, I think they are able to anticipate pedestrians, otherwise a lot would happen. They're able to get into a roundabout and into traffic, so they must know both to expect or to anticipate how people will react when they're sneaking in. And there's a lot of learning that's involved in that. Basically the pedestrians are treated as things that cannot be hit, and they're not treated as agents with whom you interact in a game-theoretic way. So I mean, it's a totally open problem, and every time somebody tries to solve it, it seems to be harder than we think. And nobody's really tried to seriously solve the problem of that dance, because I'm not sure if you've thought about the problem of pedestrians, but you're really putting your life in the hands of the driver. You know, there is a dance, there's part of the dance that would be quite complicated, but for example, when I cross the street and there is a vehicle approaching, I look the driver in the eye, and I think many people do that. And you know, that's a signal that I'm sending, and I would be sending that machine to an autonomous vehicle, and it had better understand it, because it means I'm crossing. So and there's another thing you do, that actually, so I'll tell you what you do, because I've watched hundreds of hours of video on this, is when you step in the street, you do that before you step in the street. And when you step in the street, you actually look away. Look away. Yeah. What is that, what that saying is, I mean, you're trusting that the car, who hasn't slown down yet, will slow down. Yeah. And you're telling him, I'm committed. I mean, this is like in a game of chicken. So I'm committed. And if I'm committed, I'm looking away. So there is, you just have to stop. So the question is whether a machine that observes that needs to understand mortality. Here I'm not sure that it's got to understand so much as it's got to anticipate. So and here, but you know, you're surprising me, because here I would think that maybe you can anticipate without understanding, because I think this is clearly what's happening in playing go or in playing chess. There's a lot of anticipation, and there is zero understanding. So I thought that you didn't need a model of the human and the model of the human mind to avoid hitting pedestrians. But you are suggesting that actually you do. And then it's a lot harder. So this is. Just to clarify, this is not entirely based on just the model of the human being, rather

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I fasted for 3 days | Lex Fridman

I'm doing a 72 hour fast, three days, only water, coffee, and electrolytes, sodium, potassium, magnesium. The video is brought to you by Cash App. Thanks a lot to them for being a long-time supporter of this channel. Also, Athletic Greens for being a long-time supporter of my diet. Electrolytes are coming from a few sources, including Element, one packet of which has one gram of sodium, 200 milligrams of potassium, and 60 milligrams of magnesium. I also have these in pill form, one gram of sodium, and 120 milligrams of magnesium. That's good, especially when I'm doing a lot of running. I'm currently 25 hours into the fast. I'm tracking it with the Xero app. They used to be a sponsor of the podcast. I'm not sure if they're a sponsor anymore. Anyway, I love using them. I don't care if they're a sponsor or not. That's actually true for all the sponsors. I'm still doing light exercise. I just did a slow pace run for about four miles. I also did about 100 pushups and about 50 or 60 pull-ups. I'm hoping to do the same tomorrow and the day after. Why am I doing the fast? That's an important question. I think first and foremost is to reflect on life. I know perhaps you don't need it, but I personally like to create forcing functions for myself to pause and reflect on all the things that I'm grateful for in this life. Really, I'm talking about just simple things, the fact that I'm alive at all, the fact that I have food, the fact that I have shelter, the fact that I have people who I love and that bring joy to my life, and the fact that I love basically everything about this life, all the things I get to do, I really enjoy. In fact, I enjoy basically anything I do. That I'm deeply grateful for. I'm not exactly sure why, but there's something about fasting that forces you to really appreciate how short this ride is. Like the fact that you need food to run this thing somehow is a reminder that this is a thing with an expiration date, a quickly approaching one. I'm just a hamster briefly stepping out of the hamster wheel to reflect on how awesome it is to be in this one particular cage we call Earth. I intermittent fast 16, 8, or 24 hours very often. It always makes me feel great. The second reason I'm doing the fast is for the health benefits. You can look into the science. There's a lot of writing out there about it, but I tend to prefer to be a scientist of N of 1, of myself. Every time I do the 16, 8 intermittent or the one meal a day 24 hour fast, I just feel great. The way my mind feels, the way my body feels. I want to try out what 72 hours feels like because I heard great things. Great things. People throw all kinds of medical terms around like autophagy. From a robotics perspective, I tend to think of it as a hard drive defrag, maybe like a software update. So for the hardware layer, it's in the cells, it's like a defrag. And the software layer, it's like a software update. Let's think of it that way. Finally, the third reason I'm doing the fast is to reset the body and mind. I've relaxed for the last couple of months or two. A little bit too much brisket, a little bit too much whiskey with some really kind, beautiful Texan people. But I have a lot of really difficult tasks coming up. They've been piling up and I need to get the stuff done. So it's time to get back to work, time to get focused again, time to make the best of my days, my hours and minutes. I should probably say that I currently feel great. My mind is focused. My body feels great after the run. The run felt great. Everything feels great. But this is charted territory. I am now going into uncharted territory, 48 hours towards the 72 hour mark. So let's see how that goes. But so far, it's a beautiful thing. Let's see how I feel tomorrow. Quick check-in at the end of day two, 49 hours and 57 minutes in. It says 69% of the way in, 69. I got a pretty good run in, actually about six miles and I'm now going to do about 100 push-ups and 50 pull-ups. I'm feeling pretty good. It's been a crazy busy day. I got a chance to do a four-hour podcast today. I did my usual mumbling and incohesive conversational skills, but not worse than usual. So it's at the same level and my mind is actually sharper than ever. It's really able to focus on the main task I have to do. And there's a liberating aspect to not having to think about food. Even though I eat rarely throughout the day and I eat the same thing, there's still a kind of anticipation towards what you're going to eat later in the day. As I mentioned in the podcast, actually, it feels like thinking about food is kind of like when you talk about the weather. It's like the easy thought to have. And when you don't have a chance to have the easy thoughts, you can now focus on the more difficult thoughts. Like I can anticipate the exciting thing I'm doing later tonight. I'm actually going to read The Hunger Artist again by Kafka, as was mentioned in the podcast. I used to love that book and I used to read it a lot before I even discovered even intermittent fasting. This was many, many years ago. I was captivated by the madness and the artistry of what the main character was doing. I recommend that. I think it's a short story, if I remember correctly, The Hunger Artist. Anyway, I feel great. I got a chance to kind of breathe in and appreciate the hell out of life, especially the conversation I had today was on the self-destruction of human civilization via the man-made engineering of viruses. So the fasting combined with pondering all the ways in which human civilization will destroy itself made me really appreciate the hell out of being alive. After the past couple of months of eating a whole lot of brisket and drinking a whole lot of whiskey with a lot of amazing people, I definitely have some reserves to basically fast for a very long time, so I'll be okay. I'm feeling really good. It's actually kind of exciting how this particular biological system is able to store fat for when you actually need to fast. Not this like first world, I'm going to choose to fast, but more like I have to fast because there's no food. So it's kind of amazing how biology works like that. But I definitely have a bunch of fat to lose so I need to harden the body, harden the mind, and this is a good reset for that. In the summer, I'm doing some difficult projects in my work and going to have some fun with some difficult projects in the grappling world and going to do some running with a man, Mr. David Goggins. So I can't be full of brisket and whiskey for that, or at least if I am, I need to make sure I'm doing some running and exercise. Anyway, that's way too much talking for the day. I'm going to go do some push-ups and pull-ups, take a shower, and get back to work. I'll see you tomorrow. I'm 69% in. I have 31% left and I'm looking forward to breaking the fast tomorrow, responsibly, probably with some bone broth and just a little bit of chicken breast. I'm not going to do the crazy break the fast with a giant steak, although I'm very tempted to. Even the thought of that is making me hungry. My stomach just actually woke up. It's like, wait, are we going to have some steak? No. Sometimes it feels like there's not enough hours in the day, but at the same time, when you're running and there's a little bit of hunger and you haven't eaten in a long time and you breathe in, it feels like there's so many seconds in the day. It's just, the day is so long and so full of amazing experiences. That duality is so real when you're fasting that I have so much shit to do. I don't know how I'm going to get it done. At the same time, every second is full of an eternity that I'm just grateful for. See you tomorrow. All right, here we are at the end of this fun little journey. Day three, 75 hours and 44 minutes in. I just weighed myself and I'm 170 on the dot. Actually, the first time I stepped on the scale, it said 169.9, and then I couldn't believe it. So I stepped on again and it was 170. That's why I took the picture. And it was never 169.9 again. I also weighed myself right after eating three days ago and I was just a little bit over 180. So it's about 10 pounds of water weight that I lost. Maybe I would estimate it about like one pound of actual fat. That's not why I did it. I did it to challenge myself. I did it to reset the mind. I did it to take pause and reflect on all the things I'm grateful for. Maybe if I can give a few takeaways. Usually when I do a 16 hour fast or a 24 hour fast, one of the biggest benefits is the laser focus that I'm able to attain and maintain. That rhymes. Clearly, I have not lost my sense of humor, but it hasn't improved at all either. So it's at that low bar of dad jokes, plus a little extra loopy, but it is what it is. I think for day two and day three, there was a bit of an up and down on the focus, but mostly I've been able to get even an extra level of focus that I really enjoyed. The little bit of a downside, there's a bit of a darkness to the way I saw the world. Like I was a little bit sadder, I would say, or maybe I was just acknowledging the suffering that is life. Maybe I was more honest. I'm not sure what kind of experience people usually have with sleep, but I had excellent sleep. I slept over eight hours on all the nights. I woke up refreshed. I was feeling great. Plus I was doing the running. So I ran today again, four miles. I did pushups and pull-ups, feeling great. I was taking the element potassium, magnesium, sodium, plus the salt pills. Every time I took that stuff, maybe it's placebo, but it made me feel really great. So a lot of water. I did drink tea on Sweden, obviously just green tea with mint. And actually two things helped with hunger. It was a hot tea or really cold water. I don't know how that works. I'm sure there's an explanation for it, but I did feel hungry in unpleasant ways, like a hunger ache earlier on in the process, but I kind of reframed that as an opportunity to sort of pause and think, and then the hunger kind of faded away. Because when you realize it's not that big of a deal, I have a lot of fat, I'm going to be okay, the body's naturally going to go to the fat stores. I'm talking way too much. I may have mentioned this before, but one of the big things I noticed is just the experience of being free of having to think about what I'm going to eat today. Even though I eat the same exact thing, still the experience was that I felt free to sort of focus and think about the things I have going on outside of food, like the problems I'm working on, the things I have on my schedule, even just like small stuff. As I'm saying it now, it doesn't really make sense, but I really did feel like I gained a lot of hours in the day by not having to think about food at all. One of the tougher experiences actually was about an hour ago when I went to the grocery store to get the chicken breast and the chicken bone broth, which is what I'm going to break the fast with. I don't know if it was difficult or just like meditative and beautiful of an experience of just walking through, especially the fresh produce part of the store, and just everything looked amazing. The reason I'm breaking the fast with just a little bit of chicken breast and a little bit of bone broth is because I hear bad stories when you just overeat, which is exactly what I want to do right now. I want to eat a giant steak, but I'm going to be smart about this. I'm going to have a little chicken broth, a little bit of chicken breast, and then just wait three or four hours and then eat again about a thousand calories, just make a steak, a thousand, fifteen hundred calories at night. That's it. That'd be it for the day. Then return back to normal diet, normal strict diet tomorrow. Then continuing the running, the pushups and pull-ups. Again, harden the body, harden the mind. I'm not sure if I fully conveyed this, but it was actually more challenging than I expected, but it's not so hard that I can't do it regularly. I like the Georges St-Pierre model of doing it like four times a year, especially after you fall off the wagon of dieting. I think I'll do that. Maybe I'll try like five, seven day fast at some point. Okay, way too much talking. Time to go eat. I've been looking forward to this all day. Maybe I'll get the first couple bites on camera. Let's see how good this chicken and bone broth tastes. All right, here we go. No reason to wait. We're at 76 hours and 24 minutes, and I have looked forward to this very plain, but very incredibly delicious looking chicken for quite a few hours now. So here we go. This is some good chicken. I taste the caramelized part, but most of all I taste the coconut oil actually, and the salt. The oil and the salt. I think that's what my body was craving the most. Given my keto diet, I think the fat is what I was craving. Even though I have plenty of fat, the body still, I want more. Again, it's the salt. This tastes delicious. I can't. It would be hard to just eat this, but that's all I'm doing for the next, let's say, four hours about. It's just the bone broth and the chicken. This is a really memorable moment. Oh man. Life is made up of moments like this. It doesn't take much. This is the best tasting chicken breast I've ever had in my life. Just chicken breast, some spices, salt, and 76 hours of fasting. This is incredible. Damn. Damn, it's good to be alive.

https://youtu.be/d8nQ2dZBR48

HKBhP9JISF0

UCSHZKyawb77ixDdsGog4iWA

Sterling Anderson, Co-Founder, Aurora - MIT Self-Driving Cars

Today we have Sterling Anderson. He's the co-founder of Aurora, an exciting new self-driving car company. Previously, he was the head of the Tesla Autopilot team that brought both the first and second generation autopilot to life. Before that, he did his PhD at MIT working on shared human machine control of ground vehicles, the very thing I've been harping on over and over in this class. And now he's back at MIT to talk with us. Please give him a warm welcome. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. It's good to be here. I was telling Lex just before, I think it's been a little while since I've been back to the Institute, and it's great to be here. I want to apologize in advance. I've just landed this afternoon from Korea via Germany where I've been spending the last week. And so I may speak a little slower than normal. Please bear with me. If I become incoherent or slur my speech, somebody flag it to me and we'll try to make corrections. So tonight I thought I'd chat with you a little bit about my journey over the last decade. It's been just over 10 years since I was at MIT. A lot has changed. A lot has changed for the better in the self-driving community. And I've been privileged to be a part of many of those changes. And so I wanted to talk with you a little bit about some of the things that I've learned, some of the things that I've experienced. And then maybe end by talking about sort of where we go from here and what the next steps are, both for the industry at large, but also for the company that we're building that as Lex mentioned is called Aurora. To start out with, there are a few sort of key phases or transitions in my journey over the last 10 years. As Lex mentioned, when I started at MIT, I worked with Carl Ianniema, Emilio Fazzoli, John Leonard, a few others on some of these sort of shared, adaptive automation approaches. I'll talk a little bit about those. From there, I spent some time at Tesla where I first led the Model X program as we both finished the development and ultimately launched it. I took over the autopilot program where we introduced a number of new, both active safety, but also sort of, you know, enhanced convenience features from auto steer to adaptive cruise control that we're able to refine in a few unique ways. And we'll talk a little bit about that. And then from there in December of last year, of 2016, I guess now, we started a new company called Aurora. And I'll tell you a little bit about that. So to start out with, when I came to MIT, it was 2007. The DARPA urban challenges were well underway at that stage. And one of the things that we wanted to do is find a way to address some of the safety issues in human driving earlier than potentially full self-driving could do. And so we developed what became known as the Intelligent Co-Pilot. What you see here is a simulation of that operating. I'll tell you a little bit more about that in just a second. But to explain a little bit about the methodology, the innovation, the key approach that we took that was slightly different from what traditional planning control theory we're doing was instead of designing in path space for the robot, we instead found a way to identify, plan, optimize, and design a controller subject to a set of constraints rather than paths. And so what we were doing is looking for homotopies through an environment. So imagine for a moment an environment that's pockmarked by objects, by their vehicles, by pedestrians, et cetera. If you were to create the Voronoi diagram through that environment, you would have a set of each unique set of paths or homotopies, continuously deformable paths that will take you from one location to another through it. If you then turn that into its dual, which is the Delaunay triangulation of said environment, presuming that you've got convex obstacles, you can then tile those together rather trivially to create a set of homotopies and transitions across which those paths can stake out sort of a given set of options for the human. It turns out humans tend to, this tends to be a more intuitive way of imposing certain constraints on human operation rather than enforcing that the ego vehicle stick to some arbitrary position within some distance of a safe path. You instead look to enforce only that the state of the vehicle remain within a constraint-bounded n-dimensional tube in state space. Those constraints being spatial, you imagine for a moment edges of the roadway or circumventing various objects in the roadway. Imagine them also being dynamic, right? So limits of tire friction imposed limits on side-slip angles. And so using that, what we did is found a way to create those homotopies, forward simulate the trajectory of the vehicle given its current state and some optimal set of control inputs that would optimize its stability through that. We use model predictive control in that work. And then taking that forward simulated trajectory, computing some metric of threat. For instance, if the objective function for that minimize the or maximize stability or minimize some of these parameters like wheel side slip, then wheel side slip is a fairly good indication of how threatening that optimal maneuver is becoming. And so what we did is then use that in a modulation of control between the human and the car, such that should the car ever find itself in a state where that forward simulated optimal trajectory is very near the limits of what the vehicle and it can actually handle, we will have transitioned control fully to the vehicle, to the automated system so that it can avoid an accident. And then it transitions back in some manner. And we played with a number of different methods of transitioning this control to ensure that we didn't throw off the human mental model, which was one of the key concerns. We also wanted to make sure that we were able to arrest accidents before they happen. What you see here is a simulation that was fairly faithful to the behavior we saw in test drivers up in Dearborn, Michigan. Ford provided us with a Jaguar S-type to test this on. And what we did, so what you see here is there's a blue vehicle and a gray vehicle. Both, in both cases, we have a poorly tuned driver model, in this case, a pure pursuit controller with a fairly short look ahead, shorter than would be appropriate given this scenario and these dynamics. The gray vehicle is without the intelligent copilot in the loop. You'll notice that, obviously, the driver becomes unstable, loses control, and leaves the safe roadway. The copilot, remember, is interested not in following any given path. It doesn't care where the vehicle lands on this roadway, provided it remains inside the road. In the blue vehicle's case, it's the exact same human driver model, now with the copilot in the loop. You'll notice that as this scenario continues, what you see here on the left is in this green bar is the portion of available control authority that's being taken by the automated system. You'll notice that it never exceeds half of the available control, which is to say that the steering inputs received by the vehicle end up being a blend of what the human and what the automation are providing. And what results is a path for the blue vehicle that actually better tracks the human's intended trajectory than even the copilot understood. Again, the copilot is keeping the vehicle stable, is keeping it on the road. The human is hewing to the center line of that roadway. So there were some very interesting things that came out of this. We did a lot of work in understanding what kind of feedback was most natural to provide to a human. Our biggest concern was if you throw off a human's mental model by causing the vehicle's behaviors to deviate from what they expect it to do in response to various control inputs, that that could be a problem. So we tried various things from adjusting, for instance, one of the key questions that we had early on was, if we couple the computer control and the human control via planetary gear and allow the human to feel actually a backwards torque to what the vehicle is doing, so the car starts to turn right, human will feel the wheel turn left. They'll see it start to turn left. Is that more confusing or less confusing to a human? And it turns out it depends on how experienced a human is. Some drivers will modulate their inputs based on the torque feedback that they feel through the wheel. And for instance, a very experienced driver expects to feel the wheel pull left when they're turning right. However, less experienced drivers, in response to seeing the wheel turning opposite to what the car is supposed to be doing, that's a rather confusing experience. So there were a lot of really interesting human interface challenges that we were dealing with here. We ended up working through a lot of that, developing a number of micro applications for it. One of those, at the time, Gil Pratt was leading a DARPA program focused on what they called at the time maximum mobility manipulation. We decided to see what this system could do in application to unmanned ground vehicles. So in this case, what you see is a human driver sitting at a remote console, as one would when operating an unmanned vehicle, for instance, in the military. What you see on the top left is the top-down view of what the vehicle sees. I should have played this in repeat mode. With bounding boxes bounding various cones. And what we did is we set up about 20 drivers, 20 test subjects, looking at this control screen and operating the vehicle through this track. And we set this up as a race with prizes for the winners, as one would expect, and penalized them for every barrel they hit. If they knocked over the barrel, I think they got a five-second penalty. If they brushed a barrel, they got a one-second penalty. And they were to cross the field as fast as possible. And they had no line of sight connection to the vehicle. And we played with some things on their interface. We caused it to drop out occasionally. We delayed it, as one would realistically expect in the field. And then we either engaged or didn't engage the co-pilot to try to understand what effect that had on their performance and their experience. And what we found was not surprisingly, the incidence of collisions declined. It declined by about 72% when the co-pilot was engaged versus when it was not. We also found that even with that 72% decline in collisions, the speed increased by, I'm blanking on the amount, but it was 20% to 30%-ish. Finally, and perhaps most interesting to me, after every run, I would ask the driver, and again, these were blind tests. They didn't know if the co-pilot was active or not. And I would ask them, how much control did you feel like you had over the vehicle? And I found that there was a statistically significant increase of about 12% when the co-pilot was engaged. And that is to say, drivers reported feeling more control of the vehicle 12% more of the time when the co-pilot was engaged than when it wasn't. And then I looked at the statistics, it turns out they actually, the average level of control that the co-pilot was taking was 43%. So they were reporting that they felt more in control when in fact they were 43% less in control, which was interesting and I think bears a little bit on sort of the human psyche in terms of, they were reporting the vehicle was doing what I wanted it to do, maybe not what I told it to do, which was kind of fun observation. And fun to, I think the most enjoyable part of this was getting together with the whole group at the end of the study and presenting some of this and seeing some of the reactions. So from there, we looked at a few other areas. My, Carl Yanim and I looked at a few different opportunities to commercialize this. Again, this was years ago and the industry was in a very different place than it is today. We started a company first called Gimlet, then another called Ride. This is the logo, it may look familiar to you. We turned that into, at the time it intended to roll this out across various automakers in their operations. At the time, very few saw self-driving as a technology that was really gonna impact their business going forward. They were, in fact, even ride sharing at the time was a fairly new concept that was, I think, to a large degree viewed as unproven. So, as I mentioned, December of last year, I co-founded Aurora with a couple of folks who have been making significant progress in this space for many years. Chris Hermsen, who formerly led Google's self-driving car group. Drew Bagnell is a professor at Carnegie Mellon University, exceptional machine learning and applied machine learning, was one of the founding members of Uber's self-driving car team and led autonomy and perception there. We felt like we had a unique opportunity at the convergence of a few things. One, the automotive world has really come into the full-on realization that self-driving, and particularly self-driving and ride sharing, and vehicle electrification are three vectors that will change the industry. That was something that didn't exist 10 years ago. Two, significant advances have been made in some of these machine learning techniques, in particular deep learning and other neural network approaches, in the computers that run them, and the availability of low-power GPU and TPU options to really do that well, in sensing technologies, in high-resolution radar, and a lot of the LIDAR development. So it's really a unique time in the self-driving world. A lot of these things are really coming together now. And we felt like by bringing together an experienced team, we had an interesting opportunity to build, from a clean sheet, a new platform, a new self-driving architecture, that leveraged the latest advances in applied machine learning, together with our experience of where some of the pitfalls tend to be down the road as you develop these systems, because you don't tend to see them early on. They tend to express themselves as you get into the long tail of corner cases that you end up needing to resolve. So we've built that team. We have offices in Palo Alto, California, and Pittsburgh, Pennsylvania. We've got fleets of vehicles operating in both Palo Alto and Pennsylvania. A couple of weeks ago, we announced that Volkswagen Group, one of the largest automakers in the world, Hyundai Motor Company, also one of the largest automakers in the world, have both partnered with Aurora. We will be developing, and are developing with them, a set of platforms, and ultimately will scale that, our technology, on their vehicles across the world. And one of the important elements of building Lex, I asked Lex before coming out here what this group would be most interested in hearing. One of the things that he mentioned was, what does it take to build a self-driving, build a new company in a space like this? One of the things that we found very important was a business model that was non-threatening to others. We recognize that our strengths and our experience over the last, in my case, a decade, in Chris's case, almost two, really lies in the development of the self-driving systems. Not in building vehicles, though I have had some experience there, but in developing the self-driving. And so our feeling was, if our mission is to get a technology to market as quickly, as broadly, and as safely as possible, that mission is best served by playing our position and working well with others who can play theirs, which is why you see the model that we've adopted, and is now, you'll start to see some of the fruits of that through these partnerships with some of these automakers. So at the end of the day, our aspiration and our hope is that this technology that is so important in the world in increasing safety, in improving access to transportation, in improving efficiency, in the utilization of our roadways and our cities. This is maybe the first talk I've ever given where I didn't start by rattling off statistics about safety and all these other things. If you haven't heard them yet, you should look them up. They're stark, right? The fact that most vehicles in the United States today have an average, on average, three parking spaces allocated to them. The amount of land that's taken up across the world in housing vehicles that are used less than 5% of the time. The number of people, I think in the United States, the estimate has been somewhere between six and 15 million people don't have access to the transportation they need, because they're elderly or disabled or one of many other factors. And so this technology is potentially one of the most impactful for our society in the coming years. It's a tremendously exciting technological challenge. And at the confluence of those two things, I think is a really unique opportunity for engineers and others who are not engineers who really want to get involved to play a role in changing our world going forward. So with that, maybe I'll stop with this and we can go to questions. Let's give Daryl in the warm hand. Hi, I'm Wayne, thanks for coming. I have a question. A lot of self-driving car companies are making extensive use of LiDAR, but you don't see a lot of that with Tesla. I wanted to know if you had any thoughts about that. Yeah, I don't want to talk about Tesla too much in terms of our specific, anything that wasn't public information I'm not gonna get into. I will say that for Aurora, we believe that the right approach is getting to market quickly and you get to market and doing so safely. And you get to market most quickly and safely if you leverage multiple modalities, including LiDAR. These are all just to clarify what's running in the background. These are all just Aurora videos of our cars driving on various test routes. Hi, I'm Luke from the Sloan School. A lot of customers have visceral-type connections to their automobile. I was wondering how you see that market, the car enthusiast market, being affected by AVs and then vice versa, how the AVs will be designed around those type of customers. Yeah, that's a good question. Thanks for asking, Luke. I am one of those enthusiasts. I very much appreciate being able to drive a car in certain settings. I very much don't appreciate driving in others. I remember distinctly several evenings, almost literally pounding my steering wheel, sitting in Boston traffic, on my way to somewhere. I do the same in San Francisco. I think the opportunity really is to turn sort of personal vehicle ownership and driving into more of a sport and something you do for leisure. I see it, a gentleman some time ago asked me to talk, hey, don't you think this is a problem for the country, I think you meant the world, if people don't learn how to drive? That's just something a human should know how to do. My perspective is it's as much of a problem as people not intrinsically knowing how to ride a horse today. If you wanna know how to ride a horse, go ride a horse. If you wanna race a car, go to a racetrack or go out to a mountain road that's been allocated for it. Ultimately, I think there is an important place for that because I certainly agree with you. I'm very much a vehicle enthusiast myself, but I think there is so much opportunity here in alleviating some of these other problems, particularly in places where it's not fun to drive, that I think there's a place for both. Yeah. All right. Can you hear or do I need to get? Yeah. Congratulations on the partnership that was announced recently, I think. So I have a two-part question. The first one is, so we heard last week from, I think there was a gentleman from Waymo, talking about how long they've been working on this autonomous car technology. And you seem to have ramped up extremely fast. So is there a licensing model that you've taken? I mean, how are you able to commercialize the technology in one year? So just to be clear, we're not actually commercializing. Just to distinguish, we are partnering and developing vehicles and we'll ultimately be running pilots, as we announced a week or two ago with the Moya shuttles. We are, however, I will distinguish that from broad commercialization of the technology. And I don't want to get too much into the nuances of that business model. I will say that it is one that's done in very close partnership with our automotive partners. Because at the end of the day, they understand their cars, they understand their customers, they have distribution networks. They are, our automotive partners are fairly well positioned provided they have the right support in developing the self-driving technology, they're fairly well positioned to roll it out at scale. So the second part of my question is, again, looking at this pace of adoption and the maturity of technology, do you see an open source model for autonomous cars as they become more and more? Unclear. I'm not convinced that an open source model is what gets to market most quickly. In the long run, it's not clear to me what will happen. I think there will be a handful of successful self-driving stacks that will make it. Nowhere near the number of self-driving companies today, but a handful, I think. Two questions, one is, in variably new product development, there's typically two types of bottlenecks. There's a technological bottleneck and an economic bottleneck, right? So technological bottleneck might be, hey, the sensors aren't good enough or the machine learning algorithms aren't good enough and so on, I'd be interested to hear, and it'll shift obviously over time. So I'd be interested to know what you would say is the current thing that if, hey, if this part of the architecture was 10 times better, we would, and then on the economic side, I'd be interested to know, gee, if sensors were 100 times cheaper, then so I'd be interested to hear your perspective on both. That's a great question. Let me start with the economic side of it and just to get that out of the way, because it's a little bit quicker answer. The economics of operating a self-driving vehicle on a shared network today would close, that business case closes even with high costs of sensors. That is not what's stopping us. And that's part of why the gentleman earlier who asked, should you use LiDAR or not? If your target is to initially deploy these in fleets, you would be wise to start at the top end of the market, develop and deploy a system that's as capable as possible, as quickly as possible, and then cost it down over time. And you can do that as computer vision, precision recall increase. Today, they're not good enough. And so economically, depending on your model of going to market, and we believe that the right model is through mobility services, you can cost down, you'll cost down the center. Inevitably, there's no unobtainium in LiDAR units today. There's no reason fundamentally that a should cost of a LiDAR unit will lead you to a $70,000 price point. However, if you build anything in low enough volumes, it's gonna be expensive. Many of these things will work their way into the standard automotive process. They'll work their way into tier one suppliers, and when they do, the automotive community has shown themselves to be exceptional at driving those costs down. And so I expect them to come way down. To your other question, technological bottlenecks and challenges. One of the key challenges of self-driving is and remains that of forecasting the intent and future behaviors of other actors, both in response to one another, but also in response to your own decisions in motion. That's a perception problem, but it's something more than a perception problem. It's also a prediction, and there are a number of different things that have to come together to solve this. We're excited about some of the tools that we're using in interleaving various modern machine learning techniques throughout the system to do things like project our own behaviors that were learned for the ego vehicle on others, and assume that they'll behave as we would had we been in that situation. Like an expert system kind of approach, right? Yeah, yeah, you assume nominal behavior and you guard against off nominal, right? But it's very much, it's not a solved problem, I wouldn't say. It's very much as you get into that really long tail of development, when you're no longer putting out demonstration videos, but you're instead just putting your head down and eking out those final nines, that's the kind of problem you tend to deal with. Yeah, thank you. Hi, so this question isn't necessarily about the development of self-driving cars, but more of like an ethics question. When you're putting human lives into like the hands of software, isn't there always the possibility for like outside agents with malicious intent to use it for their own gain? And how do you guys, if you do have a plan, how do you intend to protect against attacks like that? So security is a very real aspect of this that has to be solved. It's a constant game of cat and mouse. And so I think it just requires a very good team and a concerted effort over time. I don't think you solve it once, and I certainly wouldn't pretend to have a plan that solves it and is done with it. We try to leverage best practices where we can in the fundamental architecture of the system to make it less exposed, in particular key parts of the system, less exposed to nefarious actions of others. But at the end of the day, it's just a constant, just a constant development effort. Thank you for being here. So I had a question about what opportunities self-driving cars open up. Since driving has kind of been designed around like a human being at the center since the beginning, if you put a computer at the center, what society-wide differences, and maybe even within individual car differences that open up, like could cars go 150 miles an hour on the highway and get places much faster? Would cars look differently when a human doesn't need to be paying attention and stuff like that? Yeah, I think the answer is yes. And that's something that's very exciting. So one of the, I think one of the unique opportunities that automakers in particular have when self-driving technology gets incorporated into their vehicles is they can do things like play, like differentiate the user experience. They can provide services, augmented reality services or location services, many other sort of, it opens a new window into an entirely new market that automakers haven't historically played in. And it allows them to change the very vehicles themselves. As you mentioned, the interior can change as we validate some of these self-driving systems and confirm that they do in fact reduce the collision, the rate of collisions as we hope they will. You can start to pull out a lot of the extra mass and other things that we've added to vehicles to make them more passively safe, right? Roll cages, crumple zones, airbags, a lot of these things, presumably in a world where we don't crash, there is much less need for passive safety systems. So yes. Hi, I have a question about the go or no-go test that you conduct for certain features, like you mentioned the throttle control where you slow down the throttle, assuming that the driver has pressed the wrong pedal. When you test, when do you decide to launch that feature? How do you know it's definitely going to work in all scenarios because your data set might not be tested? It's a statistical evaluation in every case, right? You're right. This is part of the art of self-driving vehicle development is you will never have comprehensively captured every case, every scenario. That is, some of you may want to correct me on this. I think that's an unbounded set. It may in fact be bounded at some point, but I think it's un. And so you'll never actually have characterized everything. What you will have done, hopefully, if you do it right, is you will have established with a reasonable degree of confidence that you can perform at a level of safety that's better than the average human driver. And once you've reached that threshold and you're confident that you've reached that threshold, I think the opportunity to launch is real and you should seriously consider it. So thank you for your talk today first. And my question is, self-driving seems to be able to ultimately take over the world to some extent. But just like other technologies today that open up new opportunities, but also bring in adverse effects. So how do you respond to fear and negative effects that may come in one day? And specifically, what do you see as the positive and negative implications of future day self-driving? Positive and negative implications. So the positive ones I kind of listed and go find your favorite press article and they'll list them as well. The negative ones in the near term, I do worry a little bit about the displacement of jobs. Not a little bit, this will happen. It happens with every technology like this. I think it's incumbent on us to find a good way of transitioning those who are employed in some of the transportation sectors that will be affected into better work. There are a few opportunities that are interesting in that regard, but I think it's an important thing to start discussing now, because it's gonna take a few years. And by the time we've got these self-driving systems on the roads really starting to place that labor, I'd really like to have a new home for it. Hi, I'm Kasia from the Sloan School. My question was more about your business model, again, with partnering with both VW and Hyundai, and your just perspective on how you were able to effectively do that. Did not one of them wanna go sort of exclusive with you? And what was your sort of thought process about that? Yeah, so our mission, as I mentioned, is to get the technology to market broadly, and quickly and safely. We are, have been and remain convinced that the right way to do that is by providing it to as much of the industry as possible. To every automaker who shares our vision and our approach, we were pleased to see that both Volkswagen Group, and I'm assuming you all know the scope of Volkswagen, right? This is a massive automaker. Hyundai Motor, also very large, across Hyundai, Kia, and Genesis. They both shared our vision of how we should do this, which was important to us. They both shared a keen interest in making a difference at scale through their platforms. Volkswagen has, I think, a very admirable set of initiatives around vehicle electrification, a few other things. Hyundai is doing similar things. And so, for us, it was important that we enable everyone, and that was kind of what Aurora started to do. Hi, I had a question. Now, that I see a lot of companies are coming up with self-driving cars, right? So, most of the cars are pretty much, all the technology is bound only to the car. So, would we see something like an open network where car communicate with each other, regardless of which company they come from? And would this, in any way, increase the safety or the performance of vehicles and stuff like that? Yeah, I think you're getting it vehicle-to-vehicle, vehicle-to-infrastructure type communication. There are efforts ongoing in that, and it's certainly, it's only positive, right? Having that information available to you can only make things better. The challenge has historically been with vehicle-to-vehicle, and in particular, vehicle-to-infrastructure, or vice versa, that it doesn't scale well, one. And two, it's been slow. It's been much slower in coming than our development. And so, when we develop these systems, we develop them without the expectation that those communication protocol are available to us. We'll certainly protect for them, and it will certainly be a benefit once they're here. But until then, many of the hard problems that I would have welcomed 10 years ago, to have a beacon on every traffic light that just told me it's state, rather than having to perceive it, I would have certainly used those 10 years ago. Now, they're less significant, because we've kind of worked our way through a lot of the problems they would have solved. Thank you for your talk. My question is, what's your opinion about the cooperation of self-driving vehicles? So maybe, I think, if you can control a group of self-driving vehicles at the same time, you can achieve a lot of benefits to the traffic. Yes, that is where a lot of the benefits come from in infrastructure utilization, right, is in ride-sharing with autonomous vehicles. And specifically, the better we understand demand patterns, people movement, goods movement, the better we can sort of optimally allocate these vehicles at locations where they're needed. So yes, certainly that coordination, this is where, as I mentioned, these three vectors of vehicle electrification, ride-sharing and autonomy, or mobility as a service and autonomy, really come together with a unique value proposition. Okay, thank you. Yeah. Thank you so much for a great talk and being here. Thank you. Thank you. Thank you.

https://youtu.be/HKBhP9JISF0

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Lee Smolin: Quantum Gravity and Einstein's Unfinished Revolution | Lex Fridman Podcast #79

The following is a conversation with Lee Smolin. He's a theoretical physicist, co-inventor of loop quantum gravity, and a contributor of many interesting ideas to cosmology, quantum field theory, the foundations of quantum mechanics, theoretical biology, and the philosophy of science. He's the author of several books, including one that critiques the state of physics and its string theory called The Trouble with Physics, and his latest book, Einstein's Unfinished Revolution, The Search for What Lies Beyond the Quantum. He's an outspoken personality in the public debates on the nature of our universe, among the top minds in the theoretical physics community. This community has its respected academics, its naked emperors, its outcasts and its revolutionaries, its madmen and its dreamers. This is why it's an exciting world to explore through long-form conversation. I recommend you listen back to the episodes of Leonard Susskind, Sean Carroll, Michio Kaku, Max Stegmark, Eric Weinstein, and Jim Gates. You might be asking, why talk to physicists if you're interested in AI? To me, creating artificial intelligence systems requires more than Python and deep learning. It requires that we return to exploring the fundamental nature of the universe and the human mind. Theoretical physicists venture out into the dark, mysterious, psychologically challenging place to force principles more than almost any other discipline. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, get five stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter, at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do one or two minutes of ads now, and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency, in the context of the history of money, is fascinating. I recommend Ascent of Money as a great book on this history. Debits and credits on ledgers started around 30,000 years ago. The US dollar, of course, created over 200 years ago. And Bitcoin, the first decentralized cryptocurrency, was released just over 10 years ago. So given that history, cryptocurrency is still very much in its early days of development, but it still is aiming to, and just might, redefine the nature of money. If you get Cash App from the App Store or Google Play, and use the code LEXPODCAST, you'll get $10, and Cash App will also donate $10 to FIRST, one of my favorite organizations that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Lee Smolin. What is real? Let's start with an easy question. Put another way, how do we know what is real and what is merely a creation of our human perception and imagination? We don't know. We don't know. This is science. I presume we're talking about science. And we believe, or I believe, that there is a world that is independent of my existence and my experience about it and my knowledge of it. And this I call the real world. So you said science, but even bigger than science. Sure, sure. I need not have said this is science. I just was warming up. Warming up. Okay, now that we're warmed up, let's take a brief step outside of science. Is it completely a crazy idea to you that everything that exists is merely a creation of our mind? So there's a few, not many, this is outside of science now, people who believe perception is fundamentally what's in our human perception, the visual cortex and so on, the cognitive constructs that's being formed there, is the reality, and that anything outside is something that we can never really grasp. Is that a crazy idea to you? There's a version of that that is not crazy at all. What we experience is constructed by our brains and by our brains in an active mode. So we don't see the raw world. We see a very processed world. We feel something that's very processed through our brains, and our brains are incredible. But I still believe that behind that experience, that mirror or veil or whatever you wanna call it, there is a real world, and I'm curious about it. Can we truly, how do we get a sense of that real world? Is it through the tools of physics from theory to the experiments? Or can we actually grasp it in some intuitive way that's more connected to our ape ancestors? Or is it still fundamentally the tools of math and physics that really allow us to grasp it? Well, let's talk about what tools they are, what you say are the tools of math and physics. I mean, I think we're in the same position as our ancestors in the caves or before the caves or whatever. We find ourselves in this world, and we're curious. We also, it's important to be able to explain what happens when there are fires, when there are not fires, what animals and plants are good to eat, and all that stuff. But we're also just curious. We look up in the sky, and we see the sun and the moon and the stars, and we see some of those move, and we're very curious about that. And I think we're just naturally curious. So we make, this is my version of how we work. We make up stories and explanations. And there are two things which I think are just true of being human. We make judgments fast because we have to. We're to survive, is that a tiger or is that not a tiger? And we go. Act. We have to act fast on incomplete information. So we judge quickly, and we're often wrong, or at least sometimes wrong, which is all I need for this. We're often wrong. So we fool ourselves, and we fool other people readily. And so there's lots of stories that get told, and some of them result in a concrete benefit, and some of them don't. And. So you said we're often wrong, but what does it mean to be right? Right, that's an excellent question. To be right, well, since I believe that there is a real world, I believe that to be, you can challenge me on this if you're not a realist. A realist is somebody who believes in this real objective world, which is independent of our perception. If I'm a realist, I think that to be right is to come closer. I think, first of all, there's a relative scale. There's not right and wrong. There's right or more right and less right. And you're more right if you come closer to an exact, true description of that real world. Now, can we know that for sure? No. And the scientific method is ultimately what allows us to get a sense of how close we're getting to that real world? No on two counts. First of all, I don't believe there's a scientific method. I was very influenced when I was in graduate school by the writings of Paul Feyerabend, who was an important philosopher of science, who argued that there isn't a scientific method. There is or there isn't? There is not. There's not. Can you elaborate? Sorry if you were going to, but can you elaborate on the what does it mean for there not to be a scientific method, this notion that I think a lot of people believe in in this day and age? Sure. Paul Feyerabend, he was a student of Popper, who taught Karl Popper. And Feyerabend argued, both by logic and by historical example, that you name anything that should be part of the practice of science, say you should always make sure that your theories agree with all the data that's already been taken. And he'll prove to you that there have to be times when science contradicts, when some scientist contradicts that advice for science to progress overall. So it's not a simple matter. I think that, I think of science as a community. Of people. Of people, and as a community of people bound by certain ethical precepts, percepts, whatever that is. So in that community, a set of ideas they operate under, meaning ethically, of kind of the rules of the game they operate under. Don't lie, report all your results, whether they agree or don't agree with your hypothesis. Check, the training of a scientist mostly consists of methods of checking, because again, we make lots of mistakes, we're very error prone. But there are tools, both on the mathematics side and the experimental side, to check and double check and triple check. And a scientist goes through a training, and I think this is part of it. You can't just walk off the street and say, yo, I'm a scientist. You have to go through the training, and the training, the test that lets you be done with the training is, can you form a convincing case for something that your colleagues will not be able to shout down, because they'll ask, did you check this, and did you check that, and did you check this, and what about a seeming contradiction with this? And you've gotta have answers to all those things, or you don't get taken seriously. And when you get to the point where you can produce that kind of defense and argument, then they give you a PhD. And you're kind of licensed. You're still gonna be questioned, and you still may propose or publish mistakes, but the community is gonna have to waste less time fixing your mistakes. Yes, but if you can maybe linger on it a little longer, what's the gap between the thing that that community does and the ideal of the scientific method? The scientific method is you should be able to repeat an experiment. There's a lot of elements to what construes the scientific method, but the final result, the hope of it is that you should be able to say with some confidence that a particular thing is close to the truth. Right, but there's not a simple relationship between experiment and hypothesis or theory. For example, Galileo did this experiment of dropping a ball from the top of a tower, and it falls right at the base of the tower. And Aristotelian would say, wow, of course it falls right to the base of the tower. That shows that the Earth isn't moving while the ball is falling. And Galileo says no weight is a principle of inertia, and it has an inertia in a direction with the Earth isn't moving, and the tower and the ball and the Earth all move together. When the principle of inertia tells you it hits the bottom, it does look, therefore, my principle of inertia is right. And Aristotelian says, no, Aristotle's science is right. The Earth is stationary. And so you've gotta get an interconnected bunch of cases and work hard to line up, it took centuries to make the transition from Aristotelian physics to the new physics. It wasn't done till Newton in 1680-something, 1687. So what do you think is the nature of the process that seems to lead to progress, if we at least look at the long arc of science, of all the community of scientists? They seem to do a better job at coming up with ideas that engineers can then take on and build rockets with, or build computers with, or build cool stuff with. I don't know, a better job than what? Than this previous century. So century by century, we'll talk about string theory and so on, and kind of possible, what you might think of as dead ends and so on. Which is not the way I think of string theory. We'll straighten it out. We'll get on string straight. But there is, nevertheless, in science, very often, at least temporary dead ends. But if you look through centuries, the century before Newton and the century after Newton, it seems like a lot of ideas came closer to the truth that then could be usable by our civilization to build the iPhone, right? To build cool things that improve our quality of life. That's the progress I'm kind of referring to. Let me, can I say that more precisely? Yes, well. It's a low bar. I think it's important to get the time places right. There was a scientific revolution that partly succeeded between about 1900 or late 1890s and into the 1930s, 1940s, and so on. And maybe some, if you stretched it, into the 1970s. And the technology, this was the discovery of relativity, and that included a lot of developments of electromagnetism. The confirmation, which wasn't really well confirmed into the 20th century, that matter was made of atoms. And the whole picture of nuclei with electrons going around, this is early 20th century. And then quantum mechanics was from 1905, took a long time to develop, till the late 1920s. And then it was basically in final form. And the basis of this partial revolution, we can come back to why it's only a partial revolution, is the basis of the technologies you mentioned. All of, I mean, electrical technology was being developed slowly with this. And in fact, there's a close relation between development of electricity and the electrification of cities in the United States and Europe and so forth, and the development of the science. The fundamental physics, since the early 1970s, doesn't have a story like that so far. There's not a series of triumphs and progresses, and there's not any practical application. So just to linger briefly on the early 20th century and the revolutions in science that happened there, what was the method by which the scientific community kept each other in check about when you get something right, when you get something wrong? Is experimental validation ultimately the final test? It's absolutely necessary. And the key things were all validated. The key predictions of quantum mechanics and of the theory of electricity and magnetism. So before we talk about Einstein, your new book, before string theory, quantum mechanics, let's take a step back at a higher level question. What is, that you mentioned, what is realism? What is anti-realism? And maybe why do you find realism, as you mentioned, so compelling? Realism is the belief in an external world independent of our existence, our perception, our belief, our knowledge. A realist, as a physicist, is somebody who believes that there should be possible some completely objective description of each and every process at the fundamental level, which describes and explains exactly what happens and why it happens. That kind of implies that that system, in a realist view, is deterministic. Meaning there's no fuzzy magic going on that you can never get to the bottom of. You can get to the bottom of anything and perfectly describe it. Some people would say that I'm not that interested in determinism, but I could live with the fundamental world, which had some chance in it. So do you, you said you could live with it, but do you think God plays dice in our universe? I think it's probably much worse than that. In which direction? I think that theories can change and theories can change without warning. I think the future is open. You mean the fundamental laws of physics can change? Yeah. Okay, we'll get there. I thought we would be able to find some solid ground, but apparently the entirety of it, temporarily so. Okay, so realism is the idea that while the ground is solid, you can describe it. What's the role of the human being, our beautiful, complex human mind in realism? Do we have a, are we just another set of molecules connected together in a clever way? Or the observer, does the observer, our human mind, consciousness, have a role in this realism view of the physical universe? There's two ways, there's two questions you could be asking. Does our conscious mind, do our perceptions play a role in making things become, in making things real or things becoming? That's question one. Question two is, does this, we can call it a naturalist view of the world, that is based on realism, allow a place to understand the existence of and the nature of perceptions and consciousness in mind? And that's question two. Question two I do think a lot about, and my answer, which is not an answer, is I hope so, but it certainly doesn't yet. So what kind of? Question one I don't think so. But of course the answer to question one depends on question two. Right. So I'm not up to question one yet. So question two is the thing that you can kind of struggle with at this time. What about the anti-realists? So what flavor, what are the different camps of anti-realists that you've talked about? I think it would be nice if you can articulate for the people for whom there is not a very concrete real world, or there's divisions, or there's a, it's messier than the realist view of the universe. What are the different camps? What are the different views? I'm not sure I'm a good scholar and can talk about the different camps and analyze it. But some, many of the inventors of quantum physics were not realists, were anti-realists. And there are scholars, they lived in a very perilous time between the two world wars. And there were a lot of trends in culture which were going that way. But in any case, they said things like the purpose of science is not to give an objective, realist description of nature as it would be in our absence. This might be saying Niels Bohr. The purpose of science is as an extension of our conversations with each other to describe our interactions with nature. And we're free to invent and use terms like particle, or wave, or causality, or time, or space if they're useful to us and they carry some intuitive implication. But we shouldn't believe that they actually have to do with what nature would be like in our absence, which we have nothing to say about. Do you find any aspect of that, because you kind of said that we human beings tell stories. Do you find aspects of that kind of anti-realist view of Niels Bohr compelling? That we're fundamentally are storytellers and then we create tools of space and time and causality and whatever this fun quantum mechanics stuff is to help us tell the story of our world. Sure, I just would like to believe that there's an aspiration for the other thing. The other thing being what? The realist point of view. Do you hope that the stories will eventually lead us to discovering the real world as it is? Yeah. Is perfection possible, by the way? Is it? You mean will we ever get there and know that we're there? Yeah, exactly. That's not my, that's for people 5,000 years in the future. We're certainly nowhere near there yet. Do you think reality that exists outside of our mind, do you think there's a limit to our cognitive abilities as, again, descendants of apes who are just biological systems? Is there a limit to our mind's capability to actually understand reality? Sort of there comes a point, even with the help of the tools of physics, that we just cannot grasp some fundamental aspects of that reality. Again, I think that's a question for 5,000 years in the future. We're not even close to that limit. I think there is a universality. Here, I don't agree with David Deutsch about everything, but I admire the way he put things in his last book. And he talked about the role of explanation. And he talked about the universality of certain languages or the universality of mathematics or of computing and so forth. And he believed that universality, which is something real, which somehow comes out of the fact that a symbolic system or a mathematical system can refer to itself and can, I forget what that's called, can reference back to itself and build, in which he argued for a universality of possibility for our understanding, whatever is out there. But I admire that argument. But it seems to me we're doing okay so far, but we'll have to see. Whether there is a limit or not. For now, we've got plenty to play with. Yeah. There are things which are right there in front of us which we miss. And I'll quote my friend, Eric Weinstein, in saying, look, Einstein carried his luggage. Freud carried his luggage. Marx carried his luggage. Martha Graham carried her luggage, et cetera. Edison carried his luggage. All these geniuses carried their luggage. And not once before relatively recently did it occur to anybody to put a wheel on luggage and pull it. And it was right there waiting to be invented for centuries. So this is Eric Weinstein. Yeah. What do the wheels represent? Are you basically saying that there's stuff right in front of our eyes that once we, it just clicks, we put the wheels in the luggage, a lot of things will fall into place. Yes, I do, I do. And every day I wake up and think, why can't I be that guy who was walking through the airport? Yeah. What do you think it takes to be that guy? Because like you said, a lot of really smart people carried their luggage. What, just psychologically speaking, so Eric Weinstein is a good example of a person who thinks outside the box. Yes. Who resists almost conventional thinking. You're an example of a person who by habit, by psychology, by upbringing, I don't know, but resists conventional thinking as well, just by nature. Thank you, that's a compliment. That's a compliment? Good. So what do you think it takes to do that? Is that something you were just born with? I doubt it. Well, from my studying some cases, because I'm curious about that, obviously, and just in a more concrete way, when I started out in physics, because I started a long way from physics, so it took me a long, not a long time, but a lot of work to get to study it and get into it, so I did wonder about that. And so I read the biographies, and in fact, I started with the autobiography of Einstein and Newton and Galileo and all those people. And I think there's a couple things. Some of it is luck, being in the right place at the right time. Some of it is stubbornness and arrogance, which can easily go wrong. Yes. And I know all of these are doorways, if you go through them slightly at the wrong speed or in the wrong angle, they're ways to fail. But if you somehow have the right luck, the right confidence and arrogance, caring, I think Einstein cared to understand nature with a ferocity and a commitment that exceeded other people of his time. So he asked more stubborn questions, he asked deeper questions. I think, and there's a level of ability and whether ability is born in or can be developed to the extent to which it can be developed, like any of these things, like musical talent. You mentioned ego. What's the role of ego in that process? Confidence. Confidence, but in your own life, have you found yourself walking that nice edge of too much or too little? So being overconfident and therefore leading yourself astray or not sufficiently confident to throw away the conventional thinking of whatever the theory of the day, of theoretical physics? I don't know if I, I mean, I've contributed what I've contributed, whether if I had had more confidence in something, I would have gotten further, I don't know. Certainly I'm sitting here at this moment with very much my own approach to nearly everything. And I'm calm, I'm happy about that. But on the other hand, I know people whose self-confidence vastly exceeds mine, and sometimes I think it's justified and sometimes I think it's not justified. Your most recent book titled Einstein's Unfinished Revolution, so I have to ask, what is Einstein's Unfinished Revolution and also how do we finish it? Well, that's something I've been trying to do my whole life. But Einstein's Unfinished Revolution is the twin revolutions which invented relativity theory, special and especially general relativity, and quantum theory, which he was the first person to realize in 1905 that there would have to be a radically different theory which somehow realized or resolved the paradox of the duality of particle and wave for photons. And he was, I mean, people I think don't always associate Einstein with quantum mechanics because I think his connection with it, founding as one of the founders, I would say, of quantum mechanics, he kind of put it in the closet. Is it? Well, he didn't believe that the quantum mechanics as it was developed in the late 19th, middle late 1920s was completely correct. At first he didn't believe it at all. Then he was convinced that it's consistent but incomplete, and that also is my view. It needs, for various reasons I can elucidate, to have additional degrees of freedom, particles, forces, something to reach the stage where it gives a complete description of each phenomenon, as I was saying, realism demands. So what aspect of quantum mechanics bothers you and Einstein the most? Is it some aspect of the wave function collapse discussions, the measurement problem? Is it the? The measurement problem. I'm not gonna speak for Einstein. But the measurement problem, basically, and the fact that- What is the measurement problem, sorry? The basic formulation of quantum mechanics gives you two ways to evolve situations in time. One of them is explicitly when no observer is observing or no measurement is taking place. And the other is when a measurement or an observation is taking place. And they basically contradict each other. But there's another reason why the revolution was incomplete, which is we don't understand the relationship between these two parts. General relativity, which became our best theory of space and time and gravitation and cosmology and quantum theory. So for the most part, general relativity describes big things, quantum theory describes little things, and that's the revolution that we found really powerful tools to describe big things and little things. And it's unfinished because we have two totally separate things, and we need to figure out how to connect them so it can describe everything. Right, and we either do that, if we believe quantum mechanics, as understood now, is correct, by bringing general relativity or some extension of general relativity that describes gravity and so forth into the quantum domain that's called quantized, the theory of gravity. Or if you believe with Einstein that quantum mechanics needs to be completed, and this is my view, then part of the job of finding the right completion or extension of quantum mechanics would be one that incorporated space-time and gravity. So where do we begin? So first, let me ask, perhaps you can give me a chance, if I could ask you some just really basic questions. Well, they're not at all. The basic questions are the hardest, but you mentioned space-time. What is space-time? Space-time, you talked about a construction. So I believe that space-time is a intellectual construction that we make of the events in the universe. I believe the events are real, and the relationships between the events, which cause which are real. But the idea that there's a four-dimensional, smooth geometry which has a metric and a connection and satisfies the equations that Einstein wrote, it's a good description to some scale. It's a good approximation. It captures some of what's really going on in nature. But I don't believe it for a minute is fundamental. So, okay, we're gonna, allow me to linger on that. So the universe has events. Events cause other events. There's this idea of causality. Okay, so that's real. That's in my- In your view, is real. Or hypothesis, or the theories that I have been working to develop make that assumption. So space-time, you said four-dimensional space is kind of the location of things, and time is whatever the heck time is. And you're saying that space-time is, both space and time are emergent and not fundamental? No. Sorry, before you correct me, what does it mean to be fundamental or emergent? Fundamental means it's part of the description as far down as you go. We have this notion. As real. Yes. As real as real as it could be. Yeah, so I think that time is fundamental, and quote goes all the way down, and space does not. And the combination of them we use in general relativity that we call space-time also does not. But what is time, then? I think that time, the activity of time, is the continual creation of events from existing events. So if there's no events, there's no time. Then there's not only no time, there's no nothing. So? So I believe the universe has a history which goes to the past. I believe the future does not exist. There's a notion of a present and a notion of the past, and the past consists of, is a story about events that took place to our past. So you said the future doesn't exist. Yes. Could you say that again? Can you try to give me a chance to understand that one more time? So the events cause other events. What is this universe? Because we'll talk about locality and non-locality. Good. Because it's a crazy, I mean, it's not crazy. It's a beautiful set of ideas that you propose. But, and if causality is fundamental, I'd just like to understand it better. What is the past? What is the future? What is the flow of time, even the error of time, in our universe, in your view? And maybe what's an event? Right? Oh, an event is where something changes, or where two, it's hard to say, because it's a primitive concept. An event is a moment of time within space. This is the view in general relativity, where two particles intersect in their paths, or something changes in the path of a particle. Now, we are postulating that there is, at the fundamental level, a notion, which is an elementary notion, so it doesn't have a definition in terms of other things, but it is something elementary happening. And it doesn't have a connection to energy, or matter, or exchange of any? It does have a connection to energy and matter. So it's at that level? Yes, it involves, and that's why the version of a theory of events that I've developed with Marina Cortes, and it's, by the way, I wanna mention my collaborators, because they've been at least as important in this work as I have, as Marina Cortes in all the work since about 2013, 2012, 2013, about causality, causal sets, and in the period before that, Roberto Manguibara Unger, who is a philosopher and a professor of law. And that's in your efforts, together with your collaborators, to finish the unfinished revolution? Yes. And focus on causality as a fundamental, Yes. As fundamental to physics. And there's certainly other people we've worked with, but those two people's thinking had a huge influence on my own thinking. So in the way you describe causality, that's what you mean of time being fundamental, that causality is fundamental. Yes. And what does it mean for space to not be fundamental, to be emergent? That's very good, that there's a level of description in which there are events, there are events create other events, but there's no space, they don't live in space. They have an order in which they caused each other, and that is part of the nature of time for us. But there is an emergent, approximate description, and you asked me to define emergent, I didn't. Emergent property is a property that arises at some level of complexity, larger than and more complex than the fundamental level, which requires some property to describe it, which is not directly explicable or derivable, is the word I want, from the properties of the fundamental things. And space is one of those things in a sufficiently complex universe, space, three-dimensional position of things emerged. Yes, and we have this, we saw how this happens in detail in some models, both computationally and analytically. Okay, so connected to space is the idea of locality. Yes. That, so we talked about realism, so I live in this world, I like sports. Locality is a thing that you can affect things close to you and don't have an effect on things that are far away. It's the thing that bothers me about gravity in general, or action at a distance. Same thing that probably bothered Newton, or at least he said a little bit about it. Okay, so what do you think about locality? Is it just a construct? Is it us humans just like this idea and are connected to it because we exist and we need it for our survival, but it's not fundamental? I mean, it seems crazy for it not to be a fundamental aspect of our reality. It does. Can you comfort me, sort of as a therapist, like how do I? I'm not a good therapist, but I'll do my best. Okay. There are several different definitions of locality when you come to talk about locality in physics. In quantum field theory, which is a mixture of special relativity and quantum mechanics, there is a precise definition of locality. Field operators corresponding to events in space-time, which are space-like separated, commute with each other as operators. So in quantum mechanics, you think about the nature of reality as fields, and things that are close in a field have an impact on each other more than farther away. That's, yes. That's very comforting. That makes sense. So that's a property of quantum field theory, and it's well tested. Unfortunately, there's another definition of local, which was expressed by Einstein, and expressed more precisely by John Bell, which has been tested experimentally and found to fail. And this setup is you take two particles. So one thing that's really weird about quantum mechanics is a property called entanglement. You can have two particles interact, and then share a property without it being a property of either one of the two particles. And if you take such a system, and then you make a measurement on particle A, which is over here on my right side, and particle B, which is over here, somebody else makes a measurement of particle B, you can ask that whatever is the real reality of particle B, it not be affected by the choice the observer at particle A makes about what to measure. Not the outcome, just the choice of the different things they might measure. And that's a notion of locality, because it assumes that these things are very far space-like separated, and it's gonna take a while for any information about the choice made by the people here at A to affect the reality at B. But you make that assumption. That's called Bell locality. And you derive a certain inequality that some correlations, functions of correlations have to satisfy. And then you can test that pretty directly in experiments which create pairs of photons or other particles. And it's wrong by many sigma. In experiment, it doesn't match. So what does that mean? That means that that definition of locality I stated is false. The one that Einstein was playing with. And the one that I stated, that is, it's not true that whatever is real about particle B is unaffected by the choice that the observer makes as to what to measure in particle A. No matter how long they've been propagating at almost the speed of light, or the speed of light away from each other. It's true. So it matters, so like the distance between them. Well, it's been tested, of course. If you want to have hope for quantum mechanics being incomplete or wrong and corrected by something that changes this, it's been tested over a number of kilometers. I don't remember whether it's 25 kilometers or 100 and something kilometers. So in trying to solve the unsolved revolution, in trying to come up with a theory for everything, is causality fundamental and breaking away from locality? Absolutely. A crucial step. So in your book, essentially, those are the two things we really need to think about as a community. Especially the physics community has to think about this. I guess my question is, how do we solve? How do we finish the unfinished revolution? Well, that's, I can only tell you what I'm trying to do and what I have abandoned. Yes, exactly. As not working. As one ant, smart ant in an ant colony. Yep. Or maybe dumb, that's why, who knows? But anyway, my view of the, we've had some nice theories invented. There's a bunch of different ones. Both relate to quantum mechanics, relate to quantum gravity. There's a lot to admire in many of these different approaches but to my understanding, they, none of them completely solve the problems that I care about. And so we're in a situation which is either terrifying for a student or full of opportunity for the right student in which we've got more than a dozen attempts. And I never thought, I don't think anybody anticipated it would work out this way. Which worked partly and then at some point, they have an issue that nobody can figure out how to go around or how to solve. And that's the situation we're in. My reaction to that is twofold. One of them is to try to bring people, we evolved into this unfortunate sociological situation in which there are communities around some of these approaches. And to borrow again a metaphor from Eric, they sit on top of hills in the landscape of theories and throw rocks at each other. And as Eric says, we need two things. We need people to get off their hills and come down into the valleys and party and talk and become friendly and learn to say, not no but, but yes and. Yes, your idea goes this far, but maybe if we put it together with my idea, we can go further. Yes. So in that spirit, I've talked several times with Sean Carroll, who's also written an excellent book recently. And he kind of, he plays around, is a big fan of the many worlds interpretation of quantum mechanics. So I'm a troublemaker, so let me ask, what's your sense of Sean and the idea of many worlds interpretation? I've read many, the commentary back and forth. You guys are friendly, respect each other, but have a lot of fun debating. I love Sean and he, no, I really, he's articulate and he's a great representative or ambassador of science to the public and for different fields of science to each other. He also, like I do, takes philosophy seriously. And unlike what I do in all cases, he's really done the homework. He's read a lot, he knows the people, he talks to them, he exposes his arguments to them. And I, there's this mysterious thing that we so often end up on the opposite sides of one of these issues. It's fun though. It's fun and I'd love to have a conversation about that, but I would want to include him. I see, about many worlds. Well. No, I can tell you what I think about many worlds. I'd love to, but actually on that, let me pause. Sean has a podcast, you should definitely figure out how to talk to Sean. I actually told Sean I would love to hear you guys just going back and forth. So I hope you can make that happen eventually, you and Sean. I won't tell you what it is, but there's something that Sean said to me in June of 2016 that changed my whole approach to a problem. But I have to tell him first. Yes, and that'll be great to tell him on his podcast. So. I can invite myself to his podcast. I told him, yeah, okay, we'll make it happen. So many worlds. Anyway. What's your view? Many worlds, we talked about non-locality. Many worlds is also a very uncomfortable idea or beautiful depending on your perspective. It's very nice in terms of, I mean, there's a realist aspect to it. I think you called it magical realism. Yeah. Which is just a beautiful line. But at the same time, it's very difficult to for our limited human minds to comprehend. So what are your thoughts about it? Let me start with the easy and obvious and then go to the scientific. Okay. It doesn't appeal to me. It doesn't answer the questions that I want answered. And it does so to such a strong case that when Roberto Manguibar-Angur and I began looking for principles, and I want to come back and talk about the use of principles in science because that's the other thing I was going to say and I don't want to lose that. When we started looking for principles, we made our first principle, there is just one world and it happens once. But so it's not helpful to my personal approach, to my personal agenda. But of course, I'm part of a community. And my sense of the many worlds interpretation, I have thought a lot about it and struggled a lot with it, is the following. First of all, there's Everett himself, there's what's in Everett. And there are several issues there connected with the derivation of the Born Rule, which is the rule that gives probabilities to events. And the reasons why there is a problem with probability is that I mentioned the two ways that physical systems can evolve. The many worlds interpretation cuts off one, the one having to do with measurement, and just has the other one, the Schrodinger evolution, which is this smooth evolution of the quantum state. But the notion of probability is only in the second rule, which we've thrown away. So where does probability come from? And you have to answer the question, because experimentalists use probabilities to check the theory. Now, at first sight, you get very confused, because there seems to be a real problem. Because in the many worlds interpretation, this talk about branches is not quite precise, but I'll use it. There's a branch in which everything that might happen does happen, with probability one in that branch. You might think you could count the number of branches in which things do and don't happen, and get numbers that you can define as something like frequentist probabilities. And Everett did have an argument in that direction. But the argument gets very subtle when there are an infinite number of possibilities, as is the case in most quantum systems. And my understanding, although I'm not as much of an expert as some other people, is that Everett's own proposal failed, did not work. There are then, but it doesn't stop there. There is an important idea that Everett didn't know about, which is decoherence, and it is a phenomenon that might be very much relevant. And so a number of people post-Everett have tried to make versions of what you might call many worlds quantum mechanics. And this is a big area, and it's subtle, and it's not the kind of thing that I do well. So I consulted, that's why there's two chapters on this in the book I wrote, chapter 10, which is about Everett's version, and chapter 11. There's a very good group of philosophers of physics in Oxford, Simon Saunders, David Wallace, Harvey Brown, and a number of others. And of course, there's David Deutsch, who is there. And those people have developed and put a lot of work into a very sophisticated set of ideas designed to come back and answer that question. They have the flavor of there are really no probabilities, we admit that, but imagine if the Everett story was true and you were living in that multiverse, how would you make bets? And so they use decision theory from the theory of probability and gambling and so forth to shape a story of how you would bet if you were inside an Everettian universe and you knew that. And there's a debate among those experts as to whether they or somebody else has really succeeded. And when I checked in as I was finishing the book with some of those people, like Simon, who's a good friend of mine, and David Wallace, they told me that they weren't sure that any of them was yet correct. So that's what I put in my book. Now, to add to that, Sean has his own approach to that problem in what's called self-referencing or self-locating observers. And it doesn't, I tried to read it and it didn't make sense to me, but I didn't study it hard, I didn't communicate with Sean, I didn't do the things that I would do, so I had nothing to say about it in the book. And I don't know whether it's right or not. Let's talk a little bit about science. You mentioned the use of principles in science. What does it mean to have a principle and why is that important? When I feel very frustrated about quantum gravity, I like to go back and read history. And of course, Einstein, his achievements are a huge lesson and hopefully something like a role model. And it's very clear that Einstein thought that the first job when you want to enter a new domain of theoretical physics is to discover and invent principles and then make models of how those principles might be applied in some experimental situation, which is where the mathematics comes in. So for Einstein, there was no unified space and time. Minkowski invented this idea of space-time. For Einstein, it was a model of his principles or his postulates. And I've taken the view that we don't know the principles of quantum gravity. I can think about candidates and I have some papers where I discuss different candidates and I'm happy to discuss them. But my belief now is that those partially successful approaches are all models which might describe indeed some quantum gravity physics in some domain, in some aspect, but ultimately would be important because they model the principles and the first job is to tie down those principles. So that's the approach that I'm taking. So speaking of principles, in your 2006 book, The Trouble with Physics, you criticized a bit string theory for taking us away from the rigors of the scientific method or whatever you would call it. But what's the trouble with physics today and how do we fix it? Can I say how I read that book? Sure. I, and I'm not, this of course has to be my fault because you can't as an author claim after all the work you put in that you are misread. But I will say that many of the reviewers who are not personally involved and even many who were working on string theory or some other approach to quantum gravity told me, communicated with me and told me they thought that I was fair and balance was the word that was usually used. So let me tell you what my purpose was in writing that book, which clearly got diverted by, because there was already a rather hot argument going on and this is- On which topic, on string theory specifically or in general in physics? No, more specifically than string theory. So since we're in Cambridge, can I say that? We're doing this in Cambridge? Yeah, yeah, of course, Cambridge, just to be clear, Massachusetts and on Harvard campus. Right, so Andy Strominger is a good friend of mine and has been for many, many years. And Andy, so originally there was this beautiful idea that there were five string theories and maybe they would be unified into one and we would discover a way to break that symmetries of one of those string theories and discover the standard model and predict all the properties of the standard model particles, like their masses and charges and so forth, coupling constants. And then there was a bunch of solutions to string theory found, which led each of them to a different version of particle physics with a different phenomenology. These are called the Calabi-Yau metaphors, named after Yau, who is also here. Certainly we've been friends at some time in the past anyway and then there were, nobody was sure, but hundreds of thousands of different versions of string theory. And then Andy found there was a way to put a certain kind of mathematical curvature called torsion into the solutions and he wrote a paper, String Theory with Torsion, in which he discovered there was not formally uncountable, but he was unable to invent any way to count the number of solutions or classify the diverse solutions. And he wrote that this is worrying because doing phenomenology the old-fashioned way by solving the theory is not gonna work because there's gonna be loads of solutions for editing proposed phenomenology for anything the experiment's discovered. Now it hasn't quite worked out that way, but nonetheless, he took that word to me. We spoke at least once, maybe two or three times about that. And I got seriously worried about that. And this is a little. Sounds like an anecdote that inspired your worry about string theory in general. Well, I tried to solve the problem and I tried to solve the problem. I was reading at that time a lot of biology, a lot of evolutionary theory, like Lin-Margulis and Steve Gould and so forth. And I could take your time to go through the things that occurred to me, maybe physics was like evolutionary biology and maybe the laws evolved and there was the biologists talk about a landscape, a fitness landscape of DNA sequences or protein sequences or species or something like that. And I took their concept and the word landscape from theoretical biology and made a scenario about how the universe as a whole could evolve to discover the parameters of the standard model. And I'm happy to discuss, that's called cosmological natural selection. Cosmological natural selection. Yeah, and I published. Wow, so the parameters of the standard model, so it's the laws of physics are changing. This idea would say that the laws of physics are changing in some way that echoes that of natural selection or just it adjusts in some way towards some goal. Yes. And I published that. I wrote the paper in 88 or 89, the paper was published in 92. My first book in 1997, The Life of the Cosmos was explicitly about that. And I was very clear that what was important is that because you would develop an ensemble of universes but they were related by descent through natural selection, almost every universe would share the property that its fitness was maximized to some extent, or at least close to maximum. And I could deduce predictions that could be tested from that. And I worked all of that out and I compared it to the anthropic principle where you weren't able to make tests or make falsifications. All of this was in the late 80s and early 90s. That's a really compelling notion but how does that help you arrive? I'm coming to where the book came from. Yes. So what got me, I worked on string theory, I also worked on loop quantum gravity and I was one of the inventors of loop quantum gravity. And because of my strong belief in some other principles which led to this notion of wanting a quantum theory of gravity to be what we call relational or background independent, I tried very hard to make string theory background independent and ended up developing a bunch of tools which then could apply directly to general relativity and that became loop quantum gravity. So the things were very closely related and have always been very closely related in my mind. The idea that there were two communities, one devoted to strings and one devoted to loops is nuts and it's always been nuts. Okay, so. So anyway. There's this nuts community of loops and strings that are all beautiful and compelling and mathematically speaking and what's the trouble with all that? Why is that such a problem? So I was interested in developing that notion of how science works based on a community and ethics that I told you about. And I wrote a draft of a book about that which had several chapters on methodology of science and it was a rather academically oriented book and those chapters were the first part of the book, the first third of it and you can find their remnants in what's now the last part of The Trouble with Physics and then I described a number of test cases, case studies and one of them which I knew was the search for quantum gravity and string theory and so forth. And I was unable to get that book published. So somebody made the suggestion of flipping it around and starting with the story of string theory which was already controversial. This was 2004, 2005. But I was very careful to be detailed to criticize papers and not people. You won't find me criticizing individuals. You'll find me criticizing certain writing. But in any case, here's what I regret. Let me make your program worthwhile. Yes. As far as I know, with the exception of not understanding how large the applications to condensed matter say of ADS-CFT would get, I think largely my diagnosis of string theory as it was then has stood up since 2006. What I regret is that the same critique, I was using string theory as an example and the same critique applies to many other communities in science in all of including, and this is where I regret my own community, that is a community of people working on quantum gravity outside string theory. But, and I considered saying that explicitly. But to say that explicitly, since it's a small intimate community, I would be telling stories and naming names and making a kind of history that I have no right to write. So I stayed away from that, but was misunderstood. But if I may ask, is there a hopeful message for theoretical physics that we can take from that book? Sort of that looks at the community, not just your own work on now with causality and non-locality, but just broadly in understanding the fundamental nature of our reality. What's your hope for the 21st century in physics? That we can take? Well, that we solve the problem. That we solve the unfinished problem of my science. That's certainly the thing that I care about most. Let me say one thing. Among the young people that I work with, I hear very often and sense a total disinterest in these arguments that we older scientists have. And an interest in what each other is doing. And this is starting to appear in conferences where the young people interested in quantum gravity make a conference, they invite loops and strings and causal dynamical triangulations and causal set people. And we're having a conference like this next week, a small workshop at Perimeter. And I guess I'm advertising this. And then in the summer, we're having a big full-on conference, which is just quantum gravity. It's not strings, it's not loops. But the organizers and the speakers will be from all the different communities. And this to me is very helpful. That the different ideas are coming together. At least people are expressing an interest in that. It was a huge honor talking to you, Lee. Thanks so much for your time today. Thank you. Thanks for listening to this conversation. And thank you to our presenting sponsor, Cash App. Download it, use code LEXPODCAST. You'll get $10 and $10 will go to FIRST, an organization that inspires and educates young minds to become science and technology innovators of tomorrow. If you enjoy this podcast, subscribe on YouTube, give it five stars on Apple Podcast, follow on Spotify, support it on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words from Lee Smolin. One possibility is, God is nothing but the power of the universe to organize itself. Thanks for listening and hope to see you next time.

https://youtu.be/WgLo4gmEraU

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Tom Brands: Iowa Wrestling | Lex Fridman Podcast #245

The following is a conversation with Tom Brands, Olympic champion and world champion in freestyle wrestling, three-time NCAA wrestling champion at University of Iowa and one of the greatest coaches in the history of wrestling, leading the University of Iowa Hawkeyes for 15 years, including in 2021 winning the national championships and getting a coach of the year award, his third. He's known for his intensity, focus, and mental toughness, embodying both as a wrestler and coach the culture and spirit of Iowa wrestling. We recorded this conversation almost exactly three years ago after I attended the University of Iowa versus Iowa State wrestling meet in the historic Carver Hawkeye Arena. Tom graciously invited me to his home where his family, a couple of friends, and me spent several hours chatting about wrestling and life. We recorded this brief podcast conversation that evening and I wasn't sure where, how, or whether we'll publish it, but returning to it now three years later, I realized just how meaningful that evening was for me and even though I was nervous, didn't even put on my jacket, it's a moment I would love to share with others. The mix of intensity and heartfelt kindness from Tom and his family made me want to stay in Iowa forever. I think I will return there soon enough because of the amazing people there and because Iowa is still in many ways the heart of the indomitable spirit of American wrestling, a sport I love and to which I'm deeply grateful for humbling me early in life and helping me and many others build character through hard work. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description and now here's my conversation with Tom Brantz. What's the best motivator for you or for your athletes? Hatred of losing or love of winning? For me personally, it was definitely the hatred of losing. I was not a guy that was about pageantry. I was not a guy that was about the parade. When I wrestled in Atlanta, I rented a three-cylinder Gio with my wife, drove home and mowed the lawn because it hadn't been mowed for a month. I remember one of our neighbors driving by and they were like, they did a double take. I thought he was in Atlanta. Well, I was in Atlanta yesterday. I just sat on the stand and got a gold medal put around my neck. That's how I was. That doesn't mean that it was the right approach or the wrong approach. It's just what worked for me. When you were a kid, you and Terry, you dreamed about winning that Olympic gold. Yeah. That's about winning then. There is the lure of winning. What drives you is that as you move forward, there's just no reason that you have to settle for anything but being the best. It would get to you to the point where that's not going to happen to me again. The thing that keeps you up at night is the losses and that's not going to happen to me again. That's the thought that keeps you up at night. That's the thought that drives you in your training. That's why you do nine ropes when Gable says do three ropes and buddy pushups and you're out of here. You do nine or you do them until you can't do any more. It's a very rare ingredient. The older I get, the more rare I find it is. The ingredient of loss feeding the drive of hard training? Maybe that because everybody's so worried about the negative whatever and you're putting too much pressure on yourself. Maybe that. What I meant was it's when a coach says, okay, finish with four ropes and buddy pushups and four-way neck, I would do 12 or 10. That's rare. It's no longer about what the coach says. It's your own demons that you're trying to exercise out. What's the few losses you've had in your life? Are all of them just melt together or is there something that stands out in your mind? I'm a guy that remembers my career that well. I know that I am judged on a very small portion of my life and that's minutes of wrestling matches. There's a lot of winning, but there's some losing in there too. People think they know you because of that. They think they know you because they see you in a press conference. To go back to the original question, I don't know how to answer that. There's no losses that eat at you still? There's opponents that I have learned a great deal from. My loss to John Smith in 1991, US Open, was something that I learned a lot about. I learned a lot about positioning. I learned a lot about the importance of parterre. In a certain crazy way, I learned that I could go with the best guy in the world even though it was 14 to 4. This is when Tech Falls were 15 or 12 points. I didn't get Tech Fall. That wasn't a badge of honor for me, but I knew I could go with him because it was one point takedowns. I scored four takedowns on him. I learned that I had to move my feet. I learned what it meant to move your feet constantly. John Smith is a very, very intense competitor that people know that now, six-time World Olympic champion. I felt that firsthand, but I did not go in there taking a back seat even though the score was very lopsided. But you knew you could stand with the best of the world. I knew that this is what this is about. You know what? You move your feet and you don't give up a lace that's so damn tight that you can't feel your calf muscle. I had to get ready for the consolation side of the bracket because I believe that was in the semis. You just learn from that. It was better than learning from a win over a second-ranked senior level guy when you're a junior in college. You're wrestling the best on a stage. If you look back, you probably spent tens of thousands of hours on the mat, spilled sweat, blood, even tears maybe, maybe a few times. So technically or philosophically, how would you do any of those hours differently? Just looking back at the tens of thousands of hours. I would be more probably in my older age, I probably would have been more relaxed in my training and probably would have went another cycle if I could do it over again. In 96, I really thought that when Gable retired that I would be the next guy in line. I was wrong and that was immature of me. In terms of the coach? In terms of the coach, yes. I knew that Gable was close. I didn't know when but it just so happens 97 was his record-breaking year and then he retired. I didn't know how close he was but I knew that he went down with a bad hip injury. And so you're not going to... So what does a relaxed Tom Brands look like? You're saying you would have been a little more relaxed. More like where, you know what, I was pretty dang good and I was getting better every day but maybe doing a little bit different, a little bit smarter. And Terry actually did that going through 2000. He had to do it and he would have been in the funny farm let alone the physical farm, whatever you want to say, mentally and physically beat up. But he had to learn to less is more type approach. And how it came around was you work hard at feeling good. You work hard in your recovery. So even when you're not wrestling hard in that wrestling room and looking for the toughest partner to go, you're still working hard in your recovery. In recovery. And massage could be that. Stretching could be that. Things like that that are more fluffy. And that's something you weren't as good at in recovery? Never, never. There's not a place for it with young people because in my opinion, there's so much development to have happen. I mean when you need to learn wrestling, you need to be wrestling. And as you get older, your body won't do it anymore. And so to learn wrestling, it's more of a probably a relaxed approach. So if you had to choose between two athletes who would dominate competition, one who drills 100,000 reps of a specific takedown, specific technique, or one that spends that time live wrestling? Both. It's the same. And I like to live wrestling. I was always wanting to live wrestle. Bring the warmup into the live wrestle, let's go. But where I got really, really good was in repetition. And I was disciplined enough to know that the things that you hate to do in this sport are the things that make you the very best. And that is a rare ingredient as I've gotten older. And you spend a lot of time communicating that to younger athletes. So the thing, if you feel yourself hating something, that's probably the thing you should be doing. Yes. As a matter of fact, I had a strength coach when I was really young. He was just a freaking guy that would, he wore white, like he was almost like a nurse, nurses clothes. He wore all white from head to toe and he was in Cheyenne, Wyoming. And his first name was Walt. And he taught Terry and I to hate the bar away from you on that last rep when you're dead. And whether it's a curl, you hate it up. And then you do the negative and you hate it down and you hate that bench up and you hate it. You look at the bar and you hate it away from you. So I learned and I was young. I was young. And I remember being born, my mom's sister lived out there and we were dropped off to stay out there with our cousins. And I was born a little bit and they always treated us really good. But this was like the single most bright spot in a weightlifting, like enlightenment, even though I lifted weights. But I never knew the psychology behind lifting weights. It's just to look good. And so you can flex and look in the mirror or is it for performance? And this guy was about performance. And you said repetition. Do you mean technique? I'm talking repetition, technique, technique, technique, drill, drill, drill, hit, hit, hit, drive, finish, hit, hit, hit, drive, finish. So you believe in that? I believe in that wholeheartedly. So I mean... And I believe that you have to do it on your own. I don't believe in the coach taking you to the promised land. So in the guys today or in yourself, how often do you see people that grow the belief of doing 10,000, 20,000 reps? I think it's rare. I think it's very rare. And I think it's especially rare. I mean, you can talk about that as a coach, but it's especially rare to bring a guy to that understanding, but you never stop trying. You're always trying to reach him. I mean, we didn't have a good performance out there tonight, but you know what? You don't stop communicating. And there's a lot of programs out there that put their head down when things aren't going their way. And then as things start going their way, then they rise with the tide. There was no difference in the demeanor of our corner. And we talk about that. That's a philosophy. And so you're reaching your guys that way. So go back to your point or your question. You know, do you believe in the 10,000 reps? And yes, I do. And how do you inspire people to do that? Well, you communicate. By example, but communication. But I mean, that's a... In my experience, what I've seen is that communicating the value of repetition and drilling is a hard thing to communicate. It's hard, and it's very rare to have somebody that goes in there and will do it on their own. Do you have young guys that step up and do that? We do, and it's rare. And the guys that do it on their own and have done it on their own are the guys that are in that lineup and doing well. The other thing is that when you talk about getting to that next level, a lot of times it's, you know, what held you back was I did everything the coach asked of me and nothing more. I mean, you can be a great guy for a coach as an athlete, and you did everything that coach asked, but you did nothing more. So you're really looking for the guys that go way beyond what the coach says. We don't want guys that are looking at their watch running out of the room when practice is over. We want guys that know what they have to get done, and they might leave early, but they're not looking at their watch. They might be done early. We might be on a whole different path, and this guy just excuses himself. I'm all about that. We are not autocrats. There's an internal engine in there. Is that something you're born with, or is that something you can develop? I think you are born with it. You develop it also, and I think that there has to be comfort, and I go back to the communication, that young people are comfortable enough to communicate that I need to take the day off. So what do you mean by communication? Or I need to make a difference. Just let, exactly, so letting athletes be part of their own development. Communication to me is letting them know what they need to do to get themselves in contention to be the starting quarterback, and then to give them boosts and compliments when they earn them. I don't have time to waste with lies and cheating. When I say cheating, I'm talking about when they cheat themselves, and so those become very direct conversations, and the conversation starts like this. I don't have time to waste, and neither do you, and so why are we wasting our time? Here's what I mean by that. We're having a conversation about your accountability. If you look in the mirror and you're accountable, then we aren't taking the time to go through this. We're already on our way to solving the problem. Problem can't be solved without that understanding. And that has to do with symptoms that you see in the wrestling room. There's something where the fire's not quite there. That has to do with mental, emotional, spiritual, physical, everything, everything that you know about. I had a boss, and our athletic director is a great athletic director, and he gives us everything we need to be successful, but I had a boss. His name was Fred Mims, and I didn't think anybody could be better than him, and then all of a sudden this Gene Taylor guy came in, and then he was pretty doggone good too, and he actually was just like Fred and maybe even a little bit more current, and then he ended up taking a job at Kansas State where he's the athletic director now, and then this lady, Barbara Burke, comes in, and I didn't think anybody could be better than Gene Taylor or Fred Mims, and this Barbara Burke, she's better than both of them, and the reason why is because she's a problem solver. She doesn't waste time. She's direct, and she's a problem solver, and that's what we need. You need problem solvers. So on the flip side of problems and technique and repetition, here's a thing called toughness, mental toughness, something that maybe you or maybe even Iowa in general is a little bit known for. So how do you train mental toughness as a coach? You train mental toughness by putting them in situations that they're willing to go through but don't think they can make it, and then they go through it, and then all of a sudden those barriers are down. Is that have to do with physical usually exhaustion, the four wraps on the ropes? It has to do with that, and it has to do with understanding why we're doing it, and sometimes understanding why we're doing it might not come for months, but there's blind faith, and we have a heavyweight in the room right now, this young guy that he's like that. He doesn't necessarily understand it. He has a lot of questions, but he does it, and he's been here four months now, four and a half months now, and he's getting better every day. So mental toughness too is a matter of repetition. So that mental toughness is a matter of repetition and having an open mind and being extremely accountable, and not only accountable that when something doesn't go your way that you look in the mirror and own it, but accountable to the point of view that you know what, I got to get tough in this situation right here right now, and this is what's going to make or break me. And I talked about my own career being defined by a couple of minutes on the mat, but that's when you're going to be defined. That's how you're going to be defined. That's okay. So people are going to talk about you, so you might as well have them talking about how doggone tough you are. What about, we live in a world now, I've often in my own work, I hear about this concept of work life balance or over training. So you've been one of the hardest workers ever on the mat. You've coached some of the hardest workers ever. Do you think it's possible to over train, train too much? How big of a concern is it? I think peaking and burnout are frames of mind or burnout is a, like you let things probably get to the point where you could have arrested them with a good frame of mind. But peaking is a frame of mind and you have to know, be able to read, and that's a lot of it. And the individual athlete also has to know that it's a frame of mind. And so when you have a coach that's reading that the right way, and you have an athlete that is knowing that when zero hour comes, you're going to be ready to go. And knowing that there's light at the end of the tunnel, if you feel like you're burning that candle at both ends, light's coming at the end of the tunnel. I mean, you're good to go. So you think about Gable and that whole dream of being carried off the mat because you worked so hard. And again, do you think it's possible to over train? So you said it's mental. I do think it's possible to over train if you have a lot of distractions. So if you're looking at your watch running out of the room, then yeah, you're going to, that frame of mind isn't going to lend itself to excellency. And the thing is, is we have to accomplish what we need to get accomplished to get better every day. You can't kind of accomplish what you need to accomplish. You have to accomplish it. And when you're in that mindset, then the clock is irrelevant. There's no place for a clock in the wrestling room. And maybe a clock that times a match, but it may be a clock if, you know, we're student athletes here, but that's why we encourage our, you know, when you schedule your classes that you don't have a class that comes right up to, you know, practice time or starts as a night class, and it starts at 530, you know, go to get the 630 class or the seven o'clock. So you leave it all behind your heart. Your passion is completely innate. There's no, when you walk in that wrestling room, there's no distractions and it's never eternal. The only thing that's eternal is death. You know, there's nothing. Sometimes guys come in there and they wig out. Oh, it's an hour and 25 minutes of, oh, or an hour and 45 minutes. Oh, yeah. You have to be willing to go as long as it takes. There's no clock. There's no clock. Again, wrestlers are some of the hardest, some of the toughest people in all sports, but weight cutting often breaks people. So what's your thought on weight cutting, both nutrition wise, mental wise, how do you approach and think of it as a coach in your own career too? It's a lot of discipline and it's a lot of discipline during a very uncomfortable time period that really doesn't last that long, but it feels like it lasts long and it's painful. But once you shrink your body down and if you're hydrated, you'll get through it. If you're a little hungry, but you're eating, but you're hydrated, once you break that sweat, your energy depletion goes away. That's a fact. I've practiced that. You come in and you're yawning and you're starting to shrink your body down and it's that time of year where, hey, I got to get my body shrunk down and you're dehydrated, you are dead in the water. But if you're hungry and hydrated, when you break that sweat. Have people gotten better with that over the years, over the past few decades? I think that coach's science is better. I think that coaches communicate it. I think they always have. I think the bottom line is having the energy to implement that and taking a guy by the hand when he doesn't understand and he's new in your program and he's essential and or he's unwilling to and not disciplined enough because when you take him by the hand enough, they will learn that discipline. This is an important aspect of wrestling, buddy. You know what I'm saying? It's not just go and show up for the match. It's not about just making weight either. You got to be able to make weight. That's part of the warmup. That's part of the process getting ready to wrestle. It's the whole thing. It's the lifestyle. When did you first start believing you're going to win Olympic gold? I don't know. I mean, I found out I got really addicted to wrestling really, really fast. Started late but looking back at my life, wrestled my whole life with my twin brother. And when Terry and I would fight, it was wrestling and it was to maim. And so if you're trying to maim me, I better be tough because if I roll over and expect you to scratch my belly when you're trying to maim me, I will lose my head. And Tom and Terry Brands, there was no alpha male. And when it was on, it was on for real. What do you mean there's no alpha male? There's no alpha male. There's both. There's a lot of twins. There's a dominant twin, a lot of them. Very few times is there a situation where I'm going to win every time in everything and then he's thinking the same exact way. And Terry used to describe it like when we used to get interviewed a lot about our careers. It'd be like you grabbing a steering wheel and me grabbing a steering wheel and fighting. And that's what it was like when you would wrestle him or fight him. And so I had that benefit. So when did I know? Well, I got addicted to wrestling really, really fast in fifth grade and started to research it. And I don't know why. And talked about the Olympics and put it in my head. And I remember said something about being an Olympic champion in fifth grade and somebody made fun of me and I got in a fight in a playground. And I remember getting pulled in, getting in trouble for that. And the people that got me in trouble for that were smart enough to not rake me over the coals, but they researched or they actually found out what the fight was about. And I was distraught. I was really emotional, like crying or whatever you want to say. You don't want to admit that too many times. But it wasn't because I got beat up or got my nose bloodied or got punched in the face. Yeah. Or broke my arm or there was any pain. It was because they stomped on my dream and they doubted me. And so I fought for that. And that was a lesson. There's going to be a lot of doubters. And one thing we talk about as a staff is our staff has to be lockstep in that hallway, in our offices. And when you deviate outside of that, that is heresy. So everybody has to be on board, confident that you're going to be number one in the country. When we go forward and we go put our public foot forward, there is a decision. We are unified and there is no backbiting. And we have great people right now. And we hadn't had that before. We've had detractors in our Hawkeye Wrestling Club. We've had guys that would go out and get rolled up in ankle laces and not care in our club. And we got Brandon Sorenson, who got rolled up by James Green last night. But I'll tell you what, I don't have a problem with that. You know why? Because I know it means a lot to him. He didn't roll over. He didn't quit because he was on the consolation side of a bracket. And so when you have that and then you have, you know, if there's a disagreement, it's behind closed doors and then you're moving forward. And when you have people that when they're meeting your fans and your supporters, you know, they're talking the right way with the right message. And anything that's catty wonk is to that. You got to be careful there. You got to be careful there. So that in terms of affirmations, terms of really believing as a team, as an individual, believing that you're the best in the world, did you, I'm sure you had detractors. You had people that continued after fifth grade. And that's probably where my hatred of losing trumps my love for winning, because I wanted to shove it up their rear end bad. Yeah. And the thing is, is we maintain a high level and there's very few programs. Oklahoma state, Ohio state now, Penn state. I mean, there's four programs that try to win a national title every year and that's it. And these, these, these other teams, they get up and they got a good team and they get up and they get going. And then when, when things don't go well, okay, we're going to do it next year or this is a down year. We're going to, we're going to get right. We're three years out. So no matter what you're fighting for first, we do. And we haven't won. And you say, well, we haven't won in eight years. Well, you're right. We haven't. But look at our results are better, better than anybody out there. And it's because besides Penn state, and it's because of our mentality and because we have great people, Ryan Morningstar, Bobby Telford, Terry Brands, our medical team, even our strength coach, Quinn Holland, we're all on the same page. And when I send something, I hit it immediately. I don't have time to waste. There will not be dissension in that hallway. Everybody's in a together. Yeah. 1996 Olympic games in Atlanta. Can you take me through the day when you're going for the 62 kg gold? What did you eat? Drink? What did you think? It really doesn't matter. I have a routine that, you know, I had a routine as a competitor that I could run through right now. It was a lot of self-talk, very, very positive self-talk. Visualization. Yes. Visualization, self-talk. And that's how I was able to relax and getting ready for matches my whole life. Learned that very early age at a camp, at a developmental camp, at a young age, Terry and I did. And I can tell you what I ate and I can tell you what I did to relax. And it doesn't matter. What you have to do is you have to find that peace. And I just know that when I was getting ready for the finals match, I had gone back to my room. I had my relaxed material, you know, and I was able to relax because I prepared for it. Hopefully I'm right on this, but just looking at the insane bracket you had to go through, you had to beat, just to get to the finals, you had to beat three world champions. Eventually world champions. I mean, Dave. And you know what? I don't talk about that and nobody else does either, but everybody talks about it in their own career. So now you're making my head big. But yeah, I had a road. I had a road. You're right. That is the hardest bracket I've seen. So I've talked to a lot of Olympic champions. That is the hardest bracket I've seen of any champion. So maybe I'm confused on this, but it seemed like a really tough day for you. Did you know the bracket ahead of time? Did you know who you faced? You see the draw and it's a two-day tournament. So psychology comes into it as much as physical shape, because there's those, you got to sleep the night before after the weigh-in, then you got to sleep again that next night after your semi-final match is going to be in the morning. And then you have to go back and rest because your final match isn't until whatever time it was. And so all this relaxation and all that stuff that you just talked about, that visualization and self-talk, that's what helps you, it's your routine. And was there any doubt, any fear, anything there? The fear is the type of fear, and I just talked about this to one of my athletes today, Jack Dempsey talked about fear. And the fear of losing is what motivated him to try to take his opponent's head off. He was a boxer and that's okay. So fear of competition, fear of screwing up, fear of, oh, I don't feel good. No, no. But that little fear that, you know what, there's somebody out there that thinks that, you know what, they're going to revel in my, they're going to eat it up in my misery. They're going to love, they're going to be thriving because I fail. And I'm not going to let that happen. You're identical twin, brother, Terry. You've been at him, like you said, your whole life. And you're both some of the greatest wrestlers of all time. You won the gold medal, he won the bronze medal. You've mentioned, you know, all that really matters is the six minutes or, you know, just a few minutes, sometimes a few seconds define your whole career. So how do you think about that thin line, the tragic line at the Olympic level between winning and losing? I think you come to peace that in the end, when it's over, that you did the best you could. And that's certainly the case with Terry. His career credentials are better than mine internationally. You know, he won two world championships. I won one. And he won Olympic bronze medal. And, you know, I won an Olympic gold medal, but I only won one. And the thing is, is that's not what's important anyway. What's important is, is that when it's all over, you know, how do you look back on it? And you're kind of like, well, you just said that you made sure that you weren't going to leave anything undone. But you know what? There were tournaments where I did leave things undone. And so how do you come back from that? Well, Terry never came back from 2000 because he retired. Well, you know what? You duplicate and exceed when you're communicating to these young athletes. And because of that experience, that makes Terry a better coach. Because of, you know, 1995, that makes me a better coach. You know, realizing that there are certain things that unraveled in that year that I could have controlled looking back on it. And when you have that perspective, you can communicate. So what control is there? Can you control everything? How big of a role is luck? Control how you react to an injury. Control that. So you can't, you don't have any control of it. It's over. You know, you have whatever and whatever happened, but relax and you learn to deal with injuries better because of that. You have that experience that you let this thing maybe get the best of you. And that's just an example. And, you know, Terry put a lot of demons to rest with that bronze medal. So becoming an Olympic medalist, a few demons could relax. Well, no, he'll never admit that. And he probably is truthful. And I should, I'm speaking for him, but he's truthful when he says that. But if I look at it and bronze sucks, but if I look at it, he did put some demons to rest and I'm proud of him for it. There's something there that is a consolation in the fact that he won the consolation medal. The consolation medal sucks, but there is a consolation that he won the consolation. That's a tough medal to win, by the way. Yeah. But do you see the Shakespearean tragedy of it all, that the line between winning and losing? So you often say that, you know, winning is everything, but it feels like, especially at the Olympic level, or you talk about NCAA finals or that tournament, you know, a split second miss move can result in a loss where you dominated all the way up to there. That's where your psychology comes in and that's where the repetition and all of the self-talk and visualization and the physical shape and everything comes together. And so that doesn't happen. And tonight we got beat twice, actually three times, and we out-wrestled those. We lost three matches and we out-wrestled the guy for six minutes and 30 seconds. Or one match went to overtime. And if our guys can move forward with the right perspective, I'm confident that they'll be better. I'll tell you what, I'd take our guy over their guy any day, any day, because our guys get up for every match. And now we got a lot to work on. Right. A lot to work on. But you know what? I could say all that and I'll take our guy and blah, blah, blah. But what are they going to do tonight in their meal? How are they going to grow? What are they going to do tonight in their rest? What are they going to do tomorrow in their recovery on their own necessarily? What are they going to do Monday? Great wrestlers can use their imagination with a win that they're not satisfied with and go forward as if it was a loss. But it's still easier to go forward with that win. But they don't just, oh, I won, I'm fine, goes on. But then when they lose the exact same way that they could have lost before, then they go off the deep end. And then that's when they're going to make the change in their life. And we talked about that to our team tonight. And the mature, rare ingredient is guys that can get better even with success like it was a loss without beating themselves up. That's complicated. It is. It's a balance. You often talk about Iowa's focus on creating individual champions like Spencer Lee. Can you explain the philosophy of focusing on individuals versus the team? I think that we need to put them both together and the individual impacts the team. And, you know, we haven't done that since 2010 and we need to do a better job of putting 10 weight classes out there that contribute to the team. And if it's not 10, then it's nine. And if it's not nine, it can't be four, you know, and that takes a lot of pride. And it takes a lot of, you know, where the coach is on top of it. And, you know, you're not just working on the easy things, the glaring things, you're working on everything. What do you mean by everything? So the... Like there's just some, you know, there's ideas that when you're a coach that aren't, they're beneath the surface and you got to find them. And that's where communication comes in. Yeah. But you're talking about, yeah, we got to move forward. Well, what does that mean? Well, I know what that means, but how many guys really know what that means in their program? You know, there's so many levels of that. You've said before that winning is everything. And that means people lose. Most people lose. You know, there's really in whatever the context is only one winner. In many parts of our world today, outside of wrestling, that concept, the brutal honesty of that is uncomfortable for people. So how do you think about this very philosophical, difficult concept of, you know, there only being one winner, that winning is everything? It's kind of a really painful idea. I don't think that that's a bad thing to have that mentality. I mean, I think at Kutukov, I remember a story I read about him. He comes to mind. You know, Sargouj, I remember when he lost in London and I remember the look on his face. And those are some of the greatest wrestlers in the history of the sport, freestyle wrestling. And you know what? It's what works for you. And you can talk about being at peace with your results and that the approach is, and the journey is what it's about. But, and that's great. And that relaxes some champions and that makes some champions really, really tick. But not everybody. So it's okay. It's okay. And if that wigs you out and that really makes you uptight, then go the other route. You have to find what works for you. And that takes a lot of work. If you're lazy, forget it. Forget it. So you and Terry, but in general, how do you find the line between extremely physical, extreme physical wrestling and rough wrestling or angry wrestling? So to which degree has anger, whether it's in your wrestling room these days or in your own career, entered wrestling? Do you see it as a tool that can be used in the wrestling match? I think there's a balance and, or not even a balance. There's a line that you go up to and you can't cross it. Sportsmanship is everything. You can get dinged for points. You can get thrown out of tournaments. There's rules with flagrant misconduct where you're kicked out of the match. Other team gets the points and then you have to sit the next meet. So it's very serious. The NCAA sends a message, a very serious message about sportsmanship. And so we talk about that. And the other thing with wrestling is there's rules in wrestling. These guys that are tough guys outside of the rules, that's what you want in your opponent. That means they're frustrated. You got to be a tough guy inside the rules of the sport. That's more honorable than cold cocking somebody and knocking them out. So yeah, anger doesn't mean breaking the rules, but I mean, you know, a lot of people know you just watching you as a coach. There's quite a bit of passion there. Well, come and do what you're doing tonight. I mean, break bread with me in my kitchen and see how big of a jackass I am. No, you're a pretty nice guy. Well, I'm not asking for that necessarily, but thanks. I'm saying, you know what, as a coach, as a coach, I mean, okay, come spend a month in our program and you'll see really what kind of people we are. And there's a stigma out there because they are very threatened by our program. There's nobody else that threatens the sport of wrestling like we do. And that's the truth. There's a legend to Iowa wrestling. It's one of the most intimidating. There's a legend to John Smith. It's the same thing. But it has- They get up for John Smith. They get up for Oklahoma State. They get up for Penn State. My question is, I'll answer it this way. I'll give you an example. In my coaching career, I coached at Virginia Tech for 22 months. We recruited the number one recruiting class. We got the administration to change 100% 180 how they looked at wrestling. Here's the thing. And because of how serious we were and because we weren't idiots, we were able to do that with our administration. But my point is this, we tried to win. We tried to win. Even at Virginia Tech, it wasn't a stepping stone for me. It ended up being one quickly. And looking back on it, I was a fool to think that I'd be there for 20 years. That's what I thought. But you believed you would be. I did. I did. I did. So do you remember a time that you really pushed yourself to your limits? So Gable talks about having to be carried off the mat. Have you really found that level? I said something about that too in a book. And I think I was misquoted one time. And actually it was Gable's quote. And I was trying to make the point that Gable's quote was like this. And they were making it like it was my own words. I think it was a first wrestling tough book. But- It's a good book. It's a good book. But the story is Gable's. And I don't know if there's anybody that has done that besides him. And I think that's a very rare quality. But I've definitely been in that nirvana level of, you know, you could go all day long. And you have to shoot me to stop me. Yeah. But there's a balance because you're not going hard with and holding your breath. It's not a, it's a relaxed. And like you got a guy cornered and who's most dangerous? Well, the guy that's cornered. And so that's where you relax. I'm not bum rushing him. I'm relaxed. I'm still moving, faking very fluid. Guy falls down on his face. I run around behind him. That's offense. You don't have to just grunt to the leg and call that offense. Offense is a in and out, smooth. Now you're starting to sound like a Russian wrestler. Yeah. Well, that's, they're the best. In a certain light, looking at the history of wrestling, wrestling is much bigger than folk style, freestyle, Greco. It's one of the oldest forms of combat period. There's been cave drawings 15,000 years ago. Do you ever see, so you're one of the great coaches of all time. You're now focused on a particular rule style right now, but do you ever see wrestling as bigger than all of this, as one of the pure combats? I do. And we're raising $20 million for a facility to make it the best facility on the planet. We have a vision to build the best facility on planet earth and put the best wrestlers in it. And that is bigger than wrestling. It's for the university of Iowa and our donors are doing it for the university of Iowa, but it is about the value of wrestling to me also. There is so much value to wrestling. Blind people don't play football. They wrestle. Blind people don't play basketball. I mean, maybe they do, but it'd be very difficult. They can wrestle. Wrestling is a feel sport. Yeah, there's no ball. There's nothing. It's just two guys or two girls and that's it. That's right. I mean, I'm not going to say you can't because somebody will get a hold of this and I'll get an email or a letter that says, you said blind people can't play baseball and blah, blah. I'm just saying that blind people can wrestle very effectively. Yes. I've wrestled with my eyes shut. I mean, was honest about it too. And I was effective. So- Why was I able to be effective? Because wrestling is a sport that you can overcome a lot. Your demons that you're overcoming, they're not limited with whether I'm blind or not. The demons that are overcoming are inside you. You have to overcome those demons from within. So what's the future of Iowa wrestling look like with this facility and this momentum you have now and this great group of guys you have now? We have a good young group of guys and there is a lot of buzz in the program and probably hasn't been this much buzz for quite some time. And our job is to be relaxed and be focused and not get caught up in the buzz, but we have to put it together. And we have a catalyst, Spencer Lee, but he's going to have to get better. And we have some other catalysts as well that are going to help us in the future, but they got to get better. And so all this stuff about independence and accountability and being able to get better every day under duress and not knowing that you're getting better, but you are, you know what I mean by that? Yeah. Like the great thing about Gable was, wrestling for him was, is you were getting better and you didn't know you were getting better. Well, yeah, just like you said, grow from success. So you never allow yourself to think that you're getting good. All of a sudden you do something in the practice room that you've been working on and all of a sudden you hit it and it's like, it was automatic. And then that, you know, that multiplies success. And so if I may say so, you're a bit of a man of the Bible. What's, where do you go? What do you go to the Bible for your faith, strength, love, patience? Same things I talked about, things that you can't control, you turn them over. So the biggest thing for me is I got to turn over the things that I can't control, turn them over to that power and I'm going to be a lot better off. And that's the reason why I'm not in the funny form. Cause very competitive to me. It's very serious that we, we know that these young wrestlers come to school here to be the best that they can be and to accomplish goals that like me, when I was young, they've set out to accomplish and they chose Iowa to do that. And so we have to deliver. And because of that peace with God, you know, it's pure, it's a pure motivation. It's a pure platform. It's not, it's not doing this for my ego. We're not corrupt people. We're not liars and cheaters. And so often that gets in the way of a decent person. Yeah. First and foremost, you're a good person and God helps you be that. Yeah. And we're serious about wrestling. So a couple more questions. What's the role of family in wrestling? You mentioned your wife, who I read, turned you down when you asked her for a phone number, said it's in the phone book. That's pretty smooth. Her story of that is that she didn't want me to have to remember the number. And I say at this point, and I say, there's no way. And I remember it very clearly. Like, Hey, it's in the phone book. And I was like, okay, she's blowing me off. That's okay. But luckily, Anyway, here's the thing with family. I mean, we have great people in our program. We have great parents. We have a culture of parents that that's part of the buzz. And this class that you see wrestling right now, that's been here a year now, Lee, Miren, Costello, Warner, and then Lugo was a transfer. And I'm forgetting somebody. I don't want to forget anybody, but these parents are phenomenal. And that's a different parental culture. So the camera's dad is the same. And there's a lot of good there. And that's a big move because how we talk to parents, we don't talk to parents to get along with them. We talk to parents to help them understand where we're at with their sons. And when you can have a direct conversation with a parent who helping his son or her son, the mom helping her son to be accountable and to own it, then you can get a lot accomplished. And that's what we've been able to do. And so you're solving problems like I talked about earlier. That's part of the family. The other part of the family is the coaches are like family. The other part of the family is the coaches of significant others and wives are part of the family. And we fed, you know, we fed 40 guys and an entire coaching staff and wives and their children here at Thanksgiving. And that equals 70 people. And it's fun. It's fun. So a family means administration. Gary Barta, my athletic director, gives us everything that we need to be successful. And he has an open mind for the sport of wrestling and wrestling is important in Iowa. So that's a no brainer, but not if you're not a wrestling guy, but he sees we do it the right way. And so the commitment is there from him. If we were doofuses, you know, he, the commitment wouldn't be there. So family is everybody's all in. I mean, it's from the wrestlers to the family. It goes back to what I said earlier about our people. Our people are great. Ryan Morton Star is great. Bobby Telford is great. Bobby Telford took over for a guy named Ben Burrhow, who is great. Our medical team is great. Dr. Westerman, Dr. Wolf, Jesse Donenworth, our athletic trainer is great. Terry Brands is great. Mariah Stickley and Elise Owens, our managers, are great. My daughter's a manager as well. It's great. They're hardworking young women. Our Hawkeye Wrestling Club is where it needs to be in terms of how they help in their role. And now we have four women in there. And that's great. And, you know, at least one of their dads is super involved with us. But, and so it's one thing that I've learned is that you have to have that. And if you don't have that, then you have to address it quickly. And those outliers, you know, let's solve that problem. Let's get it out in the open here. And if they're, you know, if it doesn't work out, it's not going to work out. That's a heck of a Thanksgiving dinner. Yeah. Next year. Well, I don't know if it'd be legal, but I'd have to check with our compliance and, you know, they'd have to vet you. You could come. You can come and see what it's all about. This room is full. Oh, man. Well, yeah, I'll be back next year then. All right. Awesome. Last question. In 2014, I watched this video four years ago of you competing in, I believe, your first swim meet against your brother, Terry, and you came out victorious. Not really. Okay. So let's, I won the race. Did you cheat? Here's what happened. I had researched this thing because I'm, that's how I am. You practiced. No, I didn't. But I researched it in swimming. If you flinch on that starter block, it's a false start. You can't twitch a finger. And because they would be doing that to get their buddy to move or the guy next to him, you know, so you have to be rock solid. Well, when we went, Terry was leaning forward as the gun was going off. So he's moving. And so I was like, no, no, no, false start. No, no, no, no. And he couldn't hear me. He was already in the water. And so he took off like a bat out of, you know, where for the end of the pool and couldn't hear me and got to the end of the pool. And it was a down and back. Well, that's a hard thing to do with a guy with no body fat. And so he burned a lot of energy and he come up on that end of the pool. And he was like, where's, where's the X? He didn't see me. And so we stopped him and then he came back and then we went another one and I beat him. But it's the only time that, you know, I would say that he was tuckered out. And that's the reason why. And I also say this, we did a time where we timed my race, the one I won, and then we timed his first down to the wall. And then we timed his, the actual race where once he hit the wall, we timed him on the way back and he'd beat me. Now, how's that for being a that's pretty honest, accountable person. And I'm going to tell you something else getting in those shorts, those swim trunks as impressive. They are tight. Yeah. So is there outside of wrestling? Is there a thing that Terry got the better of you? I mean, I guess this could count as one that you're still really bitter about that you need to avenge. I mean, that's passed. I mean, we, he's got an UNO title. We have UNO world championships. He's got an UNO title. I have, I have yet to have one Morningstar has two titles. That's unprecedented. So there's only four trophies out there and Terry's got one of those. I don't have one yet. Yeah. Well, it's still time, Tom, thank you so much for letting a Russian with a tie into your home. Thanks for listening to this conversation with Tom brands to support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Marcus Aurelius. The art of living is more like wrestling than dancing. Thank you for listening and hope to see you next time.

https://youtu.be/Ww6pfsWmkdY

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Chris Urmson: Self-Driving Cars at Aurora, Google, CMU, and DARPA | Lex Fridman Podcast #28

The following is a conversation with Chris Urmson. He was the CTO of the Google self-driving car team, a key engineer and leader behind the Carnegie Mellon University autonomous vehicle entries in the DARPA Grand Challenges and the winner of the DARPA Urban Challenge. Today he's the CEO of Aurora Innovation, an autonomous vehicle software company he started with Sterling Anderson, who was the former director of Tesla Autopilot, and Drew Bagnell, Uber's former autonomy and perception lead. Chris is one of the top roboticists and autonomous vehicle experts in the world and a longtime voice of reason in a space that is shrouded in both mystery and hype. He both acknowledges the incredible challenges involved in solving the problem of autonomous driving and is working hard to solve it. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. And now here's my conversation with Chris Urmson. You were part of both the DARPA Grand Challenge and the DARPA Urban Challenge teams at CMU with Red Whittaker. What technical or philosophical things have you learned from these races? I think the high order bit was that it could be done. I think that was the thing that was incredible about the first, the grand challenges that I remember, I was a grad student at Carnegie Mellon and there we, it was kind of this dichotomy of, it seemed really hard, so that would be cool and interesting. But at the time we were the only robotics institute around, and so if we went into it and fell on our faces, that would be embarrassing. So I think just having the will to go do it, to try to do this thing that at the time was marked as darn near impossible, and then after a couple of tries, be able to actually make it happen, I think that was really exciting. But at which point did you believe it was possible? Did you, from the very beginning, did you personally, because you're one of the lead engineers, you actually had to do a lot of the work? Yeah, I was the technical director there and did a lot of the work along with a bunch of other really good people. Did I believe it could be done? Yeah, of course, right? Like, why would you go do something you thought was impossible, completely impossible? We thought it was going to be hard, we didn't know how we're going to be able to do it, we didn't know if we'd be able to do it the first time. Turns out we couldn't. That, yeah, I guess you have to. I think there's a certain benefit to naivete, right? That if you don't know how hard something really is, you try different things and it gives you an opportunity that others who are wiser maybe don't have. What were the biggest pain points? Mechanical, sensors, hardware, software, algorithms for mapping, localization, just general perception control, but the hardware, software, first of all. I think that's the joy of this field, is that it's all hard and that you have to be good at each part of it. So for the first, for the urban challenges, if I look back at it from today, it should be easy today. It should be easy today. That it was a static world, there weren't other actors moving through it, is what that means. It was out in the desert, so you get really good GPS. So that went, and we could map it roughly. And so in retrospect now, it's within the realm of things we could do back then. Just actually getting the vehicle, and there's a bunch of engineering work to get the vehicle so that we could control it and drive it. That's still a pain today, but it was even more so back then. And then the uncertainty of exactly what they wanted us to do was part of the challenge as well. Right, you didn't actually know the track heading in. You knew approximately, but you didn't actually know the route, the route that's going to be taken. That's right. We didn't know the route. We didn't even really, the way the rules had been described, you had to guess. So if you think back to that challenge, the idea was that the government would give us, DARPA would give us a set of waypoints and the width that you had to stay within between the line that went between each of those waypoints. And so the most devious thing they could have done is set a kilometer-wide corridor across a field of scrub brush and rocks and said, go figure it out. Fortunately, it really, it turned into basically driving along a set of trails, which is much more relevant to the application they were looking for. But no, it was a hell of a thing back in the day. So the legend, Red, was kind of leading that effort in terms of just broadly speaking. So you're a leader now. What have you learned from Red about leadership? I think there's a couple of things. One is, you know, go and try those really hard things. That's where there is an incredible opportunity. I think the other big one though is to see people for who they can be, not who they are. It's one of the things that I actually, one of the deepest lessons I learned from Red was that he would look at undergraduates or graduate students and empower them to be leaders, to have responsibility, to do great things that I think another person might look at them and think, oh, well, that's just an undergraduate student. What could they know? And so I think that kind of trust, but verify, have confidence in what people can become, I think is a really powerful thing. So through that, let's just like fast forward through the history. Can you maybe talk through the technical evolution of autonomous vehicle systems from the first two grand challenges to the urban challenge to today? Are there major shifts in your mind or is it the same kind of technology just made more robust? I think there's been some big, big steps. So the, for the grand challenge, the real technology that unlocked that was HD mapping. Prior to that, a lot of the off-road robotics work had been done without any real prior model of what the vehicle was going to encounter. And so that innovation, that the fact that we could get decimeter resolution models was really a big deal. And that allowed us to kind of bound the complexity of the driving problem the vehicle had and allowed it to operate at speed because we could assume things about the environment that it was going to encounter. And so that was a big step. So that was the big step there. For the urban challenge, one of the big technological innovations there was the multi-beam LiDAR and be able to generate high resolution, mid to long range 3D models of the world and use that for understanding the world around the vehicle. And that was really a kind of a game changing technology. In parallel with that, we saw a bunch of other technologies that had been kind of converging half their day in the sun. So Bayesian estimation had been, SLAM had been a big field in robotics. You would go to a conference a couple of years before that and then every paper would effectively have SLAM somewhere in it. And so seeing that those Bayesian estimation techniques play out on a very visible stage, I thought that was pretty exciting to see. And mostly SLAM was done based on LiDAR at that time. Well, yeah. And in fact, we weren't really doing SLAM per se in real time because we had a model ahead of time, we had a roadmap, but we were doing localization and we're using the LiDAR or the cameras depending on who exactly was doing it to localize to a model of the world. And I thought that was a big step from kind of naively trusting GPS, INS before that. And again, lots of work had been going on in this field. Certainly this was not doing anything particularly innovative in SLAM or in localization, but it was seeing that technology necessary in a real application on a big stage, I thought was very cool. So for the urban challenge, there was already maps constructed offline? Yes. In general. Okay. And did people do that, did individual teams do it individually? So they had their own different approaches there or did everybody kind of share that information at least intuitively? So DARPA gave all the teams a model of the world, a map. And then one of the things that we had to figure out back then was, and it's still one of these things that trips people up today, is actually the coordinate system. So you get a latitude, longitude, and to so many decimal places, you don't really care about kind of the ellipsoid of the earth that's being used. But when you want to get to 10 centimeter or centimeter resolution, you care whether the coordinate system is NADS 83 or WGS 84, or these are different ways to describe both the kind of non-sphericalness of the earth, but also kind of the, I think, I can't remember which one, the tectonic shifts that are happening and how to transform the global datum as a function of that. So getting a map and then actually matching it to reality to centimeter resolution, that was kind of interesting and fun back then. So how much work was the perception doing there? So how much were you relying on localization based on maps without using perception to register to the maps? And I guess the question is how advanced was perception at that point? It's certainly behind where we are today. We're more than a decade since the grant or the urban challenge, but the core of it was there. That we were tracking vehicles, we had to do that at 100 plus meter range because we had to merge with other traffic. We were using again Bayesian estimates for state of these vehicles. We had to deal with a bunch of the problems that you think of today of predicting where that vehicle is going to be a few seconds into the future. We had to deal with the fact that there were multiple hypotheses for that because a vehicle at an intersection might be going right or it might be going straight or it might be making a left turn. And we had to deal with the challenge of the fact that our behavior was going to impact the behavior of that other operator. And we did a lot of that in relatively naive ways, but it kind of worked. Still had to have some kind of solution. And so where does that 10 years later, where does that take us today from that artificial city construction to real cities to the urban environment? Yeah, I think the biggest thing is that the actors are truly unpredictable. That most of the time, the drivers on the road, the other road users are out there behaving well, but every once in a while they're not. The variety of other vehicles is, you have all of them. In terms of behavior, in terms of perception or both? Both. That we have, back then we didn't have to deal with cyclists, we didn't have to deal with pedestrians, didn't have to deal with traffic lights. The scale over which that you have to operate is now, is much larger than the air base that we were thinking about back then. So what, easy question, what do you think is the hardest part about driving? Easy question. Yeah. No, I'm joking. I'm sure nothing really jumps out at you as one thing, but in the jump from the urban challenge to the real world, is there something that's a particular, you foresee as very serious, difficult challenge? I think the most fundamental difference is that we're doing it for real. That in that environment, it was both a limited complexity environment because certain actors weren't there, because the roads were maintained, there were barriers keeping people separate from robots at the time, and it only had to work for 60 miles. Which, looking at it from 2006, it had to work for 60 miles. Looking at it from now, we want things that will go and drive for half a million miles. And it's just a different game. Okay. So how important, you said LiDAR came into the game early on, and it's really the primary driver of autonomous vehicles today as a sensor. So how important is the role of LiDAR in the sensor suite in the near term? So I think it's essential. But I also believe the cameras are essential, and I believe the radar is essential. I think that you really need to use the composition of data from these different sensors if you want the thing to really be robust. The question I want to ask, let's see if we can untangle it, is what are your thoughts on the Elon Musk provocative statement that LiDAR is a crutch? That is a kind of, I guess, growing pains, and that much of the perception task can be done with cameras. So I think it is undeniable that people walk around without lasers in their foreheads, and they can get into vehicles and drive them. And so there's an existence proof that you can drive using passive vision. No doubt, can't argue with that. In terms of sensors. Yeah. Yeah, in terms of sensors, right? So there's an example that we all go do it, many of us, and many of us every day. In terms of LiDAR being a crutch, sure. But in the same way that the combustion engine was a crutch on the path to an electric vehicle, in the same way that any technology ultimately gets replaced by some superior technology in the future. And really, the way that I look at this is that the way we get around on the ground, the way that we use transportation is broken. And that we have this, what was, I think the number I saw this morning, 37,000 Americans killed last year on our roads. And that's just not acceptable. And so any technology that we can bring to bear that accelerates this self-driving technology coming to market and saving lives is technology we should be using. And it feels just arbitrary to say, well, I'm not okay with using lasers because that's whatever, but I am okay with using an eight megapixel camera or a 16 megapixel camera. These are just bits of technology and we should be taking the best technology from the tool bin that allows us to go and solve a problem. The question I often talk to, well, obviously you do as well to the sort of automotive companies. And if there's one word that comes up more often than anything, it's cost and trying to drive cost down. So while it's true that it's a tragic number, the 37,000, the question is what, and I'm not the one asking this question because I hate this question, but we want to find the cheapest sensor suite that creates a safe vehicle. So in that uncomfortable trade-off, do you foresee LIDAR coming down in cost in the future, or do you see a day where level four autonomy is possible without LIDAR? I see both of those, but it's really a matter of time. And I think really, maybe I would talk to the question you asked about the cheapest sensor. I don't think that's actually what you want. What you want is a sensor suite that is economically viable. And then after that, everything is about margin and driving cost out of the system. What you also want is a sensor suite that works. And so it's great to tell a story about how it would be better to have a self-driving system with a $50 sensor instead of a $500 sensor. But if the $500 sensor makes it work and the $50 sensor doesn't work, who cares? As long as you can actually have an economic, there's an economic opportunity there. And the economic opportunity is important because that's how you actually have a sustainable business. And that's how you can actually see this come to scale and be out in the world. And so when I look at LIDAR, I see a technology that has no underlying fundamentally expense to it, fundamental expense to it. It's going to be more expensive than an imager because CMOS processes or FAB processes are dramatically more scalable than mechanical processes, but we still should be able to drive cost down substantially on that side. And then I also do think that with the right business model, you can absorb certainly more cost on the bill of materials. Yeah. If the sensor suite works, extra value is provided, thereby you don't need to drive cost down to zero. It's the basic economics. You've talked about your intuition that level two autonomy is problematic because of the human factor of vigilance, decrement, complacency, overtrust, and so on, just us being human. We overtrust the system, we start doing even more so partaking in the secondary activities like smartphones and so on. Have your views evolved on this point in either direction? Can you speak to it? So, and I want to be really careful because sometimes this gets twisted in a way that I certainly didn't intend. So, active safety systems are a really important technology that we should be pursuing and integrating into vehicles. And there's an opportunity in the near term to reduce accidents, reduce fatalities, and that's, and we should be pushing on that. Level two systems are systems where the vehicle is controlling two axes. So, braking and throttle slash steering. And I think there are variants of level two systems that are supporting the driver that absolutely we should encourage to be out there. Where I think there's a real challenge is in the human factors part around this and the misconception from the public around the capability set that that enables and the trust they should have in it. And that is where I kind of, I am actually incrementally more concerned around level three systems and how exactly a level two system is marketed and delivered. And how much effort people have put into those human factors. So, I still believe several things around this. One is people will overtrust the technology. We've seen over the last few weeks, a spate of people sleeping in their Tesla. I watched an episode last night of Trevor Noah talking about this and him, this is a smart guy who has a lot of resources at his disposal describing a Tesla as a self-driving car. And that why shouldn't people be sleeping in their Tesla? It's like, well, because it's not a self-driving car and it is not intended to be. And these people will almost certainly die at some point or hurt other people. And so, we need to really be thoughtful about how that technology is described and brought to market. I also think that because of the economic challenges we were just talking about, that technology path will, these level two driver assistance systems, that technology path will diverge from the technology path that we need to be on to actually deliver truly self-driving vehicles. Ones where you can get in and sleep and have the equivalent or better safety than a human driver behind the wheel. Because again, the economics are very different in those two worlds. And so, that leads to divergent technology. So, you just don't see the economics of gradually increasing from level two and doing so quickly enough to where it doesn't cause safety, critical safety concerns. You believe that it needs to diverge at this point into different, basically different routes. And really that comes back to what are those L2 and L1 systems doing? And they are driver assistance functions where the people that are marketing that responsibly are being very clear and putting human factors in place such that the driver is actually responsible for the vehicle. And that the technology is there to support the driver. And the safety cases that are built around those are dependent on that driver attention and attentiveness. And at that point, you can give up to some degree for economic reasons, you can give up on say false negatives. And the way to think about this is for a for collision mitigation braking system, if it half the times the driver missed a vehicle in front of it, it hit the brakes and brought the vehicle to a stop, that would be an incredible, incredible advance in safety on our roads. That would be equivalent to seat belts. But it would mean that if that vehicle wasn't being monitored, it would hit one out of two cars. And so economically, that's a perfectly good solution for a driver assistance system. What you should do at that point, if you can get it to work 50% of the time, is drive the cost out of that so you can get it on as many vehicles as possible. But driving the cost out of it doesn't drive up performance on the false negative case. And so you'll continue to not have a technology that could really be available for a self-driven vehicle. So clearly the communication and this probably applies to all four vehicles as well. The marketing and the communication of what the technology is actually capable of, how hard it is, how easy it is, all that kind of stuff is highly problematic. So say everybody in the world was perfectly communicated and were made to be completely aware of every single technology out there, what it's able to do. What's your intuition? And now we're maybe getting into philosophical ground. Is it possible to have a level two vehicle where we don't overtrust it? I don't think so. If people truly understood the risks and internalized it, then sure, you could do that safely. But that's a world that doesn't exist. That people are going to, if the facts are put in front of them, they're going to then combine that with their experience. And let's say they're using an L2 system and they go up and down the 101 every day and they do that for a month. And it just worked every day for a month. That's pretty compelling at that point. Just even if you know the statistics, you're like, well, I don't know, maybe there's something funny about those. Maybe they're driving in difficult places. Like I've seen it with my own eyes, it works. And the problem is that that sample size that they have, so it's 30 miles up and down. So 60 miles times 30 days, so 60, 180, 1,800 miles. That's a drop in the bucket compared to the 85 million miles between fatalities. And so they don't really have a true estimate based on their personal experience of the real risks, but they're going to trust it anyway, because it's hard not to. It worked for a month. What's going to change? So even if you start a perfect understanding of the system, your own experience will make it drift. I mean, that's a big concern. Over a year, over two years, even. It doesn't have to be months. And I think that as this technology moves from what I would say is kind of the more technology savvy ownership group to the mass market, you may be able to have some of those folks who are really familiar with technology, they may be able to internalize it better. And your kind of immunization against this kind of false risk assessment might last longer. But as folks who aren't as savvy about that read the material and they compare that to their personal experience, I think there that it's going to move more quickly. So your work, the program that you've created at Google and now at Aurora is focused more on the second path of creating full autonomy. So it's such a fascinating, I think it's one of the most interesting AI problems of the century, right? I just talked to a lot of people, just regular people. I don't know my mom about autonomous vehicles. And you begin to grapple with ideas of giving your life control over to a machine is philosophically interesting. It's practically interesting. So let's talk about safety. How do you think we demonstrate, you've spoken about metrics in the past. How do you think we demonstrate to the world that an autonomous vehicle and an Aurora system is safe? This is one where it's difficult because there isn't a soundbite answer that we have to show a combination of work that was done diligently and thoughtfully. And this is where something like a functional safety process is part of that is like, here's the way we did the work. That means that we were very thorough. So if you believe that what we said about this is the way we did it, then you can have some confidence that we were thorough in the engineering work we put into the system. And then on top of that, to demonstrate that we weren't just thorough, we were actually good at what we did. There'll be a collection of evidence in terms of demonstrating that the capabilities work the way we thought they did statistically and to whatever degree we can demonstrate that both in some combination of simulation, some combination of unit testing and decomposition testing, and then some part of it will be on-road data. And I think the way we'll ultimately convey this to the public is there'll be clearly some conversation with the public about it, but we'll invoke the trusted nodes and that we'll spend more time being able to go into more depth with folks like NHTSA and other federal and state regulatory bodies. And given that they are operating in the public interest and they're trusted, that if we can show enough work to them that they're convinced, then I think we're in a pretty good place. That means you work with people that are essentially experts at safety to try to discuss and show. Do you think the answer is probably no, but just in case, do you think there exists a metric? So currently people have been using number of disengagements and it quickly turns into a marketing scheme to sort of you alter the experiments you run to adjust. I think you've spoken that you don't like... Don't love it. No, in fact, I was on the record telling DMV that I thought this was not a great metric. Do you think it's possible to create a metric, a number that could demonstrate safety outside of fatalities? So, so I do. And I think that it won't be just one number. So as we are internally grappling with this, and at some point we'll be, we'll be able to talk more publicly about it, is how do we think about human performance in different tasks, say detecting traffic lights or safely making a left turn across traffic? And what do we think the failure rates are for those different capabilities for people? And then demonstrating to ourselves and then ultimately folks in regulatory role and then ultimately the public that we have confidence that our system will work better than that. And so these, these individual metrics will kind of tell a compelling story. Ultimately, I do think at the end of the day, what we care about in terms of safety is a life saved and injuries reduced. And then, and then ultimately, you know, kind of casualty dollars that people aren't having to pay to get their car fixed. And I do think that you can, you know, in aviation, they look at a kind of an event pyramid where, you know, a crash is at the top of that and that's the worst event obviously. And then there's injuries and, you know, near miss events and whatnot and, and, you know, violation of operating procedures. And you kind of build a statistical model of, of the relevance of the low severity things to the high severity things. And I think that's something where we'll be able to look at as well because, you know, an event per 85 million miles is a, you know, statistically a difficult thing, even at the scale of the U.S. To, to, to kind of compare directly. And that event, the fatality that's connected to an autonomous vehicle is significantly, at least currently magnified in the amount of attention it gets. So that speaks to public perception. I think the most popular topic about autonomous vehicles in the public is the trolley problem formulation, right? Which has let's not get into that too much, but is misguided in many ways, but it speaks to the fact that people are grappling with this idea of giving control over to a machine. So how do you win the, the hearts and minds of the people that autonomy is something that could be a part of their lives? I think you let them experience it, right? I think it's, I think, I think it's right. I think people should be skeptical. I think people should ask questions. I think they should doubt because this is something new and different. They haven't touched it yet. And I think it's perfectly reasonable. And, but at the same time, it's clear there's an opportunity to make the road safer. It's clear that we can improve access to mobility. It's clear that we can reduce the cost of mobility and that once people try that and are, you know, understand that it's safe and are able to use in their daily lives, I think it's one of these things that will, will just be obvious. And I've seen this practically in, you know, in demonstrations that I've given where I've had people come in and, you know, they're very skeptical and they, they get in a vehicle, you know, my favorite one is taking somebody out on the freeway and we're on the one-on-one driving at 65 miles an hour. And after 10 minutes, they, they kind of turn and ask, is that all it does? And you're like, it's a self-driving car. I'm not sure exactly what you thought it would do. Right. But they, you know, they, it becomes mundane, which is, which is exactly what you want a technology like this to be. Right. We don't want to be a technology that's just, you know, a little bit of a pain, which is, which is exactly what you want a technology like this to be. Right. We don't really, when I turn the light switch on in here, I don't think about the complexity of, you know, the, those electrons, you know, being pushed down a wire from wherever it was and being generated. Like, it's just, it's like, I just get annoyed if it doesn't work. Right. And, and what I value is the fact that I can do other things in this space. I can, you know, see my colleagues, or I can not be afraid of the dark. And I think that's what we want this technology to be like, is it's in the background and people get to have those life experiences and do so safely. So, putting this technology in the hands of people speaks to scale of deployment. So what do you think, the dreaded question about the future, because nobody can predict the future, but just maybe speak poetically about when do you think we'll see a large scale deployment of autonomous vehicles, 10,000, those kinds of numbers. We'll see that within 10 years. I'm pretty confident. What's an impressive scale? What moment, so you've done DARPA Challenger, there's one vehicle. At which moment does it become, wow, this is serious scale. So I think the moment it gets serious is when we really do have a driverless vehicle operating on public roads, and that we can do that kind of continuously. Without a safety driver. Without a safety driver in the vehicle. I think at that moment, we've kind of crossed the zero to one threshold. And then it is about how do we continue to scale that? How do we build the right business models? How do we build the right customer experience around it so that it is actually a useful product out in the world? And I think that is really, at that point it moves from a, what is this kind of mixed science engineering project into engineering and commercialization, and really starting to deliver on the value that we all see here, and actually making that real in the world. What do you think that deployment looks like? Where do we first see the inkling of no safety driver, one or two cars here and there? Is it on the highway? Is it in specific routes in the urban environment? I think it's gonna be urban, suburban type environments. Yeah, with Aurora, when we thought about how to tackle this, it was kind of en vogue to think about trucking, as opposed to urban driving. And again, the human intuition around this is that freeways are easier to drive on, because everybody's kind of going in the same direction, and the lanes are a little wider, et cetera. And I think that that intuition is pretty good, except we don't really care about most of the time, we care about all of the time. And when you're driving on a freeway with a truck, say at 70 miles an hour, and you got 70,000 pound load with you, that's just an incredible amount of kinetic energy. And so when that goes wrong, it goes really wrong. And that those challenges that you see occur more rarely, so you don't get to learn as quickly. And they're incrementally more difficult than urban driving, but they're not easier than urban driving. And so I think this happens in moderate speed, urban environments, because there's a lot of traffic, urban environments, because there, if two vehicles crash at 25 miles per hour, it's not good, but probably everybody walks away. And those events where there's the possibility for that occurring happen frequently. So we get to learn more rapidly, we get to do that with lower risk for everyone. And then we can deliver value to people that need to get from one place to another. And then once we've got that solved, then the kind of the freeway driving part of this just falls out. But we were able to learn more safely, more quickly in the urban environment. So 10 years and then scale 20, 30 years. I mean, who knows if a sufficiently compelling experience is created, it could be faster and slower. Do you think there could be breakthroughs and what kind of breakthroughs might there be that completely changed that timeline? Again, not only am I asking you to predict the future, I'm asking you to predict breakthroughs that haven't happened yet. So I think another way to ask that would be if I could wave a magic wand, what part of the system would I make work today to accelerate it as quickly as possible? Don't say infrastructure, please don't say infrastructure. No, it's definitely not infrastructure. It's really that perception forecasting capability. So if tomorrow you could give me a perfect model of what is happening and what will happen for the next five seconds around a vehicle on the roadway, that would accelerate things pretty dramatically. Are you, in terms of staying up at night, are you mostly bothered by cars, pedestrians, or cyclists? So I worry most about the vulnerable road users about the combination of cyclists and cars, right? Just because, or cyclists and pedestrians, because they're not in armor. The cars, they're bigger, they've got protection for the people. And so the ultimate risk is lower there. Whereas a pedestrian or cyclist, they're out on the road and they don't have any protection. And so we need to pay extra attention to that. Do you think about a very difficult technical challenge of the fact that pedestrians, if you try to protect pedestrians by being careful and slow, they'll take advantage of that. So the game theoretic dance, does that worry you from a technical perspective, how we solve that? Because as humans, the way we solve that is kind of nudge our way through the pedestrians, which doesn't feel, from a technical perspective, as a appropriate algorithm. But do you think about how we solve that problem? Yeah, I think there's, I think that was actually, there's two different concepts there. So one is, am I worried that because these vehicles are self-driving, people will kind of step in the road and take advantage of them? And I've heard this and I don't really believe it because if I'm driving down the road and somebody steps in front of me, I'm going to stop. Right, like even if I'm annoyed, I'm not gonna just drive through a person stood in the road. Right. And so I think today people can take advantage of this and you do see some people do it. I guess there's an incremental risk because maybe they have lower confidence that I'm gonna see them than they might have for an automated vehicle. And so maybe that shifts it a little bit. But I think people don't wanna get hit by cars. And so I think that I'm not that worried about people walking out of the 101 and creating chaos more than they would today. Regarding kind of the nudging through a big stream of pedestrians leaving a concert or something, I think that is further down the technology pipeline. I think that you're right, that's tricky. I don't think it's necessarily, I think the algorithm people use for this is pretty simple. Right, it's kind of just move forward slowly and if somebody is really close, then stop. And I think that that probably can be replicated pretty easily. And particularly given that you don't do this at 30 miles an hour, you do it at one, that even in those situations, the risk is relatively minimal. But it's not something we're thinking about in any serious way. And probably that's less an algorithm problem and more creating a human experience. So the HCI people that create a visual display that you're pleasantly as a pedestrian nudged out of the way. Yes. That's an experience problem, not an algorithm problem. Who's the main competitor to Aurora today? And how do you out-compete them in the long run? So we really focus a lot on what we're doing here. I think that, I've said this a few times, that this is a huge difficult problem and it's great that a bunch of companies are tackling it because I think it's so important for society that somebody gets there. So we don't spend a whole lot of time thinking tactically about who's out there and how do we beat that person individually. What are we trying to do to go faster ultimately? Well, part of it is the leadership team we have has got pretty tremendous experience. And so we kind of understand the landscape and understand where the cul-de-sacs are to some degree. And we try and avoid those. I think there's a part of it, just this great team we've built. People, this is a technology and a company that people believe in the mission of. And so it allows us to attract just awesome people to go work. We've got a culture, I think, that people appreciate that allows them to focus, allows them to really spend time solving problems. And I think that keeps them energized. And then we've invested hard, invested heavily in the infrastructure and architectures that we think will ultimately accelerate us. So because of the folks we're able to bring in early on, because of the great investors we have, we don't spend all of our time doing demos and kind of leaping from one demo to the next. We've been given the freedom to invest in infrastructure to do machine learning, infrastructure to pull data from our on-road testing, infrastructure to use that to accelerate engineering. And I think that early investment and continuing investment in those kinds of tools will ultimately allow us to accelerate and do something pretty incredible. Chris, beautifully put, it's a good place to end. Thank you so much for talking today. Thank you very much. I really enjoyed it.

https://youtu.be/Tj6NOfdfa4o

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Sara Seager: Search for Planets and Life Outside Our Solar System | Lex Fridman Podcast #116

The following is a conversation with Sarah Seager, a planetary scientist at MIT known for her work on the search for exoplanets, which are planets outside of our solar system. She's an author of two books on this fascinating topic. Plus, in a couple days, August 18th, her new book, a memoir, called The Smallest Lights in the Universe, is coming out. I read it and I can recommend it highly, especially if you love space and are a bit of a romantic like me. It's beautifully written. She weaves the stories of the tragedies and the triumphs of her life with the stories of her love for and research on exoplanets, which represent our hope to find life out there in the universe. Quick summary of the ads. Three sponsors, Public Goods, that's a new one, PowerDot, and Cash App. Click the links in the description to get a discount. It really is the best way to support this podcast. As a quick side note, let me say that extraterrestrial life, aliens, I think represent our civilization longing to make contact with the unknown, with others like us, or maybe others that are very different from us, entities that might reveal something profound about why we're here. The possibility of this is both exciting and, at least to me, terrifying, which is exactly where we humans do our best work. If you enjoy this thing, subscribe on YouTube, review it with 5 stars on Apple Podcasts, support it on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now, and never any ads in the middle that could break the flow of the conversation. I try to make these ad reads interesting if you do listen, but if you like, I give you time stamps so you can skip to the conversation, but still, please do check out the sponsors by clicking the special links in the description. It's the best way to support this podcast. This show is sponsored by Public Goods, the one-stop shop for affordable, sustainable, healthy household products. Their products have a minimalist black and white design that I find to be just clean, elegant, and beautiful. It's a style that makes me feel like I'm living in the future. I imagine we'll all be using Public Goods products once we colonize Mars. They got all the basics you need from healthy snacks like almonds, to my favorite, the bamboo toothbrush, and other stuff for personal care, home essentials, healthy food, and vitamins and supplements. I take their fish oil, for example, which I recommend highly for everyone. They use a membership model to keep costs low and pass on the savings to us, the people. They plant one tree for every order placed and have planted over a hundred thousand trees since September 2019. Visit publicgoods.com slash Lex or use code Lex at checkout to get 15 bucks off your first order. This show is sponsored by PowerDot. Get it at powerdot.com slash Lex and use code Lex at checkout to get 20% off and to support this podcast. It's an e-stim, electrical stimulation device that I've been using a lot for muscle recovery, mostly for my shoulders and legs as I've been doing the crazy amounts of body weight reps and six miles every other day now after the challenge. Yes, I'm still doing it. They call it the smart muscle stimulator since the app that goes with it is amazing. It has 15 programs for different body parts and guides you through everything you need to do. I take recovery really seriously these days and PowerDot has been a powerful addition to stretching, ice, massage, and sleep and diet. It's used by professional athletes and by slightly insane but mostly normal people like me. It's portable, so you can throw it in a bag and bring it anywhere. Get it at powerdot.com slash Lex and use code Lex at checkout to get 20% off on top of the 30-day free trial and of course to support this podcast. This show is presented by a sponsor that arguably made this whole podcast even possible. Our first sponsor, the great, the powerful Cash App, the number one finance app in the app store. I will forever be grateful to them for sponsoring this podcast. They're awesome people, awesome company, awesome product. Okay, back to the read. When you get it, use code Lex podcast. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency in the context of the history of money is fascinating. I recommend The Scent of Money as a great book on this history. Debits and credits on ledgers started around 30,000 years ago. Time flies. The US dollar created over 200 years ago and the first decentralized cryptocurrency released just over 10 years ago. So given that history, cryptocurrency is still very much in its early days of development, but it's still aiming to and just might redefine the nature of money. So again, if you get Cash App from the app store, Google Play, and use code Lex podcast, you get $10 and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now here's my conversation with Sarah Seeger. When did you first fall in love with the stars? I think I've always loved the stars. One of my first memory is of the moon. I remember watching the moon and I was in the car with my dad who, my parents were divorced and he was driving me and my siblings to his house for the weekend. And the moon was just following me. Just had no idea why that was. Yeah. So like looking up at the sky and there's this glowing thing. How do you make sense of the moon at that age? At age, like age five, there's just no way you can. I think it's one of the great things about being a kid. It's just that curiosity that all kids have. You know, I was thinking because there's these almost out there ideas of that our earth is flat floating about on the internet. And it made me think, you know, when did I first realize that the earth is like this ball that's flying through empty space? I mean, it's terrifying. It's awe inspiring. I don't know how to make sense of it. It's hard because we live in our frame of reference here on this planet. Yeah. It's nearly impossible. None of us are lucky to go to see the curvature of earth. I mean, do you remember when you realized, understood like the physics, like the layout of the solar system? Was it like, did you first have to take physics to really, like high school physics to really take that in? I think it's hard to say. I had this book when I was a child. It was in French. I grew up in Canada where French is supposedly taught to all of us English speaking Canadians. And it was this book in French, but it was about the solar system. And I just love flipping through it. It's hard to say how much, you know, you or I understand when we're kids, but it was really great book. What about the stars? When did you first learn about the stars? I have like, I do have this very incredible distinctive memory. And again, it had to do with my dad. He took us camping. Now my dad was from the UK and he was the type who you'd find wearing a tie on weekends. So camping was not in his fear, his comfort zone. We had a babysitter. Every summer we got a baby. Every summer we had a babysitter. And one summer we had Tom. He was barely older than we were. He was 14. My brother was 12. I would have been 11 or 10 maybe. And we went camping because Tom said camping's the thing. We should try it. And I just remember, I didn't aim to see the stars, but I walked out of my tent in the middle of the night and I looked up and wow, so many stars, the dark night sky and all those stars just like screaming at me. I just couldn't believe that. Honestly, like my first thought was this is so incredible, mind blowing. Like why wouldn't anyone have told me this existed? Can anyone else see this? Have you had an experience like that with anything? Yeah, I've had that. I mean, I don't know if maybe you can tell me if it's the same. I've had that with robots. There's a few robots I've met where I just fell in love with this. Like is anyone else seeing this? Is anyone else seeing that here in a robot is our ability to engineer some intelligent beings, intelligent beings that we could love, that could love us, that we can interact with in some rich ways that we haven't yet discovered? Almost like when you get a puppy, he needs to have a dog and there's this immediate bond and love. And on top of that, ability to engineer it, I had to just pause and hold myself. I don't have kids, I imagine there's a magic to that as well, where it's a totally new experience. It's like, what? Well, yeah, the stars though, unlike kids or the puppy, it's only a good thing. So you felt, you weren't terrified? To me, when I look at the stars, it's almost paralyzingly scary how little we know about the universe, how alone we are. I mean, somehow it feels alone. I'm not sure if it's just a matter of perspective, but it feels like, wow, there's billions of them out there and we know nothing about them. And then also immediately to me, somehow mortality comes into it. I mean, how did that make you feel at that time? I think as a child without articulating it, I felt that same way. Just like, wow, this is terrifying. What's out there? Like, what is this? What does it mean about us here? You're a scientist, an ex-world-class scientist, planetary scientist, astronomer. Now, I'm a bit of an idiot who likes to ask silly questions. So some questions are a little bit in the realm of speculation, almost philosophical, because we know so little. And one of the awesome things about your work is you've actually put data and real science behind some of the biggest questions that we're all curious about. But nevertheless, many of the questions might be a little bit speculative. So on that topic, just in your sense, do you think we're alone in the universe, human beings? Do you think there's life out there? Well, Lex, the funny thing is, is that as a scientist, I so don't even want to answer that. You really? No, I will answer it though. But I just love to say- You resist it naturally? Yeah, we naturally resist that because we want numbers and hard facts and not speculation. But I do love that question. It's a great question, and it's one we all wonder about. But I have to give you the scientist's answer first. Yeah, sure. Which is, we'll have the capability to answer that question soon even, starting soon. How do you define soon? How do I define soon? What do you, so much happened in the last 100 years. Right, right. And there's a difference, right? If it's 10 years or 20 years or 100 years. Yeah, there's a difference in that. Well, soon could be a decade or two decades. And the answer- By the way, journalists usually don't like that, or the people want like tomorrow, they want the news. But what it's going to take is telescopes, space telescopes, or very sophisticated ground or space-based telescopes to let us study the atmospheres of other planets far away and to look what's in the atmospheres and to look for water, which is needed for life as we know it, to look for gases that don't belong that we might attribute to life. So we have to do some really nitty gritty astronomy. So the promising way to answer this question scientifically is to look for hints of life. That's where like many of your ideas come in of what kind of hints might we actually see about this life. Right, right. That's exactly what we need to do. And I like the word you chose, hint, because it's going to be a hint. It's not going to be a 100% yay, we found it. And then it will take future generations to do more careful work to hopefully even find a way to send a probe to these distant exoplanets and to really figure this out for us. Yeah. I mean, we'll talk about the details. Those are fun. But like- But back to the speculation, maybe? The zoomed out big picture speculation question. The zoomed out big picture is yes, I believe absolutely there is life out there somewhere because the vastness of the universe is incredible. It's so breathtaking. When we look at the night sky, if you can go to that dark sky, you can see many, many hundred or even if you have good eyesight and you're somewhere very dark, you could see thousands of stars. But in our galaxy, we have hundreds of billions of stars, and our universe has hundreds of billions of galaxies. So think about all those stars out there. And even if planets are rare, even if life is rare, just because the number of stars is so huge, things have to come together somewhere, someplace in our universe. Yeah, it's so amazing to think that somebody might be looking up on another planet in a distant galaxy. I have to interrupt your reverie and get back to, in our lifetime at least, the short term. Yeah. We have to. We only have the nearest stars to look at. It's true that there are so many stars, so many hosts for planets that might have life. But in the practical question of will we find it, it has to be a star quite close to Earth, like a few light years, tens of light years, maybe hundreds of light years. And by the way, you've introduced me to a tool of eyes on exoplanets, I think, that NASA has put together. Eyes on exoplanets. It's a great software. Eyes on exoplanets. That's so cool. But anyway, can you give a sense of who our neighbors are? You said hundreds of light years. How many stars are close by? What's our neighborhood like? Are we talking about five, ten stars that we might actually have a chance to zoom in on? I'm talking about maybe a dozen or two dozen stars. And those are- With planets that look suitable for us to follow up in detail. For life. Right. But one thing that's really exciting in this field is that the very nearest star to Earth, called Proxima Centauri, is part of the Alpha Centauri star system. Cool name, by the way. Yeah, Proxima. Whoever names them. Nearby. Okay. But it sounds cool. But Proxima Centauri appears to have a planet around it. That's about an Earth-mass planet in the so-called habitable zone, or the Goldilocks zone of the host star. So think about how incredible that is. Out of all the stars out there, even the very nearest star has planets and has a planet in it. The very nearest star has planets and has a planet of huge interest to us. Yeah. Okay. So can we talk about that planet? What does it mean to be maybe possibly habitable? How does size come into play? How does what we know about gases and what kind of things are necessary for life? What are the factors that make you think that it's habitable? And by the way, maybe one way to talk about that is people know about the Drake equation, which is a very high-level, almost framework to think about what is the probability that, correct me if I'm wrong, that there's life out there. And intelligent life, I think. I don't know. But then you have an equation named after you now, which I think nicely focuses in on the more achievable and interesting part of that question, which is on whether there is habitable planets out there, or how many, I guess, habitable planets are. Right, right. Yeah. So the funny thing is, was one time I met Frank Drake, and I asked if he minded if I took his equation and kind of revamped it for this new field of exoplanet astronomy. He was totally cool with it. He's totally cool with it. He got total approval. I'm not sure if he'd actually read the stuff about my equation, but he was cool with it. He was cool with it. Okay, so I just said like 15 different things, but maybe can you tell from your perspective what is the Drake equation, and what is, sorry, the Seeger equation? Sure. Well, the Drake equation, as you said, it's a framework. It's a description of the number of civilizations out there. Of intelligent beings that are able to communicate with us by radio waves. So if you think of the movie Contact, you've seen Contact, right? We're hoping to get, we're listening in actually. It's an active field of research, listening to other stars at radio wavelengths, hoping that some intelligent civilizations are sending us a message. And the Drake equation came like at the start of that whole field to put the factors down on paper to sort of illustrate what is involved to kind of estimating. And there's no real estimate or prediction of how many civilizations are out there, but it's a way to frame the question and show you each term that's involved. So I took the Drake equation, and I called it a revised Drake equation, and I recast it for the search for planets by more traditional astronomy means. We're looking at stars, looking for planets, looking for rocky planets, looking for planets that are the right temperature for life, looking for planets that might have life that outputs gases that we might detect in the future. It's the same spirit of the Drake equation. It's not going to give us any magic numbers. So I'm going to say, hey, here's exactly what's out there. It's meant to kind of guide, guide of where we're going. Although the Drake equation did, I mean, the initial equation proposed actual numbers for those variables, right? Oh, yes. The equation proposed numbers, and you can still plug your own numbers in. And there's this really cute website that lets you, for both the Drake and my revised equation, plug in some numbers and see what you get. So, yeah. So, okay. So what are, I mean, what are the variables, but maybe also what are the critical variables? So in my equation, I set out to what are the numbers of inhabited planets that show signs of life by way of gases in the atmosphere that can be attributed to life. I could just walk through the terms. That's simpler. So the first thing I say is what are the number of stars available? And it's not that those trillions and trillions of stars everywhere. It's what are available to like a specific search. And so, for example, the MIT led NASA mission TESS is surveying the sky looking for all kinds of planets, but it can also, it also has stars. It has about 30,000 red dwarf stars. So we just take a number of stars that a given survey can access. So that's what the number of stars is. Then I wanted to know what kind of stars are quiet. I called it fraction of those stars that is quiet. In the case of TESS, the way it's looking for planets is planets that transit the star. They go in front of the star as seen from the telescope. But it turns out that some stars are very active. They're variable and they brighten and dim with time and that interferes with our observation. I apologize to interrupt. So the transiting planet. So you're really looking for a black blob, essentially, that blocks the light. We're looking for a black blob that blocks the light. And then trying to say something about the size of the planet from the frequency of that black blob's appearance and the size of that black blob, that kind of thing. Yeah, but let's just say that out of all the stars there are accessible to whatever telescope, some of them are just bad. For whatever reason, you're not gonna be able to find planets around them. So I need to know the fraction of those that are good. So again, we have the number of stars, the fraction of them that we can actually find planets around. And by the way, is our sun one such? Is our sun quiet? Our sun is quiet. OK. So I have actually two terms. One describes how quiet they are. And one is if we can find a planet around that star. These transiting planets, for example, not all planets transit. Because the planet would have to be orbiting that star in this kind of plane as viewed from you. But if a star is, for example, orbiting in the plane of the sky, it will never transit. It will never go in front of the star. So in that case, we have to have a fraction that takes into account that kind of geometric factor. LARSON And hopefully, I mean, you can assume that it's uniformly distributed, hopefully. KING Yes, we can assume and there's evidence that it's uniformly distributed, yes. So then the next, so all of these factors so far, number of stars accessible to whatever telescope you're thinking about, how many stars are quiet, fraction of stars that are quiet, fraction that are observable, in this case for the geometric factor, those are all things we can measure. And there's one more term in the Seeger equation we can measure. I call it fraction of planets in the habitable zone. Because believe it or not, we have a handle on that for a certain set of stars. We know from the Kepler space telescope that operated for a number of years, we have estimates for how many planets are in the so-called habitable zone of the host star for a certain type of star. So all those we have measurable. And then like the Drake equation itself, there are some terms we can not measure. And those ones, I call them FL, fraction of all those planets that have life on them. Because we don't know what that is. And FS, I called for spectroscopy, the fraction that have, we can use our telescope and instrument tools to look for light. Actually, FS was the ones that the planets that have life that actually gives off a gas, useful gas that might accumulate in the atmosphere. So we could eventually observe it. How do the FL and FS interplay? So these are separate terms? Separate terms. And so? So for example, you could imagine, so for example, you could imagine life, like us humans, we breathe out carbon dioxide. But our planet Earth, we already have a lot of carbon dioxide on it. Well, we have hundreds of parts per million, but it has a really strong signal. So us humans breathing out carbon dioxide, it's not helpful for any intelligent beings that are looking back at Earth, because there's already a lot of, there's already enough carbon dioxide we're not adding to it. So if there is life on a planet, and it's outputting a boring gas, that's not helpful for us to uniquely identify as being made by life versus just being there anyway, then it's not helpful. So I separated those two terms out. Soon, I think we'll have evidence that planets that can support life, at least, are common. So, okay, this is such an awesome topic. I have a million questions. What, okay, I know this is a little bit of speculation, but what's your sense about that, I think FS, which is like, that life would produce interesting gases that we'd be able to detect? Like, is there, one, is there scientific evidence? And second, is there some intuition around life producing gases, detectable hints in terms of chemistry? So interestingly enough, that entire question relates to, I'm gonna say almost my life's work, the work I'm doing now and the work I'm doing for the next 20 years. And I wish I could give you a concrete number, like 1%. Like on the worst days, it's 1%, let's say, in my mind. You know, in the best days, it's like 80%. And I could actually go into a lot of detail here, but I'll just give you the simplest things. So first of all, we make an assumption that, like us and our life here on Earth, life uses chemistry. So we use chemistry because we eat food, we breathe air, and we have metabolism that to break down food to get energy, to store energy, and then ultimately to use it. And all life here has some kind of byproduct in doing all that, some kind of waste product that goes into the atmosphere. So I like to think that life everywhere uses chemistry. Some people have imagined, like, let's imagine like a windmill, like mechanical energy, just getting energy and using it without storing it. And if there was life like that, it might not need to output a gas. So we make this basic assumption of chemistry. That's the first thing. The second more complicated thing that I and my team work on is what happens to the gas once it is produced by life. It goes into the atmosphere. And a lot of gas is just destroyed immediately, actually, by ultraviolet radiation or by oxygen. Oxygen is incredibly destructive to a lot of gases. So the gas can be produced by life, but it could be just completely destroyed by its environment. I guess we should pause on that, that you mentioned your life's work. I mean, this is just a beautiful idea that it's kind of paralyzing when you look out there and you wonder, is there life out there? It's the first paralyzing. Actually, before I encountered your work, I feel like an idiot. But, you know, it feels like there's no tool to answer that question. And then what you kind of provided is this cool idea that it might be possible to answer that by looking at the gases. I mean, that's a really interesting, that's a beautiful idea. And yeah, so we could just pause on like, that's a powerful tool, I think, that to build the intuition around. Because I was totally clueless about it. And that was kind of a big part of it. To build the intuition around, because I was totally clueless about it, and that is kind of exciting. I mean, I'm sure there's folks probably early on in your life who were very skeptical about this notion. Maybe I'm not sure, but generally you would want to be skeptical. It's like, well, all these kinds of other things could generate gases, you know, all those kind of things. Oh, that's so true. And that's a big part of this growing field is how to make sure that this gas isn't produced by another effect. But I do want to, you know, again, pausing on that and going back a bit. It's incredible to think, but like at least almost 100 years ago, there's a record of someone talking about the idea of a gas being an indicator of life elsewhere. Oh, that idea was floating about somewhere. Yes, it was totally floating about. And it comes down to oxygen, which on our planet fills our atmosphere to 20% by volume. And, you know, we rely on oxygen to breathe. You know, when you hear about the people on Mount Everest running out of air, they're really running out of oxygen. Well, they're running out of oxygen because the air is getting thinner as they climb up the mountain. But without plants and bacteria, there's plants, bacteria that also photosynthesizes and produces oxygen as a waste product. Without those, we would have virtually no oxygen. Our atmosphere would be devoid of oxygen. So, yeah, if you were to analyze Earth, is oxygen the strong indicator here? Oxygen is a huge indicator. And that's what we're hoping, that there is an intelligent civilization not too far from here around a planet orbiting a nearby star with the kind of telescopes we're trying to build. And they're looking back at our Sun, and they've seen our Earth, and they see oxygen. And they probably won't be like 100.0% sure that there's life making it. But if they go through all the possible scenarios, they'll be left with a pretty strong hint that there's life here. Yeah. Okay, but how do you detect that type of gases that are on the planet from a distance? And that's, going back to that, that's what people were skeptical about. When I first started working on exoplanets, a long time ago, people didn't believe we would ever, ever, ever study an exoplanet atmosphere of any kind. And now dozens of them are studied. There's a whole field of people, hundreds of people working on exoplanet atmospheres, actually. Wow. But first, there was a point where people didn't even know there were exoplanets. Right? When was the first exoplanet detected? The first exoplanet around a Sun-like star, anyway, was detected in the mid-1990s. That was a big deal. I kind of vaguely remember that. Well, at the time, it was a big deal, but it was also incredibly controversial. Because in exoplanets, we only had one example of a planetary system, our own solar system. And in our solar system, Jupiter, our big, massive planet, is really far from our star. And this first exoplanet around a Sun-like star was incredibly close to its star, its star. So close that people just couldn't believe it was a planet, actually. So maybe zoom out. What the heck is an exoplanet? An exoplanet is our name, like, is the name that we call a planet orbiting a star other than our Sun. Right. Extrasolar, I guess, is the name. You can call it extrasolar. Mm-hmm. Exoplanet is simpler. But I think it's worth pausing to remember that each one of those stars out there in our night sky is a Sun. Right. And our Sun has planets, Mercury, Venus, Earth, Mars, et cetera. And so for a long time, people have wondered, do those other stars or other Suns have planets? And they do. And it appears that nearly every star has a planet we call exoplanet. And there are thousands of known exoplanets already. So there's already, yeah, like, there's so many things about space that it's hard to put into one's brain because it starts filling it with awe. So yeah, if you visualize the fact that the stars that we see in the sky aren't just stars, they're like, they're Suns. And they very likely, as you're saying, will have planets around them. There's all these planets roaming about in this dimly lit darkness with potentially life. I mean, it's just mind-blowing. But maybe can you give a brief history of discovering all the exoplanets? So there's no exoplanets in the 90s. And then there's a lot of exoplanets now. So how did that come about? So many planets. How did it come about? Well, maybe another way to ask is what is the methodology that was used to discover them? I can say that. But I'd like to just say something else first. So in exoplanets, the line between what is considered completely crazy and what is considered mainstream research, legit, is constantly shifting. This is awesome, yeah. So before, when I started out on exoplanets, it was still sketchy. Like it wasn't considered a career, a thing, a place where you should be investing. Yeah. And right now, now, today, it's so many people are working in this field. A good, I don't know, at least a thousand, probably more. I don't know if that sounds like a lot to you, but it's a lot. No, it's just a legitimate field of inquiry. Yeah, legitimate field of inquiry. And what's helped us is everything that's helped everyone else. It's software, it's computers, it's hardware. It's like our phones. You have a fantastic detector in there. They didn't always have that. I don't know if you remember the so-called olden days. We didn't have digital cameras. We had film. You take a film camera, you send the film away, and eventually it comes back, and then you see your pictures, and they could all be horrible. Yeah. So yeah, I mean digital, it just changed everything. Data changed everything. Yeah. And so one thing that really helped exoplanets were detectors that were very sensitive. Because when we're looking for the transiting planets, what we're doing is we're monitoring a star's brightness as a function of time. It's like click, taking a picture of the stars every few seconds or minutes. And we're measuring the brightness of a star, like every frame. And we're looking for a drop in brightness that's characteristic of a planet going in front of the star, and then finishing its so-called transit. And to make that measurement, we have to have precise detectors. And the detectors that are making the measurement, can you do it from Earth? Are they floating about in space? Like what kind of telescope? Both. So on the ground, people are using telescopes, small telescopes that are almost just like a glorified telephoto lens. And they're looking at big swaths of the sky. And from the ground, people can find giant planets like the size of Jupiter. So it's about 10 to 12 times the size of Earth. We can find big planets because we can reach about 1% precision. So I'm not sure how much technology you want to get, but... Well, yeah, how many pixels are we talking about? Like what, uh, you mentioned phones. There's a bunch of megapixels, I think. So for exoplanets, you want to think about it as like a pixel or less than a pixel. We're not getting any information. But to be more technical, our telescope, you know, spreads the light out over many pixels, but we're not getting information. We're not tiling the planet with pixels. It's just like a point of light, or in most cases, we don't even see the planet itself, just the planet's effect on the star. But another thing that really helped was computers, because transiting planets are actually quite rare. I mean, they don't all go in front of their star. And so to find transiting planets, we look at a big part of the sky at once, or we look at tens of thousands or hundreds of thousands, or even in some cases, millions of stars at one time. And so, you know, you're not going to do this by hand, going through a million stars, counting up the brightness. So we have computer software and computer code that does the job for us and looks for a, you know, counts the brightness and looks for a signal that could be due to a transiting planet. And, you know, I just finished a job called Deputy Science Director for the MIT-led NASA mission test. And it was my purview to make sure that we got the planet candidates, the transiting light curves, out to the community so people could follow them up and figure out if they're actual planets or false positives. So publish the data so that people could just, uh, Yeah, publish the data. All the data scientists out there could crunch and see if they can discover something. Exactly, they can discover something. And in fact, the NASA policy for this mission is that all the data becomes public as soon as possible. So anyone could, it's not as easy as it sounds, though, to download the data and look for planets. But there is a group called planethunters.org, and they take the data and they actually crowdsource it out to people to look for planets. Yeah, and they often find signals that our computers and our team missed. So we mentioned exoplanets. What about Earth-like or, I don't know what the right distinction is, if it is habitable or is it Earth-like planets, but what are those different categories and how can we tell the difference and detect each? Right, right. So we're not at Earth-like planets yet. All the planets we're finding are so different from what we have in our solar system. They're just easier planets to find, but like- In which way? For example, there could be a Jupiter-sized planet where an Earth should be. We find planets that are the same size as Earth, but are orbiting way closer to their star than Mercury is to our Sun. And they're so close that, because close to a star means they also orbit faster. And some of these hot super-Earths, we call them, their year, their time to go around their star is less than a day. And they're heated so much by their star. They're heated so much by the star, we think the surface is hot enough to melt rock. So instead of running out by the bay or the river, you'll have like liquid lava. There'll be liquid lava lakes on these planets, we think. And life can't survive- Way too hot. The molecules needed for life just wouldn't be able to survive those temperatures. We have some other planets. One of the most mysterious things out there, factoid, if you will, is that the most common type of planet we know about so far is a planet that's in between Earth and Neptune size. It's two to three times the size of Earth. And we have no solar system counterpart of that planet. That is like going outside to the forest and finding some kind of creature or animal that just no one has ever seen before and then discovering that is the most common thing out there. And so we're not even sure what they are. We have a lot of thoughts as to the different types of planet it could be, but people don't really know. I mean, what are your thoughts about what it could be? Well, one thought, and this is more when we want to be rather than might be, is that these so-called mini-Neptunes, we call them, that they are what we call them, that they are water worlds, that they could be scaled up versions of Jupiter's icy moons, such that they are planets that are made of more than half of water by mass. So, yeah, and what's the connection between water and life and the possibility of seeing that from a gas perspective? Okay, so all life on Earth needs liquid water. And so there's been this idea in astronomy or astrobiology for a long time called follow the water. Find water, that will give you a chance of finding life. But we could still zoom out, and the community consensus is that we need some kind of liquid for life to originate and to survive, because molecules have to react. You don't have a way that molecules can interact with each other. You can't really make anything. And so when we think of all the liquids out there, water is the most abundant liquid in terms of planetary materials. There really aren't that many liquids. Like I mentioned liquid rock, way too hot for life. We have some really cold liquids, like almost gasoline, like ethane and methane lakes that have been found on one of Saturn's moons, Titan. That's so cold though. And for exoplanets, we can't study really cold planets because they're just simply too dark and too cold. So we usually are just left with looking for planets with liquid water. And to your point, remember we talked about how planets are less than a pixel in that way to say. So we can't see oceans on a planet. We're not going to see continents and oceans, not yet anyway. But we can see gases in the atmosphere. And if it's a small rocky planet, and this is going into some more detail, if we see a small rocky planet with water vapor in the atmosphere, we're pretty sure that means there has to be a liquid water reservoir. Because it's not intuitive in any way, but water is broken up by ultraviolet radiation from the star or from the sun. And on most planets, when water is broken up into H and O, the H, the hydrogen, will escape to space. Because just like when you think of a child letting go of a helium-filled balloon, it floats upwards. And hydrogen's a light gas and will leave from the planet. So ultimately, if you have water, unless there's an ocean, like a giant ocean, like a giant ocean, like a way to keep replenishing water vapor in the atmosphere, that water vapor should be destroyed by ultraviolet radiation. LUIS So there's a need for a liquid. I mean, I guess, is water essential or are there liquids? I mean, the chemistry here is probably super complicated. SARAH It does, but you know, there's not an infinite number of liquids. There's maybe like five liquids that can exist inside or on the surface of a planet. And water is the one that exists for the largest range of temperatures and pressures. And it's also the easiest type of planet for us to find and study is one with water vapor, rather than a cold planet that has ethane and methane lakes. LUIS What's your personal, in terms of solar systems and planets, that you're most hopeful about in terms of our closest neighbors, that you kind of have a sense that there might be somebody living over there, whether it's bacteria or somebody that looks like us? SARAH I'm hopeful that every star nearby has a planet. LUIS Every star has some life. SARAH Because it almost has to for us to make progress. We have to have that dream condition. LUIS So the dream condition is like life is just super abundant out there. SARAH Yeah, the dream, yes, the dream condition is that life is super abundant. And it's based on the thought that if there is a planet with water and continents, that it also has the ingredients for life. And that the kind of base, the base kernel thought is that if the ingredients for life is there, life will form. LUIS Life will form. SARAH That's what we're holding on to. LUIS With a relatively high probability. SARAH Yes, that's it. LUIS Okay, let's go into the land of speculation. What about intelligent life? Us humans consider ourselves intelligent, surprisingly, or unsurprisingly. Do you think about, from your perspective of looking at planets from a gas composition perspective, and in general, of how we might see intelligent life and your intuition about whether that life is even out there? SARAH I think the life is out there somewhere. The huge numbers of stars and planets. I like to think that life had a chance to evolve to be intelligent. I'm not convinced the life is anywhere near here, only because if it's hard for intelligent life to evolve, then it will be far away by definition. LUIS Well, the sad thing is, maybe from the artificial intelligence perspective, is it makes me sad there might be intelligent life out there that we're just not, like, the pathways of evolution can go in all these different directions where we might be able to communicate with it, or even detect its intelligence, or even comprehend its intelligence. I'm convinced cats are more intelligent than humans, that we're just not able to comprehend the proper measures of their intelligence. SARAH My dog is so funny. He's the golden doodle. His name's Leo. We joke that he's either a really dumb dog, and sorry, he's not here to defend himself, but he's either really dumb, or he's a really dumb dog. But he's either really dumb, or he's a super genius, just pretending to be dumb. LUIS Yeah. And it's possible he's a multidimensional projection of alien life here monitoring one of the top scientists in the world trying to find aliens, just to make sure that humans don't get out of hand. SARAH That's funny. Oh, I'm definitely gonna go in and ask him about that. Ask him about that one again. LUIS He's onto something, yeah. What might we look for in terms of signs of intelligent life? From your toolkit, do you think there are things that we should, we might be able to use or maybe in the next couple of decades discover that would be different than life that's like bacteria, that's primitive life? SARAH I still love SETI, Search for Extraterrestrial Intelligence. I like to hope that if there is a civilization out there, they're trying to send us a message. I think, like, think about it, I don't know, what are your thoughts? Like, if you think about our Earth, there's no structure we've built that intelligent civilizations could see from far away. There's literally nothing, not even the Great Wall of China. And so to think, like, why would this other civilization build a giant structure that we could see? LUIS Yeah, so with SETI, the idea is that we're both trying to hear signals and send signals, right? Or... SARAH We haven't sent, when they call that METI, messaging, and there's a big kind of fear over METI. Because, do you want to tell them you're here? It's kind of this, like, let's wait till they call us. LUIS Yeah. SARAH So, we should be... LUIS It's like a dating game, you have to, like, how many days do I wait before I call, kind of thing. SARAH Yes, it is. And so, but the funny thing is, if no one's sending us a message, if everybody's only listening, how do you make progress? LUIS That's right. And I mean, but there's also, there's the Voyager spacecraft that we have these little pixels of robots flying out all over the place. Some of them, like the Voyager, reach out really far, and they have some stuff on them. Okay, I just... SARAH We do, we have the Voyager, but they're not really going anywhere in particular, and they're moving very, very slowly on a cosmic scale. LUIS Yeah, and me saying they're far is kind of silly. SARAH Yeah, it's all relative in astronomy. It's all relative, yeah. LUIS Yeah, I just, so from a, if you look at Earth from an alien perspective, from visually and from gas composition, I wonder if it's possible to determine the degree of maybe productive energy use. I wonder if it's possible to tell, like, how busy these Earthlings are. SARAH Well, let's zoom out again and think about oxygen. So when cyanobacteria arose, like billions of years ago, and figured out how to harness the energy of the Sun for photosynthesis, they re-engineered the entire atmosphere. 20% of the atmosphere has oxygen now. Like, that is a huge scale. You know, they almost poisoned everything else by making this what was apparently very poisonous to everything that was alive. But imagine, so are we doing anything at that scale? Like, are we changing anything at like 20% of the Earth with a giant structure, or 20% of this, or 20% of that? Like, we aren't, actually. PAUL Yeah, yeah, that's humbling to think that we're not actually having that much of an impact. SARAH I know. But we are, because in a way we're destroying our entire planet. But it's humbling to think that from far away, people probably can't even tell. PAUL But from the perspective of the planet, when we say we're destroying, you know, global warming, all that kind of stuff, what we really mean is we're destroying it for a bunch of different species, including humans. But like, I think the Earth will be okay. SARAH Oh, the Earth will be, the Earth will remain. Whatever happens to us, the Earth will still be here. PAUL And it'll still be difficult to detect any difference. Like, it's sad to think that if humans destroy ourselves, except potentially with nuclear war, it would be hard to tell that anything even happened. SARAH Yeah, it would be hard to tell from far away that anything happened. PAUL What about, what are your thoughts, now this is really getting into speculation land. You've mentioned exoplanets were in the realm of, you know, there's this beautiful edge between science and science fiction, that some of us, a rare few are brave enough to walk, I think, in academia, you were brave enough to do that. I think in some sense, artificial intelligence sometimes walks that line a little bit. There is so much excitement about extraterrestrial life and aliens in this world. I mean, I don't know what, how to comprehend that excitement. But to me, it's great to see people curious, because to me, extraterrestrial life and aliens is at the core, a scientific question. And it's almost looks like people are excited about science. They're excited by the sky. They're excited by discovery. SARAH Discovery, right. PAUL And then the possibility that there's alien life that visited Earth, or is here on Earth now, is excitement about discovery in your lifetime, essentially. I mean, what do you make of that? There's recent events where DARPA or DoD released footage of these unmanned aerial phenomena, they're calling them now, UAP. They got everybody super excited, like, maybe there is, like, what's here on Earth? Do you follow this world of people who are thinking about aliens that are already here or have visited? SARAH I don't really follow it, they follow me, I'd say. Because in this field, if you're a scientist of any kind, you get, people contact us, me. PAUL They're right. SARAH There's a lot of them about, hey, I have stuff you should see. Hey, the aliens are already here, I need to tell you about it. And I know there are people out there who really believe. PAUL There's a psychology to it. SARAH There's a psychology to it. PAUL And it's fascinating. But okay, so it's similar to artificial intelligence. SARAH But like you, I'm still enamored with the point that it is out there, and that people believe so strongly, and that so many people out there believe. PAUL Believe. And I don't know, I'm not as allergic to it as some scientists are, because ultimately, if aliens showed up, or do show up, or have showed up, you know, these are going to be very difficult to study scientific phenomena. Like, in fact, like going back to cats and dogs, like, I just, I think we should be more open-minded about developing new tools, and looking for intelligent life on Earth that we haven't yet found. Or even understanding the nature of our own intelligence, because it kind of is an alien life form, the thing that's living, you know, in our skull. SARAH It's so true, and we don't understand consciousness. PAUL Yeah. SARAH It's true, we don't understand how. Biology's hard, you know, unpacking it and working it all out, it's a stretch. And they say too, that our thinking mind is like the tip of a pyramid, that everything else is happening under the hood, but what is happening? But the thing with, so the typical scientist's response to, you know, are there aliens here, is that we need to see major evidence, not like a sketchy picture of something. We need some cold hard evidence, and we just don't have that. PAUL That's exactly right. Yeah, but from my perspective, I admire people that dream, and I think that's beautiful. The thing I don't like, there's two sides of the folks that probably listen to this podcast, is those that dream, I think is beautiful, that wander what's out there, what's here on Earth. And then the other ones who are very conspiratorial and thinking that stuff is being hidden, and it becomes about institutions. RACHEL Right, right, right. Okay, I have a funny thing to tell you about that. So one of my colleagues had a really good answer to that, and it's not me saying this, so I can say this, but he said, look, he works with NASA, not at NASA, he works with government, not in the government. It's kind of mean, but he'd say, trust me, they couldn't hide it if they tried. Do you know what I'm saying? Like, we're not smart enough, we're good enough, not we, or not me, or not you, but whoever, to cover it up. It just, it's sort of a myth. MICHAEL Yeah, it makes it sad, because the people at NASA, the people at MIT, the people in academia, the people in these institutions, and yes, even in government, are often trying, they're like just curious descendants of apes. They're just, they want to do good, they want to discover stuff, they're not trying to hide stuff. In fact, most of them would, in terms of leaks, would love to discover this and release this kind of stuff. I, and... RISA Did you ever watch this show called The X-Files? MICHAEL Yeah. RISA Scully and Mulder? MICHAEL Yeah. RISA And what I love, actually, I used to put it up during my talks, my public talks, there's a picture of a UFO, or what looks like a UFO, and it says, I want to believe. MICHAEL Yeah. RISA So that's, that's where I think a lot of us are coming from. I want to believe. And it's so great, and one time, I put that up, and this very, very nice couple approached me, really nervous afterwards, and they said, hey, can we take you out for lunch sometime? And I said, sure, and they were like the nicest people. And just one of many who has an alien abduction story. And the woman could never have kids, they were older, but they didn't have kids, which for them was a real source of regret, but it was because the aliens who had abducted her had made it so that she couldn't have kids. And she had apparently something implanted behind her ear, which was somehow unimplanted later. And they were just so sincere. And they're such a lovely couple. They just wanted to share their story. MICHAEL That's, that's a real, whatever that is, that's a real thing. The mystery of the human mind is more powerful than any alien, or I mean, it's as interesting, I think, as the universe, and I think they're somehow intricately linked. Maybe getting a sense of numbers. How many stars are there in maybe, I don't know what the radius that's reasonable to think about. I don't know if the observable universe is like way too big to think about. But in terms of when we think about how many habitable planets there are, what are the numbers we're working with, in your sense? What are the scale? JILL Honestly, the numbers are probably like billions of trillions. MICHAEL Of stars. JILL Yeah, you know, in the UK, I think, I don't know if we do that here, but they will call a billion trillion, where you put like one billion followed by a trillion. Yeah, it's kind of weird. But here, I don't even know how to say the number 10 to the 20. Like, if you know what that is, that's one followed by 20 zeros. That's a big number. And we don't have a name for that number. There's so many. MICHAEL Per star, I think we kind of mentioned this. Is there a good sense? There's probably argument about this, but per star, how many planets are there? Is there a- JILL We don't have that number yet, per se. You know, we're not really there. But some people think that there's many planets per star. There's this analogy of filling the coffee cup. Like, you know, you don't usually just pour one drop, you fill it. And that planetary systems, we see stars being born that have a disk of gas and dust, and that ultimately forms planets. So the idea, this kind of concept is that planets, so many planets form too many. And eventually, some get kicked out, and you're left with like a full planetary system, a dynamically full system. And so there have to be a lot, because so many form, and a bunch survive. PEDRO I mean, that makes perfect intuitive sense, right? Like, why wouldn't that happen? JILL Right. Well, there's other thoughts too, though. These big planets that are really close to the star, we think they formed far away from the star where there's enough material to form, and they migrated inwards. And some of these planets migrating inwards due to interaction with other planets or with the disk itself, they may have cleared it out, like kicked other planets out of the system. So there's a lot of ideas floating around. We're not entirely sure. PEDRO And what about Earth-like planets? Is that, that's another level of uncertainty that... JILL It's a level of uncertainty. If we think of an Earth-like planet being an Earth around a sun in the same orbit, and Earth-like planet being an Earth-sized planet in an Earth-like orbit about a sun-like star, we're not there yet. We're not able to detect enough of those to give you a hard number. Some people have extrapolated, and they will say as many as one in five stars like our sun could be hosting a true Earth-like planet. PEDRO Wow. On the topic of space exploration, there's been a lot of exciting developments with NASA, with SpaceX, with other companies successfully getting rockets into space with humans and getting them to land back, especially with SpaceX. What are your thoughts about Elon Musk and SpaceX, Crew Dragon, while working with NASA to launch astronauts? What's your sense about these exciting new developments? JILL Well, SpaceX and other so-called commercial companies are only good news for my field because they're lowering the cost of getting to space. By having reusable rockets, it's just been incredible, and we need cheaper access to space. So from a very practical viewpoint, it's all good. About getting people, there's this dream that we have to go to Mars. Boots on Mars. PEDRO Boots on Mars. What do you think about that? You mentioned probes. What's the value of humans? Is that interesting to you from both a scientific and a human perspective? JILL Human mostly. I think it's such in our desire to explore. It's part of what it means to be human. So wanting to go to another planet and be able to live there for some time, it's just what it means to be human. You know, oftentimes in science and engineering, big, huge discoveries are made when we didn't intend to. So often this kind of pure exploratory type of research or this pure exploration research, it can lead to something really important, like the laser. We couldn't really live without that now. At the grocery, you scan your foods. There's surgery that involves lasers. GPS. We all use our GPS. We don't have GPS because someone thought, hey, it would be great to have a navigation system. And so I do support, I do, but I really think it comes primarily just from the desire to explore. PEDRO Do you think something, there's a lot of criticism and a lot of excitement about Mars. Do you think there's value in trying to go to put humans on Mars, first of all? And second of all, colonize Mars? Do you think there's something interesting that might come from there? NANCY I'm convinced there will be something interesting. I just don't know what it is yet. But I don't think having some commercial value or value in the metric of something useful is really what's motivating us. PEDRO So really, you see exploration as a long-term investment into something awesome that eventually will be commercial value. NANCY I do, actually. PEDRO Yeah. NANCY I do. PEDRO So what about visiting? Okay, I apologize, but I mean, there's an exciting longing to visit Earth-like planets elsewhere. So what's the closest Earth-like planet you think is worth visiting? And how hard is it? NANCY Wow, it is very hard. I mean, our nearest, call it Earth-mass planet, it's orbiting a star very different from our own sun, an M dwarf star, a small red star. Proxima Centauri. It's over four light years away. And we can't travel at the speed of light. We can't even travel. I mean, it would take tens of thousands of years to get there with conventional methods. So you know the movies like... PEDRO Generationally. NANCY Multigenerationally. Yeah, this movie, Passenger. Have you seen that movie? Passenger. PEDRO No. NANCY It's about a big spaceship that is traveling to another planet, and everyone's hibernating. I won't give you the spoiler alert, because one person wakes up, and then it's kind of a problem. PEDRO Okay, got it. NANCY But yeah, the multigenerational ships. I mean, when you think about where we're headed as a species, maybe we don't send people. Maybe we end up sending raw biological materials and instructions to print out humans. It sounds kind of far-fetched, but already we're printing liver cells in the lab and beating heart cells. We're starting to reconstruct body parts. I mean, the thing is, it is so hard to get to another planet that this thought of printing humans or printing life forms actually could be easier. PEDRO Yeah, that's somehow so sad to think of the idea that we would launch a successful spaceship that has multigenerational non-human life, and it's going to reach other intelligent life, and by the time they figure out where it came from, human civilization will be extinct. NANCY Wow, yeah, that is really suffering. PEDRO So that's one, there's a tempting thing to think about, what are the possible trajectories? So, you know, Elon keeps talking about us becoming multi-planetary species. I mean, sure, Mars is a part of that, but the dream is to really expand outside the solar system. And it's not clear, just like as you said, what the actual scientific engineering steps that are required to take. It seems like so daunting, so daunting. So like the smart thing seems to be to do the most achievable near daunting task, even if there doesn't seem to be a commercial application, which I think is colonizing Mars. But like from your perspective, is there some Manhattan project style huge project in space that we might want to take on? And you've had roles, you had scientist hat roles, and then you also had roles in terms of being on like committees and stuff, determining where funding goes and so on. So like, is there a huge like multi-trillion, we've been throwing the T word around recently a lot, but these huge projects that we might want to take on? NANCY Well, first of all, we want to find the planets like Earth first. Like just even finding those Earth-like planets is a billion dollar endeavor, billions of dollars endeavor. And that's so hard because an Earth is so small, so less massive, and so faint compared to our sun. It's the proverbial needle in a haystack, but worse. And we need very sophisticated space-based telescopes to be able to find these planets and to look at them and see which ones have water and which ones have signs of life on them. EDUARDO Yeah, the Starshade project that you're part of. NANCY Starshade. EDUARDO Starshade, yeah, it's probably the most badass thing I've ever seen. NANCY Right. You know what's interesting? EDUARDO Can you describe what it is first of all? NANCY So what's amazing about Starshade is it was first conceived of in the 1960s. Imagine that and revisit it every decade until now when we think we can actually build it. And Starshade is a giant specially shaped screen. It is about, there's different versions of it, but think about 30 meters in diameter. EDUARDO So you're blocking out the sun. NANCY You're effectively blocking out the star. EDUARDO Yeah. NANCY So that you can see the planet directly. And Starshade would have a spacecraft attached to it, and it would fly in space far away from Earth's gravity. And it would have to formation fly with a space telescope. So the idea is that Starshade blocks out the starlight in a very careful way. And it has to block that starlight out so that the planet that is 10 billion times fainter than the star, that only the planet light goes to the telescope. EDUARDO Yeah, so in formation, meaning the telescope flies in, you can get a presentation on this, but like it would fly like in, um, this is extremely high precision endeavor. NANCY Yeah, we had this analogy like asking a friend to hold up a dime five miles away. EDUARDO Yeah. NANCY Perfectly, like at the perfect line of sight with you. EDUARDO Yeah. And the shape of it is pretty cool. I mean, I don't know exactly what the physics of that, like what the optics are that require that shape. NANCY I can tell you. It turns out that if you block out a star, imagine blocking out a star with a circle, circularly or a square-shaped screen. You wouldn't actually be blocking it. Because the star acts like a wave, the starlight can act like a wave, and it would actually bend around the edges of the screen. And so instead of blocking out the light, you're expecting to see nothing, you would see ripples. And the analogy that I love to give, it's like throwing a pebble in a pond. You get those ripples, you get these concentric ripples and they go out, and light would do something quite similar. You'd actually see ripples of light. And those ripples of light, they're actually way brighter than the planet we'd be looking for. So we can't put a circle. LUKE So they would introduce this noise that's… NANCY Yeah, noise. And so this star shade, it's like a mathematical solution to the problem of diffraction, it's called. And this is what the first person who thought about star shade in the 1960s worked out, the mathematical shape, or one family of solutions. And the idea is that when the star shade, this very special shape like a giant flower with petals, when it blocks out the light, the light bends around the edges but interacts with itself in a way to give you a very, very dark image. It would be like throwing a pebble in a pond. And instead of getting ripples, the pond would be perfectly smooth, like incredibly smooth to one part in 10 billion. And all the waves would be on the outer edges, far away from where you dropped that pebble. LUKE And so this camera would be able to, this telescope would be able to get some signal from the planet then. NANCY Yes, and it would be hard because the planet is so faint. But with the star out of the way, the glare of that bright, bright, bright star, with that out of the way, then it becomes a much more manageable task. LUKE So how do we get that thing out there? We're still working with unlimited money. NANCY Okay, we're working with unlimited money. We have some more engineering problems to solve, but not too many more. We've been burning down our so-called tall pole list. LUKE What kind of list? NANCY We call it technology tall pole. It's the phrase where you have to figure out what are your hardest problems. LUKE That's awesome. NANCY And then break those down to solve. So the starshade, one of the really hard problems was how to formation fly at tens of thousands of kilometers. It's like, wow, that is insane. And the team broke that down actually into a sensing problem. Because of the starshade, how do you see the starshade precisely enough to control it? Because if you're shining a flashlight, you know the beam spreads out. So the starshade has a beacon, an LED or a laser, it's going to spread out so much by the time it gets to the telescope. The problem wasn't how do you tell the starshade how to move around fast enough to stay in a straight line. The problem was how are you able to sense it well enough? So problems like that were broken down, and money that came from NASA to solve problems is put towards solving it. So we've got through most of the hard problems right now. Another one was that starshade, even though it's looking at a star, light from our own sun could hit the edges of the starshade and bounce off into the telescope, believe it or not. And that would actually ruin it because we're trying to see this tiny, tiny signal. So then the question is how do you make a razor-thin edge? Those petal edges would have to be like a razor. What materials can you use? So there's a series of problems like that. LARSON Wow, so there's a materials problem in there? ZAPELLA Some of them, materials problem. LARSON Wow. ZAPELLA And there's one. So we almost finished solving all those problems, and then it's just a matter of building one and testing it in a full-scale size facility. And then building the telescope, it's just a matter of time to build everything and get it up for launch. LARSON So this is an engineering project? ZAPELLA It's a real engineering project. I actually can tell you about two other projects that are not mine. I like to call starshade mine because it was my project that I helped make it mainstream, where that line is constantly shifting. When I started, when I got this leadership role on starshade, I remember telling people about it, and it was definitely not on the mainstream okay line. It was on the giggle factor side of the line. LARSON The giggle factor. ZAPELLA And people would just laugh, like, that's dead. Like, you can never formation fly. Or they'd say, why are you working on that? That's just so not, it's not possible. LARSON This is so awesome. There's a few things you've done in your life. And that's when I first saw starshade, I was like, what? Really? And then, like, it sinks in. I mean, it's the same thing I felt with like Elon Musk or certain people who do crazy stuff. Like, and then they actually make it work. I mean, if you get starshade information flying to, like, together, I mean, how awesome is that? If you actually make that happen, even like from a robot, I'm sorry, from the robotics perspective, even if it doesn't give us good data, that's just like a cool thing to get out there. I mean, it's really exciting. ZAPELLA Really cool. So there's two other topics that aren't mine, but I still love them. LARSON Yeah. ZAPELLA One of them, let's just talk about it briefly. Because it's not a probe, but it's the idea to send a telescope very far away to 500 times the Earth-Sun distance. And this is way farther than the Voyager spacecrafts are right now. And to use our sun as a gravitational lens, to use our sun to magnify something that's behind it. It's got to sink in for a minute. LARSON Yeah, exactly. But I mean, I don't know what the physics of that is, like how to use the sun. ZAPELLA In astronomy, and Einstein thought about this initially, we can use massive objects, bend space. LARSON Yeah. ZAPELLA And so light that should be traveling like straight, it actually travels around the warped space. LARSON And somehow you figure out a way to use that for magnification. ZAPELLA You have a way to use that for magnification, that's right. There are galaxies that are lensed, so-called gravitational lens, by intervening galaxy clusters, actually. And there are microlensing events where stars get magnified as an unseen gravitational lens star passes in between us and that very distant star. It's actually a real tool in astronomy. Yeah, using gravitational lensing to magnify because it bends more rays towards you than normally would, you'd normally see. LARSON And again, we're trying to get more higher resolution images that are basically boiled down to light. ZAPELLA It boils down to light, exactly. LARSON And then you can use that to magnify. ZAPELLA And then you can maybe get more information about- ZAPELLA Well, in this case, you would ask me, let's say, if this thing could get built, it would take something like, they like to say 25 years to get from here to there, 25 years, and then it could send some information back to us. And then you'd say, so, Sarah, how many pixels? And I wouldn't say one or less than one. I'd say, you know, it could be like 10 by 10 pixels, could be 100 pixels, which would be awesome. LARSON I mean, it's still crazy that we can get a lot of information from that. ZAPELLA Crazy, right. And it's crazy for a lot of other reasons, because again, you have to line up the Sun and your target. You'd only have one telescope per target, because every star is behind the Sun in a different way. So it's a lot of complicated things. LARSON What about the second? ZAPELLA The second one, it's called Starshot. You know, Starshot means like big dreams, and it's an initiative by the Breakthrough Foundation. And Starshot is the concept to send thousands of little tiny spacecraft, which they now call star chip. So instead of starship, it's star chip. And there's a little chip, and the star chip, so like thousands of little turtles being born, they're not all going to make it. They're just going to send lots of them. And each of these star chips, once they're launched into, I guess, low Earth orbit, they will deploy a solar sail that's a few meters in diameter. And the idea is that on Earth, we would have a bank of – this one is still a bit on the other side of the line, but we'd have a bank of telescopes with lasers that would be like a gigawatt power. And these lasers would momentarily shine upwards and accelerate. They would hit these sails. They'd be like a power source for the sail. And would accelerate the sails to travel at about a 20th the speed of light. And they would – Is that as crazy as it sounds? Well, like any good engineering project, it has to be broken down into the crazy parts. And the Breakthrough Initiative, to their huge credit, is sponsoring getting over these – actually, initially, they listed 19 challenges. This is broken down into concrete things. Like one of them is, well, you have to buy the land, and you have to build the ship, one of them is, well, you have to buy the land and make sure the airspace is okay with you sending up that much power overhead. Another one is you have to have material on the sail where the lasers won't just vaporize it. So there's a lot of issues. But anyway, these sails would be accelerated to 20th the speed of light, and their journey to the nearest star would no longer be tens of thousands of years, but could be 20 years. Okay, 20. So it's not as bad as tens of thousands. CB. Yeah. CM And these thousands or however many make it, they'll go by the nearest star system and snap some images and radio the information back to Earth. Because they're traveling so fast, they can't slow down. But they'll zoom by, take some photos, send it back. CB Hi-res. CM But see, just what I want you to pause on for a second is that just by making that a real concept – and the money given won't make it happen – but what it's done is it's planted the seed. And it's shifted that line from what is crazy to what is a real project. It's shifted it just ever so slightly enough, I think, to plant the seed that we have to find a way to somehow find a way to get there. CB That is, again, to stay on that, that is so powerful. Take a big crazy idea and break it down into smaller crazy ideas, order it in a list, and knock it out one at a time. I don't know, I've never heard anything more inspiring from an engineering perspective, because that's how you solve the impossible things. So you open your new book discussing rogue planet PSO J318. I never said this out loud. Point five twenty-two. So a rogue planet, which is just this poetic, beautiful vision of a planet that, as you write, lurches across the galaxy like a rudderless ship wrapped in perpetual darkness, its surface swept by constant storms, its black skies raining molten iron. Just like the vision of that, the scary, the darkness, just how not pleasant it is for human life. Just the intensity of that metaphor. I don't know. And the reason you use that is to paint a feeling of loneliness. I think. And despair. And why, maybe on the planet side, why does it feel, maybe it's just me, why does it feel so profoundly lonely on that kind of planet? I think it's because we all want to be a part of something. A part of a family or a part of a community or a part of something. And so our solar system, and by the way, it's sort of like when you treat yourself to eating an entire tub of ice cream. I sometimes treat myself to imagine things like this and not just be so cut and dried. But when you imagine that, this planet's not part, because I don't want to give emotions to a planet per se, but the planet's not part of anything. It's somehow, it's just all on its own, just kind of out there without that warm energy from its sun. It's just all alone out there. To me it was this little discovery that I actually feel pretty good being part of this solar system. It felt like we have a sun, we have like a little family. And it felt like it sucked for the rogue planet to just floating about, not floating, flying rudderless. By the way, how many rogue planets are there in your sun? We don't know totally. I mean, there's some rogue planets that are just born on their own. I know that sounds really weird to be, how can you be born an orphan? But they just are. Because most planets are born out of a disk of gas and dust around a star. But some of these small planets are like totally failed stars. They're so failed, they're just small planets on their own. But we think that there's probably, honestly, there's another path to a rogue planet. That's one that's been kicked out of its star system by other planets, like a game of billiard balls. Something just gets kicked out. We actually think there's probably as many rogue planets as stars. No flying out there, fundamentally alone. So the book is a memoir, is about your life. And it weaves both your fascination with planets outside the solar system and the path of your life. And you lost your husband, which is a kind of central part of the book that created a feeling of the rogue planet. By the way, what's the name of the book? The name of the book is The Smallest Lights in the Universe. What's up with the title? What's the meaning? The title has a double meaning. On the face of it, it's the search for other Earths. Earths are so dim compared to the big, bright, massive star beside them. Searching for the Earths is like searching for the smallest lights in the universe. It has this other meaning too. I really hope that you or the other people listening never get to the place where you're just you've fallen off the cliff into this horrible place of huge despair. And once in a while you get a glimmer of a better life, of some kind of hope. And those are also the smallest lights in the universe. Well, maybe we can tell the full story before we talk about the glimmer of hope. What did it feel like to first find out that your husband Mike was sick? It was incredibly frustrating. Like lots of us have had some kind of problem that the doctors completely ignore. Just that they kept blowing him off. It's nothing. Are they paid to just say it's nothing? I mean, it's just insane. I was just so angry. And we finally got to a point where he was really sick. He was like in bed, not able to move basically. And it turned out all the things they ignored and not done any tests, he had like a 100% blockage in his intestine. Like 100%. Like nothing could get out, nothing could get in. And it was pretty, pretty shocking to even hear then that it could be nothing. What was the progression of it in the context of the maybe the medical system, the doctors? I mean, what did it feel like? Did you feel like a human being? I felt like a child. Like the doctors were trying to water down the real diagnosis or treat us like we couldn't know the truth or they didn't know. I felt mixed. Like it's not a good situation if you think the doctor either has no idea what he or she is doing or if the doctor's purposely, let's just say lying to you to sugarcoat it. Like I didn't know which one of it was, but I knew it was one of those. What were the things he was suffering from? Well initially he just had a random stomach ache. I hate to say that out loud because I know a lot of people will have a random stomach ache. But so he just had a bad stomach ache and then, hmm, this is weird. A few days later, another bad stomach ache, kind of gets worse, might go away for a few weeks, might come back. And at the time, all I knew was my dad had had that same thing. Not the same identical system, but he had these really weird pains and he ended up having the worst diagnosis. One of the worst diagnoses you can get from a random stomach ache is pancreatic cancer because the time, the pancreas, you can't feel anything, so by the time you feel pain, it's too late, it's spread already. So I was just beside myself. I'm like, this is like, wow, this guy, he's got a random stomach ache. All I know is another man I loved had a random stomach ache and it didn't end well. How did you deal with it emotionally, psychologically, intellectually, as a scientist? What was that like? That whole, because it's not immediate, it's a long journey. It's a long journey and you don't know where the diagnosis is going. So anyone who's suffered from a major illness, there's like always branches in the road. So he had this intestinal blockage. I can't imagine someone in their 40s having that and that be normal. But the doctor's like, it could be nothing. You could just cut it out. You don't need most of your intestine. It's a repeating pattern. Just cut that out. It could be fine. But it ended up not being fine and he was diagnosed as being terminally ill. Well, it really changed my life in a huge way. First of all, I remember immediately one summer, the summer when this happened, I started asking everyone I knew. I would ask you, I don't know if it's my job to put you on the spot, I'd say, you have one year to live or two or three. What will you do differently about your life now? Lex, you have one year to live. What would you do? I mean, it's hard. I don't know if you want to answer that. No, no, no, no. I think about it a lot. I mean, that's a really good thing to meditate on. We can talk about maybe how, why you bring that up, if it is or not a heavy question. But I get, I think about mortality a lot. And for me, it feels like a really good way to focus in on is what you're doing today, the people you have around you, the family you have, does it bring you joy? Does it bring you fulfillment? And basically, for me, long ago, try to be ready to die any day. So like today, I kind of woke up, look, if I was nervous about talking to you, I really admire your work. The book is very good and it's a super exciting topic. But then there's this also feeling like if this is the last conversation I have in my life, if I die today, will this be the right, am I glad today happened? And it is. And I am glad today happened. So that's the way. And that's so unique. I never got that answer from a single person. The busyness of life, there's goals, there's dreams, there's like planning, plans. And very few people make it happen. That's what I learned. And so a lot of these people. Oh, like you run out of time. It's not so much run out of time, but I'd come back later and be like, okay, why don't you do that? And if that's what you would do, if you're going to die a year from now, why don't you make it real? Real things, spend more time with family. Like why don't you do that? And no one had an answer, it turns out, unless you usually, unless you have, you really do have a pressing end of life. People don't do their bucket list or try to change their career. And some people can't. So we can't, like for a lot of people, they can't do anything about it. And that's fine. But the ones who can take action for some reason never do. And that was one of the ways that Mike's death or at the time his impending death really, really affected me. Because, you know, for these sick people, what I learned, he had a bucket list and he was able to do some of the bucket list. It was awesome. But he got sick pretty quickly. So if you do only have a year to live, it's ironic because you can't do the things you wanted to do because you get too sick too fast. What were the bucket list things for you that you realized like, what am I doing with my life? That was the major concept of him. After he died, I didn't know. Like I was just lost because when something that profound happens, all the things I was doing, most of the things I was doing were just meaningless. It was so tough to find an answer for that. And that's when I settled on I'm going to devote the rest of my life to trying to find another earth and to find out, to find that we're not alone. What is that longing for connection with others? What's that about? What do you think? Why is that so full of meaning? I don't know why. I mean, I think it's how we're hardwired. Like one of my friends some time ago, actually when my dad died, he never heard someone say this before, but he's like, Sarah, you know, why are we evolved to take death so harshly? Like what kind of society would we be if we just didn't care people died? That would be a very different type of world. How would we as a species have got to where we are? So I think that is tied hand in hand with why do we seek connection? It's just that what we were talking about before, that subconsciousness that we don't understand. Yeah, coupled, you know, the other side, the flip side of the coin of connection and love is a fear of loss. It's like that was again, I don't know, it's so it makes you appreciate the moment is that the thing ends. Yeah, that's definitely a hard one. The thing ends, but what? And it's hard to not, you wouldn't want to limit like it's like my dog who I love so much I'll start to cry. Like I can't think about the end. I know he'll age much faster than I will. And someday it will end, right? But it's too sad to think of. But should I not have got a dog? Should I have not brought this sort of joy into my life because I know it won't be forever? It's... Well, there's a philosopher, Ernest Becker, who wrote a book, Denial of Death, and just and Warm of the Cores, and there's another book talks about terror management theory. Sheldon Solomon, I just talked to him a few weeks ago, is a brilliant philosopher, psychologist that their theory, whatever you make of it, is that the fear of death is at the core of everything we do. So like you're... You think you don't think about the mortality of your dog, but you do. And that's what makes the experience rich. Like there's this kind of like in the shadows lurks the knowledge that this won't last forever. And that makes every moment just special in some kind of weird way that the moments are special for us humans. I mean, sorry to use romantic terms like love, but what do you make... What did you learn about love from losing it, from losing your husband? Well, I learned to love the things I have more. I learned to love the people that I have more and to not let the little things bother me as much. What about the rediscovery or like the discovery of the little lights in the darkness? So the book, I think you've brilliantly described the dark parts of your journey, but maybe can you talk about how you were able to rediscover the lights? They came in many ways. And the way to think about it is like grief is an ocean. It was tiny islands of the little lights and eventually that ocean gets smaller and smaller and the islands like become continents with lakes. So initially it'd be like the children laughing one day or my colleagues at work who rallied around me and would take me away from my darkness to work on a project. Later on, it turned out to be a group of women my age, all widows, all with children in my town. And it would be, even though it was a bit morose getting together, still very joyful at the same time. What was the journey of rediscovering love like for you? So refinding, I mean, is there some, by way of advice or insight about how to rediscover the beauty of life? Of life? It's a hard one. I think you just have to stay open to being positive and just to get out there. Do you still think about your own mortality? You mentioned that that was a thing that you would meditate on as a question when it was right there in front of you, but do you still think about it? I think I will after talking to you. But no, it's not really something I think about. I mean, I do think about the search for another earth and will I get there? Will I be able to conclude my search and is there one? I guess time goes by, that window to solve that problem gets smaller. What would bring you, again, I apologize if this makes concrete the fact that life is finite, but what would bring you joy if we discovered while you're still here? What would bring me joy? Finding another earth, an earth-like planet around a sun-like star, knowing that there's at least one or more out there, being able to see water, that it has signs of water and being able to see some gases that don't belong. So I know that the search will continue after I'm gone, enough to fuel the next generation. So just like opening the door and there's like this glimmer of hope. What do you think it will take to realize that? I mean, we've talked about all these interesting projects, Starshade especially, but is there something that you're particularly kind of hopeful about in the next 10, 20 years that might give us that exact glimmer of hope that there's earth-like planets out there? I stand behind Starshade in all cases, but there is this other kind of field that everyone is involved in because Starshade is hard. Earths are hard. But there's another category of planet star type that's easier, and these are planets orbiting small red dwarf stars. They're not earth-like at all. Think like Earth Cousin instead of Earth Twin. But there's a chance that we might establish that some of those have water and signs of life on them. That's nearer term than Starshade, and we're all working hard on that too. Let me ask, by way of recommendations, I think a lot of people are curious about this kind of stuff. Which of the three books, technical or fiction or philosophical or anything really, had an impact on your life and or you would recommend, besides of course your book? There's one book I wish everyone could read. I'm not sure if you've read it. It's actually a children's book, like a young adult book. It's called The Giver. Yes. And it is the book that kids in school read now. Sorry, that's wow. Sorry, that caught me off guard. So when I first came to this country, I didn't speak much. It's really what made me, it had a profound impact on my life. And at a really important moment, because they give it to kids. I think I was in middle school, I think, or maybe elementary. Yeah, something like that. I'm so surprised you've even heard of this book. Yeah, so they gave it, but like it's the value of giving the right book to a person at the right time. Because it's very accessible. Do we want to share what the story is without spoiling it? Yeah, you can without spoiling, right? Well, it follows this boy in this very utopic society that's like perfect. It's been all clean cut and made perfect, actually. And as he kind of comes of age, he starts realizing something's wrong with his world. And so it's part of that question, are we going to evolve as he, I mean, this isn't what's there, but it made me wonder, are we evolving to a better place? Is there a day when we can eliminate poverty and hunger and crime and sickness? And this book they pretty much have in a society that the boy's in. And it sort of follows him, and he becomes a chosen one to be like a receiver, the giver's the old wise man who retains some of the harshness of the outside world so that he can advise the people. And as this sort of boy comes of age and is chosen for this special role, he finds the world isn't what he expects. And I don't know about you, but it was so profound for me because it jolts you out of reality. It's like, oh my God, what am I doing here? I'm just going with the flow with my society. How do I think outside the box and the confines of my society, which surely carries negative things with it that we don't realize today? Yeah. And also in the flip side of that is if you do take a step outside the box on occasion, what's the psychological burden of that? Like is that a step you want to take? Is that a journey you want to take? What is that life like? I don't know. I felt like from the book you have to take it. I found from the book. I never thought, like now that you're saying it, I see what you're saying. The burden is huge, but I always felt like the answer is yes, you absolutely want to know what's outside. But you can't do that if you're very, it's hard to be objective about your own reality. Yeah. I mean, it's a very human instinct, but it also, the book kind of shows that it has an effect on you. It's a really interesting question about our society and taking a step out. It's by Lois Lowry, I think is how you pronounce it. I really do hope everyone can read it. And it is a young adult book, but it's still, it's incredibly, I'm really glad. I only read it because my kids got it for school. I just thought, okay, well, why don't I just see what this is about? And I just, wow. Yeah. Yeah. I think it's also the value of education. I think, I'm surprised you mentioned it. I've never really mentioned to anybody. I'm sure a lot of people had similar experience like me and maybe. It's a generational thing though, because the book came out, I think in the nineties. So if you're older than like me, that book didn't exist when we were in middle school. So I just do think a lot of people won't have heard of it. But it's an interesting question of like those books. I mean, I'm reminded often, I suppose the same is true as with other subjects, but books are special. So at early age, like middle school, maybe early high school, those can change the direction of your life. And also certainly teachers, they can change completely the direction of their life. There's so many stories about teachers of mathematics, teachers of physics, of any kind of subjects basically changing the direction of a human's life. It's like, not to get into the whole, almost like a political thing, but we undervalue teachers. It's a special position that they hold. That's so true. Yeah. Well, I do have two other books or two other things. One is something I came across just a few days ago, actually. It's actually a film called Picture a Scientist. And when you picture a scientist, you probably don't picture the women and women of color in this film. And it is a way to get outside your box. I really think everyone interested in science, even just peripherally, should watch this because it is shocking and sobering at the same time. And it talks about how, well, I think one of the messages across is, you know, we really are like, I don't know if we're hardwired to just like people like ourselves, but we're excluding a lot of people and therefore a lot of great ideas by not being able to think outside of how we're all stereotyping each other. So it's hard to kind of convey that. And you can just say, oh, yeah, I want to be more diverse. I want to be more open. But it's a nearly impossible problem to solve. And the movie really helps open people's eyes to it. This book I put third because unlike The Giver, people may not want to read it. It's not as relevant. But when I was in my early 20s, I went to this big, this like 800 people large conference run by the Wilderness Canoe Association in my hometown of Toronto. And there was a family friend there who I met. And he said, read this book, it'll change your life. And it actually changed my life. And it was a book called Sleeping Island by an author, P.G. Downs, who just coincidentally lived in this area, lived in the Boston area. And he was a teacher. I think at a private school. And every summer he would go to Canada with a canoe, often by himself. And he wrote this book maybe in the 40s or 50s about a trip he took in the late 1930s. And I was just shocked that even at that time, although that was a long time ago, there were large parts of Canada that were untouched by white people. And he went up there and interacted like with the natives. He called the book, it had a subtitle that was called, it was something like Journey in the Barren Lands. And when you go up north in Canada, you pass the tree line, just like on a mountain, if you hike up a mountain, you get so far north there aren't any trees. And he wrote eloquently about the land and about being out there. There weren't even any maps of the region in that time. And I just thought to myself, wow, that you could just take the summer off and explore by canoe and go and see what's out there. And it led to me just doing that, that very thing. Of course, it's different now. But going out to where the road ends and putting the canoe in the water and just, well, we had to have a plan. We didn't just explore, but go down the rivers with rapids and travel over lakes and portages and just really live. So just really explore. Screw it. That doesn't, like, it doesn't. Explore again. Explore just use from a topo map, from a topographical map from the library. That's scary? There were scary elements about it, out of it. But part of the excitement or the joy or the desire was to be scared. Like, it was to go out there and have live on the edge. And persevere. Yeah. And persevere, yeah. Do you have advice that you would give to a young person today that would like to help you maybe on the planetary science side, discover exoplanets or maybe bigger picture, just succeed in life? I do have some advice just to succeed. It's tough advice in a way, but it is to find something that you love doing that you're also very good at. In some ways, the stars have to align because you've got to find that thing you're good at or the range of things. And it actually has to overlap with something that actually you love doing every day. So it's not a tedious job. That's the best way to succeed. What were the signals that in your own life were there to make you realize you're good at something? Like, what were you good at that made you pursue a PhD and it made you pursue the search? I mean, that was the one sentence version. In my case, it was a long slog and there were a lot of things I wasn't good at initially. But so initially, I was good at high school math. I was good at high school science. I loved astronomy. And I realized those could all fit together. Like the day I realized you could be an astronomer for a job, it has to be one of my top days of my life. I didn't know that you could be that for a job. And I was good at all those things. And although my dad wanted me to do something more practical where he could be guaranteed I could support myself was another option. But initially, I wasn't that good at physics. It was a slog to just get through school and grad school. It's a very, very long time. But ultimately, when faced with a choice and I had the luxury of choosing, knowing that I was good at something and also loved it, it really carried me through. Now, I asked some of the smartest people in the world the most ridiculous question. We already talked about it a little bit, but let me ask again, why are we here? So I think you've raised this question in one of your presentations as like one of the things that we kind of as humans long to answer and the search for exoplanets is kind of part of that. But what do you think is the meaning of it all, of life? I wish I had a good answer for you. I think you're the first person ever who refused to answer the question. It's not so much refusing. I just, yeah, I mean, I wish I had a better answer. It's why we're here. It's almost like the meaning is wishing there was a meaning, wishing we knew. I love that. That's a great way to say it. Sarah, like I said, the book is excellent. I admired your work from afar for a while. I think you're one of the great stars at MIT. It makes me proud to be part of the community. So thank you so much for your work. Thank you for inspiring all of us. Thanks for talking today. Thank you so much, Lex. Thanks for listening to this conversation with Sarah Seeger and thank you to our sponsors, Public Goods, PowerDot and Cash App. Click the links in the description to get a discount. It's the best way to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Firestarz on Apple Podcasts, support it on Patreon, connect with me on Twitter, Alex Friedman, spelled I'm not sure how. Just keep typing stuff in until you get to the guy with the tie in the thumbnail. And now let me leave you with some words from Carl Sagan. Somewhere, something incredible is waiting to be known. Thank you for listening and hope to see you next time.

https://youtu.be/-jA2ABHBc6Y

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Consciousness is an Explanation of What Already Has Been Computed (John Hopfield) | AI Podcast Clips

Let alone consciousness. Let alone consciousness, yes, yes. Because that's tied up in there too. You can't just put that on another shelf. Every once in a while I get interested in consciousness, and then I go and I've done that for years, and ask one of my bettors, as it were, their view on consciousness. It's been interesting collecting them. What is consciousness? Let's try to take a brief step into that room. Well, I asked Marvin Minsky, did you go on consciousness? And Marvin said, consciousness is basically overrated. It may be an epiphenomenon. After all, all the things your brain does, which are actually hard computations, you do non-consciously. And there's so much evidence that even the simple things you do, you can make decisions, you can make committed decisions about them. The neurobiologist can say, he's now committed, he's going to move the hand left, right, left, left, before you know it. So, his view that consciousness is not… that's just like little icing on the cake. The real cake is in the subconscious. Yeah, subconscious, non-conscious. Non-conscious, what's the better word, sir? It's only that Freud captured the other word. Yeah, that's a confusing word, subconscious. Nicholas Chater wrote an interesting book. I think the title of it is The Mind is Flat. And flat, in a neural net sense, might be flat is something which is a very broad neural net without really any layers in depth, whereas a deep brain would be many layers and not so broad. In the same sense that if you push Minsky hard enough, he would probably have said, consciousness is your effort to explain to yourself that which you have already done. Yeah, it's the weaving of the narrative around the things that have already been computed for you. That's right. And so much of what we do for our memories of events, for example, if there's some traumatic event you witness, you will have a few facts about it correctly done. If somebody asks you about it, you will weave a narrative which is actually much more rich in detail than that, based on some anchor points you have of correct things, and pulling together general knowledge on the other, but you will have a narrative. And once you generate that narrative, you are very likely to repeat that narrative and claim that all the things you have in it are actually the correct things. There was a marvelous example of that in the Watergate slash impeachment era of John Dean. John Dean, you're too young to know, had been the personal lawyer of Nixon. And so John Dean was involved in the cover-up, and John Dean ultimately realized the only way to keep himself out of jail for a long time was actually to tell some of the truths about Nixon. And John Dean was a tremendous witness. He would remember these conversations in great detail, and very convincing detail. And long afterward, some of the tapes, the secret tapes as it were, from which these, John was, Dean was recalling these conversations, were published. And one found out that John Dean had a good, but not exceptional, memory. What he had was an ability to paint vividly, and in some sense accurately, the tone of what was going on. By the way, that's a beautiful description of consciousness. Do you, like where do you stand in your, today? So perhaps this changes day to day, but where do you stand on the importance of consciousness in our whole big mess of cognition? Is it just a little narrative maker, or is it actually fundamental to intelligence? That's a very hard one. When I asked Francis Crick about consciousness, he launched forward in a long monologue about Mendel and the peas. Yeah. And how Mendel knew that there was something, and how biologists understood that there was something in inheritance, which was just very, very different. And the fact that inherited traits didn't just wash out into a gray, but were this or this, and propagated. That was absolutely fundamental to biology, and it took generations of biologists to understand that there was genetics, and it took another generation or two to understand that genetics came from DNA. But very shortly after Mendel, thinking biologists did realize that there was a deep problem about inheritance. And Francis would have liked to have said, and that's why I'm working on consciousness. But of course, he didn't have any smoking gun in the sense of Mendel. And that's the weakness of his position. If you read his book, which he wrote with Koch, I think. Yeah, Christoph Koch, yeah. I find it unconvincing for the smoking gun reason. So I've gone on collecting views without actually having taken a very strong one myself, because I haven't seen the entry point. Not seeing the smoking gun from the point of view of physics, I don't see the entry point. Whereas in neurobiology, once I understood the idea of a collective, an evolution of dynamics, which could be described as a collective phenomenon, I thought, ah, there's a point where what I know about physics is so different from any neurobiologist that I have something I might be able to contribute. And right now there's no way to grasp at consciousness from a physics perspective. From my point of view, that's correct. And of course, people, physicists like everybody else, think very muddily about things. You ask the closely related question about free will. Do you believe you have free will? Physicists will give an offhand answer, and then backtrack, backtrack, backtrack, where they realize that the answer they gave must fundamentally contradict the laws of physics. Naturally, answering questions of free will and consciousness naturally lead to contradictions from a physics perspective, because it eventually ends up with quantum mechanics, and then you get into that whole mess of trying to understand how much, from a physics perspective, how much is determined, already predetermined, how much is already deterministic about our universe. There's lots of different… And if you don't push quite that far, you can say, essentially all of neurobiology, which is relevant, can be captured by classical equations of motion. Right. Because in my view of the mysteries of the brain are not the mysteries of quantum mechanics, but the mysteries of what can happen when you have a dynamical system, a quantum driven system, with 10 to the 14 parts. That complexity is something which is… The physics of complex systems is at least as badly understood as the physics of phase coherence in quantum mechanics.

https://youtu.be/KrdZ46MfNrM

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Elon Musk as Inspiration for Science Fiction (Alex Garland) | AI Podcast Clips

Drawing inspiration from real life, so for devs, for Ex Machina, look at characters like Elon Musk. What do you think about the various big technological efforts of Elon Musk and others like him that he's involved with, such as Tesla, SpaceX, Neuralink? Do you see any of that technology potentially defining the future worlds you create in your work? So Tesla is automation, SpaceX is space exploration, Neuralink is brain-machine interface, somehow a merger of biological and electric systems. In a way I'm influenced by that almost by definition because that's the world I live in and this is the thing that's happening in that world. And I also feel supportive of it. So I think amongst various things Elon Musk has done, I'm almost sure he's done a very, very good thing with Tesla for all of us. It's really kicked all the other car manufacturers in the face, it's kicked the fossil fuel industry in the face and they needed kicking in the face and he's done it. And so that's the world he's part of creating and I live in that world, just bought a Tesla in fact. And so does that play into whatever I then make? In some ways it does, partly because I try to be a writer who quite often filmmakers are in some ways fixated on the films they grew up with and they sort of remake those films in some ways. I've always tried to avoid that. And so I look to the real world to get inspiration and as much as possible sort of by living I think. And so yeah, I'm sure. Which of the directions do you find most exciting? Space travel. Space travel. So you haven't really explored space travel in your work. You've said something like if you had unlimited amount of money, I think I read it at AMA, you would make like a multi-year series of space wars or something like that. So what is it that excites you about space exploration? Well, because if we have any sort of long-term future, it's that. It just simply is that. If energy and matter are linked up in the way we think they're linked up, we'll run out if we don't move. So we got to move. But also how can we not? It's built into us to do it or die trying. I was on Easter Island a few months ago, which is, as I'm sure you know, in the middle of the Pacific and difficult for people to have got to, but they got there. And I did think a lot about the way those boats must have set out into something like space. It was the ocean and how sort of fundamental that was to the way we are. And it's the one that most excites me because it's the one I want most to happen. It's the thing, it's the place where we could get to as humans. Like in a way I could live with us never really unlocking, fully unlocking the nature of consciousness. I'd like to know, I'm really curious, but if we never leave the solar system and if we never get further out into this galaxy or maybe even galaxies beyond our galaxy, that feels sad to me because it's so limiting. There's something hopeful and beautiful about reaching out, any kind of exploration, reaching out across earth centuries ago and then reaching out into space. So what do you think about colonization of Mars? So go to Mars. Does that excite you, the idea of a human being stepping foot on Mars? It does. It absolutely does. But in terms of what would really excite me, it would be leaving the solar system in as much as that I just think, I think we already know quite a lot about Mars. And but yes, listen, if it happened, that would be, I hope I see it in my lifetime. I really hope I see it in my lifetime. It would be a wonderful thing.

https://youtu.be/ApVFK3FjgMI

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Clara Sousa-Silva: Searching for Signs of Life on Venus and Other Planets | Lex Fridman Podcast #195

The following is a conversation with Clara Souza Silva, a quantum master chemist at Harvard, specializing in spectroscopy of gases that serve as possible signs of life on other planets, most especially the gas phosphine. She was a co-author of the paper that in 2020 found that there is phosphine in the atmosphere of Venus and thus possible extraterrestrial life that lives in its atmosphere. The detection of phosphine was challenged, reaffirmed, and is now still under active research. Quick mention of our sponsors Onnit, Grammarly, Blinkist, and Indeed. Check them out in the description to support this podcast. As a side note, let me say that I think the search for life on other planets is one of the most important endeavors in science. If we find extraterrestrial life and study it, we may find insights into the mechanisms that originated life here on earth, and more than life, the mechanisms that originated intelligence and consciousness. If we understand these mechanisms, we can build them. But more than this, the discovery of life on other planets means that our galaxy and our universe is teeming with life. This is humbling and terrifying, but it is also exciting. We humans are natural explorers. For most of our history, we explored the surface of the earth and the contents of our minds. But now, with space-faring vessels, we have a chance to explore life beyond earth, their physics, their biology, and perhaps the contents of their minds. This is the Lex Friedman Podcast, and here is my conversation with Clara Souza Silva. Since you're the world expert in, well, in many things, but one of them is phosphine, would it technically be correct to call you the Queen of Phosphine? I go for Dr. Phosphine. Queen is an inherited title, I feel. But you still rule by love and power, so, but while having the doctor title. I got it. Kindness. Kindness, kindness. In September 2020, you co-authored a paper announcing possible presence of phosphine in the atmosphere of Venus, and that it may be a signature of extraterrestrial life. Big maybe. Big maybe. There was some pushback, of course, from the scientific community that followed. Friendly, loving pushback. Then in January, another paper from University of Wisconsin, I believe, confirmed the finding. So, where do we stand in this saga, in this mystery of what the heck is going on on Venus, in terms of phosphine and in terms of aliens? Okay, let's try to break it down. Okay. The short answer is we don't know. I think you and the rest of the public are now witnessing a pretty exciting discovery, but as it evolves, as it unfolds, we did not wait until we had years of data from 10 different instruments across several layers of the atmosphere. We waited until we had two telescopes with independent data months apart. But still, the data is weak, it's noisy, it's delicate, it's very much at the edge of instrument sensibility, sensitivity. And so, we still don't even know if it is phosphine. We don't even really know if the signal is real. People still disagree about that. And I think at the more philosophical end of how this happened, I think it is a distinction, and myself and other co-authors were talking about this, it's a distinction between hypotheses generation and hypotheses testing. Now, hypothesis testing is something that I think is the backbone of the scientific method, but it has a problem, which is if you're looking through very noisy data and you want to test the hypotheses, you may by mistake create a superior signal. The safest, more conservative approach is hypothesis generation. You see some data and you go, what's in there with no bias? Now, this is much safer, much more conservative. And when there's a lot of data, that's great. When there isn't, you can clean the noise and take out the signal with it, the signal with the bathwater, whatever the equivalent of the analogy would be. And so, I think the healthy discourse that you described is exactly this. There are ways of processing the data, completely legitimate ways, checked by multiple people and experts where the signal shows up and then phosphine is in the atmosphere of Venus and some where it doesn't. And then we disagree what that signal means. If it's real and it is an ambiguously phosphine, it is very exciting because we don't know how to explain it without life. But going from there to Venusians is still a huge jump. And so- Venusians. So, that would be the title for the civilization if it is a living and thriving on Venus's Venusians. Until we know what they call themselves, that's the name, yes. So, this is the early analysis of data or analysis of early data. It was nevertheless, you waited until the actual peer-reviewed publication to- Of course. And analysis of the two different instruments months apart. So, that's ALMA and JCMT, the two telescopes. I mean, it's still, I mean, it's really exciting. What did it feel like sort of sitting on this data? Like kind of anticipating the publication and wondering, and still wondering, is it true? Like how does it make you feel that a planet in our solar system might have phosphine in the atmosphere? It's nuts. It's absolutely nuts. In a- I mean- In the best possible way? I've been working on phosphine for over a decade. Before it was cool. Before it was cool. Before anyone could spell it or heard of it. And at the time, people either didn't know what phosphine was or only knew it for being just possibly the most horrendous molecule that ever graced the Earth. And so, no one was a fan. And I'd been considering looking for it because I did think it was an unusual and disgusting but very promising sign of life. I've been looking for it everywhere. I really didn't think to look in the solar system. I thought it was all pretty rough around here for life. And so, I wasn't even considering the solar system at all, never mind next door Venus. It was only the lead author of the study, Jane Greaves, who thought to look in the clouds of Venus and then reached out to me to say, I don't know phosphine, but I know it's weird. How weird is it? And the answer is very weird. LR And so, the telescopes were looking at- this is visual data. LS That's what I mean by visual. You wouldn't see the phosphine. LR Well, but I mean, it's a telescope. LS It's remote. LR It's remote. You're observing, you're what, zooming in on this particular planet. I mean, what does the sensor actually look like? How many pixels are there? What does the data kind of look like? It'd be nice to kind of build up intuition of how little data we have based on which. I mean, if you look at like, I've just been reading a lot about gravitational waves. And it's kind of incredible how from just very little, like probably the world's most precise instrument, we can derive some very foundational ideas about our early universe. And in that same way, it's kind of incredible how much data, how much information you can get from just a few pixels. So, what are we talking about here in terms of based on which this paper saw possible signs of phosphine in the atmosphere? LS So, phosphine, like every other molecule, has a unique spectroscopic fingerprint, meaning it rotates and vibrates in special ways. I calculated how many of those ways it can rotate and vibrate, 16.8 billion ways. What this means is that if you look at the spectrum of light, and that light has gone through phosphine gas on the other end, there should be 16.8 billion tiny marks left, indentations left in that spectrum. We found one of those on Venus, one of those 16.8 billion. So, now the game is, can we find any of the other ones? CB Yeah. LS But they're really hard to spot. They're all in terrible places in the electromagnetic spectrum. And the instruments we use to find this one can't really find any other one. There's another one of the 16.8 billion we could find, but it would take many, many days of continuous observations, and that's not really in the cards right now. LR I mean, how do you, there's all kinds of noise, first of all. LS Yes. LR There's all kinds of other signal. So, how do you separate all of that out to pull out just this particular signature that's associated with phosphine? CB So, the data kind of looks somewhat like a wave, and a lot of that is noise, and it's a baseline. And so, if you can figure out the exact shape of the wave, you can cancel that shape out, and you should be left with a straight line, and if there's something there, an absorption, so a signal. So, that's what we did. We tried to find out what was this baseline shape, cleaned it out, and got the signal. That's part of the problem. If you do this wrong, you can create a signal. But that signal is at 8.904 wave numbers, and we actually have more digits than that, but I don't remember by heart. And ALMA in particular is a very, very good telescope, array of telescopes, and it can focus on exactly that frequency. And in that frequency, there are only two known molecules that absorb it all. So, that's how we do it. We look at that exact spot where we know phosphine absorbs the other molecules, SO2. LR If there is extraterrestrial life, whether it's on Venus or on exoplanets where you looked before, how does that make you feel? How should it make us feel? Should we be scared? Should we be excited? Let's say it's not intelligent life. Let's say it's microbial life. Is it a threat to us? Are we a threat to it? Or is it only, not only, but mostly, possibly to understand something fundamental, something beautiful about life in the universe? LS Hard to know. You would have to bring on a poet or a philosopher on the show. CB I feel those things. I just don't know if those are the right things to feel. I certainly don't feel scared. I think it's rather silly to feel scared. Definitely don't touch them. Sometimes in the movies, don't go near it. Don't interfere. I think one of the things with Venus is because of phosphine, now there is a chance that Venus is inhabited. In that case, we shouldn't go there. We should be very careful with messing with them, bringing our own stuff there that contaminates it. Venus has suffered enough. If there's life there, it's probably the remains of a living planet, the very last survivors of what once was potentially a thriving world. And so, I don't want our first interaction with alien life to be a massacre. So, I definitely wouldn't want to go near out of a, let's say, galactic responsibility, galactic ethics. And I often think of alien astronomers watching us and how disappointed they would be if we messed this up. So, I really want to be very careful with anything that could be life. But certainly, I wouldn't be scared. Humans are plenty capable of killing one another. We don't need extraterrestrial help to destroy ourselves. LRSKY-CB2 I'm scared mostly of other humans. DGNAEYS Exactly. LRSKY-CB2 But this life, if there is life there, it does seem just like you said, it would be pretty rugged. It's like the cockroaches or Chuck Norris. I don't know. It's something that survived through some very difficult conditions. DGNAEYS That doesn't mean it would handle us. It could be like War of the Worlds. Just because you're resilient in your own planet doesn't mean you can survive another. Even our extremophiles, which are very impressive, we should all be very proud of our extremophiles, they wouldn't really make it in the Venusian clouds. So, I wouldn't expect, because you're tough, even Chuck Norris tough, that you would survive on an alien planet. LRSKY-CB2 And then from the scientific perspective, you don't want to pollute the data gathering process by showing up there. The observer can affect the observed. DGNAEYS How heartbreaking would it be if we found life on another planet and then we're like, oh, we brought it with us. It was my sandwich. LRSKY-CB2 But that's always the problem, right? And certainly a problem with Mars, because we visited. If there is life on Mars or remains of life on Mars, it's always going to be a question of like, well, maybe we planted it there. DGNAEYS Let's not do the same with Venus. It's harder because when we try to go to Venus, things melt very quickly. And so, it's a little harder to pollute Venus. It's very good at destroying foreigners. LRSKY-CB2 Yeah. Well, in terms of Elon Musk and terraforming planets, Mars is stop number one, then Venus maybe after that. So, can we talk about phosphine a little bit? So, you mentioned it's a pretty- DGNAEYS Love phosphine. LRSKY-CB2 What's your Twitter handle? It's like Dr. Phosphine? DGNAEYS It's Dr. Phosphine, yes. You'll be surprised here. It wasn't taken already. I just grabbed it. Didn't have to buy it off anyone. LRSKY-CB2 Yeah. So, what is it? What's phosphine? You already mentioned it's pretty toxic and DGNAEYS Troublesome. LRSKY-CB2 And outside- DGNAEYS Troublesome. LRSKY-CB2 Troublesome. Sorry. LRSKY-CB2 No, I love it. I'm going to stop calling it troublesome. DGNAEYS So, maybe what are some things that make it interesting chemically? And why is it a good sign of life when it's present in the atmosphere like you've described in your paper aptly titled the phosphine as a biosignature gas in exoplanet atmospheres? I suppose you wrote that paper before Venus. LRSKY-CB2 I did, yes. And no one cared. In that paper, I said something like, if we find phosphine on any terrestrial planet can only mean life. And everyone's like, yeah, that sounds about right. Let's go. And then Venus shows up. And I was like, are you sure? I'm like, I was sure before I was sure. Now that it's right here, I'm less sure now that my claims are being tested. So, phosphine is a fascinating molecule. So, it's shaped like a pyramid with a phosphorus up top and then three hydrogens. It's actually quite a simple molecule in many ways. It's the most popular elements in the universe, carbon, hydrogen, nitrogen, oxygen, phosphorus, sulfur. When you add hydrogen to them, it makes quite simple, quite famous molecules. You do it to oxygen, you get water. You do it to carbon, you get methane. You do it to nitrogen, you get ammonia. These are all molecules people have heard of. But you do it to phosphorus, you get phosphine. People haven't heard of phosphine because it's not really popular on Earth. We really shouldn't find it anywhere on Earth because it is extremely toxic to life. It interacts with oxygen metabolism and everything you know and love uses oxygen metabolism. And it interacts fatally. So, it kills in several very imaginative and very macabre ways. So, it was used as a chemical warfare agent in the First World War and most recently by ISIS. So, really bad. Most life avoids it. Even life that might not avoid it, so life that doesn't use oxygen metabolism, anaerobic life, still has to put crazy amounts of effort into making it. It's a really difficult molecule to make, thermodynamically speaking. It's really difficult to make that phosphorus want to be together with that hydrogen. So, it's horrible. Everyone avoids it. When they're not avoiding it, it's extremely difficult to make. You would have to put energy in, sacrifice energy to make it. And if you did go through all that trouble and made it, it gets reacted with the radicals in the atmosphere and gets destroyed. So, we shouldn't find it anywhere and yet we do. It's kind of a weird molecule that seems to be made by life and we don't even know why. Life clearly finds a use for it. It's not the only molecule that life is willing to sacrifice energy to make, but we don't know how or why life is even making it. So, I don't know absolutely mysterious, absolutely deadly, smells horrifically. When it's made, it produces other kind of diphosphenes and it's been reported as smelling like garlicky fishy death. Once someone referred to it as smelling like the, let me see if I remember, the rancid diapers of the spawn of Satan. Yeah, very vivid. And so- You're a poet after all. I didn't call that, someone else did. And so, it's just this horrific molecule, but it is produced by life, we don't know why. And when it is produced by life, it's done with enormous sacrifice and the universe does not sacrifice, life sacrifices. And so, it's this strange contradictory molecule that we should all be avoiding and yet seems to be an almost unambiguous sign of life on rocky planets. Okay, can we dig into that a little bit? So, on rocky planets, is there biological mechanisms that can produce it? You said that why is unclear, why life might produce it, but is there an understanding of what kind of mechanisms might be able to produce it, this very difficult to produce molecule? We don't know yet. The enzymatic pathways of phosphine production by life are not yet known. This is not actually as surprising as it might sound. I think something like 80% of all the natural products that we know of, so we know biology makes them, we don't know how. It is much easier to know life produces something because you can put bacteria in a Petri dish and then watch and then that gas is produced, you go, oh, life made it. That actually happened with phosphine. But that's much easier to do, of course, than figuring out what is the exact metabolic pathway within that life form that created this molecule. So, we don't know yet. Phosphine is really understudied. No one had really heard of it until now-ish. What you were presenting is the fact that life produces phosphine, not the process by which it produces phosphine. Is there an urgency now? If you were to try to understand the mechanisms, the, what did you call them, enzymatic pathways that produce phosphine, how difficult is that of a problem to crack? It's really difficult. If I'm not mistaken, even the scent of truffles, obviously a billion dollar industry, huge deal. Until quite recently, it wasn't known exactly how those scents, those molecules that create this incredible smell were produced. This is a billion dollar industry. As you can imagine, there is no such pressure. There's no phosphine lobby or anything that would push for this research. I hope someone picks it up and does it. And it isn't crazy because we know that phosphine is really hard to make. We know it's really hard for it to happen accidentally. Even lightning and volcanoes that can produce small amounts of phosphine, it's extremely difficult for even these extreme processes to make it. So it's not really surprising that only life can do it because life is willing to make things at a cost. So maybe on the topic of phosphine, what, again, you've gotten yourself into trouble. I'm gonna ask you all these like high level poetic questions. I apologize. No, I would love it. Okay. When did you first fall in love with phosphine? It wasn't love at first sight. It was somewhere between a long relationship and Stockholm syndrome. When I first started my PhD, I knew I wanted to learn about molecular spectrum and how to simulate it. I thought it was really outrageous that we as a species couldn't detect molecules remotely. We didn't have this perfect catalog ready of the molecular fingerprint of every molecule we may want to find in the universe. And something as basic as phosphine, the fact that we didn't really know how it interacted with light, and so we couldn't detect it properly in the galaxy, I was so indignant. And so initially, I just started working on phosphine because people hadn't before. And I thought we should know what phosphine looks like. And that was it. And then I read every paper that's ever been published about phosphine. It was quite easy because there aren't that many. And that's when I started learning about where we had already found it in the universe and what it meant. I started finding out quite how little we know about it and why. And it was only when I joined MIT and I started talking to biochemists that it became clear that phosphine wasn't just weird and special and understudied and disgusting. It was all these things for oxygen-loving life. And it was the anaerobic world that would welcome phosphine. And that's when the idea of looking for it on other planets became crystallized. Because oxygen is very powerful and very important on Earth, but that's not necessarily going to be the case on other exoplanets. Most planets are oxygen-poor. Overwhelmingly, most planets are oxygen-poor. And so finding the sign of life that would be welcomed by everything that would live without oxygen on Earth seemed so cool. LBW But ultimately, the project at first was born out of the idea that you want to find that molecular fingerprint of a molecule. And this is just one example. And that's connected to then looking for that fingerprint elsewhere in a remote way. And obviously, at that time, where exoplanets already, when you were doing your PhD, and by the way, I should say your PhD thesis was on phosphine. LS It was all on phosphine, 100% on phosphine, with a little bit of ammonia. I have a chapter that I did where I talked about phosphine and ammonia. But no, phosphine was very much my thesis. LBW But at that time, when you're writing it, there was already a sense that exoplanets are out there and we might be able to be looking for biosignatures on those exoplanets? LS Pretty much. So I finished my PhD in 2015. We found the first exoplanets in the mid to late 90s. So exoplanets were known. It was known that some had atmospheres. And from there, it's not a big jump to think, well, if some have atmospheres, some of those might be habitable, and some of those may be inhabited. LBW So how do you detect? You started to talk about it, but can we linger on it? How do you detect phosphine on a faraway thing, rocky thing, rocky planet? What is spectroscopy? What is this molecular fingerprint? What does it look like? You've kind of mentioned the wave, but what are we supposed to think about? What are the tools? What are the uncertainties? All those kinds of things. LS So the path can go this way. You've got light, kind of pure light. You can crack that light open with a prism or a spectroscope or water and make a rainbow. That rainbow is all the colors and all the invisible colors, the ultraviolet, the infrared. And if that light was truly pure, you could consider that rainbow to just cover continuously all of these colors. But if that light goes through a gas, we may not see that gas. We certainly cannot see the molecules within that gas, but those molecules will still absorb some of that light, some but not all. Each molecule absorbs only very specific colors of that rainbow. And so if you know, for example, that shade of green can only be absorbed by methane, then you can watch as a planet passes in front of a star. The planet's too far away, you can't see it. And it has an atmosphere. That atmosphere is far too small, you definitely can't see it. But the sunlight will go through that atmosphere. And if that atmosphere is methane, then on the other side, that shade of blue, I can't remember if I said blue or green, but that color will be missing because methane took it. And so with phosphine, it's the same thing. It has specific colors, 16.8 billion colors, that it absorbs it and nothing else does. And so if you can find them and notice them missing from the light of a star that went through a planet's atmosphere, then you'll know that atmosphere contains the molecule. How cool is that? That's incredible. So you can have this fingerprint within the space of colors, and there's a lot of molecules. And I mean, I wonder, that's a question of like how much overlap there is. How close can you get to the actual fingerprint? Like can phosphine unlock the iPhone with its lights on? It says 16.8 billion. So presumably this rainbow is discretized into little segments somehow. How many total are there? How a lot is 16.8 billion? It's a lot. We don't have the instruments to break these, break any light into this many tiny segments. And so with the instruments we do have, there's huge amounts of overlap. Methane, as an example, a lot of the ways it's detectable is because the carbon and the hydrogens, they vibrate with one another. They move, they interact. But every other hydrocarbon, acetylene, isoprene, has carbon and hydrogens also vibrating and rotating. And so it's actually very hard to tell them apart at low resolutions. And our instruments can't really cope with distinguishing between molecules particularly well. But in an ideal world, if we had infinite resolution, then yes, every molecule spectral features will be unique. Yeah. Like almost too, like it would be too trivial. At the quantum level, they're unique. At the quantum level, yes. At our level, there's huge overlap. Yeah. But then you can start to then, what, try to disambiguate like what the fact that certain colors are missing, what does that mean? And hopefully they're missing in a certain kind of pattern where you can say with some kind of probability that it's this gas, not this gas. Exactly. So you're solving that gaseous puzzle. I got it. Okay. We can go back to Venus actually and show that. So with this, I mentioned there was two molecules that could be responsible for that signal, the resolution that we have. It was phosphine and SO2, sulfur dioxide. And at that resolution, it could really be one or the other, but in that same bandwidth, so in the kind of the same observations, there was another region where phosphine does not absorb. We know that, but SO2 does. So we just went and checked and there was no signal. So we thought, oh, then it must be phosphine. And then we submitted the paper. The rest is history. I got it. Well, yeah, that's beautifully told. So the telescopes we're talking about are sitting on earth. Can it help solving this molecular fingerprint problem if we do a flyby? Does it help if we get closer and closer or are telescopes pretty damn good for this kind of puzzle solving? Telescopes are pretty good, but the earth's atmosphere is a pain. I mean, I'm very thankful for it, but it does interrupt a lot of measurements and a lot of regions where phosphine would be active. They are not available. The earth is not transparent in those wavelengths. So being above the atmosphere would make a huge difference. Then proximity matters a lot less, but just escaping the earth's atmosphere would be wonderful. But then it's really hard to stay very stable. And if there is phosphine on Venus, there's very little of it in the clouds. And so the signal is very weak. And the telescopes we can use on earth are much bigger and much more stable. So it's a bit of a trade-off. So are you comfortable with this kind of remote observation? Is it at all helpful to strive for going over to Venus and grabbing a scoop of the atmosphere? Or is remote observation really a powerful tool for this kind of job? Like the scoop is not necessary. Well, a lot of people want to scoop. I get it. I get it completely. That's my natural inclination, yeah. I don't want to scoop specifically because if it is life, I want to know everything I can remotely before I interfere. So that's my, I've got ethical reasons against the scoop more than engineering reasons against the scoop. But I have some engineering reasons against the scoop. Scoop is not a technical term, but I feel like now it's too late. Thank you for going along with this. It's too late to take it back. I appreciate it. We don't understand the clouds well enough to plan the scoop very well. Because it's not that saturated, like there's not that much of it present. No, and the place is nasty. It's not going to be easy to build something that can do the task reliably and can be trusted, the measurements can be trusted, and then pass that message on. So actually I'm for an orbiter. I think we should have orbiters around every solar system body whose job is just to learn about these places. I'm disappointed we haven't already got an orbiter around every single one of them. It's small, it can be a small satellite. It's just getting data, figuring out how do the clouds move, what's in them, how often is there lightning and volcanic activity, where's the topography, is it changing? Is there a biosphere actively doing things? We should be monitoring this from afar. And so I'm for over the atmosphere, hopefully around Venus, that would be, that would be my choice. Okay, so now recently Venus is all exciting about phosphine and everything. Is there, is there other stuff maybe before we were looking at Venus or now looking out into other solar systems? Is there other promising exoplanets or other planets within the solar system that might have phosphine or might have other strong biosignatures that we should be looking for like phosphine? There's a few, but outside the solar system, all are promising candidates. We know so little about them. For most of them, we barely know their density. Most of them, we don't even know if they have an atmosphere, never mind what that atmosphere might contain. So we're still very much at the stage where we have detected promising planets, but they're promising in that they're about the right size, about the right density. They could have an atmosphere and they're about the right distance from their host star. But that's really all we know. Near future telescopes will tell us much more, but for now, we're just guessing. So you said near future, so there's hope that there'll be telescopes that can see that far enough to determine if there's an atmosphere and perhaps even the contents of that atmosphere? Absolutely. JWST launching later this year, we'll be able to get a very rough sense of the main atmospheric constituents of planets that could potentially be habitable. And that's this year. What's the name of the- JWST, the James Webb Space Telescope. Okay. And that's going to be out in space, past the atmosphere? Yes. Is there something interesting to be said about the engineering aspect of the telescope? I mean, it's an incredible beast, but it's a beast of many burdens. So it's going to do- See, you are a poet. Yeah, I love it. This is very eloquent. You're speaking to the audience, which I appreciate. So yes, it's a giant engineering project. And is it orbiting something? So it's going to be above the atmosphere and it will be doing lots of different astrophysics. And so some of its time will be dedicated to exoplanets. But there's an entire astronomy field fighting for time before the cryogenic lifetime of the instrument. And so when I was looking for the possibility of finding phosphine on distant exoplanets, I used JWST as a way of checking with this instrument that we will launch later this year, could we detect phosphine on an oxygen poor planet? And there I put very much a hard stop where some of my simulations said, yes, you can totally do it, but it will take a little under the cryogenic lifetime of this machine. So then I had to go, well, no one's going to dedicate all of JWST to look for my molecule that no one cared about. So we're very much at that edge, but there'll be many other telescopes in the coming decades that will be able to tell us quite a lot about the atmospheres of potentially habitable planets. So you mentioned simulation. This is super interesting to me. And this perhaps could be a super dumb question, but- Not a huge thing. I am going to prove you wrong on that one. You simulate molecules to understand how they look from a distance is what I understand. Like, what does that simulation look like? So it's talking about which colors of the rainbow will be missing. Is that the goal of the simulation? That's the goal, but it's really just a very, very nasty Schrödinger's equation. So it's a quantum simulation. Oh, so it's simulating at the quantum level. Yes. So I'm a quantum astrochemist. Hi, I'm Clara. I'm a quantum astrochemist. That's how we should have started this conversation. Can you describe the three components of that, quantum, astro, and chemist, and how they interplay together? So I study the quantum behavior of molecules, hence the quantum and the chemist, specifically so I can detect them in space and see astro. So what I do is I figure out the probability of a molecule being in a particular state. There's no deterministic nature to the work I do. So every transition is just a likelihood. But if you get a population of that molecule, it will always happen. And so this is all at the quantum level. It's a Schrödinger equation on, I think, 27 dimensions. I don't remember it by heart. And what this means is I'm solving these giant quantum matrices. And that's why you need a lot of computer power, giant computers, to diagonalize these enormous matrices, each of whom describes a single vibrational behavior of a molecule. So I think phosphine has 17.5 million possible states it can exist in, and transitions can occur between pairs of these states. And there's a certain likelihood that they'll happen. This is the quantum world. Nothing is deterministic. There's just a likelihood that it will jump from one state to another. And these jumps, they're transitions, they're transitions. And there's 16.8 billion of them. When energy is absorbed, that corresponds to this transition. We see it in the spectrum. This is more quantum chemistry than you had asked for. I'm sorry. No, no, I'm sorry. Brain's broken. So when the transitions happen between the different states, somehow the energy maps the spectrum. Exactly. Energy corresponds to a frequency, and a frequency corresponds to a wavelength, which corresponds to a color. And so there's some probability assigned to each color then? Exactly. And that probability determines how intense that transition will be, how strong. And so you run this kind of simulation for a particular, let's say that's 17.5 squared or something like that. Exactly. 17.5 million energies, each one of whom involves diagonalizing a giant matrix with a supercomputer. Actually, I wonder what the most efficient algorithm for diagonalization is. But there's some kind of- There's many. There's many, yeah. Depends on kind of the shape of the matrix. So they're not random matrices. So some are more diagonal than others. And so some need more treatment than others. Most of the work ends up going in describing the system, this quantum system in different ways until you have a matrix that is close to being diagonal, and then it's much easier to clean it up. So how hard is this puzzle? So you're solving this puzzle for phosphine, right? Are we supposed to solve this puzzle for every single molecule? Exactly. Oh boy. Yes, I calculated if I did the work I did for phosphine, again, for all the molecules for which we don't have spectra, for which we don't have a fingerprint, it would take me 62,000 years, a little over. 62,000 years. Well, time flies when you're having fun. Okay. But you're right that there are about 16,000 molecules we care about when looking for a new Earth or when we try to detect alien biosignatures. If we want to detect any molecules from here, we need to know their spectra, and we currently don't. Solving this particular problem, that's my job. What was that? I mean, that's absolutely correct. I could have not said it better myself. Did you take that from my website? Yeah, I think I stole it. And your website is excellent, so it's a worthy place to steal stuff from. Thank you. How do you solve this problem for the 16,000 molecules we care about, of which phosphine is one? Yes. And so taking a step a little bit out of phosphine, is there- But we were having so much fun. We were having so much fun. No, we're not saying bye. It's sticking around. I'm just saying more friends coming to the party. How do you choose other friends to come to the party that are interesting to study as we solve one puzzle at a time through the space of 16,000? So we've already started. Out of those 16,000, we understand water quite well, methane quite well, ammonia quite well, carbon dioxide. I could keep going. And then we understand molecules like acetylene, hydrogen cyanide, more or less. And that takes us to about 4% of those 16,000. We understand about 4% of them, more or less. Phosphine is one of them. But the other 96%, we just really have barely any idea at all of where in the spectrum of light they would leave a mark. I can't spend the next 62,000 years doing this work. And I don't want to, even if somehow I was able, that wouldn't feel good. So one of the things that I try to do now is move away from how I did phosphine. So I did phosphine really the best that I could, the best that could be done with the computer power that we have, trying to get each one of those 16.8 billion transitions mapped accurately, calculated. And then I thought, what if I do a worse job? What if I just do a much worse job? Can I just make it much faster and then it's still worth it? How bad can I get before it's worthless? And then could I do this for all the other molecules? So I created exactly this terrible, terrible system. So what's the answer to that question, that fundamental question I ask myself all the time in other domains? How crappy can I be before I'm useless? Before somebody notices. Turns out pretty crappy because no one has any idea what these molecules look like. Anything is better than nothing. And so I thought, how long will it take me to create better than nothing spectra for all of these molecules? And so I created RASCAL, Rapid Approximate Spectral Calculations for All. And what I do is I use organic chemistry and quantum chemistry and kind of cheat at them both. I just try to figure out what is the fastest way I could run this. And I simulate rough spectra for all of those 16,000. So I've managed to get it to work. It's really shocking how well it works considering how bad it is. Is there insights you could give to the tricks involved in making it fast? Like what are the, maybe some insightful shortcuts taken that still result in some useful information about the spectra? The insights came from organic chemistry from decades ago. When organic chemists wanted to know what a compound might be, they would look at a spectrum and see a feature and they would go, hmm, I've seen that feature before. That's usually what happens when you have a carbon triple bonded to another carbon. And they were mostly right. Almost every molecule that has a carbon triple bonded to another one looks like that. Has other features different that distinguish them from one another, but they have that feature in common. We call these functional groups. And so most of that work ended up being abandoned because now we have mass spectrometry, we've got nuclear magnetic resonance spectroscopy. So people don't really need to do that anymore. But these ancient textbooks still exist and I've collected them all, as many as I could. And there are hundreds of these descriptions where people have said, oh, whenever you have an iodine atom connected to this one, there's always a feature here. And it's usually quite sharp and it's quite strong. And some people go, oh yeah, that's a really broad feature every time that combination of atoms and bonds. So I've collected them all and I've created this giant dictionary of all these kind of puzzle pieces, these Lego parts of molecules. And I've written a code that then puts them all together in some kind of Frankenstein's monster of molecules. So you ask me for any molecule and I go, well, it has these bonds and this atom dangling off this atom and this cluster here. And I tell you what it should look like and it kind of works. So this creates a whole portfolio of just kind of signatures that we could look for. Rough, very rough signatures. But still useful enough to analyze the atmospheres, the telescope generated images of other planets. Close. Right now it is so complete. So it has all of these molecules that it can tell you, say you look at an alien atmosphere and there's a feature there. It can tell you, oh, that feature, that's familiar. It could be one of these 816 molecules. That narrows them down. Best of luck. Yes. So I think the next step, which is what I'm working on, is telling you something more useful than it could be one of those 816 molecules. That's still true. I wouldn't say it's useful. So it can tell you, but only 12% of them also have a feature in this region. So go look there. And if there's nothing there, it can't be those and so on. It can also tell you things like you will need this much accuracy to distinguish between those 816. So that's what I'm working on, but it's a lot of work. Yeah. So this is really interesting, the role of computing in this whole picture. You mentioned code. So you as a quantum astrochemist, there is some role for programming in your life, in your past life, in your current life, in your group. Oh yeah, almost entirely. I'm a computational quantum astrochemist, but that doesn't roll off the tongue very easily. So this is fundamentally computational. If you want to be successful in the 21st century and doing quantum astrochemistry, you want to be computational? Absolutely. All quantum chemistry is computational at this point. Okay. Does machine learning play a role at all? Is there some extra shortcuts that can be discovered through... You see all that success with protein folding, a problem that's thought to be extremely difficult to apply machine learning to because it's... I mean, mostly because there's not a lot of already solved puzzles to train on. I suppose the same exact thing is true with this particular problem, but is there hope for machine learning to help out? Absolutely. Currently you've laid out exactly the problem. The training set is awful. And because there's so... A lot of this data that I'm basing it on is literally many decades old. The people who worked on it and data that I get, often they're dead. And the files that I've used, some of them were hand drawn by someone tired in the 70s. So I can of course have a program training on these, but I would just be perpetuating these mistakes without hope of actually verifying them. So my next step is to improve this training set by hand, and then try to see if I can apply machine learning on the full code of the full 16,000 molecules, and improve them all. But really I need to be able to test the outcomes with experimental data, which means convincing someone in a lab to spend a lot of money putting very dangerous gases in chambers and measuring them at outrageous temperatures. So it's a work in progress. And so collecting huge amounts of data about the actual gases. So you are up for doing that kind of thing too? So actually doing the full end to end thing, which is like having a gas, collecting data about it, and then doing the kind of analysis that creates the fingerprint, and then also analyzing using that library, the data that comes from other planets. So you do the full. Full from birth to death. Interesting. Yes, I worked in an industrial chemistry laboratory when I was much younger in Slovenia. And there I worked in the lab actually collecting spectrum and predicting spectrum. What's it like to work with a bunch of gases that are like not so human friendly? Terrifying. It's horrific. It's so scary. And I love my job. I'm willing to clearly sacrifice a lot for it. Job stability, money, sanity. But I only worked there for a few months. It was really terrifying. There's just so many ways to die. Usually you only have a handful of ways to die every day. But if you work in a lab, there's so many more, orders of magnitude more. And I was very bad at it. I'm not a good hands-on scientist. I want a laptop connected to a remote supercomputer or a laptop connected to a telescope. I don't need to be there to believe it. And I am not good in the lab. Yeah, when there's a bunch of things that can poison you, a bunch of things that could explode and they're gaseous, and they're often, maybe they might not even have a smell or they might not be visible. It's like- So many of them give you cancer. It's just so cruel. And some people love this work, but I've never enjoyed experimental work. It's so ungrateful. It's so lonely. Well, most, I mean, so much work is lonely if you find enjoying it, but you enjoy the results of it. Yes. I'm very thankful for all the experimentalists in my life, but I'll do the theory. They do the experiment and then we talk to one another and make sure it matches. Okay, beautiful. What are spectroscopic networks? Those look super cool. Are they related to what we were talking about? The picture looked pretty. Oh, yes, slightly. So remember when I mentioned the 17.5 million energy levels? Yes. There are rules for each molecule on which energy levels it can jump from and to, and how likely it is to make that jump. And so if you plot all the routes it can take, you get this energy network, which is like a ball. So these are the constraints of the transitions that could be taken. Exactly for each molecule. Interesting. And so it's not a fully connected, it's sparse somehow? Yes, you get islands sometimes. You get a molecule can only jump from one set of states to another and it's trapped now in this network. It can never go to another network that could have been available to other siblings. Is there some insights to be drawn from these networks? Like something cool that you can understand about a particular molecule because of it? Yes. Some molecules have what we call forbidden transitions, which aren't really forbidden because it's quantum. There are no rules. No, I'm not sure. There are rules, it's just the rules are very often broken in the quantum world. And so forbidden transitions doesn't actually mean they're forbidden. Low probability. Exactly. They just become deeply unlikely. Yeah. Cool. And so you could do all the same. I'm coming from a computer science world, I love graph theory. So you can do all the same graph theoretic kind of analysis of clusters or something like that, or all those kinds of things and draw insights from it. Cool. And they're unique for each molecule. So the networks that you mentioned, that's actually not too difficult a layer of quantum physics. By then all the energies are mapped. So we've had high school children work on those networks. And the trick is to not tell them they're doing quantum physics until like three months in when it's too late for them to back out. And then you're like, you're a quantum physicist now. And it's really nice. Yeah. Okay. But like the promise of this, even though it's 16,000, even just a subset of them, that's really exciting because then you can do as the telescope data get better and better, especially for exoplanets, but also for Venus, you can then start like getting your full, like you know how you get like blood worked on or like you get your genetic testing to see what your ancestors are. You can get the same kind of high resolution information about interesting things going on on a particular planet based on the atmosphere. Right? Exactly. How cool would that be if we could scan an alien planet and go, oh, this is what the clouds are made of. This is what's in the surface. These are the molecules that are mixing. Here are probably oceans because you can see these types of molecules above it. And here are the Hadley cells. Here are how the biosphere works. We could map this whole thing. Wouldn't it be cool if the aliens like are aware of these techniques and like would spoof like the wrong gases just to like pretend that's how they can be, it's like an invisibility cloak. They can generate gases that would throw you off or like, or do the opposite. They pretend they will artificially generate phosphine. So like the dumb apes on earth again, like go out like flying in different places because it's just fun. It's like some teenager alien somewhere just pranking. I was asked that exact question this Saturday by a 70 year old boy in Canada. Oh, old seven? Seven, yeah. Yes. But it was the first time I'd been asked that question. This is the second in a week. We're kindred spirits, him and I. We can. They can prank us to some extent, but this work of interpreting an alien atmosphere means you're reading the atmosphere as a message. And it's very hard to hide signs of life in an atmosphere because you can try to prank us, but you're still going to fart and breathe and somehow metabolize the environment around you and call that whatever you call that and release molecules. And so that's really hard to hide. You can go very quiet. You can throw out some weird molecule to confuse us further, but we can still see all your other metabolites. Yes. It's hard to fake. You kind of mentioned water. What other gases are there that we know about that are high likelihood as biosignatures in terms of life? I mean, what are your other favorites? So we got phosphine, but what else is a damn good signal that you think about that we should be looking for if we look at another atmosphere? Is there gases that come to mind? Are there all possible biosignatures that we should love equally? There's many. So there's water. We know that's important for life as we know it. There's molecular oxygen on earth. That's probably the most robust sign of life, particularly combined with small amounts of methane. And it's true that the majority of the oxygen in our atmosphere is a product of life. And so if I was an alien astronomer and I saw Earth's atmosphere, I would get a Nobel, I think. What would you notice? I mean, this is really- I would be very excited about this. About the oxygen. About finding 20%, 21% of oxygen atmosphere. That's very unusual. So would that be the most exciting thing to you from an alien perspective about Earth in terms of analyzing the atmosphere? What are the biosignatures of life on earth, would you say, in terms of the contents of the atmosphere? Is oxygen, high amount of oxygen, pretty damn good sign? I mean, it's not as good as the TV signals we've been sending out. Those are slightly more robust than oxygen. Oxygen on its own has false positives for life. So there's still ways of making it. But it's a pretty robust sign of life in the context of our atmosphere with the radiation that the sun produces, our position in relation to the sun, the other components of our atmosphere, the volcanic activity we have. All of that together makes the 20% of oxygen extremely robust sign of life. But outside that context, you could still produce oxygen without life. But phosphine, although better in the sense of it is much harder to make, it has lower false positives, still has some. So I'm actually against looking for specific molecules, unless we're looking for like CFCs. If we find CFCs, that's definitely aliens, I feel confident. Chlorofluorocarbons. And so if aliens have been watching us, they would have been going, oh no, CFCs, I mean, they're not gonna last long. Everyone's writing their thesis on the end of the earth. And then we got together, we stopped using them. I like to think they're really proud of us. They literally saw our ozone hole shrinking. They've been watching it and they saw it happen. I think to be honest, they're more paying attention to the whole nuclear thing. I don't think they care. It's not gonna bother them. Oh, I mean, worried about us. Oh, yes. No, worried about us. I mean, this is why the aliens have been showing up recently. If you look at, I mean, there is probably there's a correlation with a lot of things, but what the UFOlogists quote unquote often talk about is that there seems to be a much higher level of UFO sightings since like in the nuclear age. So like if aliens were indeed worried about us, like if you were aliens, you would start showing up when the living organisms first discovered a way to destroy the entire colony. Couldn't the increase in sightings not have to do with the fact that people now have more cameras? It's an interesting thing about science, like with UFO sightings, it's like either 99.9% of them are false or 100% of them are false. The interesting thing to me is in that 0.01%, there's a lot of things in science that are like these weird outliers that are difficult to replicate. You have like, there's even physical phenomena, ball lightning. There's difficult things to artificially create in large amounts or observe in nature in large amounts in such a way that you can do to apply the scientific method. There could be just things that like happen like a few times or once and you're like, what the hell is that? And that's very difficult for science to know what to do with. I'm a huge proponent of just being open-minded because when you're open-minded about aliens, for example, is it allows you to think outside of the box in other domains as well. And somehow that will result, like if you're open-minded about aliens and you don't laugh it off immediately, what happens is somehow that's going to lead to a solution to P equals NP or P not equals NP. Like in ways that you can't predict, the open-mindedness has tertiary effects that will result in progress, I believe, which is why I'm a huge fan of aliens because it's like, because too many scientists roll their eyes at the idea of aliens, alien life. And to me, it's one of the most exciting possibilities and the biggest, most exciting questions before all of human civilization. So to roll your eyes is not the right answer. To roll your eyes presumes that you know anything about this world as opposed to just knowing 0.0001% of this world. And so being humble in the face of that, being open to the possibility of aliens, visiting earth is a good idea. Not everything though. I'm not so open-minded to the flat earth hypothesis. There's a growing number of people believing in, but even then- Or the inner earth, I've got shouted out in a public talk about it. So like the earth is hollow? Yeah. My understanding is that there's this conspiracy theory that as far as I can tell has no grounding in reality is that there's a slightly smaller earth inside this one, which is just too cute as a concept. And you can access it, I think from Antarctica. And that's where we keep, and I quote, the mammoths and the Nazis. Yeah. I mean, that one is ridiculous, but like I do like- Hey, I thought you were keeping an open mind. I am. This is- This is- I genuinely think that's more likely than aliens visiting the earth. And I say this as someone who has dedicated her life to finding alien life. And so that's how improbable I think the visitations are because interstellar distances are so huge that it's just not really worth it. See, I have a different view on this whole thing. I think the aliens that look like little green men are like extremely low probability event. Like mammoths and Nazis under? Yeah. Yeah. That's similar. Okay. That level. Okay. But other kind of ideas, like the sad thing to me, and I think, in my view, if there's other alien civilizations out there and they visited earth, neither them or perhaps just us would be even able to detect them. Like we wouldn't be able we wouldn't be open-minded enough to see it. Because our understanding of what is life. And I just talked to Sarah Walker, who's- You know Sarah. Yeah. We talked for three hours about the question of what is life. Sarah's a good person to talk to about what is life. But the whole point is we don't really, we have a very narrow-minded view of what is life. And when it shows up, and it might be already here, trees and dolphins and so on. Very good choices. And, or mountains, or I don't know, or the molecules in the atmosphere, or like I, people make fun of me, but I do think that ideas are kind of aliens themselves, or consciousness could be the aliens, or it could be the method by which they communicate. We don't know shit about the way our human mind works. And the fact that this thing is- Could be a quantum process. Please don't. I understand this. It's not woo-woo. I'm not, I, we could, but it very well could be. There could be something at the physics level, right? It could be at the chemical, at the biological level, things that are happening that we're just close, too close-minded. Because our conception of life is at the level of, like us, like at the jungle level of mammals. And on the time scale, that's the human time scale, we may not be able to perceive what alien life is actually like. The scale at which their intelligence realizes itself, we may not be able to perceive. And the other thing that's really important about alien visitations, whether it happened or not, is especially after COVID in 2020, I'm losing a little bit of faith of our government being able to handle that well. Not our government, but us as a society, as a collective, being able to deal with new things in an effective way that's inspiring, that's efficient, that, like, whether it's, if it's a dangerous thing to deal with it, to alleviate the danger, whether it's the possibility of new discoveries and something inspiring to ride that wave and make it inspiring, all those kinds of things. I honestly think if aliens showed up, they would look around, everybody would ignore them, and the government might, like, hide it, try to, like, see, to keep it from the Chinese and the Russians, if it's the United States, call it a military secret in a very close-minded way. And then the bureaucracy would drown it away to where, through paperwork, the poor aliens would just, like, waste away in a cell somewhere. Like, there's a certain... That would not happen. That would never happen. Part of the reason that I feel so confident that aliens have not visited, because they would have had to visit just to have a look remotely, you know, from Neptune or something, which makes no sense, because interstellar travel is so difficult that it would be quite a ridiculous proposition. But that's the bit that I think is technically possible. If they did come here and they were visible by anyone, detectable by anyone, the thought that any government, no matter, or any military could just contain them, these beings are capable of traveling interstellar distances, when we can barely go to the moon, like, barely go to the moon. These things would be way, way, way, way farther. Way. And the fact that we think our puny military, of any, even if all the military in the world got together, and the fact that they could somehow contain this, it's... It's like ants trying to contain a human that visited them. Exactly. And scientists. You would have to bring scientists on board. You've met a lot of scientists. How good are they at keeping secrets? Because in my experience, they're absolutely appalling at keeping secrets. Yeah, that's terrible. Even the phosphine on Venus thing, which was a pretty well-kept secret. Oh, this is true. You had a bunch of people that were... I told my dad. You know, my dad knew. And hopefully didn't tell anyone, but if there had been an alien visiting, he probably would have told the mate, you know. And so, these secrets could not be kept by any scientist that I know, and certainly not collaborative scientists, which would be needed. You need all sorts of scientific teams. So, between the pathetic power of any world's military compared to any civilization capable of traveling, and our absolute inability to keep secrets, absolutely not. I will bet everything that we have not been visited because we are too pathetic to hold that truth. Well, let me push back if we're making like a $10 bet. The possibility here that the main... Say there exists one alien civilization, other intelligent alien civilization in the galaxy. To me, if they visit Earth, what's going to visit Earth is like the crappy, like the really crappy... Short straw. Yeah, yeah. Like this really dumb thing that's, I don't know, like the early Game Boys or something. I think there's a cartoon about this. There's an alien that gets sent to Earth, Commander Spiff or something, and it's kind of a punishment or something. But that's not possible. That's the thing because interstellar distances are so hard to cross. You have to do it on purpose. You have to do it on purpose. It has to be a big, big deal. And we know this because, yes, you're right, we don't know enough about galactic biology. We don't know what the universal rules of biology or biochemistry are because we only have the Earth. But we do know that the laws of physics are universal. We can predict behavior in the universe and then see it happen based on these laws of physics. We know that the laws of chemistry are universal. We know the periodic table is all they have to choose from. So yes, there may be some sort of unimaginable intelligence, but they still have to use the same periodic table that we have access to. They still have a finite number of molecules they can do things with. So they still have to use the resources around them, the stars around them, the universe around them. And we know how much energy is in these places. And so, yes, they may be very capable, capable beyond our wildest dreams, but they're still in the same universe. And we know a lot of those rules. We're not completely blind. But there's a colleague of yours at Harvard, Kamran Vafa, he's a theoretical physicist. I don't know if you know him. I've only joined Harvard about six months ago. Okay. It's time to meet all the theoretical physicists. So he's a string theorist, but his idea is that aliens that are sophisticated enough to travel interstellar, like those kinds of distances, will figure out actually ways to hack the fabric of the universe enough to have fun in other ways. Like this universe is too boring. Like you would figure out ways to create other universes or like you go outside the physics as we know it. So the reason we don't see aliens visiting us all over the place is they're having fun elsewhere. This is like way too boring. We humans think this is fun, but it's actually mostly empty space that no fun is happening. Like there's no fun in visiting earth for a super advanced civilization. So he thinks like if alien civilizations are out there, they found outside of our current standard models of physics, ways of having fun that don't involve us. But- That's probably true. But even the notion of visiting that's so literally pedestrian. Of course, we want to go there because going there is the only thing we know. We see a thing we want, we want to go there and get it. But that is probably something they've no longer got need for. I specifically don't particularly want to go to space. Sounds awful. None of the things I like are going to be there. And my whole work is my whole career is finding life and understanding the universe. So I care a lot. But I care about knowing about it and I feel no need to go there to learn about it. And I think as we develop better tools, hopefully people will feel less and less need to go everywhere that we know about. And I would expect any alien civilization worth assault have developed observation tools and tools that allow them to understand the universe around them and beyond without having to go there. This going is so wasteful. Yeah. So more focused on the knowledge and learning versus the colonization, like the conquering and all those kinds of things. That's beneath them. That's beneath them. I mean, that said, do you think there's any hopeful search for life through phosphine and other gases? Do you think there's other alien civilizations out there? First, do you think there's other life out there? First, do you think there's life in the solar system? Second, do you think there's life in the galaxy? And third, do you think there's intelligent life in the solar system or the galaxy outside of earth? So intelligent life, I have no idea. It seems deeply unlikely possible, but I'm not even sure if it's plausible. So that's a special thing to you about earth is somehow intelligent life came to be. Yes. And it's only very briefly, probably extremely briefly. Oh, you mean like it's always going to be like we're going to destroy ourselves? Exactly. Oh boy. And life will continue on earth happily, probably more happily. So- Trees and the dolphins will be here, I'm telling you. And the cockroaches and the incredible fungi, they'll be fine. So life on earth will be fine, was fine before us and will be fine after us. So I'm not that worried about intelligent life, but I think it is unlikely. Even on earth is unlikely out of what is it, 5 billion species across the history of the earth. There's been one, an intelligent one and for a blink of an eye, possibly not much longer than that. So I wouldn't bet on that at all, though I would love it, of course. I wanted to find aliens since I was a little girl. And so of course, I initially wanted to find ones that I could be friends with. And I've had to let go of that dream because it's so deeply implausible. But see the nice, and sorry to interrupt, but the nice thing about intelligent alien civilizations, they may have more biosignatures than non-intelligent ones. So they might be easier to detect. That would be the hope. On earth, that's not the case, but it could be the case elsewhere. Oh, it's not the case on earth. Most of the biosignatures we have on earth are created by quite simple life. If you don't count pollution, pollution is all, all us babies. LB So you don't see polluting gases as a possible like- CT I look for polluting gases. I would love to find polluting gases. Well, I'd be worried for them, of course, the same way I think about my alien colleagues all the time looking at us, and I'm sure they worry about our pollutions. But it would be a really good, robust, unambiguous sign of life if we found complex pollutants. So I look for those too. I just don't have any hope of finding them. I think intelligent life in the galaxy at the same time that we're looking is deeply implausible. But life, I think, is inevitable. And if it is inevitable, it is common. So I think there'll be life everywhere in the galaxy. Now how common that life is, I think will depend a lot on whether there's life in the solar system beyond earth. So I'll adjust my expectations very much based on there being life in the solar system. If there's life in the Venusian clouds, if there's life in the, if there are biosignatures coming out of the plumes of Enceladus, if there's life on Titan. LB Yeah, that's right. Enceladus, yeah, yeah, plumes of Enceladus. That's the Saturn one? CT It's the moon that has the geysers that come out. And so you can't see that under the subterranean oceans, but- LB It's supposed, so it would be in the atmosphere. I was gonna ask you about that one. Have you looked at that? Is that a hope for you to use the tools you're using with RASCO and other ways for detecting the 16,000 molecules that might be biosignatures to look at Enceladus? CT Yes, that's absolutely the plan. LB What's the limiting factor currently? Is it the quality of the telescopes? What's the quality of the data? CT Yeah, the quality of the data, the observational data, and also the quality of RASCO and other associated things. So we're missing a lot of fundamental data to interpret the data that we get, and we don't have good enough data. But hopefully we will, in the coming decades, we'll get some information on Titan. We have Dragonfly going over. We'll get the plumes of Enceladus. We will look at the clouds of Venus, and there's other places. And so if we find any life or any sign of life ever, like on Mars, then I'll adjust my calculations and I'll say life is not just inevitable and common, but extremely common. Because all of these places we've mentioned, the subterranean oceans on Enceladus, the methane oceans of Titan, the clouds of Venus, the acidic clouds of Venus, these are places that are very different from the places where we find life on Earth, even the most extreme places. And so if life can originate in all of these completely different habitats, then life is even more resourceful than we thought, which means it's everywhere. LB That's really exciting if it's everywhere. If there's life on just one of the moons, if it's on Mars. CW Anywhere. Anywhere in the solar system, and I will bet everything I own that every solar system, every planetary system has a potential for habitability. Because even if they don't have a habitable planet, they'll have moons around other giant planets, and there'll be so much life. So for me, that's the only thing to figure out now, whether life is inevitable and quite common throughout the galaxy or everywhere. But it's somewhere between those two. Intelligent life, I make no bets. And if I had to bet, I would be against. LB To me, like two discoveries in the 21st century would change everything. One is, and maybe I'm biased, but one is a discovery of life in the solar system. I feel like that would change our whole conception of how unique we are in the universe. I think I'm much more eager than you are to jump from basic life to intelligent life. I feel like if there's life everywhere, the odds are there has, we cannot... Oh, I see. You're saying there could have been many intelligent civilizations out there, but they just keep dying out. It's like little- CW Yeah, us detecting them, ships in the night. LB Ships in the night. Now that's ultra sad. Just like- CW Is it sad? LB A graveyard of this. CW The earth is not better for having us. It doesn't owe us anything. Would you be sad to find alien giraffes? Would you be disappointed if you found alien giraffes? Because I would not. LB No, well, giraffes, first of all, they look goofy with their necks and everything, but- CW But no, we do not shit on giraffes. Giraffes are wondrous animals, are deeply understudied. We still know so little about them because no one does PhDs in giraffes. I am, to this point, I made a PhD in phosphine when people aren't doing PhDs in giraffes. We do not know enough about giraffes. LB I think it was like Ricky Gervais that did a whole like long thing about- CW You can't trust Ricky Gervais to talk about giraffes. That is not his expertise. LB Yeah, but it's a stupid necks. It doesn't make any sense. I mean, that's fine. CW Giraffes are very resourceful animals who do incredible things and can kick a lion in the face. LB Why don't you climb the tree? Why don't you climb the tree? You don't need to grow through the lengthy evolutionary process. CW You don't need to be shitting on giraffes. LB Okay, fine. CW Giraffes are wondrous animals. LB I would very appreciate that. CW I take it back. LB I take it back. I apologize. I trust your expertise on this. The thing that makes humans really fascinating, and I think the earth, but I'm a human, is we create- CW A climber. LB Yeah. We create things that are, yes, there's all the ugliness in the world. There's all the biological and the chemical level. There's the pollution. But we create beauty. If you even from a physics perspective look at symmetry as somehow capturing beauty, the breaking of symmetries, stuff grounded in all the different definitions of symmetry, we're good at creating things. CW So are spiders. LB But not giraffes. Okay. But yes, this is- CW Spiders. LB Yes, this is the point. CW There are spiders that create little bubbles of air so they can breathe underwater. They can literally scuba dive. There are spiders that can create parachutes so they can glide. And talk about symmetry, look what spiders can do. And I just thought of spiders, but if I was an alien species coming to earth, there'll be plenty to wonder and we would just be one- LB One of the things. CW Yeah, clunky, naked monkey. LB Yeah, the ants might be even more fascinating. CW The ants. Ants can figure out exactly through some emergent consciousness what the maximum distance between their trash, their babies, and their food is just from without any of them knowing how to do this. And collectively they've learned how to do this. If I was an alien species, I'll be looking at that. LB Well, so that was the other thing I was going to mention. The second thing is I tend to believe we can engineer consciousness, but at the basic level, understand the source of consciousness. Because if consciousness is unique to humans and if we can engineer it, that gives me hope that it could be present elsewhere in the universe. That's the other thing that makes, it's an open question, that makes humans perhaps special is not maybe the presence of consciousness, but somehow a presence of elevated consciousness. It does, again, maybe human-centric, but it feels like we're more conscious than giraffes, for example, and spiders. CW Yes, I won't deny that. There is something special about humans. They're my favorite species. LB They are. CW They are. Some of my best friends are humans. LB I think highly of humans. It's great. I just don't have great hope for our longevity. And specifically, I don't have great hope given that we're the only species that are 5 billion that did this cool consciousness trick. I don't want to bet on finding a kinship elsewhere. LB That's quite interesting to think about. I don't think I've even considered that possibility that there would be life in the solar system. So that indicates that very possibly life is like literally everywhere. CW Everywhere it can happen, it does. LB Yeah. And especially what we're discovering with the exoplanets now, how numerous they are, or Earth-like, habitable, quote unquote, planets. They're everywhere. CW The most common type of planet is rocky, it seems. LB But I didn't consider the possibility that life is like literally everywhere. And yet, intelligent life is nowhere long enough to communicate with each other, to form little clusters of civilizations that expand beyond the solar system and so on. Man, maybe becoming a multi-planetary species is a less likely pursuit than we imagined. CW I agree. LB But one of the things that makes humans beautiful is we hope. CW But I hope for humanity. And one of the things I hope for is that we become less obsessed with conquering, and we become less obsessed with spreading ourselves. I hope that we transcend that, that we're happy with the universe without having to go and take it. LB So you can hope for the species without hoping for a multi-planetary existence. That is only, I think, the drive of our most primitive instincts to go and take, to go and plant a flag somewhere. We love planting a flag somewhere. And maybe we could overcome that minor drive. CW And once we do, the AI systems we build will destroy us because we're too peaceful, and they will go and conquer and plant the flags. LB Best of luck to them. The cockroaches will be happy to keep to their business as they always have. CW I tend to believe that robots can have the same elegance and consciousness and all the qualities of kindness and love and hope and fear that humans have. LB In principle, they could, yes. I don't really trust the people who make them. LB This is about the giraffe comment, isn't it? LB I haven't forgiven you for shitting on giraffes. What have they done to you? LB Just as a small tangent, your master's thesis is also fascinating. Maybe we could talk about it for just a little bit. It's titled, Influence of a Star's Evolution on its Planetary System. LB So this interplay between a star and a planet, is there something interesting you could say about what you've learned about this journey that a star takes and the planets around it? CW Well, when I was younger and I was told what would happen ultimately to the Earth as the sun expands towards a red giant and Mercury would just like fall in and then Venus would fall in and the sun doesn't care. And it just seemed so... I felt so small. I felt like the Earth and everything on it, it's just the universe doesn't care. Even our sun doesn't care. And I think I felt like our sun should feel some sort of responsibility for its planets. And it just felt like such a violent and neglectful parent. LB It's like a parent eating its own children. CW It's horrible. It's just a horrible notion. But it made me think, what if there's some sort of generation? And so, at the time when I was doing my master's, there was a notion of the white dwarf cemetery, which is this idea that when stars become white dwarfs, that death is so horrible that planets, potentially habitable planets that could have been habitable before, they're now gone. There's no chance for life. But then I thought, what if life returns? Now it's a white dwarf, it's calmed down, it's not going to go anywhere. White dwarfs are very stable across universal time scales. And so, could you have planets around the white dwarf that could themselves get life again? Life doesn't care. And so, my work was basically killing dozens of planets, thousands of times. I just ran thousands and thousands of end body simulations. LB You simulated this? CW Yeah. So, I simulated the star growing and just eating all these planets up and just absolute chaos. The orbits of the planets would change as the star loses mass. So, you would have Jupiter planets just crashing into the other planets, throwing them into the sun early. It was terrifying to watch these simulations. It was absolute carnage. But if you run thousands of these simulations, some systems find new balance ways of staying alive. Some systems post-star death find stable orbits again for billions of years, more than enough for life to originate again. And so, that was my idea during that time that Thesis was trying to explore this notion of life coming back and this idea of the universe doesn't care if you're here or not, and it will go about its business. Andromeda will crash into us and doesn't care. No one cares if you're alive in the universe. And so, letting go of that preciousness of life, I found very useful at that stage in my career. And instead, I just thought if life is inevitable, it doesn't matter that it came by four billion years ago, it can start again four billion years later. And maybe that is nice. Maybe that's where hope lies, the Phoenix rising everywhere. Planets being destroyed and created and we're here now, and others will be more or less here-ish billions of years later. Lexi Lovett So, accepting the cycle of death and life and, yeah. Andromeda I'm not taking it personally. Lexi Lovett Not taking it personally. Andromeda The sun doesn't owe us anything. Lexi Lovett Yeah. Andromeda He's not a bad parent. It's not a parent at all. Lexi Lovett Yeah. I was looking at the work of Freeman Dyson and seeing how this universe eventually will just be a bunch of supermassive black holes before they also evaporate. Andromeda A bunch of tiny black holes too. Lexi Lovett Yeah. Andromeda Absolutely quiet. Everyone, all the black holes a little too far away from one another to even interact until it's just silence forever. But until then, many, many cycles of death and destruction and rebirth. Andromeda And rebirth. You kept bringing up, sort of coding stuff up. I wanted to ask two things. First of all, what programming language do you like? And also what, because you're as a computational quantum astrochemist. No, yes. Lexi Lovett No, no, that's correct. Andromeda That's right. You're kind of, you could say you're actually understanding some exceptionally complicated things with one of the things you're using is the tools of computation of programming. Is there a device you can give to people? Because I know quite a few that have not practiced that tool and have fallen in love with a particular science or whatever it's biology and chemistry and physics and so on. And if they were interested in learning to program and learning to use computation as a tool in their particular science, is there advice you can give on programming and also just maybe a comment on your own journey and the use of programming in your own life? Andromeda Well, I'm a terrible programmer. A lot of scientists, their programming is bad because we never learned formal programming. We learned science, physics, chemistry, and then we were told, oh, you have to get these equations modeled and run through a simulation. And you're like, okay, so I'm going to learn how to code to do this. And you learn just as much as you need to run these simulations and no more. So they're rarely optimized. They're really clunky. Six months later, you can't read your own code. My variable names are extremely embarrassing. I still have error messages for different compilation errors that say things like, at least your dad loves you, Clara. It doesn't help me at all. Nathan So, there's that humor. Andromeda Yeah. Nathan Yes. Andromeda It's just like you suck at coding, but there's other things in your life. So I'm a bad programmer. And so if that will give hope to anyone else who's a bad programmer, I can still do pretty impressive science. But I learned, I think I started learning MATLAB and Java when I was in college. It did me no good at all. It has not been particularly useful. I learned some Fortran. That was very useful, even though it's really not a fun language because so much of legacy code is in Fortran. And so if you want to use other people's code who have now retired, Fortran will be nice. And then I used IDL to visualize. So that simulation and body simulation, that was all Fortran and IDL. But thankfully, since I've left college, I've just learned Python like a normal person, and that has been much nicer. So most of my code now is in Python. Yossi I should also make a few quick comments as well. So one is, you say you're sort of bad at programming. I've worked with a lot of excellent scientists that are quote unquote bad at programming. They're not. It gets the job done. In fact, there's a downside to sort of, especially getting a software engineering education. If I were to give advice, especially if you're doing a computer science degree and you're doing software engineering, is not to get lost in the optimization of the correct, there's an obsession, you can see it in Stack Overflow, of the correct way to do things. And I think you can too easily get lost in constantly trying to optimize and do things the correct way when you actually never get done. The same thing happens, you have communities of people obsessed with productivity, and they keep researching productivity hacks, and then they spend like 90% plus of their time figuring out how to do things productively, and they never actually do anything. So there's a certain sense if you focus on the task that needs to be done, that's what programming is for. So not over optimizing, not thinking about variable names in the following sense. Sometimes you think, okay, I'm going to write code that's going to last for decades. In reality, your code, if it's well written or poorly written, will be very likely obsolete very quickly. And the point is to get the job done really well. So there's a trade off there that you have to make sure to strike. I should also comment as a public service announcement, or a request, if there's any world class Fortran or Cobalt programmers out there, I'm looking for them, I want to talk to you. That will not be me. I'm a terrible Fortran programmer. But it's fascinating because so much of the world in the past and still runs programming languages, and there's like no experts on it. They're all retiring. I disagree slightly in that I think because I can get the job done, I'm a programmer. But because no one else can look at my code and know how I got my job done, I'm a bad programmer. That's how I'm defining it. Including myself six months later. I'm working with a new student right now and she sent me some messages on Slack being like, what is this file that you've got with some functions around? And I was like, this was from 2018. It wasn't that long ago. And I can no longer remember what that code does. I'm going to spend now two days reading through my own code and trying to improve it. And I do think that's frustrating. And so, I think my advice to any young people who want to get into astronomy or astrobiology or quantum chemistry is that I certainly find it much easier to teach the science concepts to a programmer than the programming to a scientist. And so, I would much, much faster hire someone who knows programming but barely knows where space is than teach programming to an astronomer. Oh, that's fascinating. Yeah. Okay. This is true. I mean, yeah, there's some basics. I'm focusing too much on the silver lining because the people that write like MATLAB code, yeah, single letter variable names, those kinds of things. And it's accessibility, right? I want my code to be open source. And it is. It's on GitHub. Anyone can download it. But is it really open source if it's written so cryptically, so poorly that no one can really use it to its full functionality? Have I really published my work? And that weighs on me. I feel guilty for my own inadequacies as a programmer. You can only do so much. So, I've already learned quantum chemistry and astrophysics. So, you know. Yeah. I mean, there's all kinds of ways to contribute to the world. One of them is publication. But publishing code is a fascinating way to contribute to the world, even if it's very small, very basic element. Great code. I guess I was also kind of criticizing the software engineering process versus like, which is a good thing to do. It's code that's readable, almost like without documentation, it's readable. It's understandable. The variable names, the structure, all those kinds of things. That's the dream. That's the dream. This is a dumb question. What do you... No, no. Tell me a dumb question. I want to hear it. Okay. I mean, okay. This is the question about beauty. It's way too general. It's very impossible. It's like asking what's your favorite band. What's your favorite music band? Oh, I thought you meant Wavelength band. I was like, I definitely have favorite Wavelength bands. Absolutely. Well, it's hard to narrow it down, huh? Okay. What to you is the most beautiful idea in science? That's not a dumb question. Do you want to try that question again, proudly? Okay. I have a really good question to ask you. Okay. Don't oversell it. I've got an okay question to ask you, you know? Yeah. What to you is the most beautiful idea in science? Something you just find inspiring or just maybe the reason you got into science or the reason you think science is cool? My favorite thing about science is the connection between the scales. When I was little and I wanted to know about space, I really felt that it would make me feel powerful to be able to predict the heavens, something so much larger than myself that felt really powerful. It was almost a selfish desire, and that's what I wanted. There was some control to being able to know exactly what the sky would do. And then as I got older and I got more into astronomy, and I didn't just want to know how the stars moved, I wanted to know how the planets around them moved. And then as I got deeper into that field, I really didn't care that much about the planets. I wanted to know about the atmospheres around the planets and then the molecules within those atmospheres and what that might mean. So I ended up shrinking my scale until it was literally the quantum scale. And now all my work, the majority of my work is on this insane quantum scale. And yet I'm using these literal tiny, tiny tools to try and answer the greatest questions that we've ever been able to ask. And this crossing of scales from the quantum to the astronomical, that's so cool, isn't it? Yeah, it spans the entirety, the tiny and the huge. That's the cool thing about, I guess, being a quantum astrochemist is you're using the tools of the tiny to look at the heavenly bodies, the giant stuff. And the potential life out there, that this is the thing that connects us, that you can't escape the rules of the quantum world and how universal they themselves are despite being probabilistic. And that makes me feel really pleased to be in science, but in a really humbling way. And it's no longer this thirst for power. I feel less special the more work I do, less exceptional the more work I do. I feel like humans and the earth and our place in the universe is less and less exceptional. And yet I feel so much less lonely. And so it's been a really good trade-off that I've lost power, but I've gained company. Wow, that's a beautiful answer. I don't think there's a better way to actually end it. You're right. I asked a mediocre question and you came through. You made the question good by a brilliant answer. You're the Michael Jordan and I'm the, who's the Dennis Rodman? I'll be the Dennis Rodman. This is a- I don't know enough about basketball. I mean, literally you've reached the peak of my basketball knowledge because I know that those people are basketball- But that's it. Pros, I believe, but only because I watch Space Jam, I think. Are there books or movies in your life long ago or recently? Do you have any time for books and movies? Had an impact on you? What ideas did you take away? I absolutely have time for books and movies. I try as best I can to not work very hard. I mostly fail, I should point out, but I think I'm a better scientist when I don't work evenings and weekends. If I get four good hours in a day, I often don't. I often get eight crappy hours, emails, meetings, bad code, data processing. But if I can get four high quality scientific hours, I just stop working for the day because I know it's diminishing returns after that. So I have a lot of time. I try to make as much time as I can. Can you kind of dig into what it takes to be, one, productive, two, to be happy as a researcher? Because I think it's too easy in that world to basic... Because you have so many hats, you have to wear so many jobs, you have to be a mentor, a teacher, a head of a research group, do research yourself. You have to do service, all the kinds of stuff you're doing now with education. Interviews. So as a public science, being a public communicator, that's a job. The whole thing. Pays very poorly. I'll pay you in Bitcoin. I'll take Bitcoin. Bitcoin. So is there some advice you can give to the process of being productive and happy as a researcher? I think sadly, it's very hard to feel happy as a scientist if you're not productive. It's a bit of a trap, but I certainly find it very difficult to feel happy when I'm not being productive. It's become slightly better if I know my students are being productive, I can be happy. But I think a lot of senior scientists, once they get into that mindset, they start thinking that their student science is theirs. And I think this happens a lot with senior scientists. They have so many hats, as you mentioned, they have to do so much service and so much admin that they have very little time for their own science. And so they end up feeling ownership over the junior people in their labs and their groups. And that's really heartbreaking. I see it all the time. And that, I think I've escaped that trap. I feel so happy even when I'm not productive, when my students are productive. I think that sensation I was describing earlier, they only need to be half as productive as me for me to feel like I've done my job for humanity. So that has been the dynamic I've had to worry about. But to be productive is not clear to me, what do you have to do? You have to not be miserable otherwise. I find it extremely hard when I'm having conflicts with collaborators, for example, kind of very hard to enjoy the work we do, even if the work is this fantastical phosphine or things that I know I love, still very difficult. So I think choosing your collaborators based on how well you get along with them is a really sound scientific choice. Having a miserable collaborator ruins your whole life. It's horrible. It makes you not want to do the science. It probably makes you do clumsy science because you don't focus on it. You don't go over it several times. You just want it to be over. And so I think in general, just not being a douchebag can get so much good science done. Just find the good people in your community and collaborate with them, even if they're not as good scientists as others, you'll get better science out. Yeah, don't be a douchebag yourself and surround yourself by other cool people. Exactly. And then you'll get better science than if you had tried to work with three geniuses who are just hell to be around. Yeah, I mean, there's parallel things like that. I'm very fortunate now. I was very fortunate at MIT to have friends and colleagues there too. They were incredible to work with. But I'm currently sort of, I'm doing a lot of fun stuff on the side, like this little podcast thing. And I mentioned to you, I think robotics related stuff. I was just at Boston Dynamics yesterday, checking out their robots. And I'm currently, I guess, hiring people to help me with a very fun little project around those robots. Want to put an ad in? No, I have more applications I can possibly deal with. There's thousands. So it's not an ad, it's the opposite. It's like- We need to put an ad out for someone to help you go through the applications. Well, that too is already there. That's over 10,000 people applied for that. An infinite master Yoshikun doll of application management. But the point is, it's not exactly... The point is, what I'm very distinctly aware of is life is short and productivity is not the right goal to optimize for, at least for me. The right goal to optimize for is how happy you are to wake up in the day and to work with the people that you do, because the productivity will take care of itself. Agreed. So it's so important to select the people well. And I think one of the challenges with academia, as opposed to the thing I'm currently doing, is saying goodbye is sometimes a little bit tougher. Because- Really tough. Your colleagues are there. I mean, goodbye hurts. And then if you have to spend the rest, for many years to come, still surrounded by them in the community, it's tougher. It kind of adds, puts extra pressure to stay in that relationship, in that collaboration. And in some sense, that makes it much more difficult, but it's still worth it. It's still worth it to break ties if you don't... If you're not happy, if there's not that magic, that dance. I talked to this guy named Daniel Kahneman. Oh, I know. Danny Kahneman. Danny, yeah. Boy, did that guy make me realize what a great collaborator is. Well, he had Tversky, right? Yeah. But obviously, they had a really deep collaboration there, but I collaborated with him on a conversation, just talking about... I don't know what we were talking about. I think cars, autonomous vehicles. But the brainstorming session, I'm like a nobody. And the fact that he would, with that childlike curiosity, and that dance of thoughts and ideas, and the push and pull, and the lack of ego, but then enough ego to have a little bit of a stubbornness over an idea, and a little bit of humor, and all those things. It's like, holy shit, that person. Also, the ability to truly listen to another human. It's like, okay, that's what it takes to be a good collaborator. It made me realize that I've been very fortunate to have cool people in my life, but there's levels even to the cool. Yeah, I don't think you can compete with Danny Cantermurn on cool. He's just incredible. But it was like, okay, I guess what I'm trying to say is that collaboration is an art form, but perhaps it's actually a skill, is allowing yourself to develop that skill, because that's one of the fruitful skills. And praise it in students. And I think it is something you can really improve on. I've become a better collaborator as the years have gone on. I don't have some innate collaborative skills. I think they're skills I've developed. And I think in science, there's this really destructive notion of the lone wolf, the scientist who sees things where others don't. Then that's really appealing, and people really like either fulfilling that or pretending to be fulfilling that. And first of all, it's mostly a lie. Any modern scientist, particularly in astronomy, which is so interdisciplinary, any modern scientist that's doing it on their own is doing a crappy job, most likely, because you need an independent set of eyes to help you do things. You need experts in the subfields that you're working on to check your work. But most importantly, it's just a bad idea. It doesn't lead to good science, and it leaves you miserable. I recently had some work that I was avoiding, and I thought, maybe I should pursue a scientific project, because I don't care enough about the outcome, and it's going to be a lot of hard work. And I was trying to balance these two things. It can be really difficult, and the outcome is that maybe 10 people will cite me in the next decade, because no one's asking for this question to be answered. And then I found myself working with this collaborator, Jason Dittman, and I spent a whole afternoon, hours with him working on this. And time flew by, and I just felt taller, and I could breathe better. I was happier. I was a better person when it was done, and that's because he's a great collaborator. He's just a wonderful person that brings out joy out of science that you're doing with him. And that's really the trick. You find the people that make you feel that way about the science you're doing, and you stop worrying about being the lone wolf. That's just a terrible dream that will leave you miserable, and your science will be shit. And since I'm Russian, just murder anybody who doesn't fall into that beautiful collaborative relationship. We were talking about books. Books, yes. Is there books, movies? Why was I talking about my productivity? Oh, you said you maybe don't have time for books and movies. And you said you must make time for books and movies. Make time to not work. Make time to not work whatever that looks like to you. But there's plenty. When I was younger, I found a lot of my scientific fulfillment in books and movies. Now as I got older, I have plenty of that in my work, and I try to read outside my field. I read about Danny Kahneman's work instead. But when I was little, it was Contact, the book, the Carl Sagan book. I really thought I was just like Ellie, and I was going to become Ellie. It really resonated with me, that character, and the notions of life and space and the universe. Even the idea of then the movie came out, and I got to put Jodie Foster in that, which helped. But even the notion of if it is just us, what an awful waste of space, I find extremely useful as a concept to think. Maybe we are special, but that would suck, is a really nice way of thinking of the search for life, that it's much better to not be special and have company. I got that from Carl Sagan. So that's what I always recommend. Let me ask one other ridiculous question. We talked about the death and life cycle that is ever present in the universe until it's not, until it's supermassive and little black holes too at the end of the universe. What do you think is the why, the meaning of it all? What do you think is the meaning of life here on Earth, and the meaning of that life that you look for, whether it's on Venus or other exoplanets? I think there's none. I find enormous relief in the absence of meaning. I think chasing for meaning is a human desire. The universe doesn't give two shits about. But you still enjoy... I enjoy finding meaning in my life. I enjoy finding where the morality lies. I enjoy the complication of that desire. And I feel that is deeply human, but I don't feel that it's universal. LR It's somehow absolute, like we conjure it up. We bring it to life through our own minds, but it's not in any kind of fundamental way real. LS No. And the same way the Sun is not to be blamed for destroying its own planets, the universe doesn't care because it has no meaning. It owes us nothing. And looking for meaning in the universe is demanding answers. Who are we? We're nothing. We don't get to demand anything, and that includes meaning. And I find it very reassuring because once there is no meaning, I don't have to find it. LR Yeah. Once there's no meaning, it's a kind of freedom in a way. You sound a bit like... LS I'm happy about it. This isn't a depressing outlook as far as I'm concerned. LR It's happiness. Yeah. So, I mean, there's a... I don't know if you know who Sam Harris is, but he, despite the pushbacks from the entirety of the world, really argues hard that free will is an illusion, that the deterministic universe and it's all already been predetermined, and he's okay with it. And he's happy with it, that he's distinctly aware of it, and that's okay. LS The quantum world will disagree with him on the deterministic nature of nature. LR Well, he's not saying it's deterministic, but he's saying that the randomness doesn't help either. Randomness does not help in the experience of feeling like you're the decider of your own actions, that he kind of is okay with being a leaf flowing on the river, or being the river, as opposed to having or being like a fish or something that can decide its swimming direction. He's okay just embracing the flow of life. I mean, in that same way, it kind of sounds like your conception of meaning. I mean, it just is. The universe doesn't care. It just is what it is, and we experience certain things, and some feel good and some don't. And that's life. LS But I don't feel like that about life. I think life does have meaning, and it's laudable to look for that meaning in life. I just don't think you can apply that beyond life, and certainly not beyond Earth, that this notion of meaning is a human construct, and so it only applies within us and the other life forms and planet types that suffer from our intrusions or rejoice from our interactions. But this meaning is ours to do as we please. We've created it, we've created a need for it, and so that's our problem to solve. I don't apply it beyond us. I think we as humans have a lot of responsibilities, but they're moral responsibilities, and a lot of the responsibilities are much more easily fulfilled if you find meaning in them. So I think there's value to meaning, whether it's real or not. I just think we gain nothing from trying to anthropomorphize the entire universe. And also, that's the height of hubris. That's not for us to do. LR Yeah, it also could be, just like duality in quantum mechanics, it could be both that there is meaning and then there isn't. And we're somehow depending on the observer, depending on the perspective you take on the thing. LS I mean, even on Earth, that's true. But whether things have meaning or not depends a lot on who's looking. LR Whether it's us humans, the aliens, or the giraffes. Clara, this was an incredible conversation. I mean, I learned so much, but I also am just inspired by the passion you have in- LS Not finding meaning in the universe. LR Yeah, right. For someone who finds- LS I'm very passionate about not finding meaning in the universe. LR You're the most inspiring nihilist I've ever met. I'm just kidding. You are truly an inspiring communicator of everything from phosphine to life to quantum astrochemistry. I can't wait to see what other cool things you do in your career, in your scientific life. Thank you so much for wasting your valuable time with me today. I really appreciate it. LR It was my pleasure. I'd already got my four hours of productivity before I got here, and so it's not a waste. LR It's all downhill from there. Thank you. Thanks for listening to this conversation with Clara Sousa Silva, and thank you to Onnit, Grammarly, Blinkist, and Indeed. Check them out in the description to support this podcast. And now let me leave you with some words from Konstantin Tsiolkovsky. The Earth is the cradle of humanity, but mankind cannot stay in the cradle forever. Thank you for listening, and hope to see you next time.

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Stephen Schwarzman: Going Big in Business, Investing, and AI | Lex Fridman Podcast #96

The following is a conversation with Stephen Schwarzman, CEO and co-founder of Blackstone, one of the world's leading investment firms with over $530 billion of assets under management. He's one of the most successful business leaders in history. I recommend his recent book called, "'What It Takes'," that tells stories and lessons from his personal journey. Stephen is a philanthropist and one of the wealthiest people in the world. Recently, signing the Giving Pledge, thereby committing to give the majority of his wealth to philanthropic causes. As an example, in 2018, he donated $350 million to MIT to help establish his new College of Computing, the mission of which promotes interdisciplinary, big, bold research in artificial intelligence. For those of you who know me, know that MIT is near and dear to my heart and always will be. It was and is a place where I believe big, bold, revolutionary ideas have a home. And that is what is needed in artificial intelligence research in the coming decades. Yes, there's institutional challenges, but also there's power in the passion of individual researchers, from undergrad to PhD, from young scientists to senior faculty. I believe the dream to build intelligence systems burns brighter than ever in the halls of MIT. This conversation was recorded recently, but before the outbreak of the pandemic. For everyone feeling the burden of this crisis, I'm sending love your way. Stay strong, we're in this together. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. Quick summary of the ads. Two sponsors, Masterclass and ExpressVPN. Please consider supporting the podcast by signing up to Masterclass at masterclass.com slash Lex and getting ExpressVPN at expressvpn.com slash LexPod. This show is sponsored by Masterclass. Sign up at masterclass.com slash Lex to get a discount and support this podcast. When I first heard about Masterclass, I thought it was too good to be true. For $180 a year, you get an all-access pass to watch courses from, to list some of my favorites, Chris Hadfield on space exploration, Neil deGrasse Tyson on scientific thinking communication, Will Wright, creator of SimCity and Sims on game design, Carlos Santana on guitar, Gary Kasparov on chess, Daniel Negrano on poker, and many, many more. Chris Hadfield explaining how rockets work and the experience of being launched into space alone is worth the money. By the way, you can watch it on basically any device. Once again, sign up at masterclass.com slash Lex to get a discount and to support this podcast. This show is sponsored by ExpressVPN. Get it at expressvpn.com slash LexPod to get a discount and to support this podcast. I've been using ExpressVPN for many years. I love it. It's easy to use, press the big power on button and your privacy is protected. And if you like, you can make it look like your location is anywhere else in the world. I might be in Boston now, but it can make it look like I'm in New York, London, Paris, or anywhere else in the world. This has a large number of obvious benefits. Certainly, it allows you to access international versions of streaming websites like the Japanese Netflix or the UK Hulu. ExpressVPN works on any device you can imagine. I use it on Linux, shout out to Ubuntu 2004, Windows, Android, but it's available everywhere else too. Once again, get it at expressvpn.com slash LexPod to get a discount and to support this podcast. And now here's my conversation with Steven Schwarzman. Let's start with a tough question. What idea do you believe, whether grounded in data or in intuition, that many people you respect disagree with you on? Well, there isn't all that much anymore since the world's so transparent. But one of the things I believe in, put it in the book, what it takes is, is if you're gonna do something, do something very consequential. Do something that's quite large, if you can, that's unique. Because if you operate in that kind of space, when you're successful, it's a huge impact. The prospect of success enables you to recruit people who wanna be part of that. And those type of large opportunities are pretty easily described. And so not everybody likes to operate at scale. Some people like to do small things because it is meaningful for them emotionally. And so occasionally you get a disagreement on that. But those are life choices rather than commercial choices. That's interesting. What good and bad comes with going big? See, we often, in America, think big is good. What's the benefit, what's the cost? In terms of just bigger than business, but life, happiness, the pursuit of happiness? Well, you do things that make you happy. It's not mandated. And everybody's different. And some people, if they have talent, like playing pro football, other people just like throwing the ball around, not even being on a team. What's better? Depends what your objectives are, depends what your talent is, depends what gives you joy. So in terms of going big, is it both for impact on the world and because you personally, it gives you joy? Well, it makes it easier to succeed, actually. Because if you catch something, for example, that's cyclical, that's a huge opportunity, then you usually can find some place within that huge opportunity where you can make it work. If you're prosecuting a really small thing and you're wrong, you don't have many places to go. So I've always found that the easy place to be and the ability where you can concentrate human resources, get people excited about doing like really impactful big things, and you can afford to pay them, actually, because the bigger thing can generate much more in the way of financial resources. So that brings people out of talent to help you. And so altogether, it's a virtuous circle, I think. How do you know an opportunity when you see one in terms of the one you wanna go big on? Is it intuition, is it facts, is it back and forth deliberation with people you trust? What's the process? Is it art, is it science? Well, it's pattern recognition. And how do you get to pattern recognition? First, you need to understand the patterns and the changes that are happening. And that's either, it's observational on some level. You can call it data, or you can just call it listening to unusual things that people are saying that they haven't said before. And I've always tried to describe this. It's like seeing a piece of white lint on a black dress, but most people disregard that piece of lint. They just see the dress. I always see the lint. And I'm fascinated by how did something get some place it's not supposed to be? So it doesn't even need to be a big discrepancy. But if something shouldn't be someplace in a constellation of facts that sort of made sense in a traditional way, I've learned that if you focus on why one discordant note is there, that's usually a key to something important. And if you can find two of those discordant notes, that's usually a straight line to someplace. And that someplace is not where you've been. And usually when you figure out that things are changing or have changed, and you describe them, which you have to be able to do because it's not some odd intuition. It's just focusing on facts. It's almost like a scientific discovery, if you will. When you describe it to other people in the real world, they tend to do absolutely nothing about it. And that's because humans are comfortable in their own reality. And if there's no particular reason at that moment to shake them out of their reality, they'll stay in it, even if they're ultimately completely wrong. And I've always been stunned that when I explain where we're going, what we're doing, and why, almost everyone just says, that's interesting. And they continue doing what they're doing. And so I think it's pretty easy to do that. But what you need is a huge data set. So before AI and people's focus on data, I've sort of been doing this mostly my whole life. I'm not a scientist, let alone a computer scientist. And you can just hear what people are saying when somebody says something or you observe something that simply doesn't make sense. That's when you really go to work. The rest of it's just processing. You know, on a quick tangent, pattern recognition is a term often used throughout the history of AI. That's the goal of artificial intelligence, is pattern recognition, right? But there's, I would say, various flavors of that. So usually, pattern recognition refers to the process of the, we said dress and the lint on the dress. Pattern recognition is very good at identifying the dress, is looking at the pattern that's always there, that's very common and so on. You almost refer to a pattern that's like in, what's called outlier detection in computer science, right? The rare thing, the small thing. Now, AI is not often good at that. Do you, just almost philosophically, the kind of decisions you made in your life, based scientifically, almost on data, do you think AI in the future will be able to do? Is it something that could be put down into code or is it still deeply human? It's tough for me to say, since I don't have domain knowledge in AI to know everything that could or might occur. I know, sort of in my own case, that most people don't see any of that. I just assumed it was motivational. But it's also sort of, it's hard wiring. What are you wired or programmed to be finding or looking for? It's not what happens every day. That's not interesting, frankly. I mean, that's what people mostly do. I do a bunch of that too, because that's what you do in normal life. But I've always been completely fascinated by the stuff that doesn't fit. Or the other way of thinking about it, it's determining what people want without them saying it. That's a different kind of pattern. You can see everything they're doing. There's a missing piece. They don't know it's missing. You think it's missing, given the other facts you know about them. And you deliver that, and then that becomes sort of very easy to sell to them. To linger on this point a little bit, you've mentioned that in your family, when you were growing up, nobody raised their voice in anger or otherwise. And you said that this allows you to learn to listen and hear some interesting things. Can you elaborate, as you have been, on that idea? What do you hear about the world if you listen? Well, you have to listen really intensely to understand what people are saying, as well as what people are intending. Because it's not necessarily the same thing. And people mostly give themselves away. No matter how clever they think they are. Particularly if you have the full array of inputs. In other words, if you look at their face, you look at their eyes, which are the window on the soul, it's very difficult to conceal what you're thinking. You look at facial expressions and posture. You listen to their voice, which changes. When you're talking about something you're comfortable with or not, are you speaking faster? Is the amplitude of what you're saying higher? Most people just give away what's really on their mind. They're not that clever. They're busy spending their time thinking about what they're in the process of saying. And so if you just observe that, not in a hostile way, but just in an evocative way, and just let them talk for a while, they'll more or less tell you almost completely what they're thinking, even the stuff they don't want you to know. And once you know that, of course, it's sort of easy to play that kind of game. Because they've already told you everything you need to know. And so it's easy to get to a conclusion if there's meant to be one, an area of common interest, since you know almost exactly what's on their mind. And so that's an enormous advantage, as opposed to just walking in some place and somebody telling you something and you believing what they're saying. There's so many different levels of communication. So a powerful approach to life you discuss in the book on the topic of listening and really hearing people is figuring out what the biggest problem and bothering a particular individual or group is, and coming up with a solution to that problem, and presenting them with a solution, right? In fact, you brilliantly describe a lot of simple things that most people just don't do. It's kind of obvious. Find the problem that's bothering somebody deeply. And as you said, I think you've implied that they will usually tell you what the problem is. But can you talk about this process of seeing what the biggest problem for a person is, trying to solve it, and maybe a particularly memorable example? Yeah, sure. You know, if you know you're gonna meet somebody, there are two types of situations. Chance meetings, and you know, the second is you know you're gonna meet somebody. So let's take the easiest one, which is you know you're gonna meet somebody. And you start trying to make pretend you're them. It's really easy. What's on their mind? What are they thinking about in their daily life? What are the big problems they're facing? So if they're, you know, to make it a really easy example, you know, make pretend, you know, they're like President of the United States. Doesn't have to be this president. It can be any president. So you sort of know what's more or less on their mind because the press keeps reporting it. And you see it on television. You hear it. People discuss it. So you know if you're gonna be running into somebody in that kind of position, you sort of know what they look like already. You know what they sound like. You know what their voice is like. And you know what they're focused on. And so if you're gonna meet somebody like that, what you should do is take the biggest unresolved issue that they're facing and come up with a few interesting solutions that basically haven't been out there or that you haven't heard anybody else was thinking about. So just to give you an example, I was sort of in the early 1990s and I was invited to something at the White House which was a big deal for me because I was like a person from no place. And I had met the president once before because it was President Bush because his son was in my dormitory. So I had met him at Parents' Day. I mean it's just like the oddity of things. So I knew I was gonna see him because that's where the invitation came from. And so there was something going on and I just thought about two or three ways to approach that issue. And at that point I was separated and so I had brought a date to the White House and so I saw the president and we sort of went over in a corner for about 10 minutes and discussed whatever this issue was. And I later went back to my date. It was a little rude but it was meant to be confidential conversation and I barely knew her. And she said, what were you talking about all that time? I said, well, you know, there's something going on in the world and I've thought about different ways of perhaps approaching that and he was interested. And the answer is of course he was interested. Why wouldn't he be interested? There didn't seem to be an easy outcome. And so conversations of that type, once somebody knows you're really thinking about what's good for them and good for the situation, it has nothing to do with me. I mean, it's really about being in service to the situation, then people trust you and they'll tell you other things because they know your motives are basically very pure. You're just trying to resolve a difficult situation and help somebody do it. So these types of things, that's a planned situation. That's easy. It's just sometimes you just come upon somebody and they start talking and that requires different skills. You can ask them, what have you been working on lately? What are you thinking about? You can ask them, has anything been particularly difficult? And you can ask most people if they trust you for some reason, they'll tell you. And then you have to instantly go to work on it. And that's not as good as having some advanced planning, but almost everything going on is like out there. And people who are involved with interesting situations, they're playing in the same ecosystem. They just have different roles in the ecosystem. And you can do that with somebody who owns a pro football team that loses all the time. We specialize in those in New York. And you already have analyzed why they're losing. Inevitably, it's because they don't have a great quarterback, they don't have a great coach, and they don't have a great general manager who knows how to hire the best talent. Those are the three reasons why a team fails. Because there are salary caps, so every team pays a certain amount of money for all their players. So it's gotta be those three positions. So if you're talking with somebody like that, inevitably, even though it's not structured, you'll know how their team's doing and you'll know pretty much why. And if you start asking questions about that, they're typically very happy to talk about it because they haven't solved that problem. In some case, they don't even know that's the problem. It's pretty easy to see it. So I do stuff like that, which I find is intuitive as a process, but leads to really good results. Well, the funny thing is when you're smart, for smart people, it's hard to escape their own ego and the space of their own problems, which is what's required to think about other people's problems. It requires for you to let go of the fact that your own problems are all important and then to talk about your, I think while it seems obvious, and I think quite brilliant, it's a difficult leap for many people, especially smart people, to truly empathize with the problems of others. Well, I have a competitive advantage. I like it. Which is, I don't think I'm so smart. That's good. So it's not a problem for me. Well, the truly smartest people I know say that exact same thing. Yeah, being humble is really useful, competitive advantage, as you said. How do you stay humble? Well, I haven't changed much. Since? Since I was in my mid-teens. I was raised partly in the city and partly in the suburbs. And whatever the values I had at that time, those are still my values. I call them middle-class values. That's how I was raised. And I've never changed. Why would I? That's who I am. And so the accoutrement of the rest of your life has gotta be put on the same solid foundation of who you are. Because if you start losing who you really are, who are you? So I've never had the desire to be somebody else. I just do other things now that I wouldn't do as a middle-class kid from Philadelphia. I mean, my life has morphed on a certain level. But part of the strength of having integrity, of personality, is that you can remain in touch with everybody who comes from that kind of background. And even though I do some things that aren't like that, in terms of people I'd meet or situations I'm in, I always look at it through the same lens. And that's very psychologically comfortable and doesn't require me to make any real adjustments in my life, and I just keep plowing ahead. There's a lot of activity and progress in recent years around effective altruism. I wanted to bring this topic with you because it's an interesting one from your perspective. You can put it in any kind of terms, but it's philanthropy that focuses on maximizing impact. How do you see the goal of philanthropy, both from a personal motivation perspective and a societal big picture impact perspective? Yeah, I don't think about philanthropy the way you would expect me to, okay? I look at sort of solving big issues, addressing big issues, starting new organizations to do it, much like we do in our business. We keep growing our business, not by taking the original thing and making it larger, but continually seeing new things and building those, and sort of marshaling financial resources, human resources. And in our case, because we're in the investment business, we find something new that looks like it's gonna be terrific, and we do that, and it works out really well. All I do in what you would call philanthropy is look at other opportunities to help society, and I end up starting something new, marshaling people, marshaling a lot of money, and then at the end of that kind of creative process, so somebody typically will ask me to write a check. I don't wake up and say, how can I give large amounts of money away? I look at issues that are important for people. In some cases, I do smaller things because it's important to a person, and I can relate to that person. There's some unfairness that's happened to them, and so in situations like that, I'd give money anonymously and help them out. And it's like a miniature version of addressing something really big. So at MIT, I've done a big thing, helping to start this new school of computing, and I did that because I saw that there's sort of like a global race on in AI, quantum, and other major technologies, and I thought that the US could use more enhancement from a competitive perspective, and I also, because I get to China a lot and I travel around a lot compared to a regular person, I can see the need to have control of these types of technologies so when they're introduced, we don't create a mess like we did with the internet and with social media, unintended consequence that's creating all kinds of issues and freedom of speech and the functioning of liberal democracies. So with AI, it was pretty clear that there was enormous difference of views around the world by the relatively few practitioners in the world who really knew what was going on, and by accident, I knew a bunch of these people who were like big famous people, and I could talk to them and say, why do you think this is a force for bad? And someone else, why do you feel this is a force for good? And how do we move forward with the technology but at the same time make sure that whatever is potentially sort of on the bad side of this technology with, for example, disruption of workforces and things like that, that could happen much faster than the Industrial Revolution, what do we do about that and how do we keep that under control so that the really good things about these technologies, which will be great things, not good things, are allowed to happen? So to me, this was one of the great issues facing society, the number of people who were aware of it were very small. I just accidentally got sucked into it, and as soon as I saw it, I went, oh my God, this is mega, both on a competitive basis globally, but also in terms of protecting society and benefiting society. So that's how I got involved, and at the end, sort of the right thing that we figured out was sort of double MIT's computer science faculty and basically create the first AI-enabled university in the world and in effect be an example, a beacon to the rest of the research community around the world academically, and create a much more robust US competitive situation among the universities, because if MIT was gonna raise a lot of money and double its faculty, well, you could bet that a number of other universities were gonna do the same thing. At the end of it, it would be great for knowledge creation, great for the United States, great for the world. And so I like to do things that I think are really positive things that other people aren't acting on that I see for whatever the reason. First, it's just people I meet and what they say, and I can recognize when something really profound is about to happen or needs to, and I do it, and at the end of the situation, somebody says, can you write a check to help us? And then the answer is sure, I mean, because if I don't, the vision won't happen. But it's the vision of whatever I do that is compelling. And essentially, I love that idea of whether it's small at the individual level or really big, like the gift to MIT to launch the College of Computing. It starts with a vision, and you see philanthropy as, the biggest impact you can have is by launching something new, especially on an issue that others aren't really addressing. And I also love the notion, and you're absolutely right, that there's other universities, Stanford, CMU, I'm looking at you, that would essentially, the seed will create other, it'll have a ripple effect that potentially might help you us be a leader or continue to be a leader in AI, this potentially very transformative research direction. Just to linger on that point a little bit, what is your hope long-term for the impact the college here at MIT might have in the next five, 10, even 20, or let's get crazy, 30, 50 years? Well, it's very difficult to predict the future when you're dealing with knowledge production and creativity. Yeah, MIT has obviously some unique aspects globally, and there's four big sort of academic surveys. I forget whether it was QS, there's the Times in London, the US News, and whatever. One of these recently, MIT, was ranked number one in the world, right? So leave aside whether you're number three somewhere else, in the great sweep of humanity, this is pretty amazing. So you have a really remarkable aggregation of human talent here. And where it goes, it's hard to tell. You have to be a scientist to have the right feel. But what's important is you have a critical mass of people, and I think it breaks into two buckets. One is scientific advancement, and if the new college can help sort of either serve as a convening force within the university, or help sort of coordination and communication among people, that's a good thing, absolute good thing. The second thing is in the AI ethics area, which is in a way equally important, in a way equally important, because if the science side creates blowback, so that science is a bit crippled in terms of going forward, because society's reaction to knowledge advancement in this field becomes really hostile, then you've sort of lost the game in terms of scientific progress and innovation. And so the AI ethics piece is super important, because in a perfect world, MIT would serve as a global convener, because what you need is you need the research universities, you need the companies that are driving AI and quantum work, you need governments who will ultimately be regulating certain elements of this, and you also need the media to be knowledgeable and trained so we don't get sort of overreactions to one situation, which then goes viral, and it ends up shutting down avenues that are perfectly fine to be walking down or running down that avenue, but if enough discordant information, not even correct necessarily, sort of gets, is pushed around society, then you can end up with a really hostile regulatory environment and other things. So you have four drivers that have to be sort of integrated. And so if the new school of computing can be really helpful in that regard, then that's a real service to science, and it's a service to MIT. So that's why I wanted to get involved for both areas. And the hope is, for me, for others, for everyone, for the world, is for this particular college of computing to be a beacon and a connector for these ideas. Yeah, that's right, I mean, I think MIT is perfectly positioned to do that. So you've mentioned the media, social media, the internet, this complex network of communication with flaws, perhaps. Perhaps you can speak to them. I personally think that science and technology has its flaws but ultimately is, one, sexy, exciting. It's the way for us to explore and understand the mysteries of our world. And two, perhaps more importantly for some people, it's a huge way to, a really powerful way to grow the economy, to improve the quality of life for everyone. So how do we get, how do you see the media, social media, the internet as a society having a healthy discourse about science? First of all, one that's factual and two, one that finds science exciting, that invests in science, that pushes it forward, especially in this science fiction, fear-filled field of artificial intelligence? I think that's a little above my pay grade because trying to control social media to make it do what you want to do appears to be beyond almost anybody's control. And the technology is being used to create what I call the tyranny of the minorities. Okay, a minority is defined as two or three people on a street corner. Doesn't matter what they look like, doesn't matter where they came from, they're united by that one issue that they care about and their job is to enforce their views on the world. And in the political world, people just are manufacturing truth and they throw it all over and it affects all of us. And sometimes people are just hired to do that, I mean, it's amazing. And you think it's one person, it's really just sort of a front for a particular point of view. And this has become exceptionally disruptive for society and it's dangerous and it's undercutting the ability of liberal democracies to function. And I don't know how to get a grip on this and I was really surprised when we, you know, I was up here for the announcement last spring of the College of Computing and they had all these famous scientists, some of whom were involved with the invention of the internet and almost every one of them got up and said, I think I made a mistake. And as a non-scientist, I never thought I'd hear anyone say that and what they said is, more or less, to make it simple, we thought this would be really cool, inventing the internet, we could connect everyone in the world, we can move knowledge around, it was instantaneous, it's a really amazing thing. He said, I don't know that there was anyone who ever thought about social media coming out of that and the actual consequences for people's lives. You know, there's always some younger person, I just saw one of these yesterday, it was reported on the national news, he killed himself when people used social media to basically, you know, sort of ridicule him or something of that type. This is dead. This is dangerous. And, you know, so I don't have a solution for that other than going forward, you can't end up with this type of outcome. Using AI to make this kind of mistake twice is unforgivable. So interestingly, at least in the West and parts of China, people are quite sympathetic to, you know, sort of the whole concept of AI ethics and what gets introduced when and cooperation within your own country, within your own industry, as well as globally, to make sure that the technology is a force for good. On that really interesting topic, since 2007, you've had a relationship with senior leadership with a lot of people in China. And an interest in understanding modern China, their culture, their world, much like with Russia, I'm from Russia, originally, Americans are told a very narrow one-sided story about China that I'm sure misses a lot of fascinating complexity, both positive and negative. What lessons about Chinese culture, its ideas as a nation, its future, do you think Americans should know about, deliberate on, think about? Well, it's sort of a wide question that you're asking about. You know, China's a pretty unusual place. First, it's huge. You know, you got, it's physically huge. It's got a billion three people. And the character of the people isn't as well understood in the United States. Chinese people are amazingly energetic. If you're one of the billion three people, one of the things you gotta be focused on is how do you make your way, you know, through a crowd of a billion 2.99999 other people. Another word for that is competitive. Yes, they are individually highly energetic, highly focused, always looking for some opportunity for themselves because they need to, because there's an enormous amount of just literally people around. And so, you know, what I've found is they'll try and find a way to win for themselves. And their country is complicated because it basically doesn't have the same kind of functional laws that we do in the United States and the West. And the country is controlled really through a web of relationships you have with other people. And the relationships that those other people have with other people. So it's an incredibly dynamic culture where if somebody knocks somebody up on the top who's three levels above you and is in effect protecting you, then you're like a, you know, sort of a floating molecule there, you know, without tethering, except the one or two layers above you, but that's gonna get affected. So it's a very dynamic system, and getting people to change is not that easy because if there aren't really functioning laws, it's only the relationships that everybody has. And so when you decide to make a major change and you sign up for it, something is changing in your life. There won't necessarily be all the same people on your team. And that's a very high-risk enterprise. So when you're dealing with China, it's important to know almost what everybody's relationship is with somebody. So when you suggest doing something differently, you line up these forces. In the West, it's usually you talk to a person and they figure out what's good for them. It's a lot easier. And in that sense, in a funny way, it's easier to make change in the West, just the opposite of what people think. But once the Chinese system adjusts to something that's new, everybody's on the team. It's hard to change them, but once they're changed, they are incredibly focused in a way that it's hard for the West to do in a more individualistic culture. So there are all kinds of fascinating things. One thing that might interest the people who are listening, we're more technologically based than some other group. I was with one of the top people in the government a few weeks ago, and he was telling me that every school child in China is going to be taught computer science. Now imagine 100% of these children. This is such a large number of human beings. Now, that doesn't mean that every one of them will be good at computer science, but if it's sort of like in the West, if it's like math or English, everybody's gonna take it. Not everybody's great at English. They don't write books, they don't write poetry, and not everybody's good at math. Somebody like myself, I sort of evolved to the third grade and I'm still doing flashcards. I didn't make it further in math, but imagine everybody in their society is gonna be involved with computer science. I just even pause on that, I think computer science involves at the basic beginner level programming and the idea that everybody in the society would have some ability to program a computer is incredible. For me, it's incredibly exciting and I think that should give United States pause and consider what, talking about philanthropy and launching things, there's nothing like launching, sort of investing in young, the youth, the education system because that's where everything launches. Yes, well, we've got a complicated system because we have over 3,000 school districts around the country. China doesn't worry about that as a concept. They make a decision at the very top of the government that that's what they want to have happen and that is what will happen. And we're really handicapped by this distributed power in the education area, although some people involved with that area will think it's great, but you would know better than I do what percent of American children have computer science exposure, my guess, no knowledge, would be 5% or less. And if we're gonna be going into a world where the other major economic power, sort of like ourselves, has got like 100% and we got five and the whole computer science area is the future, then we're purposely or accidentally actually handicapping ourselves and our system doesn't allow us to adjust quickly to that. So, you know, issues like this, I find fascinating and if you're lucky enough to go to other countries, which I do, and you learn what they're thinking, then it informs what we ought to be doing in the United States. So the current administration, Donald Trump, has released an executive order on artificial intelligence. Not sure if you're familiar with it, in 2019. Looking several years ahead, how does America sort of, we've mentioned in terms of the big impact, we hope your investment in MIT will have a ripple effect, but from a federal perspective, from a government perspective, how does America establish, with respect to China, leadership in the world at the top for research and development in AI? I think that you have to get the federal government in the game in a big way. And that this leap forward technologically, which is gonna happen with or without us, you know, really should be with us, and it's an opportunity, in effect, for another moonshot kind of mobilization by the United States. I think the appetite actually is there to do that. At the moment, what's getting in the way is the kind of poisonous politics we have. But if you go below the lack of cooperation, which is almost the defining element of American democracy right now in the Congress, if you talk to individual members, they get it, and they would like to do something. Another part of the issue is we're running huge deficits. We're running trillion dollar plus deficits. So how much money do you need for this initiative? Where does it come from? Who's prepared to stand up for it? Because if it involves taking away resources from another area, our political system is not real flexible to do that. If you're creating this kind of initiative, which we need, where does the money come from? And trying to get money when you've got trillion dollar deficits, in a way, could be easy. What's the difference of a trillion and a trillion? A little more. But it's hard with the mechanisms of Congress. But what's really important is this is not an issue that is unknown, and it's viewed as a very important issue. And there's almost no one in the Congress when you sit down and explain what's going on who doesn't say we've gotta do something. Let me ask the impossible question. You didn't endorse Donald Trump, but after he was elected, you have given him advice, which seems to me a great thing to do, no matter who the president is, to positively contribute to this nation by giving advice. And yet, you've received a lot of criticism for this. So on the previous topic of science and technology and government, how do we have a healthy discourse, give advice, get excited, conversation with the government about science and technology without it becoming politicized? Well, it's very interesting. So when I was young, before there was a moonshot, we had a president named John F. Kennedy from Massachusetts here, and in his inaugural address as president, he asked not what your country can do for you, but what you can do for your country. Now, we had a generation of people my age, basically people who grew up with that credo. And sometimes you don't need to innovate. You can go back to basic principles, and that's good basic principle. What can we do? Americans have GDP per capita of around $60,000. It's not equally distributed, but it's big. And people have, I think, an obligation to help their country. And I do that, and apparently I take some grief from some people who project on me things I don't even vaguely believe. But I'm quite simple. I tried to help the previous president, President Obama. He was a good guy, and he was a different party, and I tried to help President Bush, and he's a different party. I sort of don't care that much about what the parties are. I care about, even though I'm a big donor for the Republicans, but what motivates me is what are the problems we're facing? Can I help people get to sort of a good outcome that'll stand any test? But we live in a world now where sort of the filters and the hostility is so unbelievable. In the 1960s, when I went to school, and university, I went to Yale, we had so much stuff going on. We had a war called the Vietnam War. We had sort of black power starting, and we had a sexual revolution with the birth control pill. There was one other major thing going on, and the drug revolution. There hasn't been a generation that had more stuff going on in a four-year period than my era, yet there wasn't this kind of instant hostility if you believed something different. Everybody lived together and respected the other person. And I think that this type of change needs to happen, and it's gotta happen from the leadership of our major institutions. And I don't think that leaders can be bullied by people who are against sort of the classical version of free speech and letting open expression and inquiry. That's what universities are for, among other things, Socratic methods. And so I have, in the midst of this onslaught of oddness, I believe in still the basic principles, and we're gonna have to find a way to get back to that. And that doesn't start with the people sort of in the middle to the bottom who are using these kinds of screens to shout people down and create an uncooperative environment. It's gotta be done at the top with core principles that are articulated. And ironically, if people don't sign on to these kind of core principles where people are equal and speech can be heard and you don't have these enormous shout down biases subtly or out loud, then they don't belong at those institutions. They're violating the core principles. And that's how you end up making change, but you have to have courageous people who are willing to lay that out for the benefit of not just their institutions, but for society as a whole. So I believe that will happen, but it needs the commitment of senior people to make it happen. Courage, and I think for such great leaders, great universities, there's a huge hunger for it. So I am too very optimistic that it will come. I'm now personally taking a step into building a startup first time, hoping to change the world, of course. There are thousands, maybe more, maybe millions of other first-time entrepreneurs like me. What advice, you've gone through this process, you've talked about the suffering, the emotional turmoil it all might entail. What advice do you have for those people taking that step? I'd say it's a rough ride, and you have to be psychologically prepared for things going wrong with frequency. You have to be prepared to be put in situations where you're being asked to solve problems you didn't even know those problems existed. For example, renting space, it's not really a problem unless you've never done it. You have no idea what a lease looks like, right? You don't even know the relevant rent in a market. So everything is new, everything has to be learned. What you realize is that it's good to have other people with you who've had some experience in areas where you don't know what you're doing. Unfortunately, an entrepreneur starting doesn't know much of anything, so everything is something new. I think it's important not to be alone because it's sort of overwhelming, and you need somebody to talk to other than a spouse or a loved one because even they get bored with your problems. Getting a group, if you look at Alibaba, Jack Ma was telling me they basically were like a financial death's door at least twice, and the fact that it wasn't just Jack, people think it is because he became the public face and the driver, but a group of people who can give advice, share situations to talk about, that's really important. And that's not just referring to the small details like renting space. No. It's also the psychological burden. Yeah, and because most entrepreneurs at some point question what they're doing because it's not going so well, or they're screwing it up and they don't know how to unscrew it up because we're all learning, and it's hard to be learning when there are like 25 variables going on. If you're missing four big ones, you can really make a mess. And so the ability to in effect have either an outsider who's really smart that you can rely on for certain type of things, or other people who are working with you on a daily basis. Most people who haven't had experience believe in the myth of the one person, one great person makes outcomes, creates outcomes that are positive. Most of us, it's not like that. If you look back over a lot of the big successful tech companies, it's not typically one person. And you will know these stories better than I do because it's your world, not mine. But even I know that almost every one of them had two people. I mean, if you look at Google, that's what they had, and that was the same at Microsoft at the beginning. And it was the same at Apple. People have different skills, and they need to play off of other people. So the advice that I would give you is make sure you understand that so you don't head off in some direction as a lone wolf and find that either you can't invent all the solutions, or you make bad decisions on certain types of things. This is a team sport. Entrepreneur means you're alone, in effect. And that's the myth, but it's mostly a myth. Yeah, I think, and you talk about this in your book, and I could talk to you about it forever, the harshly self-critical aspect to your personality and to mine as well in the face of failure. It's a powerful tool, but it's also a burden that's very interesting, very interesting to walk that line. But let me ask in terms of people around you, in terms of friends, in the bigger picture of your own life, where do you put the value of love, family, friendship, in the big picture journey of your life? Well, ultimately, all journeys are alone. It's great to have support. And when you go forward and say, your job is to make something work, and that's your number one priority, and you're gonna work at it to make it work, it's like superhuman effort. People don't become successful as part-time workers. It doesn't work that way. And if you're prepared to make that 100 to 120% effort, you're gonna need support, and you're gonna have to have people involved with your life who understand that that's really part of your life. Sometimes you're involved with somebody, and they don't really understand that, and that's a source of conflict and difficulty. But if you're involved with the right people, whether it's a dating relationship or a spousal relationship, you have to involve them in your life, but not burden them with every minor triumph or mistake. They actually get bored with it after a while, and so you have to set up different types of ecosystems. You have your home life, you have your love life, you have children, and that's like the enduring part of what you do. And then on the other side, you've got the sort of unpredictable nature of this type of work. What I say to people at my firm who are younger, usually, well, everybody's younger, but people who are of an age where they're just having their first child, or maybe they have two children, that it's important to make sure they go away with their spouse at least once every two months. It's just some lovely place where there are no children, no issues. Sometimes once a month, if they're sort of energetic and clever. And that- And reaffirm your values as a couple. And you have to have fun. If you don't have fun with the person you're with, and all you're doing is dealing with issues, then that gets pretty old. And so you have to protect the fun element of your life together. And the way to do that isn't by hanging around the house and dealing with sort of more problems. You have to get away and reinforce and reinvigorate your relationship. And whenever I tell one of our younger people about that, they sort of look at me, and it's like the scales are falling off of their eyes, and they're saying, geez, I hadn't thought about that. I'm so enmeshed in all these things, but that's a great idea. And that's something, as an entrepreneur, you also have to do. You just can't let relationships slip because you're half overwhelmed. Beautifully put, and I think there's no better place to end it. Steve, thank you so much. I really appreciate it. It was an honor to talk to you. My pleasure. Thanks for listening to this conversation with Stephen Schwarzman, and thank you to our sponsors, ExpressVPN and Masterclass. Please consider supporting the podcast by signing up to Masterclass at masterclass.com slash Lex, and getting ExpressVPN at expressvpn.com slash LexPod. If you enjoy this podcast, subscribe on YouTube, review it with Five Stars and Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from Stephen Schwarzman's book, What It Takes. It's as hard to start and run a small business as it is to start a big one. You will suffer the same toll financially and psychologically as you bludgeon it into existence. It's hard to raise the money and to find the right people. So if you're going to dedicate your life to a business, which is the only way it will ever work, you should choose one with a potential to be huge. Thank you for listening and hope to see you next time.

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Pixel 6 AI explained | Lex Fridman

Here's the new Pixel 6 Pro from Google. You're now seeing the results of it running a computationally intensive neural network in real time that I put on there for testing purposes. It's using TensorFlow Lite and the new Tensor chip that is optimized for AI. I am unboxing this AI because as a robotics and AI person, I'm interested in seeing how innovation in AI hardware and software is increasingly taking over the smartphone space. Also, unboxing AI makes me think of Pandora's box, the myth that serves as the metaphor for the mystery and the power of AI. I know this is just a phone, but let's pause for a second to think. This computer has over 200,000 times the processing power of the computer that first landed humans on the moon and over 2 million times the RAM. We are engineering our way to superhuman intelligence one phone at a time. One small step for phone and soon enough, one giant leap for a hybrid of machine and mankind. Let's talk about the specs. Here's the comparison of the Pixel 6 to the Pixel 6 Pro across various specs, highlighting what to me are the key differences in yellow and in green, what are the key similarities? So key differences, $300 in price. Also the Pixel 6 Pro has a slightly higher display, slightly higher resolution and a 120 Hertz refresh rate versus the 90 Hertz refresh rate. Though honestly, I've been using both phones for almost a week now and I don't feel any difference between them. The key similarity to me on the AI and the computational side is that they both have the same SoC system on a chip, the Google Tensor. To me, the RAM and storage are very important but once you get to a certain threshold, it really doesn't matter. 12 gigabytes feels the same as eight gigabytes and the same goes for the storage. Both phones have a 50 megapixel wide angle. Now that produces a 12 megapixel image because Google combines the two by two pixel groups into single effective pixel to cut noise and improve color dynamic range. There's also the 12 megapixel ultra wide that's used to decrease noise for both the photos and the videos. And the Pro has a 48 megapixel telephoto lens which results in one key difference I think. It provides a 4X optical zoom plus a 20X digital zoom via machine learning via their super resolution algorithm. The rest to me is pretty much the same. Both phones feel amazing in my hand but of course, me being who I am, I care mostly about what's on the inside and that's the Google Tensor. Now let's talk about the Tensor chip. My main flagship phone for machine learning applications this year has been the Samsung Galaxy S21 Ultra 5G pictured here with the Pixel 6 and the Pixel 6 Pro. The Galaxy Brain is powered by Snapdragon 888. The Pixel Brain is powered by the new Tensor chip. Both are truly amazing machines. I think AI innovation in both hardware and software will be what matters in flagship smartphones over the next decade. This is where the battle is. Let's now look at the details of the technical specs of the Tensor system on a chip and also the philosophical vision behind its architecture. The key components of the architecture of the Tensor system on a chip are the CPUs, the GPU, ISP, TPU, Context Hub, and the Titan M2. Depending on the application, various components of this chip can be used at the same time, leading to what Google is calling heterogeneous computing. For the CPU, there is two big CPU cores with a Cortex-X1. There's two medium CPU cores with the A76 and there's four small CPU cores with the A55. This is in contrast with the most common design for the flagships, which is one big Cortex-X1 core and three medium A78 cores. It's funny that Google says that having one big CPU core is good for benchmarks but not good for the experience. It's funny because, as you'll see in the benchmarks, the Pixel 6 actually performs really well on the single core Geekbench 5 test. Performance-wise, the benefit of having two Cortex-X1s is that you can distribute a thermal budget across them so there's less overheating on intensive tasks like 4K 60 FPS video. So in initial tests, there's a lot less overheating so you'll be able to shoot video for much longer. Besides the CPUs, there's the GPU. There's an upgrade in that. There's the ISP, Image Signal Processor, that's optimized for image and video processing in terms of machine learning. And then there's the more general machine learning engine that's the Tensor Processing Unit. The Context Hub does ultra-low power ambient computing and the Titan M2 does hardware security. Like I said, I've been using the Galaxy S21 Ultra with a Snapdragon 888 for many months now. And so it's nice to take a look at some benchmarks for the CPU, GPU, and NPU for these two flagship chips. Now, the big caveat here, as you probably know, is that benchmarks often don't reflect real-life performance so arguably they don't actually matter. But the main takeaway story here is that these are both amazing chips. In Geekbench 5 CPU benchmark, Pixel 6 outperforms the Galaxy S21 on single-core test and the Galaxy S21 outperforms Pixel 6 on the multi-core test. For the Geekbench machine learning benchmark, the Snapdragon wins on the CPU and the GPU and the Pixel 6 wins on the NPU. The Geekbench machine learning benchmark, by the way, uses TensorFlow Lite. And there's also the AI Benchmark 4 that's specialized for machine learning. It runs a huge number of different neural networks on the devices. And there, once again, Pixel 6 far outperforms Galaxy S21. In fact, it leads every other smartphone on the current AI Benchmark 4 leaderboard. Again, I think the takeaway here in terms of benchmarks is that Pixel 6 does well on machine learning tasks and Snapdragon does well on CPU, GPU-centric tasks. But they're both, again, incredible machines. I think the important thing here is what does this heterogeneous computing enable in terms of software features? And the Pixel 6 provides a huge number of seamlessly integrated machine learning algorithms, increasing the vibrancy of the color with the HDR Plus for the images and HDR Net for the video, improving the accuracy and the efficiency of the face detection, again, both for images and video. And then there's just a huge number of cool features like face on blur, motion mode that adds blur to moving objects. There's the magic eraser that's actually shown here on screen where you can select certain parts of the object. They can be removed and then intelligently filled based on what the background is. Then for images, there's real tone that's looking at skin color, making sure this shows up looking great on photos. Honestly, the video is where the fun is. Like I said, HDR Net, that's an incredible use of neural networks. I actually personally think super resolution algorithms are one of the coolest applications of computer vision in terms of its maybe simplicity and usefulness and impact. And there's a huge number of applications outside of visual domain. So speech, automatic speech recognition, you're talking about deployment of state-of-the-art ASR algorithms that pay attention to context, pauses, is able to do noise removal. And on the language side, there's neural machine translation. Obviously Google is taking natural language NLP really seriously in both the textual domain in speech, that's audio, and again, back to images and video. This is incredible leveraging to do heterogeneous computing on AI hardware to enable all kinds of cool computational photography features. Okay, let's look at some takeaways. My two favorite AI chips for Android now are the Google Tensor and the Snapdragon 888. Time will tell which wins for which applications, but for now competition in this space is great for everyone. If you want me to talk about other AI systems or about running machine learning code on this and on other phones, let me know. I'll close with a quote from Eliezer Yudkowsky. By far, the greatest danger of AI is that people conclude too early that they understand it. Thanks for watching and hope to see you next time.

https://youtu.be/OSRDheEe0ik

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Dava Newman: Space Exploration, Space Suits, and Life on Mars | Lex Fridman Podcast #51

The following is a conversation with Dava Newman. She's the Apollo Program Professor at MIT and the former Deputy Administrator of NASA and has been a principal investigator on four spaceflight missions. Her research interests are in aerospace biomedical engineering, investigating human performance in varying gravity environments. She has designed and engineered and built some incredible spacesuit technology, namely the Biosuit that we talk about in this conversation. Due to some scheduling challenges on both our parts, we only had about 40 minutes together. And in true engineering style, she said, I talk fast, you pick the best questions, let's get it done. And we did. It was a fascinating conversation about space exploration and the future of spacesuits. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. For the first time, this show is presented by Cash App, the number one finance app in the App Store. Cash App is the easiest way to send money to your friends, and it is also the easiest way to buy, sell, and deposit Bitcoin. Most Bitcoin exchanges take days for bank transfer to become investable. Through Cash App, it takes seconds. Invest as little as $1, and now you own Bitcoin. I have several conversations about Bitcoin coming up on this podcast. Decentralized digital currency is a fascinating technology in general to explore, both at the technical and the philosophical level. Cash App is also the easiest way to try and grow your money with their new investing feature. Unlike investing tools that force you to buy entire shares of stock, Cash App, amazingly, lets you instantly invest as little or as much as you want. Some stocks in the market are hundreds, if not thousands of dollars per share, and now you can still own a piece with as little as $1. Brokerage services are provided by Cash App Investing, a subsidiary of Square and member SIPC. I'm also excited to be working with Cash App to support one of my favorite organizations called FIRST, which is best known for their FIRST Robotics and LEGO competitions that seeks to inspire young students in engineering and technology fields all over the world. That's over 110 countries, 660,000 students, 300,000 mentors and volunteers, and a perfect rating on Charity Navigator, which means the donated money is used to maximum effectiveness. When you sign up for Cash App and use the promo code LEXPODCAST, you'll instantly receive $10, and Cash App will also donate $10 to FIRST, an amazing organization that I've personally seen inspire girls and boys to learn, to explore, and to dream of engineering a better world. Don't forget to use the code LEXPODCAST when you download Cash App from the App Store or Google Play Store today. And now, here's my conversation with Dava Newman. You circumnavigated the globe on boat. So, let's look back in history. 500 years ago, Ferdinand Magellan's crew was first to circumnavigate the globe, but he died, I think people don't know, like halfway through, and so did 242 of the 260 sailors that took that three-year journey. What do you think it was like for that crew at that time heading out into the unknown to face probably likely death? Do you think they were filled with fear, with excitement? Probably not fear. I think in all of exploration, the challenge and the unknown, so probably wonderment, and then just the, when you really are sailing the world's oceans, you have extreme weather of all kinds. When we were circumnavigating, it was challenging, new dynamic, you really appreciate Mother Earth, you appreciate the winds and the waves. So, back to Magellan and his crew, since they really didn't have a three-dimensional map of the globe, of the Earth when they went out, just probably looking over the horizon thinking, what's there, what's there? So, I would say that the challenge had to be really important in terms of the team dynamics and that leadership had to be incredibly important. Team dynamics, how do you keep people focused on the mission? So, you think the psychology, that's interesting. There's probably echoes of that in the space exploration stuff we'll talk about. So, the psychology of the dynamics between the human beings on the mission is important? Absolutely. For a Mars mission, it's lots of challenges, technology, but since I specialize in keeping my astronauts alive, the psychosocial issues, the psychology of psychosocial challenges, psychosocial team dynamics, leadership, we're all people. So, that's always a huge impact, one of the top three, I think, of any isolated, confined environment and any mission that is really pretty extreme. So, your Twitter handle is Deva Explorer. So, when did you first fall in love with the idea of exploration? That's a great question. Maybe as long as I can remember, as I grew up in Montana, in the Rocky Mountains, in Helena, in the capital, and so literally, Mount Helena was my backyard, was right up there. So, exploring, being in the mountains, looking at caves, just running around, but always being in nature. So, since my earliest memory, as I think of myself as kind of exploring the natural beauty of the Rocky Mountains where I grew up. So, exploration is not limited to any domain, it's just anything. So, the natural domain of any kind, going out to the woods into a place you haven't been, it's all exploration. I think so. Yeah, I have a pretty all-encompassing definition of exploration. So, what about space exploration? When were you first captivated by the idea that we little humans can venture out into the space, into the great unknown of space? So, it's a great year to talk about that, the 50th anniversary of Apollo 11. I was alive during Apollo, and specifically Apollo 11. I was five years old, and I distinctly remember that. I remember that humanity, I'm sure I probably didn't know their names at the time, Neil Armstrong, Buzz Aldrin, and never forget Michael Collins in orbit. Those three men doing something that just seemed impossible, seemed impossible a decade earlier, even a year earlier. So, the Apollo program really inspired me. And then I think it actually just taught me to dream. Any impossible mission could be possible with enough focus. I'm sure you need some luck, but you definitely need the leadership, you need the focus of the mission. So, since an early age, I thought, of course, people should be interplanetary. Of course, we need people on Earth, and we're going to have people exploring space as well. That seemed obvious at that age, of course. It opened it up. Before we saw men on the moon, it wasn't obvious to me at all. But once we understood that, yes, absolutely, astronauts, that's what they do. They explore, they go into space, and they land on other planets or moons. So, again, maybe a romanticized philosophical question, but when you look up at the stars, knowing that there's at least 100 billion of them in the Milky Way galaxy, right? So, we're really a small speck in this giant thing that's the visible universe. How does that make you feel about our efforts here? I love the perspective. I love that perspective. I always open my public talks with a big Hubble Space Telescope image, looking out into, you mentioned just now, the solar system, the Milky Way. Because I think it's really important to know that we're just a small pale blue dot. We're really fortunate. We're on the best planet by far. Life is fantastic here. That we know of. You're confident this is the best planet? I'm pretty sure it's the best planet that we know of. I mean, I search my researches in mission worlds, and when will we find life? I think actually probably the next decade, we find probably past life, probably the evidence of past life on Mars, let's say. You think there was once life on Mars? Impossibly, yeah. Do you think there's currently? I'm more comfortable saying probably 3.5 billion years ago, I feel pretty confident there was life on Mars, just because then it had an electromagnetic shield, it had an atmosphere, has a wonderful gravity level, 3 Hg is fantastic. You're all super human, we can all slam dunk a basketball, it's going to be fun to play sports on Mars. So I think we'll find past, fossilized, probably the evidence of past life on Mars. Currently, that's again, we need the next decade, but the evidence is mounting for sure. We do have the organics, we're finding organics, we have water, seasonal water on Mars. We used to just know about the ice caps, you know, North and South Pole. Now we have seasonal water. We do have the building blocks for life on Mars. We really need to dig down into the soil, because everything on the top surface is radiated. But once we find out, will we see any lifeforms, will we see any bugs? I leave it open as a possibility. But I feel pretty certain that past life or fossilized lifeforms we'll find. And then we have to get to all these ocean worlds, these beautiful moons of other planets, since we know they have water. And we're looking for some simple search for life, follow the water, you know, carbon based life, that's the only life we know. There could be other life forms that we don't know about, but it's hard to search for them because we don't know. So in our search for life in the solar system, it's definitely, you know, search, you know, follow the water and look for the building blocks of life. So you think in the next decade, we might see hints of past life or even current life? I think so. That's pretty optimistic. I love the optimism. I'm pretty optimistic. Do humans have to be involved, or can this be robots and rovers and... Probably teams. I mean, we've been at it on Mars in particular, 50 years, we've been exploring Mars for 50 years. Great data, right? Our images of Mars today are phenomenal. Now we know how Mars lost its atmosphere, you know, we're starting to know because of the lack of the electromagnetic shield. We know about the water on Mars. So we've been studying 50 years with our robots, we still haven't found it. So I think once we have a human mission there, we just accelerate things. It's always humans and our rovers and robots together. But we just have to think that 50 years we've been looking at Mars and taking images and doing the best science that we can. People need to realize Mars is really far away. It's really hard to get to. You know, this is extreme, extreme exploration. We mentioned Magellan first, or all of the wonderful explorers and sailors of the past, which kind of are lots of my inspiration for exploration. Mars is a different ballgame. I mean, it's eight months to get there, a year and a half to get home. I mean, it's really extreme. Harsh environment in all kinds of ways. But the kind of organism we might be able to see hints of on Mars are kind of microorganisms, perhaps. Yeah, and remember that humans, we're kind of, you know, we're hosts, right? We're hosts to all of our bacteria and viruses, right? Do you think it's a big leap from the viruses and the bacteria to us humans? Put another way, do you think on all those moons, beautiful, wet moons that you mentioned, you think there's intelligent life out there? I hope so. I mean, that's the hope. But, you know, we don't have the scientific evidence for that now. I think all the evidence we have in terms of life existing is much more compelling, again, because we have the building blocks of life now. When that life turns into intelligence, that's a big unknown. If we ever meet, do you think we would be able to find a common language? I hope so. We haven't met yet. It's just so far. I mean, do physics just play a role here? Look at all these exoplanets, 6,000 exoplanets. I mean, even the couple dozen Earth-like planets that are exoplanets that really look like habitable planets. These are very Earth-like. They look like they have all the building blocks. I can't wait to get there. The only thing is, they're 10 to 100 light years away. So scientifically, we know they're there. We know that they're habitable. They have, you know, everything going for them, right? You know, we call them the Goldilocks zone, not too hot, not too cold, just perfect for habitability for life. But now the reality is if they're 10, at the best, to 100, to thousands of light years away. So what's out there? But I just can't think that we're not the only ones. So absolutely life, life in the universe, probably intelligent life as well. Do you think there needs to be fundamental revolutions in how we, the tools we use to travel through space in order for us to venture outside of our solar system? Or do you think the ways, the rockets, the ideas we have now, the engineering ideas we have now will be enough to venture out? Well, it's a good question. Right now, you know, because again, speed of light is a limit. We don't have warp speed warp drive to explore our solar system, to get to Mars, to explore all the planets. Then we need technology push, but technology push here is just advanced propulsion. It'd be great if I could get humans to Mars in say, you know, three to four months, not eight months. I mean, half the time, 50% reduction. That's great in terms of safety and wellness of the crew. And orbital mechanics, but physics rules, you know, orbital mechanics is still there. Physics rules. We can't defy physics. I love that. So invent a new physics. I mean, look at quantum, you know, look at quantum theory. Yeah, you never know. Exactly. I mean, we are always learning. So we definitely don't know all the physics that exist too, but we're, we still have to, it's not science fiction. You know, we still have to pay attention to physics in terms of our speed of travel for space flight. So you were the deputy administrator of NASA during the Obama administration. There's a current Artemis program that's working on a crewed mission to the moon and then perhaps to Mars. What are you excited about there? What are your thoughts on this program? What are the biggest challenges do you think of getting to the moon, of landing to the moon once again, and then the big step to Mars? Well, I love, you know, the moon program now, Artemis. It is definitely, we've been in low earth orbit. I love low earth orbit too, but I just always look at it as three phases. So low earth orbit where we've been 40 years. So definitely time to get back to deep space, time to get to the moon. There's so much to do on the moon. I hope we don't get stuck on the moon for 50 years. I really want to get to the moon, spend the next decade first with lander, then humans. There's just a lot to explore, but to me, it's a big technology push. It's only three days away. So the moon is definitely the right place. So we kind of buy down our technology. We invest in specifically habitats, life support systems. We need suits. We really need to understand really how to live off planet. We've been off planet and low earth orbit, but still, that's only 400 kilometers up, 250 miles, right? So we get to the moon. It really is a great proving ground for the technologies. And now we're in deep space. Radiation becomes a huge issue, again, to keep our astronauts well and alive. And I look at all of that investment for moon, moon exploration to the ultimate goal, you know, the horizon goals, we call it, to get people to Mars. But we just don't go to Mars tomorrow, right? We really need a decade on the moon, I think investing in the technologies, learning, making sure the astronauts are, they're healthy, you know, they're safe and well. And also learning so much about in situ research utilization, ISRU, in situ resource utilization is huge when it comes to exploration for the moon and Mars. So we need a test bed. And to me, it really is a lunar test bed. And then we use those same investments to think about getting people to Mars in the 2030s. Lex Mayer So developing sort of a platform of all the kind of research tools of all the, what's the resource utilization, can you speak to that? Jennifer Yeah, so ISRU for the moon, it's, we'll go to the South Pole. And fascinating, we have images of it. Of course, we know there's permanently shaded areas and like by Shackleton crater, and there's areas that are permanently in the sun. Well, it seems that there's a lot of water ice, you know, water that's trapped in ice, and the lunar craters. That's the first place you go. Why? Because it's water. And when you want to try to, it could be fuel, you know, life support systems. So you kind of get and you go where the water is. And so when the moon is kind of for resources utilization, but to learn how to can we make the fuels out of the resources that are on the moon, we have to think about 3D printing, right? You don't get to bring all this mass with you, you have to learn how to literally live off the land. We need a pressure shell, we need to have an atmosphere for people to live in. So all of that is going to bind down the technology doing the investigation doing the science, what are the basically called lunar volatiles? You know, what is that ice on the moon? How much of it is there? How what are the resources look like? To me that helps us that's just the next step in getting humans to Mars. And it's cheaper and more effective to sort of develop some of these difficult challenges, like solve some of these challenges, practice, develop, test and so on on the moon. Absolutely. Absolutely. And people are gonna love to, you know, you get to the moon, you get to you have a beautiful Earth rise, I mean, you have the most magnificent view of Earth being off planet. So it just makes sense. I think we're gonna have thousands, lots of people, hopefully 10s of 1000s in low Earth orbit, because low Earth orbit, it's a beautiful place to go and look down on the Earth, but people want to return home. Think the lunar explorers will also want to do round trips. And you know, be on the moon three day trip, explore do science also because the lunar day is 14 days and lunar nights, also 14 days. So in that 28 day cycle, you know, half of it is in light half of its in dark. So people would probably want to do, you know, couple week trips, month long trips, not longer than that. What do you mean by people? What do you people explore? Yeah, astronauts are going to be civilians in the future to not all not all astronauts are going to be government astronauts. Actually, when I was at NASA, we changed, we actually got the law changed to recognize astronauts that are not only government employees, you know, NASA astronauts or European Space Agency astronauts or Russian Space Agency that astronauts because of the big push we put in the private sector, that astronauts, essentially, you're going to be astronauts, you get over 100 kilometers up. And I think once you've done orbital orbital flight, then you're an astronaut. So a lot of private citizens are going to become astronauts. Do you think one day you might step foot on the moon? I think it'd be good to go to the moon. I'd give that a shot. Mars, I'm gonna, it's my life's work to get the next generation to Mars. That's that's, that's, that's you or even younger than you, you know, my students generation will be the Martian explorers. I'm just working to facilitate that. But that's not going to be me. Hey, the moon's pretty good. And it's a lot tough. I mean, it's still a really tough mission. It's an extreme mission. Exactly. It's great for exploration, but doable. But again, before Apollo, we didn't think getting humans to the moon was even possible. So we kind of made that possible. But we need to go back. We absolutely need to go back. We're investing in the heavy lift launch capabilities that we need to get there. We haven't had that, you know, since the Apollo days, since Saturn V. So now we have three options on the board. That's what's so fantastic. NASA has its, you know, space launch system. SpaceX is going to have its heavy capability. And Blue Origin is coming along too with heavy lift. So that's pretty fantastic. From where I sit, I'm the Apollo program professor. Today I have zero heavy lift launch capability. I can't wait. Just in a few years, we'll have three different heavy lift launch capabilities. So that's pretty exciting. You know, your heart is perhaps with NASA. But you mentioned SpaceX and Blue Origin. What are your thoughts of SpaceX and the innovative efforts there from the sort of private company aspect? Oh, they're great. Remember that the investments in SpaceX is government funding. It's NASA funding, it's US Air Force funding, just as it should be. Because they're betting on a company who is moving fast, has some new technology development. So I love it. So when I was an athlete, it really was under our public-private partnerships. So necessarily, the government needs to fund these startups. Now SpaceX is no longer a startup. But, you know, it's been at it for 10 years. It's had some accidents, learned a lot of lessons. But it's great because it's the way you move faster. And also some private industry folks, some private businesses will take a lot more risk. That's also really important for the government. What do you think about that culture of risk? I mean, sort of NASA and the government are exceptionally good at delivering sort of safe, like there's a little bit more of a culture of caution and safety and sort of this kind of solid engineering. And I think SpaceX, while it has the same kind of stuff, it has a little bit more of that startup feel where they take the bigger risk. Is that exciting for you to see, seeing bigger risks in this kind of space? Absolutely. And the best scenario is both of them working together, because there's really important lessons learned, especially when you talk about human spaceflight, safety, quality assurance. These things are the utmost importance, both aviation and space, you know, when human lives are at stake. On the other hand, government agencies, NASA can be European Space Agency, you name it, they become very bureaucratic, pretty risk averse, move pretty slowly. So I think the best is when you combine the partnerships from both sides. Industry necessarily has to push the government, take some more risk. You know, like there's smart risk, or I actually gave an award at NASA for failing smart. Failing smart. I love that. You know, so you can kind of break open the culture, say, no, look at Apollo, that was a huge risk. It was done well. So there's always a culture of safety, quality assurance, you know, engineering, you know, at its best. But on the other hand, you want to get things done. And you have to also get them, you have to bring the cost down, you know, for when it comes to launch, we really have to bring the cost down and get the frequency up. And so that's what the newcomers are doing. They're really pushing that. So it's about the most exciting time I can imagine for space flight. Again, a little bit, it really is the democratization of space flight, opening it up, not just because the launch capability, but the science we can do on a CubeSat, what you can do now for very, those used to be, you know, student projects that we would go through, conceive, design, implement, and think about what a small satellite would be. Now they're the most, you know, these are really advanced instruments, science instruments that are flying on little teeny CubeSats that pretty much anyone can afford. So there's not a, there's every nation, you know, every place in the world can fly a CubeSat. And so that's... What's a CubeSat? Oh, CubeSat is a, this is called 1U, and CubeSats we measure in terms of units. So you know, just in terms of I put my both my hands together, that's one unit, two units, three. So little small satellites. So CubeSats are for small satellites. And we actually go by mass as well, you know, small satellite might be 100 kilos, 200 kilos, well under 1000 kilos. CubeSats then are the next thing down from small sats, you know, basically, you know, kilos, tens of kilos, things like that. But kind of the building blocks, CubeSats are fantastic design, fantastic design, it's kind of modular design. So I can take a 1U, one unit of CubeSat. And, you know, but what if I have a little bit more money in payload, I can fly three of them, and just basically put a lot more instruments on it. But essentially, think about something the size of a shoebox, if you will, you know, that would be a CubeSat. And those, how do those help empower you in terms of doing science in terms of doing experiments? Oh, right now, there's getting back to private industry, Planet, the company is, you know, flying CubeSats, and literally looking down on Earth, and orbiting Earth, taking a picture, if you will, of Earth every day, every 24 hours covering the entire Earth. So in terms of Earth observations, in terms of climate change, in terms of our changing Earth, it's revolutionizing, because they're affordable, we can put a whole bunch of them up. The telecoms, we're all, you know, on our cell phones, and we have GPS, we have our telecoms. But those used to be very expensive satellites providing that service. Now we can fly a whole bunch of modular CubeSats. So it really is a breakthrough in terms of modularity, as well as cost reduction. So that's one exciting set of developments. Is there something else that you've been excited about, like reusable rockets, perhaps, that you've seen in the last few years? Yeah, well, the reusability, you had, the reusability is awesome. I mean, it's just the best. Now we have to remember, the shuttle was a reusable vehicle. And the shuttle is an amazing, it's an aerospace engineer, you know, I mean, the shuttle is still just the most gorgeous, elegant, extraordinary design of a space vehicle. It was reusable, it just wasn't affordable. But the reusability of it was really critical, because we flew it up, it did come back. So the notion of reusability, I think, absolutely. Now what we're doing with, we, you know, like global we, but with SpaceX and Borgene, sending the rockets up, recovering the first stages where if they can regain 70% cost savings, that's huge. And just seeing the control, you know, the control and dynamics, just seeing that rocket come back and land. Oh, yeah, that's... It never gets old. It's exciting every single time you look at it and say, that's magic. So it's so cool. To me, the landing is where I stand up, start clapping, just the control. Yeah, just the algorithm, just the control algorithms. And hitting that landing, it's, you know, it's gymnastics for rocket ships. But to see these guys stick a landing, it's just wonderful. So every time, like I say, every time I see, you know, the reusability and the rockets coming back and landing so precisely, it's really exciting. So it is, it is actually, that's a game changer. We are in a new era of lower costs and a lot, the higher frequency. And it's the world, not just NASA, it's many nations are really upping their frequency of launches. So you've done a lot of exciting research, design, engineering on spacesuits. What does the spacesuit of the future look like? Well, if I have anything to say about it, it'll be a very, it'll be a very tight-fitting suit. We use mechanical counterpressure to pressurize right directly on the skin. Seems that it's technically feasible. We're still at the research and development stage. We don't have a flight system, but technically it's feasible. So we do a lot of work in the materials. You know, what materials do we need to pressurize someone? What's the patterning we need? That's what our patents are in, the patterning, kind of how we apply this. It's a third of an atmosphere. Just to sort of take a little step back, you have this incredible biosuit where it's tight-fitting, so it allows more mobility and so on. So maybe even to take a bigger step back, like what are the functions that a spacesuit should perform? Sure. So start from the beginning. A spacesuit is the world's smallest spacecraft. So I really, that's the best definition I can give you. Right now we fly gas pressurized suits, but think of developing and designing an entire spacecraft. So then you take all those systems and you shrink them around a person, provide them with oxygen debris, scrub out their carbon dioxide, make sure they have pressure. They need a pressure environment to live in. So really the spacesuit is a shrunken spacecraft in its entirety, has all the same systems. Communication as well, probably. Yeah, communications, exactly. So you really, thermal control, a little bit of radiation, not so much radiation protection, but thermal control, humidity, oxygen debris. So all those life support systems as well as the pressure production. So it's an engineering marvel, the spacesuits that have flown because they really are entire spacecraft, that is small spacecraft that we have around a person, but they're very massive, but 140 kilos, the current suit, and they're not mobility suits. So since we're going back to the moon and Mars, we need a planetary suit, we need a mobility suit. So that's where we've kind of flipped the design paradigm. I study astronauts, I study humans in motion, and if we can map that motion, I want to give you full flexibility, move your arms and legs. I really want you to be like an Olympic athlete, an extreme explorer. I don't want to waste any of your energy. So we take it from the human design. So I take a look at humans, we measure them, we model them, and then I say, okay, can I put a spacesuit on them that goes from the skin out? So rather than a gas pressurized shrinking that spacecraft around the person, say, here's how humans perform. Can I design a spacesuit literally from the skin out? So that's what we've come up with, mechanical counterpressure, some patterning, and that way it could be order of magnitude less in terms of the mass, and it should provide maximum mobility for a moon or Mars. LUIS So what's mechanical counterpressure? Like, how the heck can you even begin to create something that's tight-fitting? And still doesn't protect you from the elements and so on, and the whole the pressure thing? JILL That's the challenge, it's a big design challenge. We've been working on it for a while. So you can either put someone in a balloon, that's one way to do it, that's conventional, that's the only thing we've ever done. That's a gas pressurized suit. So put someone in a balloon. It's only a third of an atmosphere to keep someone alive. So that's what the current system is. So depending on what units you think, and 30 kilopascals, you know, 4.3 pounds per square inch. LUIS So much less than the pressure that's on Earth. You can still keep a human alive with 0.3, and it's alive and happy. JILL Alive and happy. And you know, you mix the gases. We're having this chat, and we're at one sea level in Boston at one atmosphere. LUIS Oxygen and nitrogen. JILL Oxygen, nitrogen, you put a suit, if we put someone to a third of an atmosphere, so for mechanical counterpressure now, so one way is to do it with a balloon, and that's what we currently have. Or you can apply the pressure directly to the skin. I only have to give you a third of an atmosphere. Right now, you and I are very happy in one atmosphere. So if I put that pressure, a third of an atmosphere on you, I just have to do it consistently, you know, across all of your body and your limbs. And it'll be a gas pressurized helmet. Doesn't make sense to shrink wrap the head. See the blue mangrove. That's a great act. But we don't need to, there's no benefits of like shrink wrapping the head. You put, you know, gas pressurized helmet, because the helmet, then the future of suits you asked me about, the helmet just becomes your information portal. So it will have augmented reality. It'll have all the information you need. Should have, you know, the maps that I need. I'm on the moon. Okay, well, hey, smart helmet. Then show me the map, show me the topography. Hopefully it has the lab embedded too. If it has really great cameras, maybe I can see with that regolith. That's just lunar dust and dirt. What's that made out of? We talked about the water. So the helmet then really becomes this information portal is how I see kind of the IT architecture of the helmet is really allowing me to, you know, use all of my modalities of an explorer that I'd like to. So cameras, voiceover images, if it were really good, it would kind of be, would have lab capabilities as well. Okay. So the pressure comes from the body, comes from the mechanical pressure, which is fascinating. Now, what aspect, when I look at bio-suit, just the suits you're working on, sort of from a fashion perspective, they look awesome. Is that a small part of it too? Oh, absolutely. Because the teams that we work with, of course, I'm an engineer, there's engineering students, there's design students, there's architects. So it really is a very much a multidisciplinary team. So sure, colors, aesthetics, materials, all those things we pay attention to. So it's not just an engineering solution. It really is a much more holistic, it's a suit, it's a suit, you're, you know, you're dressed in a suit now, it's a form fitting. So we really have to pay attention to all those things. And so that's the design team that we work with. And my partner, Ghetradi, you know, we're partners in this in terms of, he comes from an architecture, industrial design background. So bringing those skills to bear as well. We team up with industry folks who are in, you know, athletic performance and designers. So it really is a team that brings all those skills together. So what role does the spacesuit play in our long-term staying in Mars, sort of exploring the, doing all the work that astronauts do, but also perhaps civilians one day, almost like taking steps towards colonization of Mars? What role does a spacesuit play there? So you always need a life support system, pressurized habitat. And I like to say, we're not going to Mars to sit around. So you need a suit. You're, you know, even if you land and have the lander, you're not going there to stay inside. That's for darn sure. We're going there to search for the evidence of life. That's why we're going to Mars. So you need a lot of mobility. So for me, the suit is the best way to give the human mobility. We're always still going to need rovers. We're going to need robots. So for me, exploration is always a suite of explorers. Some people are going to, some of the suite of explorers are humans, but many are going to be robots, smart systems, things like that. But I look at it as kind of all those capabilities together make the best exploration team. So let me ask, I love artificial intelligence and I've also saw that you've enjoyed the movie Space Odyssey, 2001, Space Odyssey. Let me ask the question about how 9000, that makes a few decisions there that prioritizes the mission over the astronauts. Do you think from a high philosophical question, do you think HAL did the right thing of prioritizing the mission? I think our artificial intelligence will be smarter in the future for a Mars mission. It's a great question. The reality is for a Mars mission, we need fully autonomous systems. We will get humans, but they have to be fully autonomous. And that's a really important, that's the most important concept because there's not going to be a mission control on earth, 20 minute time lag, there's just no way you're going to control. So fully autonomous, so people have to be fully autonomous as well, but all of our systems as well. And so that's the big design challenge. So that's why we test them out on the moon as well. When we have a, okay, a few second, three second time lag, you can test them out. We have to really get autonomous exploration down. You asked me earlier about Magellan, Magellan and his crew, they left, right? They were autonomous. They were autonomous, they left and they were on their own to figure out that mission. Then when they hit land, they have resources as in-situ resource utilization and everything else they brought with them. So we have to, I think, have that mindset for exploration. Again, back to the moon, it's more of the testing ground, the proving ground with technologies. But when we get to Mars, it's so far away that we need fully autonomous systems. So I think that's where again, AI and autonomy come in, a really robust autonomy, things that we don't have today yet. So they're on the drawing boards, but we really need to test them out because that's what we're up against. So fully autonomous, meaning like self-sufficient, there's still a role for the human in that picture. Do you think there'll be a time when AI systems just beyond doing fully autonomous flight control will also help or even take mission decisions like Hal did? That's interesting. It depends. I mean, they're going to be designed by humans. I think as you mentioned, humans are always in the loop. I mean, we might be on earth, we might be in orbit on Mars, maybe the systems that land are down on the surface of Mars. But I think we're going to get, we are right now just on earth-based systems, AI systems that are incredibly capable and training them with all the data that we have now, petabytes of data from earth. What I care about for the autonomy and AI right now, how we're applying it in research is to look at earth and look at climate systems. I mean, that's the, it's not for Mars to me today. Right now, AI is to eyes on earth, all of our space data, compiling that using supercomputers, because we have so much information and knowledge and we need to get that into people's hands. We need, first there's the educational issue with climate and our changing climate. Then we need to change human behavior. That's the biggie. So this next decade, it's urgent we take care of our own spaceship, which is spaceship earth. So that's to me where my focus has been for AI systems, using whatever's out there, kind of imagining also what the future situation is. What's the satellite imagery of earth of the future. If you can hold that in your hands, that's going to be really powerful. Will that help people accelerate positive change for earth and for us to live in balance with earth? I hope so. And kind of start with the ocean systems. So oceans to land to air and kind of using all the space data. So it's a huge role for artificial intelligence to help us analyze, I call it curating the data, using the data. It has a lot to a visualizations as well. Do you think, and a weird dark question, do you think human species can survive if we don't become interplanetary in the next century or a couple of centuries? Absolutely, we can survive. I don't think Mars is option B actually. So I think it's all about saving spaceship earth and humanity. I simply put, earth doesn't need us, but we really need earth. All of humanity needs to live in balance with earth because earth has been here a long time before we ever showed up and it'll be here a long time after. It's just a matter of how do we want to live with all living beings, much more in balance because we need to take care of the earth and right now we're not. So that's the urgency. And I think it is the next decade to try to live much more sustainably, live more in balance with earth. I think the human species has a great long optimistic future, but we have to act. It's urgent. We have to change behavior. We have to realize that we're all in this together. It's just one blue bubble. It's for humanity. So when I think people realize that we're all astronauts, that's the great news is everyone's been an astronaut. Spaceship earth. We're all astronauts on spaceship earth and this is our mission. This is our mission to take care of the planet. And yet, as we explore out from our spaceship earth here, out into the space, what do you think the next 50, 100, 200 years look like for space exploration? I'm optimistic. So I think that we'll have lots of people, thousands of people, tens of thousands of people, who knows, maybe millions in low earth orbit. That's just a place that we're going to have people and actually some industry, manufacturing, things like that. That dream, I hope we realize getting people to the moon so I can envision a lot of people on the moon. Again, it's a great place to go. Living or visiting? Probably visiting and living. If you want to, most people are going to want to come back to earth, I think, but there'll be some people and it's not such a long, it's a good view. It's a beautiful view. So I think that we will have many people on the moon as well. I think there'll be some people, you told me, wow, hundreds of years out. So we'll have people, we'll be interplanetary for sure as a species. So I think we'll be on the moon. I think we'll be on Mars. Venus, no, it's already a runaway greenhouse gas. So not a great place for science. Jupiter, all of within the solar system, great place for all of our scientific probes. I don't see so much in terms of human physical presence. We'll be exploring them. So we live in our minds there because we're exploring them and going on those journeys. But it's really our choice in terms of our decisions of how in balance we're going to be living here on the earth. When do you think the first woman, first person will step on Mars? Step on Mars? Well, I'm going to do everything I can to make sure it happens in the 2030s. 2030s? Say mid, you know, 2020, mid-20, you know, 2025, 2035, we'll be on the moon. And hopefully with more people than us. But first with, you know, a few astronauts, it'll be global, international folks. But we really need those 10 years, I think, on the moon. And then so by later in the decade, in the 2030s, we'll have all the technology and know-how and we need to get that human mission to Mars done. We live in exciting times. And, Deva, thank you so much for leading the way. And thank you for talking today. I really appreciate it. Thank you. My pleasure. Thanks for listening to this conversation. And thank you to our presenting sponsor, Cash App. Remember to use code LEXPODCAST when you download Cash App from the App Store or Google Play Store. You'll get 10 bucks, $10, and $10 will go to FIRST, a STEM education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future. Thank you and hope to see you next time.

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Donald Knuth: Ant Colonies and Human Cognition | AI Podcast Clips

You did mention that you thought that an understanding of the way ant colonies are able to perform incredibly organized tasks might well be the key to understanding human cognition. So these fundamentally distributed systems. So what do you think is the difference between the way Don Knuth would sort a list and an ant colony would sort a list or perform an algorithm? Sorting a list isn't the same as cognition though, but I know what you're getting at is, well, the advantage of ant colony, at least we can see what they're doing. We know which ant has talked to which other ant and it's much harder with the brains to know to what extent neurons are passing signal. So I'm just saying that ant colony might be, if they have the secret of cognition, think of an ant colony as a cognitive single being rather than as a colony of lots of different ants. I mean, just like the cells of our brain and the microbiome and all that is interacting entities, but somehow I consider myself to be a single person. Well, an ant colony, you can say might be cognitive somehow and I mean, okay, I smash a certain ant and the organism's saying, hmm, that stung, what was that? But if we're going to crack the secret of cognition, it might be that we could do so by psyching out how ants do it because we have a better chance to measure the communicating by pheromones and by touching each other and sight but not by much more subtle phenomenon like electric currents going through. But even a simpler version of that, what are your thoughts of maybe Conway's Game of Life? Okay, so Conway's Game of Life is able to simulate any computable process and any deterministic process is. I like how you went there. I mean, that's not its most powerful thing, I would say. I mean, it can simulate it but the magic is that the individual units are distributed and extremely simple. Yes, we understand exactly what the primitives are. The primitives, just like with the ant colony, even simpler though. But still, it doesn't say that I understand life. I mean, it gives me a better insight into what does it mean to have a deterministic universe? What does it mean to have free choice, for example? Do you think God plays dice? Yes, I don't see any reason why God should be forbidden from using the most efficient ways to. I mean, we know that dice are extremely important in efficient algorithms. There are things that couldn't be done well without randomness and so I don't see any reason why God should be prohibited from. When the algorithm requires it, you don't see why the physics should constrain it.

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MIT 6.S094: Deep Learning for Human Sensing

Today we will talk about how to apply the methods of deep learning to understanding the sense in the human being. The focus will be on computer vision, the visual aspects of a human being. Of course, we humans express ourselves visually, but also through audio, voice and through text. Beautiful poetry and novels and so on, we're not going to touch those today, we're just going to focus on computer vision. How we can use computer vision to extract useful actionable information from video, images, video of human beings, in particular in the context of the car. So, what are the requirements for successfully applying deep learning methods in the real world? So, when we're talking about human sensing, we're not talking about basic face recognition of celebrity images. We're talking about using computer vision, deep learning methods to create systems that operate in the real world. And in order for them to operate in the real world, there are several things. They sound simple, some are much harder than they sound. First and the most important, here from most to less, more to less critical, ordered, is data. Data is everything, real world data. We need a lot of real world data to form the data set on which these supervised learning methods can be trained. I'll say this over and over throughout the day today, data is everything. That means data collection is the hardest part and the most important part. We'll talk about how that data collection is carried out here in our group at MIT, all the different ways we capture human beings in the driving context, in the road user context, pedestrian, cyclist. But the data, it starts and ends at data. The fun stuff is the algorithms, but the data is what makes it all work. Real world data. Okay, then once you have the data, okay, data isn't everything, I lied. Because you have to actually annotate it. So what do we mean by data? There's raw data, video, audio, LIDAR, all the types of sensors we'll talk about to capture real world road user interaction. You have to reduce that into meaningful, representative cases of what happens in that real world. In driving, 99% of the time, driving looks the same. It's the 1%, the interesting cases that we're interested in. And what we want is algorithms, to train learning algorithms on those 1%. So we have to collect 100%, we have to collect all the data, and then figure out an automated, semi-automated ways to find the pieces of that data that could be used to train neural networks and that are representative of the general kinds of things that happen in this world. Problem, efficient annotation. Annotation isn't just about drawing bounding boxes on images of cats. Annotation tooling is key to unlocking real world performance. Systems that successfully solve some problem, accomplish some goal in real world data. That means designing annotation tools for a particular task. Annotation tools that are used for glance classification, for determining where drivers are looking, is very different than annotation tools used for body pose estimation. It's very different than the tooling that we use for psych fuse, investing thousands of dollars for the competition for this class, to annotate fully seen segmentation where every pixel is colored. There needs to be tooling for each one of those elements, and they're key. That's HCI question. That's a design question. There's no deep learning. There's no robotics in that question. It's how do we leverage human computation, the human brain to most effectively label images such that we can train neural networks on them. Hardware. In order to train these networks, in order to parse the data we collect, and we'll talk about, we have now over five billion images of data, of driving data. In order to parse that, you can't do it on a single machine. You have to do large-scale distributed compute, and large-scale distributed storage. And finally, the stuff that's the most exciting, that people, this class, and many classes, and much of the literature is focused on, is the algorithms. The deep learning algorithms. The machine learning algorithms. The algorithms that learn from data. Of course, that's really exciting and important, but what we find time and time again in real world systems is that as long as these algorithms learn from data, so as long as it's deep learning, the data is what's much more important. Of course, it's nice for the algorithms to be calibration free, meaning they learn to calibrate, self-calibrate. We don't need to have the sensors in an exact same position every time. That's a very nice feature. The robustness of the system is then generalizable across multiple vehicles, multiple scenarios. And one of the key things that comes up time and time again, and we'll mention today, is a lot of the algorithms developed in deep learning are really focused for computer vision, are focused on single images. Now, the real world happens in both space and time, and we have to have algorithms that both capture the visual characteristics, but also look at the sequence of images, sequence of those visual characteristics that form the temporal dynamics, the physics of this world. So it's nice when those algorithms are able to capture the physics of the scene. The big takeaway I would like, if you leave with anything today, unfortunately, it's that the painful, boring stuff of collecting data, of cleaning that data, of annotating that data, in order to create successful systems is much more important than good algorithms, or great algorithms. It's important to have good algorithms, as long as you have neural networks that learn from that data. Okay, so today I'll talk, I'd like to talk about human imperfections, and the various detection problems, the pedestrian body pose, glance, emotion, cognitive load estimation, that we can use to help those humans as they operate in the driving context. And finally, try to continue with the idea, the vision, that fully autonomous vehicles, as some of our guests speak, as I spoke about, and Sterling Anderson will speak about tomorrow, is really far away. That the humans will be an integral part of the operating, cooperating with AI systems. And I will continue on that line of thought to try to motivate why we need to continuously approach the autonomous vehicle, the self-driving car paradigm in a human-centered way. Okay, first, before we talk about human imperfections, let's just pause and acknowledge that humans are amazing. We're actually really good at a lot of things. That's sometimes sort of fun to talk about how much, how terrible of drivers we are, how distracted we are, how irrational we are, but we're actually really good at a lot of things. And that's why I'm here today. I'm here to talk about the human imperfections that we're actually really damn good at driving. Here's a video of a state-of-the-art soccer player, Messi, the best soccer player in the world, obviously. And a state-of-the-art robot on the right. Same thing. Well, it's not playing, but I assure you the American Ninja Warrior, Casey, is far superior to the DARPA humanoid robotics systems shown on the right. Okay, so continuing on the line of thought to challenge us here that humans are amazing is, you know, there's a record high in 2016 in the United States. There was over 40,000 since many years. It crossed the 40,000 fatalities mark. More than 40,000 people died in car crashes in the United States. But that's in 3.2 trillion miles traveled. So that's one fatality per 80 million miles. That's one in 625 chance of dying in a car crash in your lifetime. Interesting side fact, for anyone in the United States, folks who live in Massachusetts are the least likely to die in a car crash. Montana is the most likely. So for everyone that thinks of Boston Drives as terrible, maybe that adds some perspective. Here's a visualization of Waze data across a period of a day showing you the rich blood of the city, that the traffic flow of the city, the people getting from A to B on a mass scale and doing it, surviving, doing it okay. Humans are amazing. But they're also flawed. Texting, sources of distraction with a smartphone, the eating, the secondary tasks of talking to other passengers, grooming, reading, using navigation system. Yes, sometimes watching video and manually adjusting or adjusting the radio. And 3,000 people were killed and 400,000 were injured in motor vehicle crashes involving distraction in 2014. Distraction is a very serious issue for safety. Texting, every day more and more people text. Smartphones are proliferating our society. 170 billion text messages are sent in the United States every month. That's in 2014. You can only imagine what it is today. Eyes off road for five seconds is the average time your eyes are off the road while texting, five seconds. If you're traveling 55 miles an hour in that five seconds, that's enough time to cover the length of a football field. So you're blindfolded. You're not looking at the road in five seconds, the average time of texting. You're covering the entire football field. So many things can happen in that moment of time. That's distraction. Drunk driving. 31% of traffic fatalities involve a drunk driver. Drug driving. 23% of nighttime drivers tested positive for a legal prescription or over-the-counter medication. Distracted driving, as I said, is a huge safety risk. Drowsy driving. People driving tired. Nearly 3% of all traffic fatalities involve a drowsy driver. If you are uncomfortable with videos that involve risk, I urge you to look away. These are videos collected by AAA of teenagers, a very large-scale naturalistic driving data set, and it's capturing clips of teenagers being distracted on their smartphone. So this is a video of teenagers being distracted on their smartphone. So once you take it in, the problem we're against. So in that context of human imperfections, we have to ask ourselves, is the human-centered approach to autonomy in systems, autonomous vehicles, that are using artificial intelligence to aid the driving task? Do we want to go, as I mentioned a couple of lectures ago, the human-centered way or the full autonomy way? The tempting path is towards full autonomy, where we remove this imperfect, flawed human from the picture altogether, and focus on the robotics problem of perception and control and planning and driving policy. Or do we work together, human and machine, to improve the safety, to alleviate distraction, to bring driver attention back to the road and use artificial intelligence to increase safety through collaboration, human-robot interaction versus removing the human completely from the picture. As I've mentioned, as Sterling will certainly talk about tomorrow and rightfully so, and yesterday or on Tuesday, Emilio has talked about, the L4 way is grounded in literature, is grounded in common sense in some sense. It's, you can count on the fact that humans, the natural flaws of human beings to overtrust, to misbehave, to be irrational about their risk estimates, will result in improper use of the technology. And that leads to what I've showed before, the public perception of what drivers do in semi-autonomous vehicles. They begin to overtrust. The moment the system works well, they begin to overtrust. They begin to do stuff they're not supposed to be doing in the car, taking it for granted. A recent video that somebody posted, this is a common sort of more practical concern that people have, is, well, the traditional ways to ensure the physical engagement of the driver is by saying they should touch the wheel, the steering wheel every once in a while. And of course, there's ways to bypass the need to touch the steering wheel. Some people hang objects, like a can, off of the steering wheel. In this case, brilliantly, I have to say, they shove an orange into the wheel to make the touch sensor fire and therefore be able to take their hands off the autopilot. And that kind of idea makes us believe that there's no way that, you know, humans will find a way to misuse this technology. However, I believe that that's not giving the technology enough credit. Artificial intelligence systems, if they're able to perceive the human being, are also able to work with the human being. And that's what I'd like to talk about today. Teaching cars to perceive the human being. And it all starts with data. It's all about data, as I mentioned. Data is everything in these real world systems. With the MIT naturalistic driving data set of 25 vehicles, of which 21 are equipped with Tesla autopilot, we instrument them. This is what we do with the data collection. Two cameras on the driver. We'll see the cameras on the face, capturing high definition video of the face. That's where we get the glance classification, the emotion recognition, cognitive load, everything coming from the face. Then we have another camera, a fisheye, that's looking at the body of the driver. And from that comes the body pose estimation, hands-on wheel, activity recognition. And then one video looking out for the full scene segmentation for all the scene perception tasks. And everything is being recorded, synchronized together with GPS, with audio, with all the cam coming from the car on a single device. Synchronization of this data is critical. So that's one road trip in the data. We have thousands like it, traveling hundreds of miles, sometimes hundreds of miles under automated control, in autopilot. That's the data. Again, as I said, data is everything. And from this data, we can both gain understanding what people do, which is really important. And that's why we have the data collection. Understanding what people do, which is really important to understand how autonomy, successful autonomy, can be deployed in the real world. And to design algorithms for training, for training the deep learning, the deep neural networks, in order to perform the perception task better. 25 vehicles, 21 Teslas, Model S, Model X, and now Model 3. Over a thousand miles collected a day. Every single day, we have thousands of miles in the Boston, Massachusetts area, driving around. All of that video being recorded. Now over 5 billion video frames. There's several ways to look at autonomy. One of the big ones is safety. That's what everybody talks about. How do we make these things safe? But the other one is enjoyment. Do people actually want to use it? We can create a perfectly safe system. We can create it right now. We've had it forever, before even cars. A car that never moves is a perfectly safe system. Well, not perfectly, but almost. But it doesn't provide a service that's valuable. It doesn't provide an enjoyable driving experience. So okay, what about slow-moving vehicles? That's an open question. The reality is with these Tesla vehicles, and L2 systems, doing automated driving, people are driving 33% of miles using Tesla Autopilot. What does that mean? That means that people are getting value from it. A large fraction of their driving is done in an automated way. That's value, that's enjoyment. The glance classification algorithm we'll talk about today is used as one example that we use to understand what's in this data. Shown with the bar graphs there, and the red and the blue. Red is during manual driving, blue is during autopilot driving. And we look at glance classification, regions of where drivers are looking, on-road and off-road. And if that distribution changes with automated driving or manual driving, and with these glance classification methods, we can determine that there's not much difference, at least until you dig into the details, which we haven't done. And the aggregate, there's not a significant difference. That means people are getting value, enjoying using these technologies, but yet they're staying attentive, or at least not attentive, but physically engaged. When your eyes are on the road, you might not be attentive, but you're at the very least physically, your body's positioned in such a way, your head is looking at the forward roadway, that you're physically in position to be alert, and to take in the forward roadway. So they're using it, and they don't overtrust it. And that's, I think, the sweet spot that human-robot interaction needs to achieve, is the human gaining through experience, through exploration, through trial and error, exploring and understanding the limitations of the system to a degree that overtrust can occur. That seems to be happening in this system. And using the computer vision methods I'll talk about, we can continue to explore how that can be achieved in other systems. When the fraction of automated driving increases, from 30% to 40% to 50% and so on. It's all about the data, and I'll harp on this again. The algorithms are interesting. I will mention, of course, it's the same convolutional networks. It's the same networks that take in raw pixels, and extract features of interest. It's 3D convolutional neural networks that take in a sequences of images, and extract the temporal dynamics along with the visual characteristics of the individual images. It's RNNs, LSTMs, that use the convolutional neural networks to extract features, and over time, look at the dynamics of the images. These are pretty basic architectures, the same kind of deep neural network architectures, but they rely fundamentally and deeply on the data, on real-world data. So, let's start where, perhaps on the human sensing side, it all began, which is pedestrian detection. Decades ago. To put it in context, pedestrian detection here, shown from left to right, on the left is green, showing the easier human sensing tasks tasks of sensing some aspect of the human being, pedestrian detection, which is detecting the full body of a human being in an image or video, is one of the easier computer vision tasks. And on the right, in the red, micro saccades, these are tremors of the eye, or measuring the pupil diameter, or measuring the cognitive load, or the fine blink dynamics of the eye, the velocity of the blink, with micro glances and eye pose, are much harder problems. So you think body pose estimation, pedestrian detection, face classification detection, recognition, head pose estimation, all those are easier tasks. Anything that starts getting smaller, looking at the eye, and everything that start getting fine-grained, this is much more difficult. So we start at the easiest, pedestrian detection. And as the usual challenges of all of computer vision, we've talked about, is the various styles of appearance. So the inter-class variation, the different possible articulations of our bodies, superseded only perhaps by cats, but us humans are pretty flexible as well. The presence of occlusion, from the accessories that we wear, to occluding self-occlusion, and occluding each other. But crowded scenes have a lot of humans in them, and they occlude each other, and therefore being able to disambiguate, to figure out each individual pedestrian, is a very challenging problem. So how do people approach this problem? Well, there is a need to extract features, from raw pixels. Whether that was Harkascades, Hogg, or CNN, through the decades, the sliding window approach was used. Because the pedestrians can be small in an image, or big, so there's the problem of scale. So you use a sliding window, to detect where that pedestrian is. You have a classifier, that's given a single image, says is this a pedestrian or not. You take that classifier, you slide it across the image, to find where all the pedestrians are seen are. So you can use non-neural network methods, or you can use convolution neural networks, for that classifier. It's extremely inefficient. Then came along, R-CNN, Fast R-CNN, Fast R-CNN. These are networks, that as opposed to doing a complete sliding window approach, are much more intelligent, clever about generating the candidates to consider. So as opposed to considering, every possible position of a window, different scales of the window, they generate more, a small subset of candidates, that are more likely. And finally, using a CNN classifier for those candidates, whether there's a pedestrian or not. Whether there's an object of interest or not, a face or not. And using non-maximal suppression, because there's overlapping bounding boxes, to figure out what is the most likely bounding box, around this pedestrian, around this object. That's R-CNN. And there's a lot of variants, now with Mask R-CNN, really the state-of-the-art localization network. Mask also adds to this, on top of the bounding box, also perform segmentation. There's VoxelNet, which does three-dimensional and LiDAR data, uses localization and point clouds. So it's not just using a 2D images, but in 3D. But it's all kind of grounded, in the R-CNN framework. Okay, data. So we have large-scale data collection, going on here in Cambridge. If you've seen cameras or LiDAR, various intersections throughout MIT, we're part of that. So for example, here's one of the intersections, we're collecting about 10 hours a day, instrumenting it with various sensors, I'll mention. But we see about 12,000 pedestrians a day, across that particular intersection. Using 4K cameras, using stereo vision cameras, 360, now the Insta360, which is an 8K 360 camera, GoPro, LiDAR of various sizes, the 64 channel or the 16. And recording. This is where, this is where the data comes from. This is from the 360 video. This is from the LiDAR data of the same intersection. This is for the 4K camcorders, pointing at a different intersection. And the different, then capturing the entire 360 view, with the vehicles approaching, and the pedestrians making crossing decisions. This is understanding the negotiation, that pedestrians, the nonverbal negotiation, that pedestrians perform in choosing to cross or not. Especially when they're jaywalking, and everybody jaywalks. Especially if you're familiar with this particular intersection, there's more jaywalkers than non-jaywalkers. It's a fascinating one. And so we record everything about the driver, and everything about the pedestrians. And again, RCNN, this is where it comes in, is you do, bounding box detection of the pedestrians, here the vehicles as well. And allows you to convert this raw data, into hours of pedestrian crossing decisions. And begin to interpret it. That's pedestrian detection, bounding box. For body pose estimation, body pose estimation, is the more difficult task. Body pose estimation is also finding the joints. The hands, the elbows, the shoulders, the hips, knees, feet. The landmark points in the image, x, y position, that mark those joints. That's body pose estimation. So why is that important in driving for example? It's important to determine the vertical position, or the alignment of the driver. Seat belts and the, sort of the airbag testing, is always performed, and the seat belt testing is performed, with the dummy, considering the frontal position, in a standard dummy position. The greater and greater degrees of automation, comes more capability and flexibility, for the driver to get misaligned, from the standard quote-unquote dummy position. And so body pose, or at least upper body pose estimation, allows you to determine, how often these drivers get out of line, from the standard position. General movement. And then you can look at hands on wheel, smartphone, smartphone detection, activity, and help add context to glance estimation, that we'll talk about. So some of the more traditional methods, or sequential, is detecting first the head, and then stepping, detecting the shoulders, the elbows, the hands. The deep pose holistic view, which has been the, a very powerful, successful way for multi-person pose estimation, is performing a regression, of detecting body parts, from the entire image. It's not sequentially stitching bodies together, it's detecting the left elbow, the right elbow, the hands individually. It's performing that detection, and then stitching everything together afterwards. Allowing you to deal, with the crazy deformations of the body that happen, the occlusions, and so on. Because you don't need all the joints to be visible. And with this cascade of pose regressors, meaning, these are convolutional neural networks, that take in a raw image, and produce an xy position, of their estimate of each individual joint. Input is an image, output is an estimate of a joint, of an elbow, shoulder, whatever, one of several landmarks. And then you can build on top of that, every estimation, zooms in on that particular area, and performs a finer and finer grain estimation, of the exact position of the joint. Repeating it over and over and over. So through this process, we can do part detection in multi-person, in multi-person scene that contain multiple people. So we can detect the head, the neck here, the hands, the elbows, shown in the various images on the right, that don't have an understanding, who the head, the elbows, the hands belong to. It's just performing a detection, without trying to do individual person, detection first. And then, finally, connecting, or not finally, but next step is connecting with, part affinity fields, is connecting those parts together. So first you detect individual parts, then you connect them together. And then through bipartite matching, you determine which is, who is that each individual body part, most likely belonging to. So you kind of stitch the different people together, in the scene, after the detection is performed with the CNN. We use this approach for detecting, the upper body, specifically the shoulders, the neck, and the head, eyes, nose, ears. That is used to determine, the position of the driver, relative to the standard dummy position. For example, looking during autopilot driving, 30 minute periods, we can look at, on the x-axis is time, and the y-axis is the position of the neck point, that I pointed out in the previous slide, that the midpoint between the two shoulders, the neck, is the position over time, relative to where it began. This is the slouching, the sinking into the seat. Allowing the car to know that information, and allowing us, or the designers of safety systems, to know that information is really important. We can use the same body pose algorithm, to from the perspective of the vehicle, outside the vehicle perspective. The vehicle looking out, is doing the, as opposed to just playing pedestrian detection, using body pose estimation. Again, here in Kendall Square, vehicles crossing, observing pedestrians, making crossing decisions, and performing body pose estimation, which allows you to then, generate visualizations like this, and gain understanding like this. On the x-axis is time, on the y-axis is, on the top plot in blue, is the speed of the vehicle. The speed of the vehicle, the ego vehicle, from which the camera is observing the scene. And on the bottom, in green, in green, up and down is a binary value. Whether the pedestrian is zero, when the pedestrian is not looking at the car, one when the pedestrian is looking at the car. So we can look at thousands of episodes like this, crossing decisions, nonverbal communication decisions, and determine using body pose estimation, the dynamics of this nonverbal communication. Here, just nearby, by Media Lab, crossing, there's a pedestrian approaches, we can look in green there, when the pedestrian glances, looks away, glances at the car, looks away. Fascinating glance behavior that happens. Interesting most people look away, before they cross. Same thing here, this is an example, we have thousands of these. Body pose estimation allows you to, get this fine-grained information, about the pedestrian glance behavior, pedestrian body behavior, hesitation. Glance classification, one of the most important things in driving, is determining where drivers are looking. If there's any sensing, that I advocate, and is, has the most impact in the driving context, is for the car to know, where the driver is looking. And at the very crude, region level, information of, is the driver looking on-road or off-road? That's what we mean by glance classification. It's not, the standard gaze estimation problem of, X, Y, Z, determining where the eye pose, and the head pose combine, to determine where the driver is looking. No, this is classifying two regions, on-road, off-road, or six regions, on-road, off-road, left, right, center stack, rear view mirror, and instrument cluster. So it's region-based, glance allocation, not the geometric gaze estimation problem. Why is that important? It allows you to address it, as a machine learning problem. It's a subtle but critical point. Every problem we try to solve in human sensing, in driver sensing, has to be learnable, from data. Otherwise it's not, it's not amenable to, application in the real world. We can't design systems in the lab, that are deployed without learning, if they involve a human. It's possible to do, SLAM localization, by having really good sensors, and doing localization, using those sensors, without much learning. It's not possible to design systems, that deal with lighting variability, and the full variability of human behavior, without being able to learn. So gaze estimation, the geometric approach, of finding the landmarks in the face, and from those landmarks, determining the, the orientation of the head, and the orientation of the eyes, there's no learning there, outside of actually, training the systems, to detect the different landmarks. If we convert this, into a gaze classification problem, shown here, glance classification, is, when taking the raw video stream, determining in post, so humans are annotating this video, is the driver, which region the driver is looking at. That's, we're able to do, by converting the problem, into a simple variant of classification. On road, off road, left, right. The same can be done for pedestrians. Left, forward, right. It can annotate, the regions of where they're looking, and using that kind of classification approach, determine, are they looking at the cars or not? Are they looking away? Are they looking at their smartphone? Without doing the 3D gaze estimation, again, it's a subtle point, but think about it, if you wanted to estimate, exactly where they're looking, you need that ground truth. You don't have that ground truth, unless you, there's no, in the real world data, there's no way to get the information, about where exactly people were looking. You're only inferring. So you have to convert it, into a region-based classification problem, in order to be able to train neural networks on this. And the pipeline is the same. The source video, here, the face, the 30 frames a second video, coming in of the driver's face, or the human face. There is some degree of calibration that's required. You have to determine, approximately where the sensor is, that's taking in the image. Especially for the glance classification task, because it's region-based, it needs to be able to estimate, where the forward roadway is. Where the camera frame is, relative to the world frame. The video stabilization, and the face frontalization, all the basic processing, that remove the vibration of the noise, that remove the physical movement of the head, that remove the shaking of the car, in order to be able to determine stuff, about eye movement and blink dynamics. And finally, with neural networks, there is nothing left, except taking in the raw video of the face, for the glance classification tasks, and the eye for the cognitive load tasks. Raw pixels, that's the input to these networks. And the output is whatever the training data is. And we'll mention each one. So whether that's cognitive load, glance, emotion, drowsiness, the input is the raw pixels, and the output is whatever you have data for. Data is everything. Here, the face alignment problem, which is a traditional geometric approach, to this problem, is designing algorithms, that are able to detect accurately, the individual landmarks in the face, and from that estimate the geometry, of the head pose. For the classification version, we perform the same kind of alignment, or the same kind of face detection alignment, to determine where the head is. But once we have that, we pass in just the raw pixels, and perform the classification on that. As opposed to doing the estimation, it's classification. Allowing you to perform, what's shown there on the bottom, is the real-time classification, of the head. And the real-time classification, of where the driver is looking. Road, left, right, center stack, instrument cluster, and rear view mirror. And as I mentioned, annotation tooling is key. So we have a total 5 billion video frames, one and a half billion of the face, that would take, tens of millions of dollars to annotate, just for the glance classification, fully. So we have to figure out what to annotate, in order to train the neural networks, to perform this task. And what we annotate, is the things that the network, is not confident about. The moments of high lighting variation, the partial occlusions, from the light or self-occlusion, and the moving out of frame, the out of frame occlusions. All the difficult cases, going from frame to frame to frame, here in the different pipelines, starting at the top, going to the bottom. Whenever the classification has a low confidence, we pass it to the human. It's simple. We're relying on the human, only when the classifier is not confident. And the fundamental trade-off, in all of these systems, is what is the accuracy, we're willing to put up with. Here in red and blue, we're not confident. Here in red and blue, in red is human choice, decision, in blue is machine task. In red, we select the video, we want to classify. In blue, the neural network performs, the face detection task, localizing the camera, choosing what is the angle of the camera, and provides a trade-off, between accuracy and percent frames, it can annotate. So certainly, a neural network can annotate glance for the entire data set, but it would achieve accuracy, in the case of glance classification, of low 90% classification, on the sixth class task. Now, if you wanted a higher accuracy, then it will only be able to achieve that, for a smaller fraction of frames. That's the choice. And then, a human has to go in, and perform the annotation, of the frames, that the algorithm was not confident about. And it repeats over and over. The algorithm is then trained, on the frames that were annotated by the human. And it repeats this process, over and over on the frames, until everything is annotated. Yes. Yes, absolutely. The question was, do you ever observe that, the classifier is highly confident, about the incorrect class? Yep. Right. Question was, well then, how do you deal with that? How do you account for that? How do you account for the fact that, highly confident predictions, can be highly wrong? Yeah, false positives. False positives, that you're really confident in. There's no, at least in our experience, there's no good answer for that. Except, more and more training data, on the things you're not confident about. That usually seems to deal, generalize over cases. We don't encounter, obvious large categories of data, where you're really confident, about the wrong thing. Usually, some degree of human annotation, fixes most problems. Annotating the low confidence, part of the data, solves all incorrect issues. But of course, that's not always true, in the general case. You can imagine a lot of scenarios, where that's not true. For example, one thing we always perform, is for each individual person, we usually annotate, a large amount of the data, manually, no matter what. So we have to make sure, that the neural network, has seen that person, in the various, in the various ways, their face looks like, with glasses, with different hair, with different lighting variation. So we want to manually annotate that. It's over time, we allow the machine, to do more and more of the work. So what's resulting in this, in the glance classification case, is you can do real-time classification. You can give the car information, about whether the driver's looking, on road or off road. This is critical information, for the car to understand. And you want to pause for a second, to realize that, when you're driving a car, for those who drive, or for those who've driven any kind, a car with any kind of automation, it has no idea, about what you're up to at all. It has no, it doesn't have any information, about the driver, except if they're touching, the steering wheel or not. More and more now, with the GM super cruise vehicle, and Tesla now, has added a driver facing camera, they're slowly starting to think about, moving towards perceiving the driver. But most vehicles on the road today, have no knowledge of the driver. This knowledge is almost common sense, and trivial for the car to have. It's common sense, how important this information is, where the driver is looking. That's the glance classification problem. And again, emphasizing that we've converted, it's been three decades of work, on gaze estimation. Gaze estimation is doing, head pose estimation, so the geometric orientation of the head, combining the orientation of the eyes, and using that combined information, to determine where the person is looking. We convert that, into a classification problem. So the standard gaze estimation definition, is not a machine learning problem. Glance classification, is a machine learning problem. This transformation is key. Emotion. Human emotion is a fascinating thing. So the same kind of pipeline, stabilization, cleaning of the data, raw pixels in, and then the classification is emotion. The problem with emotion, if I may speak as an expert, human. Not an expert in emotions, just an expert at being human, is that, there is a lot of ways to customize emotion, to categorize emotion, to define emotion, to define emotion, whether that's for the, the primary emotion of the Paris scale, with love, joy, surprise, anger, sadness, fear. There's a lot of ways to mix those together, to break those apart, into hierarchical taxonomies. And the way we think about it, in the driving context at least, there is a general emotion recognition task, sort of, I'll mention, I'll mention it, but it's kind of how we think about primary emotions, is detecting the broad categories of emotion, of joy and anger, of disgust and surprise. And then there is application specific emotion recognition, where you're using the facial expressions, that all the various ways that we can deform our face, to communicate information, to determine the, a specific question about the interaction of the driver. So first for the general case, these are the building blocks. I mean there is, there's countless ways of deforming the face, that we use to communicate with each other. There's 42 individual facial muscles, that can be used to form those expressions. One of our favorite tools to work with, is the Affectiva SDK. This is their, their task with the general emotion recognition task. General emotion recognition task, is taking in raw pixels, and determining categories of emotion. Very subtleties of that emotion in a general case, producing a classification of anger, disgust, fear, surprise, so on. And then mapping, I mean essentially what these algorithms are doing, whether, whether they're using deep neural networks or not, whether they're using face alignment, to do the landmark detection, and then tracking those landmarks over time, to do the facial actions. They're determined, they're mapping the expressions, the component, the various expressions we can make, with our eyebrows, with our nose, and mouth, and eyes, to map them to the emotion. So I'd like to highlight one, because I think it's an illustrative one, for joy, an expression of joy is smiling. So there's an increased likelihood, that you observe a smiling expression on the face, when joy is experienced, or vice versa. If there's an increased probability of a smile, there's an increased probability of emotion of joy being experienced. And then joy, an experience has a decreased probability likelihood, of brow raising and brow furrowing. So if you see a smile, that's a, that's a plus for joy. If you see brow raise, brow furrow, brow furrow is a minus for joy. That's for the general emotion recognition task, that's been well studied, that's sort of the core of effective computing movement, from the visual perspective, again from the computer vision perspective. For the application specific perspective, which we're really focused on, again data is everything. What are you annotating? We can take, here we have a large scale data set of drivers, interacting with a voice-based navigation system. So they're tasked with, in various vehicles, to enter a navigation, so they're talking to their GPS using their voice. This is for, depending on the vehicle, depending on the system, in most cases an incredibly frustrating experience. So we have them perform this task, and then the annotation is self-report. After the task, they say on a scale of one to ten, how frustrating was this experience? And what you see on top, is, is the expressions detected and associated with, a satisfied, a person who said a, a ten on the satisfaction, so a one on the frustration scale. Is perfectly satisfied with a voice-based interaction. On the bottom, is frustrated, as a, I believe a nine, on the frustration scale. So, the feature, the strongest there, the expression, remember joy, smile was the strongest indicator of frustration, for all our subjects. That was the strongest expression. Smile was the thing that was always there, for frustration. There's other various, frowning that followed, and shaking the head and so on, but smiles were there. So that shows you the kind of clean difference between, general emotion recognition task, and the application specific. Here, perhaps they enjoyed an absurd, moment of joy at the, frustration they were experiencing. You can sort of get philosophical about it, but the practical nature is, they were frustrated with the experience, and were using the 42 muscles of the face, that make expressions, to do classification of frustrated or not. And their data does the work, not the algorithms. It's the annotation. A quick mention, for the AGI class next week, for the artificial general intelligence class, one of the competitions we're doing, is we have a, JavaScript, face, that's trained with a neural network, to form various expressions, to communicate, with the observer. So we're interested in creating emotion, which is a nice mirror coupling, of the emotional recognition problem. It's gonna be super cool. Cognitive load, we're starting to get, to the eyes. Cognitive load, is the degree to which a human being is, accessing their memory, or is lost in thought. How hard they're working, in their mind, to recollect something, to think about something. That's cognitive load. And to do a quick pause of, eyes as the window to cognitive load, eyes the window to the mind. There's a different ways the eyes move. So there's pupils, the black part of the eye, they can expand and contract, based on various factors, including the lighting variations in the scene. But they also expand and contract, based on cognitive load. That's a strong signal. They can also move around. There's ballistic movements, the cades. When we look around, eyes jump around the scene. They can also, do something called smooth pursuit, when you, and connecting to our animal past, can see a delicious meal, flying by, or running by, that your eyes can follow it perfectly. They're not jumping around. So when we read a book, our eyes are using saccadic movements, when they jump around, and when the smooth pursuit, the eyes moving perfectly smoothly. Those are the kinds of movements, we have to work with. And cognitive load can be detected, by looking at various factors of the eye. The blink dynamics, the eye movement, and the pupil diameter. The problem is, in the real world, and real world data, with lighting variations, everything goes out the window, in terms of using pupil diameter, which is the standard way to measure, non-contact way to measure cognitive load in the lab, when you can control lighting conditions, and use infrared cameras. When you can't, all that goes out the window, and all you have is the blink dynamics, and the eye movement. So, neural networks to the rescue. 3D convolutional neural networks, in this case, we take a sequence of images of the eye, through time, and use 3D convolutions, as opposed to 2D convolutions. On the left, is everything we've talked about, previous to this, is 2D convolutions, when the convolution filter, is operating on the XY 2D image. Every channel is operated on, by the filter, individually, separately. 3D convolutional neural networks, separately, 3D convolutions, combine those, convolve across the, across multiple images, across multiple channels. Therefore, being able to learn, the dynamics of the scene, through time as well, not just spatially, temporal. And data, data is everything. For cognitive load, we have, in this case, 92 drivers, so how do we, sort of, perform the cognitive load, classification task? We have these drivers, driving on the highway, and performing the, what's called the N-back task. Zero back, one back, two back. And that task involves, hearing numbers being read to you, and then recalling those numbers, one at a time. So when zero back, the system gives you a number, seven, and then you have to just say, that number back, seven. And it keeps repeating that, it's easy. It's supposed to be the easy task. One back is when you hear a number, you have to remember it, and then, for the next number, you have to say the number previous to that. So you kind of have to keep one number in your memory always, and not get distracted, by the new information coming up. With two back, you have to do that, two numbers back. So you have to use memory more and more, with two back. So cognitive load is higher and higher. Okay, so what do we do? So what do we do? We use face alignment, face frontalization, and detecting the eye closest to the camera, and extract the eye region. And now we have this nice, raw pixels of the eye region, across six seconds of video. And we take that, and put that into 3D convolutional neural network, and classify simply, one of three classes. Zero back, one back, and two back. So we have a ton of data, of people on the highway, performing these tasks, and back tasks. And that forms the classification, supervised learning training data. That's it. The input is 90 images, it's at 15 frames a second. And the output is one of three classes. Face frontalization, I should mention, is the technique developed under, for face recognition. Because most face recognition tasks, require frontal face orientation. Is also what we use here, to normalize everything, that we can focus in on the exact blink. It's taking the, it's taking whatever the orientation of the face, and projecting into the frontal position. Taking the raw pixels of the face, is detecting the eye region, zooming in, and grabbing the eye. Where you find, and this is where the intuition builds. It's a fascinating one. What's being plotted here, is the relative movement of the pupil. The relative movement of the eye, based on the different cognitive loads. For cognitive load on the left of zero, so when your mind is not that lost in thought. And cognitive load of two on the right, when it is lost in thought, the eye moves a lot less. Eye is more focused on the forward roadway. That's an interesting finding, but it's only an aggregate. And that's what the neural network is tasked with doing, with extracting on a frame by frame basis. This is a standard 3D convolutional architecture. Again, taking in the image sequence as the input, cognitive load classification as the output, and classifying on the right, is the accuracy that's able to achieve, of 86%. That's pretty cool. From real world data. The idea is that you can just plop in a webcam, get the video, going into the neural network, and it's predicting a continuous stream, from zero to two of cognitive load. Because every single zero back, one back, two back classes, have a confidence that's associated with them, so you can turn that into a real value between zero and two. And what you see here is a plot, of three of the people on the team here, driving a car, performing a task of conversation. And in white, showing the cognitive load, frame by frame, at 30 frames a second, estimating the cognitive load of each of the drivers. From zero to two on the y-axis. So these are high cognitive load, and showing in on the bottom, red and yellow, of high medium cognitive load. And when everybody's silent, the cognitive load goes down. So we can perform now, with this simple neural network, with the training data that we formed, we can extend that to any arbitrary new data set, and generalize. Okay, those are some examples of how neural networks can be applied. And why is this important? Again, is, while we focus on the sort of the perception task, of using neural networks, of using sensors and signal processing, to determine where we are in the world, where the different obstacles are, and form trajectories around those obstacles. We are still far away from completely solving that problem. I would argue 20 plus years away. The human will have to be involved. And so when it's the system is not able to control, when the system is not able to perceive, when there's some flawed aspect about the perception, or the driving policy, the human has to be involved. And that's where we have to know, let the car know, what the human is doing. That's the essential element of human-robot interaction. The most popular car in the United States today, is the Ford F-150. No automation. The thing that sort of inspires us, and makes us think, that transportation can be fundamentally transformed, is the Google self-drive, the Waymo car, and all of our guest speakers, and all the folks working on autonomous vehicles. But if you look at it, the only people who are at a mass scale, or beginning to, are actually injecting automation into our daily lives, is the ones in between. It's the Tesla, it's the L2 systems, it's the Tesla system, the Super Cruise, the Audi, the Volvo S90s, the vehicles that are slowly adding some degree of automation, and teaching human beings how to interact with that automation. And here it is again, the path towards mass scale automation, where steering wheel is removed, the consideration the human is removed, I believe is more than two decades away. On the path to that, we have to understand, and create successful human-robot interaction. Approach autonomous vehicles, autonomous systems, in a human-centered way. The mass scale integration of these systems, of the human-centered systems, like the Tesla vehicles. Tesla is just a small company right now. The kind of L2 technologies, have not truly penetrated the market, have not penetrated our vehicles, even the new vehicles being released today. I believe that happens in the early 2020s. And that's going to form the core of our algorithms, that will eventually lead to the full autonomy. All of that data, what I mentioned with Tesla, with the 32% miles being driven, all of that is training data for the algorithms. The edge cases arise there. That's where we get all this data. In our data set at MIT is 400,000 miles. Tesla has a billion miles. So that's all training data, on the way, on the stairway, to mass scale automation. Why is this important, beautiful, and fundamental to the role of AI in society? I believe that self-driving cars, when they're in this way, are focused on the human-robot interaction, are personal robots. They're not perception control systems, tools like a Roomba, performing a particular task. When human life is at stake, when there's a fundamental transfer between it, of life, of a human being, giving their life over to an AI system directly, one-on-one, there's a transfer. That is kind of a relationship that is one indicative of a personal robot. This is, it requires all the things of understanding, communication, of trust. These are fascinating to understand how a human-robot can form trust enough to create a really, an almost one-to-one understanding of each other's mental state, learn from each other. Oh boy. So, one of my favorite movies, Good Will Hunting, we're in Boston, Cambridge. Have to, have to, gonna regret this one. This is Robin Williams, speaking about human imperfections. So I'd like you to take this quote, and replace every time he mentions girl with car. People call those things imperfections. Robin Williams is talking about his wife who passed away in the movie. Talking about her imperfections. They call these things imperfections, but they're not. That's the good stuff. And then we get to choose who we let into our weird little worlds. You're not perfect sport, and let me save you the suspense. This girl you met, she isn't perfect either. You know what? Let me save you the suspense. You're not perfect sport. This girl you met, she isn't perfect either. You know what? Let me just. Well, that'll be the idiosyncrasies that only I know about. You're not perfect sport. Let me save you the suspense. This girl you met, she isn't perfect either. But the question is, would they not be perfect for each other? That's the whole deal. That's what intimacy is all about. Now you could do everything in the world sport, but the only way you'd find that is by getting in a shop. So the approach we're taking in building the autonomous vehicle we are here at MIT in our group, it's the human-centered approach to autonomous vehicles that we're going to release in March of 2018 in the streets of Boston. Those who would like to help, please do. I will talk, run a course on deep learning for understanding the humans at CHI 2018. We'll be going through tutorials that go far beyond the visual, the convolutional neural network-based detection of various aspects of the face and body. We'll look at natural language processing and how that's going to be used in the future. We'll look at natural language processing, voice recognition, and GANs. If you're going to CHI, please join. Next week, we have an incredible course that aims to understand, to begin to explore the nature of intelligence, natural and artificial. We have Josh Tenenbaum, Ray Kurzweil, Lisa Barrett, Nate Derbinski looking at cognitive modeling architectures, Andrej Karpathy, Stephen Wolfram, Richard Moyes talking about autonomous weapon systems and AI safety, Mark Rybert from Boston Dynamics and the amazing, incredible robots I have, and Ilya Tsitskever, from OpenAI and myself. So what next? For folks registered for this course, you have to submit by tonight a deep traffic entry that achieves a speed of 65 miles an hour and I hope you continue to submit more that win the competition. The high performer award will be given to folks, the very few folks who achieve 70 miles an hour faster. We will continue rolling out segfuse, having hit a few snags and invested a few thousands of dollars in the sanitation process of annotating a large-scale data set for you guys. We'll continue this competition that will take us into a submission towards NIPS where we would hope to submit the results for this competition and DeepCrash, the deeper enforcement learning. These competitions will continue through May 2018. I hope you stay tuned and participate. There's upcoming classes. The AGI class I encourage you to come to is going to be fascinating and there's so many cool, interesting ideas that we're going to explore. It's going to be awesome. There's an introduction to deep learning course that I'm also a part of where I get a little bit more applied and get folks who are interested in the very basic algorithms of deep learning how to get started with those hands-on. And there's an awesome class I ran last year for those who took this class last year. We also talked about it the global business of AI and robotics. The slides are online. I encourage you to click a link on there and register. It's in the spring. It's once a week and it truly brings together a lot of cross-disciplinary folks to talk about ideas of artificial intelligence and the role of AI and robotics in society. It's an awesome class. And if you're interested in applying deep learning methods in automotive space, come work with us. We have a lot of fascinating problems to solve or collaborate. So with that, I'd like to thank everybody here, everybody across the community that's been contributing. We have thousands of submissions coming in for deep traffic and I'm just truly humbled by the support we've been getting and the team behind this class is incredible. Thank you to Nvidia, Google, Amazon, Alexa, Autolive and Toyota. And today we have shirts, extra large, extra, extra large and medium over there, small and large over there. Large over there. The big and small people over here and then the medium-sized people over here. So just grab it, grab one and enjoy. Thank you very much.

https://youtu.be/Z2GfE8pLyxc

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Yannis Pappas: History and Comedy | Lex Fridman Podcast #175

The following is a conversation with Giannis Papas, a comedian who co-hosted the podcast History Hyenas that I came across when I was researching the Battle of Crete from World War II. He and his co-host were hilarious in their rants about history and about life. The chemistry they have is probably the best of any co-hosted comedy podcast or even podcast in general that I've ever heard. As of a few weeks ago, unfortunately, History Hyenas is no more, at least for now, because all good things must come to an end. But Giannis hosts a new podcast called Long Days with Giannis Papas, plus he has a comedy special on YouTube for free. Quick mention of our sponsors, Wine Access, Blinkist, Magic Spoon, and Indeed. Check them out in the description to support this podcast. As a side note, let me say that some of you have noticed that I have not spoken with too many computer scientists, physicists, biologists, or engineers recently. The reason has to do mostly with the risk aversion of many of these folks in the time of COVID, especially as they get closer to taking the vaccine. I'm tested several times a week and still some people are just more willing than others to have an in-person conversation in these times. I only do these podcasts in person because I look for the possibility of a genuine human connection. I'm willing to sacrifice a lot for that. Maybe it's silly, but I look for the magic that Charles Bukowski writes about in his poem Nirvana, the magic that is somehow in the air on those rare occasions when two people meet, talk, and you notice that while on the surface you may be worlds apart, you're still somehow woven from the same fabric. I've had that with many guests. Jim Keller comes to mind, but many others as well. I'm an AI person. Machine learning, robotics, computer science is my passion. Trust me, I can't wait to be having more technical conversations again, but I will also continue to mix in comedians, musicians, historians, and of course, wise, all-seeing sages like Giannis Papas and Tim Dillon, just to keep it, as Tim likes to say, fun. This is the Lex Friedman Podcast, and here is my conversation with Giannis Papas. You've co-hosted, until recently, an amazing history comedy podcast called The History Hyenas. So you're a bit of a student of history. Yeah, an F student of history. F student, okay. I thought it was more like a D minus. D minus, yeah. Still got to repeat the grade if you get all D minuses. I actually had a.67 GPA average my freshman year, and I had to do it again. This podcast is going to be the spectrum of human intelligence. It runs the gamut from there to here. So this is going to set the low bar for anything. I'm barely sliding into human. I'm closer to chimp. And I bring that up that you're also friends with the great, the powerful Tim Dillon. So let's talk about power and the corrupting effects of power. Sometimes I look at Tim Dillon as he grows in power. I thought you meant in size. Size, I think they're correlated. Yeah. I've been in Austin a couple days. I saw him once. We had eight meals in one day. Eight meals. Yeah. So I feel like I've been here longer than I have just because of the meals with Dillon. Kid likes biscuits and barbecue. Okay. So he's more like, see, I was imagining Putin or something like that. He's more like the North Korean dictator. All right. They get along great, those two. Yeah. They would get, I mean, Tim Dillon and King John Uhm would be like, they could make like a buddy cop movie. They would get along like Lethal Weapon. That would be a good pitch movie. Great podcast. Yeah, that would be a great podcast. Yeah. Yeah. So much to talk about. So many similar ideas about the world. So what do you think the world would look like if Tim Dillon was given absolute power? He seems like a person that's an interesting study of the corrupting effects of power. Yeah. You don't want to give him power. I don't even want him wearing a suit. I want a guy who's as thoughtful and educated as you wearing a suit. Because suits corrupt you. You put that suit on, you start feeling that power. Yeah. Definitely. It's like, you know, yeah, I don't even want Tim Dillon in a suit. Power would, he would kill people. He'd get rid of anything that he deemed. I mean, if you made a lobster roll and it wasn't up to Tim Dillon's standard, he would have you executed. The entire restaurant staff is just gone. He would have people below his food standard executed. There'd be programs, not of people who are political dissidents, but of people who don't meet his food standard. His cuisine standard is high and he's usually right. Do you think power does corrupt people? Yes. Like one of the reasons we mentioned offline Joe Rogan, he's been an inspiration to me because he gets, forget power, just more famous and famous. And yes, probably a bit of power in terms of influence. And he's still pretty much the same guy. I'm not sure that's going to be true for everybody. Do you ever think, ask yourself that question? Yeah. He's a rare breed. He's like a benign king. Most people I meet who are like really powerful are like douchebags. And that's how they got there. I think that's, psychopaths have the advantage because they don't have feelings. And Joe's a rare example. He's just a powerhouse of will. And I do think about that. Yeah. I think I should be stopped right now. Just stop me right now because yeah, power for me, I would, when people get power, they indulge. I don't think it changes anyone. It just reveals your darkest. People aren't supposed to have anything they want. You got to be able to struggle for everything. So I would have a harem. I'd be like a Roman dictator. Yeah. I'd like a Roman emperor. I mean, people call them emperors. They were dictators. The most effective leaders are dictators. I hope we get back to that. Democracy hasn't worked. I'm ready for a succession of Caesars and I want to start with AOC. It's true. Dictators get the job done. They do. They do. At certain point you got, that's why social workers can only get you so far. You need action. I was a social worker for five years and all you do is ask about medications and you don't solve anything. I do ask myself of that, like, cause I'm more in the tech space of constructing systems that prevent me from being corrupt. Cause right now I'm all about love and all about those kinds of things. But I wonder, you said like, it just reveals the darkness. The problem is we might not be aware of our own darkness. I have the same feeling about money, actually. I've been avoiding thinking about money, like basically constructing my moral system. My moral compass around money. So like the moment I feel a little too happy about the idea of owning some cool shiny thing, I started to think, okay, I'm not going to own that shiny thing cause I'm afraid of the slippery slope of it. Yeah. You ever think about that kind of stuff? Yeah. The funny thing about the capitalist system is it puts sort of a profit motive above of beauty and you notice when you see certain cities, especially in the old days, where like buildings used to be beautiful and now they're just like boxes. They throw a kid up and it's just for all profit margin. It's the illusion of permanence that, you know, it's like, oh, let me get as much money as I can. You're like, yeah, you know, my dad used to say, you know, everyone, it's a cliche, but you can't take it with you. So it's kind of, it's comical to me that we're here trying to get this infinite amount, like they were, it's like Sisyphus. We're all trying to climb this hill, but I mean, the rock's going to fall on us. So I think that's a healthy outlook. Yeah. My dad always used to say before he passed, you know, he would say, you can't, you have to survive not only physically, but you have to survive emotionally. I think a lot of people forget about the emotional part of survival. You have to survive emotionally and humor and understanding reality in its objective context helps with that. Accepting reality as this ephemeral thing that you're in really just a part of, but not as significant as your ego wants you to believe is a start. That's a good foundation for surviving emotionally. What's that mean, surviving emotionally? Like what's an ideal life look like for you? You can't take things too seriously. You can't, because they're ephemeral. They're not permanent. Nothing's permanent. Your bank account's not permanent. Your problems aren't permanent. Nothing's permanent. Your abilities aren't permanent. Your memory's not permanent. Your dick getting hard's not permanent. Can I curse on this or does this go out the door? Yeah. You can curse to your heart's content. Okay. Yeah. I mean, gender's not even permanent anymore. I think I'm going to change maybe and live my second half as another gender just to have, I'm bored with this gender. So it's like nothing is permanent. And so accepting that emotionally is a good start to being more flexible. You got to be flexible. Like my dad used to say, anything too stiff snaps. You got to, you know, it's a cliche and people have said it a bunch of different ways, but Bruce Lee's right, man. Be water. Be water. Yeah. Bukowski has this quote about love, that love is a fog that fades with the first light of reality. So he's a romantic, that guy. But that even love is a thing that just doesn't last very long. No. You know, some people would disagree with that. Maybe it morphs. Like water, it changes, right? It might not be, it might not be this, because he's mostly just loved like prostitutes, I think. So his- The best kind of love, yeah. No demand, no responsibilities. Yeah. It's a financial transaction. Yeah. Ephemeral as ever. You mentioned your dad, he passed away a year and a half ago. What did you learn from him? I love my dad. My dad, I would say my dad was my hero. He was just, my dad really embodied those values. And I think for better or worse, it's made me who I am. My dad was a painter, he was a lawyer, he was a lieutenant in the military. New Yorker. New Yorker, born and bred Brooklyn. His dad, surprise, owned a diner. So that's sort of the Greek passport. That's the immigration passport for Greeks in New America. And yeah, my dad played football. My dad did what he wanted, he lived as he wanted at all costs. And I think I got that from him for better or worse. I think it's hurt me in my pursuits. If you consider money and fame to be paramount, I've always done what I wanted. If I stopped wanting to do it, I just stopped doing it. I think I got that from my dad. So maybe for better or worse, that's what I learned from him. But that's a real currency, feeling like you're in love with what you're doing when you're doing it. Maybe perhaps that's worth more than money. I don't know. You miss him? Yeah, every day, every day. But I'm happy that he got 91 years. It's very rare. I mean, he smoked for 60 years. Talk about a guy who was an outlier. I mean, he smoked like 60 years, like packs. I mean, and he didn't die from that. He died, he had prostate cancer, which is the way men should go. Your dick should give out. It should start from the dick. I mean, we focus so much of our life on the dick that that's the way, that's a successful life. And that's why every man eventually gets prostate cancer, because that is the universe's way of saying, like, the thing you focused on the most is, you put the most energy into, is the thing that's spent. And it's going to, your rotting is going to start there. So that's a successful life. And it just spread all over his body and he slowly died. I was with him when he died, and that meant a lot to me, because me and my brother weren't talking at the time, because we're Greeks, we're talking again, but that's how it is. You got a few brothers, right? I got two brothers, but I wanted to make sure I was with him when he died and I got lucky and I was in the room with him when he died. You were in the room with your brother and you weren't? No, my brother wasn't there. We were kind of doing shifts. I was there, I spent the night, the night my dad died. He died early in the morning and I heard the death rattle, the last breath, and it was just, I think it was, he knew I was there. And I think that just probably meant something to him and I'm just glad I was there. Does that make you sad that life is ephemeral, like you said? Yeah. That you die? Yeah. What do you think about your own death? Do you meditate on that? I think the actual, if there is a point to life, it's to hopefully not fear death, to accept reality. I think that's important. I think so much goes awry in the human condition when we lose touch with reality. Every political system that's led to mass murder and everything, I think because it's, because the tenets of those political philosophies ended up being utopian. They were detached from reality, detached from nature. And so I think it's very important to accept and acknowledge your own mortality. I think it's the foundation for what makes a good person, a moral person, a contributing member of society, because it's true. True things should be the foundation of all things. If what you believe is based on illusion, you're going to end up doing destruction. Whether that destruction's on a scale of one to 10, you are going to be destructed because it's not real. It's a fantasy, it doesn't exist. See, the thing is though, truth is about, I don't think you can ever reach truth. Truth is about constantly digging. And to push back on your idea that you should accept death, I think the more honest response to death, so the least honest is to run away from it, create illusions that help you imagine that there's not a death. The next is to accept it, but the real honest one is to fear it. Because I mean, I'm with Ernest Becker as a philosopher, wrote a book called Denial of Death. He says that like much of the human condition is based in the fear of mortality. That we, like that's the creative force of the human energy. Like Freud said, you want to sleep with your mother. He said, no, that's not what motivates you. Maybe his mom wasn't hot though, I mean, or he wasn't Greek. Because apparently at a poll, we found that all things good and bad. Yeah. Thanks, thanks for that. Thanks. I just don't know if his mom was a looker or not. I mean, I'd have to Google it. All right. Yeah. I'll look up on Google images. Yeah. No, but I think the honest, as he says, the thing that we run away from is that there's a terror, he calls it like terror. There's something called terror management theory. That's some philosophers after him followed on, that we're basically trying to run away from this fear. And acceptance is actually creating an illusion for yourself. Like you can actually accept something as terrifying as this. So he's more with the Stoics. The Stoic constantly meditate on their death. I mean, they, what does that mean? I mean, it's kind of, it's, you know, acceptance of death isn't a thing you do like on a Monday and then you're done. It's a thing you constantly have to meditate on, like reminding yourself, like this ride is over. It could be over today. And that's something you're, if you think about every single day, it gives you the appreciation of Woody Allen movies, at least. It gives the appreciation of basically everything, including Woody Allen movies, which shows you how deep your appreciation for life could be. I've actually haven't been following much of Woody Allen, but apparently he's been a troublemaker for most of his life. He's, yeah, I mean, you know, he's caused a little bit of strife. He's left a little, yeah, he's left a little confusion in his wake for sure. But I mean, you know, that's another one. Separate the art from the artist. He's got, I mean, the guys will go down in history as the greatest, he's made, I mean, a movie a year. And they're all, you can always find something good about each movie, like the dialogue or whatever. I love what you're saying. It's interesting, but the only thing I would say to push back a little bit, since we're playing a little table tennis here, is I don't know if it's a choice to fear death. That's more of an, it seems more instinctual. It seems like something that nature wants you to do because I've been in positions where I thought I was gonna die, like I've been shot and I had those moments. And then nature also, you know, kicks in an instinct, which is acceptance, where you kind of, I don't know, it's a chemical release or whatever, I don't know, you know, we're robots, basically. So some sort of chemical is released that protects you, but there is an acceptance. I don't know how much of it was a conscious choice, probably very little. And that's the point I'm making is it's instinctual. We don't really have a choice in fearing death. Otherwise, there would be no progression. We wouldn't, all life seems to want to survive, not by choice, but by instinct. So he argues that the fear is not the instinctual choice, the instinctual of it's not the animalistic stuff. That's the thing that makes it special is what humans are able to do is to have a knowledge that we're going to die one day. Animals don't have that. Animals' fear is instinctual. It's like, holy shit, what's that sound over there? He says we're actually able to contemplate the fact that this ride ends. And that kind of cognitive construct is difficult for us to deal with. Like, what the hell does that mean? Like, just to think about it's going to be over at a certain point, it's just over, lights out. Like, it's very difficult to kind of load that into whatever this like little brain we got. Like, what does that actually mean? Maybe that's what gives everything meaning. Because if everything lasted forever, if this went on ad infinitum, there would be no meaning to it. It'd be like, hey, if I don't see you tomorrow, I'll see you in a million years. There would be no meaning, there'd be no urgency, there would be no feelings, there'd be nothing of magnitude or superficiality. It would all just be this kind of, it would be torture. It would actually, that would actually be torture to be here forever. I mean, I'm already sick of this place. And I'm just in my 40s, like I'm done. I'm sick of me, I'm sick of everything. You know, a lot of people, when they talk about immortality, they consider mortality appealing because you get a chance to do basically all these things you might not get a chance to do otherwise. Like all the kinds of travel broadly, explore, read every book, explore every idea, do every hobby, all those kinds of things. Somebody I was talking to mentioned the reality of being immortal would be more likely, I like this idea, more likely would be you just sitting there doing nothing because, and putting off all that travel and exploration till later, because you'll always have time. And so what you're gonna have, what actual immortality would look like for a bunch of humans is people sitting there doing nothing. It'd be like a Greek caffeine, just sitting around drinking coffee, watching. I love it. I mean, it's a lazy man's paradise, yeah. But it's so interesting because that rings true to me for what humans are like, is we'll basically just put off all those exciting adventures and just be lazy, become lazier and lazier and lazier because you'll always have a chance to do all the exciting things. And we'll just get, we'll basically become Tim Dillon. We'll just sit there and have a podcast and that's it. He works hard. Yeah, I mean, that sounds actually like heaven, dude. That's speaking of my heart, really. I mean, I'm at heart, I'm a very lazy person. I always try to find ways to lie down. Like if I'm sitting, I'll figure out a way to kind of contort myself to later. That's an interesting thing to like, yeah, if you can always push something off. Yeah, I like that. I think that's heaven. And- See, we just changed your mind. You kind of like the immortality. Yeah, I kind of like it. No, so there'll be no thirsts. No, you can always put it off. Hey, I wanna, I wanna, I wanna have, I wanna bang this girl. You're like, I'll put it off. But now I'm thinking about Muslim heaven and they may be offering the best deal. I mean, if it was an expo and they had a booth, I may go with them because they offer, they offer 62 or 72, but then I'd get sick of them. I'd wanna, I don't know. I always wondered like, are you given the 62 virgins or you choose, can you create them like an avatar, like a video game? Or are you just given- I don't know what the number, why it's important to have that high number. First of all, I think it's a mistranslation about the virgins, but outside of that, outside of that, I feel like the conversation is really important. I don't think they ever specify like what kind of books these girls read. Like what are they into? Like the quality of the conversation, I think if you're talking about eternity, the quality of the intellect and the conversation and the personalities is way more important. And the Greeks have an ancient expression, padmetronariston, which my mother always used to say, which is everything in moderation, nothing in excess. So try and always get the status quo. And yeah, that many women, eventually it's like the Magic Johnson effect, Isaiah Thomas effect, it's just too much. And you're gonna end up banging a dude, is what I'm saying. You're gonna get sick of it because it's too much. And there's going to be a eunuch that finds its way into your harem. That's been proven throughout history, every empire, when you have all that power. And again, this goes back to power corrupting. If you have, if there's no struggle, there's no meaning, the value is from the journey, the working hard, the struggle. And if it's just given to you because you're a sultan or you're Alexander the Great or whatever, you're gonna get bored and you're gonna bang a dude. I think that's a scientific axiom, actually. Eventually you'll get bored and bang a dude. Yeah, but I think it won't stop there. I think you'll go to animals, you'll go to robot. I mean, eventually it all ends up in robots and then the robots rebel and then the humans will be destroyed. Yeah. I'm sorry. If we're speaking truth, you said the value of life, one of the highest ideals is to seek truth. I think if we're being honest. Can I ask you a quick question? If you live in a small, I come from small islands, right? And so there's a stereotype that that's where they bang animals. But if you come from a very small community, an island or something, and you have the choice of banging a family member or an animal, which one is worse on the moral scale? Because you're technically not related to the animal. Right. This is interesting. I mean, all of these are human constructs, these ideas. But for me personally, taboo, would be more taboo to have sex with a family member. Yeah. I mean, animal, I mean, okay. It's good to know where you stand on that. I think if viewers, if they didn't have, they didn't know they had that question. They just learned a little bit about you. And now I know. I look forward to the internet clipping that out. Yeah. I mean, there is, listen, outside of that, I do think about that a lot. It sounds ridiculous about morality connected to animals in terms of all the factory farming and so on. It seems like that's one of the things we'll look, because I love meat, but I kind of feel bad about it. And bad in a way where I think if we look like 100 years from now, we'll look back at this time as like one of the great, like tortures and injustices that we humans have committed. And I mean, all that has to do with the sex of the animal, has to do with consent and about the experience of suffering of animals. The reason I think about that personally a lot, because I think about robotics, I think about creating artificial consciousnesses, artificial beings that have some elements of the human nature. And then you start to think like, well, what does it mean to suffer? What does it mean for entity to exist such that it deserves rights? This is something that the founding fathers were thinking about, like, all men are created equal. What is it, which, who is included in the men, who's not in that sentence? And are animals included in that, are robots. I honestly think that there will be a civil rights movement for robots in the future. I don't know. Is that the Turing test, the way you try to, is that what they call it, where you're trying to see if AI can think like a human or whatever, or feel like a human? Well, the Turing test closely defined is more about talk like a human. So you can imagine systems they're able to, you can have a conversation like this, and I would be a robot, for example. But that doesn't mean I would, in society, that doesn't mean I deserve rights. Or that doesn't mean I would be conscious. It doesn't mean that I would be able to suffer and to experience pleasure and dream and all those kinds of human things. The question isn't whether you're able to talk, which is passed in the Turing test. The question is whether you're able to feel, to be, I mean, I go back to suffering. The thing that our documents protect us against is suffering. Like we don't want humans to suffer. And if a robot can suffer, that discussion starts being about like, well, shouldn't we protect them? Currently, we don't protect animals. We protect that dog. There's laws, there's actual legislation that protects dogs. For torture. Places, yeah. And you know what? Dogs is something I don't think people really understand enough about. It's one of my obsessions. So they, my dad always used to say, he'd go, those things are basically human. And I mean, they dream, they have anxiety. And what people often overlook about dogs is without dogs, we wouldn't be here. We would not have ever evolved from hunter-gatherer to agrarian to, you know, civilization. We wouldn't have cities, we wouldn't have anything. I mean, they are our partner in survival. And they are a magical animal. There's no animal that was, it was like destiny almost. I mean, a malleable animal. There's no animal that's that malleable that in a few generations, you can tailor to a specific job that you need. And without that animal, without dogs doing that animal, protecting our crops from scavengers and stuff like that, you know, the list goes on, we wouldn't be here. So we, that's an often overlooked fact that human evolution was not done in a vacuum just with humans. I mean, without dogs, we would have never evolved. I mean, we weren't the apex predator for most of our existence. We weren't even the apex predator. I mean, we're getting eaten by hyenas, which my favorite animal. And, you know, it's kind of an injustice to, I mean, I'm kind of mad at dogs. We deserve to get eaten by hyenas, but without dogs, we wouldn't be here. And dogs deserve the protection. So do horses. They fucking lugged us around for thousands of years. And now these fucking German psychopaths are eating them or whatever. We should not eat horse meat just on like, be a good dude, man. These things lugged us around for generations. They're beautiful, you know, ride them or I don't know. I don't know. But it rubs me the wrong way that we eat horses. Yeah. The horses one is interesting. And one of my favorite books is Animal Farm by Orwell. And the horses don't get a good ending in that. I kind of, my spirit animal, I suppose, is the horse from Animal Farm, Boxer, where he says, I will work harder. That's his motto. I work really hard at stupid things. That's basically what I did. I just hit my head against the wall for no reason whatsoever. But that probably fulfills, you have a big brain. You were probably born with a big brain that kind of fulfills. Killing neurons. It's exercise for you. Yes. Yes. Don't you think some animals deserve to be eaten though? Kind of like hyenas. Come on, dude. I mean, you got to respect the hyena. Okay. So first of all, let me just comment on the dog thing. There is a conferences on dog cognition from a perspective of people that study psychology, cognitive science, neuroscience. Dogs are fascinating. The way they move their eyes. They're able to, they're the only other animal besides humans. They're able to communicate with their eyes. They can look at a thing and look back at you and look back at the thing to communicate that we're all like through our eyes communicate that we're collaborating. So every other animal uses their eyes to actually look at things. The dogs use it to like communicate with us humans. It's fascinating. There's a lot of other elements of dogs that are amazing. Yeah. I mean, if it wasn't for them, they're the ones, they were our first alarm system for predators. They would defend us. I mean, the Basenji is one of the most ancient dogs. I mean, they're tiny, but they're fearless. Yeah. And they would chase off lions. Like, you know, there'd be packs of them and they'd chase off lions and protect the tribes. I even get tingles like thinking about dogs. Cause I have a dog. I love my dog. It's just, and there's something about when you're walking with your dog off leash in the woods, it like, there's something about it. That's like, that, that tugs at that millions of years of evolution. Like that gut, you know, it's like I had a Finnish friend of mine. He's a comic. Tommy Valamis once told me he was like, he was like the gut. He's like, I believe in that, like that gut, you know, when you have that feeling, he's like, always trust that because that is million. Those are all your ancestors. That's the survival instinct of all your ancestors at the beginning of time, you know, telling you like, Hey, something's off here. Something's, you know, so don't get in the car with Ted Bundy is what I'm saying. Ladies, how fucking stupid, who, how can you fall for that? You know, he's got a fucking sling on, don't get in. Yeah. Follow the gut. My question to you, are psychopaths essentially robots? So first of all, let's not, you're using the word robot in a derogatory way that I'm triggered by. Okay. Yeah. And you should be offended. You should be because you know what? People are always scared of robots, but I actually, I have, I've made the sort of, I've made it to say, Hey, I've thought about it. Like robots have been nothing but helpful. It's the people we should be scared of. Right. Again, we're kind of missing the most destructive thing is us because it's, but robots are helpful. I mean, this is a fucking robot. You know, I went on hotel tonight. I'm already booked up. You know, I got my, I can change my flight. If, if this barbecue with Rogan goes 16 hours, which whatever Rogan wants to do, I'll do if he wants to kick me in the chest, I'll let him kick me in the chest, whatever. Robots are helpful. No. Yeah. Tanks and autonomous weapon systems don't kill people. People kill people. Yeah. That's yeah. The NRA is about to click that for you. A lot of love for dogs. I appreciate it very much. And at the same time, you have the other thing that people seem to have love for, which is cats. And on the flip side of everything you've said, I'm trying to understand what have cats ever done for human civilization. They keep rodents away. The domesticated cat is very important. It keeps rodents away. Yeah. That's what they were domesticated for. I mean, there's psychopathic killers who end up killing innocent neighborhood chipmunks and birds. They really affect the balance of the local ecosystem. But if you have love for cats, too, not as much as dogs. I mean, dogs are like you said, they look at humans. I actually read an article there. Some people were theorizing they're smarter than chimps because of the way they can work with humans. And there was one border collie that spoke like 300 words, like a quarter, like a lang, almost part of language. And their nose is like a mat. I mean, that's like magic, dude. If you can smell in my ass to what I had for breakfast from miles away. That's intelligence. That's intelligence. I mean, in some ways that their nose, if you were to put it on a scale, maybe their nose is more intelligent than our brain for what it does. You know, it's like, I mean, dude, they can smell you from miles away. You ever see a dog just like sniffing, catching? I mean, it's smelling like, I don't remember the date on it, but it's like they have like millions of receptors or something where we only, you know, thank God we don't have their nose. That would be, that would make sex weird. It would be a little too intense. I think you mentioned when you were talking about Woody Allen separating the art from the artist. So that brings to mind Vladimir Putin. How about that transition? I don't know. I'm so sorry. But if you look at just powerful leaders throughout history, Stalin, Hitler, but even model ones like Putin, and we're talking about power, how do you explain them? You said that power reveals, not corrupts, but do you think there's some element to which power corrupted Hitler, power corrupted Stalin after he gained power? And the same with Putin. When Putin gained power in 2000, do you think the amount of power that he was in possession with for many years, do you think that corrupted him? I mean, we're joking about dictators get the job done. There is some sense in certain countries where dictator is the only thing that can stabilize a nation. The counter argument to that for democracies is like, yeah, but that's a short-term solution for a long-term problem. So you want to embrace chaos of democracy. That might be violent. There might be a lot of just constant changing of leadership. There might be a lot of corruption in the short term, but if you stay strong with the ideals of democracy, then you'll ultimately create something that as beautiful and stable as the United States. The sad thing is, is I don't know if history tells that story. It's like I said, you look at Greece, you look at Rome, democracy kind of failed. The majority of Rome, the most successful empire that we've had was a dictatorship for most of its run. So, but I do believe in a republic, which is sort of a limited democracy. I do believe in what we have here. I believe in common law. I believe in individual rights. But yeah, I think you said it. Nobody could have said it better. Yeah, it's a short-term solution. You look at Saddam Hussein, he kind of, you know, when we took him out, then there was a lot of infighting that happened that he was kind of keeping at bay because he was a strong man, dictator. Well, he's an interesting one. Sorry to interrupt. From my understanding, I'm sure people will correct me, but when Saddam Hussein first came to power, he was, he's quite progressive. So like, as far as I understand, the signs of an evil dictator weren't exactly there. So again, there's, I don't know if power revealed or power corrupted. Or that could have been the initial subterfuge to kind of get everybody, you know, Hitler also is a champion of the people, let's build some new roads. It's what psychopaths do. And that's why it's interesting to me. I'm not sure if power corrupts psychopaths. And now that we know that we can do these CAT scans and brain scans, we can do these brain scans, again, we know that they're born that way. Power definitely corrupts people who have the capacity to feel and for empathy. Power, I'm not sure, I don't think power corrupts people who were born psychopathic with that condition or sociopaths who had, who, you know, who were closer to psychopath and then had some traumatic life. You know, I just think, you know, the best way to get away with whatever nefarious thing you want to do to feel, I guess the only thing psychopaths can feel is that excitement, is to pretend to be the opposite of what you are. Yeah. That's what killers do. That's what the worst people do. Look at Bill Cosby. I mean, he was, what better way to hide, you know, it's like what wokeness is now. It's like, I'm such a great person. And you're like, are you? It's a great, the best way to hide is to pretend to be the opposite of what you are. Just like Ted Bundy. I'm just an innocent, helpful guy. And then boom, next thing you know, you're getting your tit bit off. It's really well said. It's actually kind of funny because I talk about love a lot. And I think the people that kind of look at me with squinty eyes, they wonder, like, how many bodies are in that closet? You know what I mean? Like, there's something about the duality of like, we're so skeptical as a culture. Like if somebody is just like, seems to be kind of sort of, I don't know, positive and all that kind of, you know, how do I put it? Just simple, simple minded in the positivity they express. They think like, there's some demons in there. Yeah. Especially if you're a New Yorker, we don't trust any, the nicer you are, the more skeptical we are. I've struggled with that down here. I've been like, what's your angle? And they're like, nah, dude, just, I wanted to show you the best tacos, man. And I'm like, did you really, what do you want? Because in New York, it's like, if anyone's nice to you, they want something. Yeah. And that's, the pro side to that is it makes you very street smart. The downside to that is it makes you way too cynical. Yeah. I definitely experienced that here in Texas, but people are super, super nice. And they're like, do all this cool shit for you. And you wonder, what's the angle? Yeah. What are we doing here? You mentioned hyenas as your favorite animal. I forgot to ask you, what the hell were you thinking? Why is hyenas your favorite animal? Yeah. It's a fascinating animal. Let's look at the whole animal kingdom. Like, why is that? Where do you put, so you like dogs. Love, my favorite. Your favorite is dogs. But they're kind of outside the animal kingdom because you're thinking about wolves. So the animal kingdom is in nature. Dogs escaped nature. They kind of did, yeah. Together with humans, like in a collaborative way. Exactly. So within nature, within the animal kingdom, why not lions or bears? Because lions are predictable. Lions are just, they're regal and kind of, they bore me. It's like the hot chick. It's like, we get it. You were born the best. Yeah. You know, I like a scrappy, by any means necessary, intelligent and cunning. But aren't they dishonest? Yeah. And that's why I like them. Yes, they're dishonest. They employ chicanery. And that's just a sign of how intelligent they are and how self-reliant they are and how brutal they are. They're brutally honest in how much they lie. Yeah. You know, because it's just, they're trying to get the job done. You know, lions are just like, they're too gifted. Everyone hates the fucking, you know, if I went to school with you, I'd be like, of course Lex knows the fucking answer. Lex was born smarter than me. You know, and you'd probably hate me because I was the kid always seeking attention and making people, it's like, that's not interesting. The guy that claws his way to the top, and those are hyenas. They're also fascinating just by merely who they are. I mean, they're not related to any other animal. They're more closely related to cats than they are dogs, even though they look more like a dog. Yeah. But they're very, like, very tangentially related even to cats. So they're their own kind of thing, which is kind of mysterious. I don't think they fully figured out. And the pseudopenis thing is the, I mean, it is the talk of the- Can you explain the pseudopenis? Yeah. So it's a matriarchal society, by the way. So that's the unique in and of itself that this, we're talking about an apex predator that is matriarchal, much like, you know, the praying mantis. It's very rare, though. And they are fucking brutal and vicious. And the women are bigger and they let their cubs fight, a lot of fratricide. And they do that because they're like, hey, you're weaker. They're like, I let your brother kill you. And the women have penises. The women have pseudopenises that they give birth out of. And the birth is violent, but they roll around with just huge pieces. They're glue guns who just fucking swinging, you know? And the women are just run the show. And it's just cool that they have these pseudopenises. It's almost romantic the way you describe it. They have the strongest bite force. They pulverize bone. Like when they eat an animal, the animal's gone. There's no bones. They eat everything. They can pulverize. Their bite is so powerful. They pulverize bone and eat it. So if they consume an animal, the animal was there and then the animal's gone. There's nothing for the vultures there to grab. Yeah, I'm gonna have to revisit the hyenas because my experience with the hyenas was from, first of all, History of Hyenas, your show, has rebranded them for me. But The Lion King, which is a cartoon, I guess, that I get emotional at every time. I hope, I probably have father issues. Guy. Probably just have feelings. You're a good guy. Everyone gets that. I have feelings. Yeah, you have feelings. That one gets everybody. I don't know. I get every father-son movie, like Blow, Wajani Depp, and Ray Liotta. Damn, that's a good movie. And whenever there's the disappointment in the father that his son has become this incredibly successful drug lord that then ends up with nothing in prison, just the sadness of them communicating through letters. That gets me every time. But the hyenas are not presented that well in that. No, they're usually portrayed as like, it's really sad that they're portrayed that way. The lions, like lions aren't dicks. Lions are dicks. The alpha lions will kill the cubs of another rival. They do all types of dick shit. And yeah, hyenas are more interesting. They'll just roll in like a hyena will, like you said, they'll lie. Because when you watch the Serengeti, animals will hang out with each other by water. So one hyena will just kind of roll in and pretend like it's not hungry and then bang, they'll use any means necessary to take an animal down. Lions will just use brute strength. Hyenas use cunning. And you can even go on the internet and find memes of this where hyenas will grab the big animal by the balls and just like will sneak up behind it and bite its balls. And you'll watch an animal 10 times the size of the hyena just slowly go down. It's brutal, but it's fucking hilarious. So I think that's, I don't know if you follow the channel Nature's Metal. That one weighs heavy on me. With the hyenas and the balls. It's tough to intellectualize it. It's tough to think that the entirety of life on earth has this history of predators being violent, just like just the murder that we come from. Yeah. It's crazy. Just like we were talking about meditating on death. I actually, I keep following and unfollowing that Instagram channel because like sometimes it's too much. Like I can't continue with the day after like seeing the brutality, the honest brutality of that. I don't know how to make sense of it. It's important to acknowledge, I think, because it's real. And we do come from that. We are, we evolve from that. It's important. We still do that. We're just hidden from it. You know, when you go to the supermarket and get your slab of meat, you're so disconnected from where that meat came from. It came from that. And often that's uglier to watch. Then because there's some honesty, you know, the nature channels only show, that's why we have so much sympathy with the prey. And this is where I think the same thing with mafia movies. They don't show what the mafia really does. They glorify the good parts. That's why I like State of Grace because it's really just shaking down old people and fucking being dicks. It's not driving nice cars and being like, you know, so, and animal channels do the same thing. They only show when the cheetah gets it because that's the exciting part. But what most people don't know is that those predators strike out almost always. A majority of the time, the prey wins. And so if you saw that and put it in context, you might not hate it as much when the predator actually gets the little fawn or whatever, because it's so many fawns got away. It's so hard to capture your prey. And, you know, we don't have the, they, no documentary is going to sit around and show you the, you know, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the. Thank you for this perspective. Murder is difficult. So like, this is the, they never talk about for people who murder, how difficult that is. It's tough. To trap somebody, to convince them, to come back to your place. Give it some respect, put some respect on Ted Bundy's name. Yeah. It's not easy to convince somebody to get in your Volkswagen Beagle and- The cleanup. And then you have to kind of plan ahead because you want to keep doing the murder, mass murder. You've got to learn how to saw them up, put them in duffle bags, bury. You gotta learn how to dig, you gotta learn how to hide, you gotta learn how to lie. I mean, it's a lot that goes into it that we need to put a little respect on. Yeah. Yeah, and you have to figure out which tools work the best for the song and all those kinds of things. So thank you for the perspective. That's what I was hoping we would bring to this table. So you got a little bit Greek in you. One of the episodes on History of Hyenas, you talked about the Battle of Crete, where the Greeks, your people, in 1941, in the early stages of World War II, is one of the most epic battles of the war. In fact, in 1941, in a speech made at the Reichstag, Hitler paid tribute to the bravery of the Greeks, saying, it must be said, for the sake of historical truth, that amongst all our opponents, only the Greeks fought with the endless courage and defiance of death. So, okay, what do you make of this battle? What do you make of the spirit of the Greek people? This is one of the closest things to me because my mother was actually on the island of Crete during this, the first aerial invasion in history. A lot of people don't know that. So this is a very significant battle. First time there was an invasion from the sky. And my mother was a little girl and she lived through four years of Nazi occupation there. So my mother was a human rights lawyer and everything, but she just always hated Germans. It's just what it is. She hated Germans and she never got over it. So the most progressive, open-minded woman just could not get over this. It's a monumental battle that a lot of historians in retrospect have now looked back on and said, because the Nazis, first off, you gotta take it back to when Hitler instructed Mussolini, because let's be honest, Mussolini was Hitler's bitch. You know what I mean? It was like, if it was Fantasy Island, Hitler was the fucking, and Mussolini was boss, the plane guy. Mussolini ever say no to Hitler or even maybe, it's always like, yes. Yes, yes, we will do it. And it's like, yeah, you have to take Greece. And so, yeah. So Italy being much bigger than Greece, Greece is a tiny country, nine, 10 million. So Italy invaded Greece, you know, and Hockey Day's a big, it's a big holiday for Greeks. And this speaks to the spirit. Greeks infight until we have a common enemy and then we unite. You see it throughout history, Sparta and Athens. You see it in Greek families, where the brothers will fight, but then as soon as we have a common enemy, we unite. And maybe it's an overactive brain. We think too much, our tradition's philosophy, and we overthink things and we fight with each other and take things personally. We're ultra passionate. But when Italy said, hey, we're gonna move troops through, you know, a Greek said, okie, which means no. And that was, and then Italy attacked and we beat the shit out of them. A much bigger country, much more well-equipped country. Greece beat the shit of them, kicked them back into Albania. Actually, not only repelled them, actually like conquered some ground in Albania, pushed them back. And then Hitler was like, fuck, you know, I was planning my march to Russia, but I have to go down because, he basically said to Mussolini, like, you know, you're basically bitch slapped. I'm like, Fredo, like, I gotta do this myself because you're such a fucking bitch. So then the Nazis invaded Greece. Obviously they took the mainland with fight and shot out. The Greeks never give credit to the British in New Zealand and Australian troops that were there. You know, they were a large part of this, the majority of it. But the Greeks fight, dude, civilians. I mean, they fought, you know, the Ottomans were there 400 years. You go to Greece now, there's no evidence. There's virtually no evidence of them ever being there. That's the Greek spirit. Kick them out and we kicked out hummus too. So it's like, your culture's gone, you're gone. Because Greeks are, it's philophthimo, it's called philophthimo and it's a real thing. Philophthimo is a, it's very little, you can't translate it, but it's kind of like honor, loyalty, friendship, altruism. It's a, you can't define it, but Greeks know it and were taught it from our families. It's a vibe and it's a Greek cultural thing. And we're an old culture and philophthimo is what it's called, philophthimo. And it's love, it's passion and it comes out and it comes out. And so Hitler had to postpone his invasion of Russia, went down the island of Crete, took 10 days to conquer. It's an island, to put that in perspective, the country of France fell in three or four days. I can't even remember, because they fucking just rolled over. So what does a couple hours matter when you're that much of a fucking pussy? What is a couple hours, 12 hours, fucking three or four days? The island of Crete took the Germans 10 days to conquer. And because of that, and because of the Greek resistance, Hitler had to postpone his invasion of Russia to winter. And of course that was his downfall just as it was Napoleon's. And never dude, never try to invade Russia. They got millions of people to throw at death. Every time you read about Russians in history books, like and a million died. I mean, you just guys throw millions of people at the problem and don't fuck with that Russian winter and don't fuck with Russian people, dude, they're tough. People in New York know that. You don't go to fucking sheep's head bay and start talking shit. You'll end up in a fucking car trunk and they'll brutally murder you. I do not fuck with Russians. Amen. And there's a lot of people, a lot of historians argue that that battle was because of the Russian winter, because of delaying the Russian invasion, but also psychologically delaying the invasion. It was the first time, I think it was the first time the Germans failed or didn't succeed like they wanted to early in the war, which is a little like psychologically the impact of that I think is immeasurable. And also a lot of people argue from a military strategy perspective that just like you said, it was an aerial attack and that Hitler didn't think that that kind of attack would then be useful for the rest of the war. So that's a really part, whereas it might've been very useful. So it's really interesting how these little battles can steer the directions of war. Of course, me growing up in the Soviet Union, we didn't hear much about this battle. Just like you said, millions of Soviets died. All those people in history that you read about dying, those are all civilians, but I mean, not all, but a very large number of them are civilians and their stories, obviously that's the rooted, the literature, the poetry, the music, just the way people talk, the way they drink vodka, the way they love, the way they hate, the way they fear, that's all like rooted in World War II and World War I. And so, but we never kind of think about Europe and we certainly growing up, didn't think about their role in the United States. All this, there's plenty of stories of heroism in the Soviet Union, enough for many lifetimes. So, but it was fascinating to read from a Greek perspective, cause I don't have many Greek friends. I hope you didn't change that. This is the beginning of a love affair of your people. Likewise, the Americans don't hear about the Soviet contribution to the end of World War II because obviously we became enemies after that because of the two systems. But yeah, without the Russians, World War II wouldn't have been won either. Yeah, the stories are written by the victors. That's really interesting. Just looking at history, you wonder what's missing. I'll tell you what's missing that I know for a fact. Cause my dad told me combat's hell and he would tell me the reality of what it's really like, guys pissing themselves, calling for their mother, the fog of war, obviously, fratricide happens all the time, it's pandemonium. I mean, there's skill involved, but I mean, there's no, like, it's a lot of it is just luck. My dad said, my dad won three, he got medals, purple hearts, all that shit. And he said, the reason was is cause he can't, he always said, this is another thing he told me, you can't pin a medal on a dead guy. So it's like, those are the guys who deserve it, but you can't pin a medal. You can't do the pomp and suit with. And I'll tell you one thing is that it is written by the victors and all these leaders, they say we're in the front, we're not in the front. We're not in the, whenever the history books say, he led his troops into battle. It's like, did he really? Did he, so then how did he live? Cause they put like kids in the front, you know? It's like, nobody limps back from the front with like a injury, you know? That's army PR, you know, whenever you read, you know, 27 soldiers died, 14 were injured. The word injured is PR. That's like injured, was he? Did he sprain his ankle? Did he need, did he get carried off the court? Or, you know, he was maimed. I mean, he was like, his leg was blown off, you know? It's like, so I think that, you know, Alexander the Great was just kind of in the back on his horse and just kind of, he had his eunuch blown a few times and he was like, is it bad up there? And then like after that, he was like, okay, my scribe, give me my scribe. Okay, when you write this down, could you put me in the front? Yeah, and I was just, make me a big hero. And I was in there and then he, you know, he just blew his, you know, he had sex with his eunuch and rode off into the sunset because there's just no way you survive in the front, especially warfare back then. I mean, it's like brutal. Then again, you have like Genghis Khan. The sense I got that he was a little bit up on the front, at least at first. Yeah. Or is that also, is he a little bit Alexander the Great? Give me my scribe, yeah, it's all lore. I mean, you ever play the game of telephone? You know, it's like, you know, there's no video cameras back then. So shit just get, turns into myth, you know? And there's no way he was in the front. There's no way, he wouldn't have lived. You know, he was probably good on horseback because those dudes were good on horseback. It was like Game of Thrones back then. You had all these different people and they kind of, yeah, the Mongols were wild, dude. They are actually said like, they started like, they were more adaptable to the horse because they were so good on horseback that kids started to be born like kind of bow-legged, like to fit the horse, it's wild. And they would stretch their heads and shit like that. They'd wrap them and stretch their head so they find like Mongol skulls and they look like cone heads. And they were brutal and vicious. And they would maraud and rape and all the fun stuff that, you know, when you visit other places back then, there's no tchotchke stops and souvenir shops. What you do is you take women and those are the tokens, you know, you burn a few huts, different. Tourism was different back then. Yeah. Yeah, that's another difficult thing. Just we're talking about nature and predators to think about the long stretch of history where it was just murder. Yeah. And we made so much progress, I guess, in the past couple of centuries. The United States is a shining example of that. But do you think also that it's that effect that we were, a lot of good things had to happen too or else we wouldn't be here. So do we just focus, isn't it like a car crash effect that like we're, you know, the rubber neck where everyone pulls over to see a car crash. Are we just only focusing on the negative things of history because they're just more exciting to us? Like, it's just not, it's boring to be like, yeah, and then there was a bunch of villagers and they ate every day and danced and- And loved, yeah. I wonder how different those people were, you know? Like they might've had the same exact loves and fears and like they perhaps had the same kind of brilliant ideas in their head, if not more brilliant. And we kind of think about like this moment in history is like the most special moment. Like we're doing the coolest shit, but we're doing the most amazing, building the most amazing things. But maybe they were building amazing things in their different way with like less technological, but in the space of ideas, in the space of just all the different, the camaraderie, in the space of like concepts, mathematics, all those kinds of things. Yeah, I mean, Greece, you look at the architecture, it still stands up. I mean, all the government, it's still arguably, I mean, as far as objective beauty, it's hard to argue that Greco-Roman, it's just something about it with the columns. It's just, it's powerful. It's, I don't know, even Ayn Rand would probably appreciate it. She doesn't, no, no, no. So in your history of hyenas, that unfortunately has come to an end. We were talking about empires coming to an end, all empires fall. Yeah. That one, well, it may rise again. Empires might rise, who knows, who knows? I'm obviously a fan, so I hope it does rise again. But you've seemed to develop your own language. Can you, you know, it's what it is. What is that? What the hell? Is this some kind of medical condition or can you explain like the linguistic essentials that catch us up to the linguistic essentials that people need to know to understand the way you speak? You know Leopold and Loeb? You know the story of those two? They murdered that kid and they had this weird relationship. Anyway, it's an interesting thing to Google, Leopold and Loeb, these two guys who ended up murdering a kid because they developed their own language with each other and this own reality and this weird thing. And they wanted to know what it's like to murder a kid and they murder a kid. It's a famous story in American lore and history, or whatever, famous case. But this phenomenon, yeah, me and Chris got together. It wasn't as dark as Leopold and Loeb. We didn't murder a kid, but we murdered a podcast. Or at least stabbed it a few times. Yeah, it was something in the organic chemistry of me and Chris that I think we'll both end up appreciating even probably more than we do now, that it's mysterious. I gotta be honest with you. It was a thing that, it wasn't conscious, wasn't intentional. It was something that happened in the music of our energies that just went. It's fascinating. Like when you hear someone sing or when a jazz band hits a rhythm or even when I'm on stage and I just catch a rhythm, it's like, dude, I didn't make a choice there. I don't know what that is. I don't know how to explain it, but it comes from somewhere else. And I don't know what it is. It's beyond my comprehension, but with Chris, there was this magical chemistry that, I have chemistry with a lot of people and it can be funny. And I enjoy- I feel zero chemistry here, brother. No, this is great. This is great, yeah. It's a little bit more intelligent than when me and Chris did. But me and Chris, I think we connected on the funny bone. Like I found him so funny and we found the same things funny. And from that, these organic expressions came from some part of our brains that was created from this chemistry. And yeah, we just developed this language and this cult following and people were really upset when we ended, but it was the right thing to end because like all things that end, it was kind of done a few episodes even before we finished. And I think we pulled the plug before it started rolling downhill. Like all great flings. There's your long relationship. Long marriages are boring and comfortable. The one you really like fucking always ends abruptly and sadly, but you always look back and you jerk off to it. So you guys made love? We made, yeah. So it was like a hot fling with me and him and it was intense and we burned the candle at both ends. And I think that podcast was meant to be three years and maybe people will go back and appreciate it and listen to it over and over again. And I think the new things we do, people will love. I'm doing long days now, that podcast, and people seem to enjoy it. I've been really enjoying the long days, yeah, on YouTube. I just found myself just like staring at you ranting. Same with Tim Dillon. I really enjoyed whatever those rants are, the genius of just one thing after the other, but definitely the chemistry almost as a study. I remember the reason I first started listening to it, I was trying to get a perspective on certain historical moments. Like it was interesting. I tuned in to learn history. Yeah, I came for the history and like stayed for the chaos. And it could crack open and clean out. And yeah, it was almost, I listened to Rogan like this sometimes. I'll re-listen to an episode to try to understand why was this so fun to listen to? It's almost like trying to analyze humor or something like that. But it's nice from a conversational perspective, like why was this so easy to listen to? And with History of Hyenas, like why is the chemistry so good? It's so, it's weird. It's weird. Because there's not many podcasts like that. I don't know any with the chemistry like that. It's interesting. And it's kind of sad that the fling with a prostitute in Vegas has to end. But that's what makes it special. It's the Bukowski thing with the fog. The British office, one of my favorite shows was that. It ended very quick. It's only a couple of seasons or something like that. And that was tragic, but that took guts to just end it. Given all the money you could have made, given all the, you just end it. And that's what makes it like truly special. Yeah, and I'll tell you, man, I'll just emphasize it. Cause I marvel at it too. Cause as a guy who tries to always figure out what the causes of things, I gotta be honest, man, looking back on that, even with retrospective wisdom, you know, that 2020 hindsight, we've been done a couple of months now. It's something that I can't explain. It's something that I don't know how you quantify it. I don't know how you describe it. It's musical. It's really kind of rhythmic. So. Maybe like a Netflix show about history. That's in the future. That, with the two of you. Yeah, who knows. You guys will meet like, with that, the way you meet with a fling, like a decade from now at a diner and you're both way fatter and uglier. And then you just reminisce over some cigarettes and coffee. I could be, yeah, it could be. Yeah. But it's definitely a classic podcast that people can go back and appreciate. It's fast paced and it was unique. What was it like to research for, I mean, it was really scholarly, the depth of research that you performed. It sometimes felt like you almost read an entire Wikipedia article beforehand. That's exactly true. We were, one fan, we attracted such funny people to that podcast and the fans were so funny. And one fan called us, nicknamed us Wikipedia sluts. And so it just stuck. Yeah, we just would read Wikipedia. I would do a lot more research than Chris. Yeah. And so I would actually, once in a while he'd get into it too, but for very interesting episodes, I got some subject matter would just pull me in, like Bernie Madoff, just to think of one that was recent, it was one of our last ones. And I think one of our better episodes. And I'm glad that it kind of ended after that because it was rare to, I think we started to slip a little bit. I got fascinated and I did a lot of research for Bernie Madoff, but usually, yeah, we'd pull up Wikipedia and we'd have fun. We were sort of the antithesis of Dan Carlin. I mean, you went to Dan Carlin for accuracy and thoughtfulness and you went to us for, it was a hang with histories. That's why history hyenas was such an appropriate name because it was a little bit of history. Some episodes were more hyena, more wild, and a little history. And some were a little more dense, like the battle of Crete and less hyena. So you were always gonna get both. You're either gonna get a majority of one or the other. Yeah, and Dan Carlin's the lion, I guess. Yeah, you got both. And you got predictably good. Yeah. I mean, what are your thoughts about, I mean, he's a storyteller too. He gets a lot of criticism from the historians, quote unquote. That's why he likes to not, he keeps saying he's not a historian, but what are your thoughts about hardcore history with Dan Carlin? Like, was he an inspiration to the podcast you were doing? Or like an account, like almost like a reverse psychology inspiration where you wanted to do some kind of opposing type of podcast in history? Or was history always just like a launching pad to just talk shit about human nature? More of the latter. I wasn't even aware of his podcast when we started. Oh, interesting. Yeah, and so it was just very organic. Again, like the chemistry, me and Chris became very good friends. We started the podcast. First, we did a web series called Bay Ridge Boys, which has its sort of little cult following. We did like five episodes and ended it. And then we did the podcast. And hyenas were my favorite animal. And I talk about them passionately. And I told Chris about them. And then he started appreciating them. And we both love history. I majored in history. It's one of the things I love. I go to museums all the time. I go to history, I do history tours, so does he. And so it was just sort of a natural, let's do a history podcast. And it gave us something to talk about each episode to sort of lean our, you know, hang our hats on and riff off of. So it had nothing to do with Dan's. What I think about Dan's, I think it's great. I think even if he's inaccurate in the opinions of the historical community, it starts conversations, which is good. It's like this thing where people go, oh, it's dangerous rhetoric. It's like, no, rhetoric only becomes dangerous when education fails. What's going on in America is education has failed. So if you call someone online dangerous, it's not him that's dangerous. It's the fucking stupid people that's dangerous. And it's the fault of this country. We didn't listen to Aristotle. The future of a civilization depends on public education. And we failed. Education has failed. Kids are not interested in shit. And so- Well, in some sense, those, like Dan's podcast, and podcasts can be incredibly educational. That's, he's, the storytelling that pulls you in ultimately leads to you internalizing these stories and remembering them and thinking through them and all those kinds of things that is much more powerful than you book on history that's accurate. I think often it inspires you to go learn more. So it's like, I know we did that. I mean, people would go, hey, I went and learned about this because they knew with us, there was no pretense, which was great, that we had no standard. So it's like, nobody came to us for historical accuracy, but I was kind of turned on by the fact that it inspired people to go learn about this stuff or to at least know, like Battle of Crete, like you said, a very underappreciated battle. Even Winston Churchill said, from here on, we will no longer say that Greeks fight like heroes, but heroes fight like Greeks. I mean, it was a monumental battle and not talked about enough. And our podcast would inspire people to go actually learn more, to go listen to Dan Carlin or to go pick up a book or to do research on their own. And so I think podcasts, Dan Carlin's obviously much more accurate than us, but it's good that people are going to podcasts like yours to learn shit. Joe is really like the progenitor of that. I mean, having intellectuals on and getting the public interested with this new medium in people who are intelligent, it's nice. Because what the mainstream press pushes out is horseshit, gorgeous horseshit. It's got a beautiful veneer, but no substance. And so this is a nice pushback. Yeah, the authenticity of Joe's show. I mean, I started listening from the very beginning, doing my, in grad school, like a technical person, and he just pulled me in and made me curious to learn about all kinds of things and use my own critical reasoning skills on some of the bullshit guess he's had and some of the most inspiring guess he's had. So I'll teach you to think. Can you, I don't know much about Bernie Madoff as a small tangent. Can you tell me who the hell is Bernie Madoff? Oh, Bernie Madoff is the GOAT, the greatest thief of all time, dude. Hedge fund guy, ran a hedge fund and pulled, stole the most money in the history of America. I mean, a con artist. And he does, people obviously, he's become, he's a household name because of the magnitude of his crime, but you got to appreciate, again, you got to appreciate what went into this and how long he was able to pull it off by tricking the smartest and richest people in the world. And a brilliant scam. The con man, a con man is short for confidence man. And it came from, yeah, a con man, basically they exude confidence and they trick people by playing on their ego and blind spots. And the word comes from a guy, I can't remember where, but what he used to do, I can't remember the guy's name, whatever. You can Google it, con man. But it's very interesting. The first con man that is on record, what he would do, he would go to very rich people and he'd be very well-dressed, right? And he'd go, I bet you don't have the confidence to give me your watch. And he would play on the egos of these very powerful and rich people and they would give him the watch for some reason, some sort of reverse psychology bullshit. And he'd take the watch and he would just steal it. So, because basically saying like, you don't have the confidence to give me the watch because you don't, I don't know, you don't think I'm gonna give it back. And he would just take it. So, Bernie Madoff was a very sophisticated con man. And again, we were talking about people pretending to be the opposite of what they are. Bernie hid his thievery in how available he was to his clients, how he would show up at every bar mitzvah, every birthday. He was always available for their phone calls. And he played on their egos. He made it so people wanted to invest in him. Like they were competing. He made it very exclusive. He wouldn't just take anyone. And there was a method behind that madness because he wanted the whales that wouldn't notice that he had this pyramid scheme going. And so what he would do is he would just rob from the richer and he just kept, it was like he'd pay back the richer with the guy who was a little less, and it was a pyramid scheme. And he was able to do it for so long and steal so much money. And he would win people over with the scheme because with that scheme, he was the only guy who could provide, who could guarantee like a 1% return even during times of recession. And because he was such a good con man, he hijacked people's reasoning with his charm. And that's what con artists do. That's what psychopaths do. They're so fucking charming. They get you in that Volkswagen Beetle. Because if they use their reasoning for one second, they'd go, hey, nobody can provide 1% returns during recessions. How the fuck is this guy doing it? I'll tell you how he's doing it. He's stealing from another guy to pay you. You fucking idiot. So charisma is a sense of that, maybe you can help explain something to me, something I have been affected by. I'm being way too loud for your listeners. There's gonna be comments like, tell this guy to calm down. I'm sorry, I'm Greek apostrophat. Yeah, we do. No, that's beautiful. I love it. This is something that I have been thinking about and have encountered indirectly is Jeffrey Epstein. And I have a sense because of MIT, because of all the other people that have been touched, the wrong term, by Jeffrey Epstein, in the sense that- Literally touched. Literally and figuratively. And it's always felt to me like there's not a deep conspiracy. I don't know. But it felt to me like there's not some deeply rooted conspiracy where like Eric Weinstein thinks that there's some probability that Jeffrey Epstein is a front for like an intelligence agency, whether it's Israeli or the CIA, I don't know, but is a front for something much, much bigger. And then I always thought that he's just, maybe you can correct me, but more of the Bernie Madoff variety, where he's just a charismatic guy who may be a psychopathic in some sense, so also a pedophile, but just charismatic and is able to convince people of that 1% of any idea that, in the case of scientists, is able to convince these people that their ideas matter. So one thing, scientists don't really, despite what people say, I don't think they care about money as much as people think. People are ridiculous when they think that. Yeah, that's why people get into science, for the money. The person who has to get into science are obsessed with minutiae, and they do the scientific method. You know how boring that is? Like you have to have a love for it in order to do it. But the thing- Love and truth. What drives you is for your ideas to be then heard. And when a rich guy comes over, probably super charismatic, is going to tell you that your ideas, especially for some of these outsiders at MIT, at Harvard, at Caltech, at all these sort of big science, like physics, biology, artificial intelligence, computing fields, to hear somebody say that your ideas are brilliant, that ideas matter, it's pretty powerful, especially when you've been an outsider. Like he's talked to a bunch of people who had outsider ideas. The big negative for me of modern academia is that most people, actually like most communities, most people think the same, and there's just these brilliant outsiders. And the outsiders are just derided. And so when you have Jeffrey Epstein, like a hyena, sorry, sorry, sorry, going from on the outside and picking off these brilliant minds that are the outsiders, he can use charisma to convince them to collaborate with him, to take his funding. And then thereby he builds a reputation, like slowly accumulates these people that actually results in a network of like some of the most brilliant people in the world, and then pulls in people like Bill Gates and I don't know, political figures. I tend to believe one person can do that. Yeah, I mean, look at Hitler. Charisma is blinding. I think that's what Kahneman, speaking of Bernie Madoff, that's one of their major tools is flattery, just glib, superficial charm. It creates those blind spots. People wanna hear how great they are. They wanna be flattered. It takes your defenses down, plays to our ego, how much we're all just pieces of garbage. I wanna hear how great we are. We want that love from our mother and our father. It's Freudian. And they know because they're not burdened with that need, they're not burdened with that empathy or emotions, and they just see things very calculatively. They play, they know that we're prey in their game, and they use that against us. And that is why someone who is not that intelligent, like Hitler, can probably convince a lot more intelligent people. And that's why we can't give Tim Dillon power because he already stands on a stage. I mean, if we let that guy, I mean, he will just take over a country and everyone who can't cook well will be eliminated. So it's like- I wonder why he keeps complimenting me while we're in private. Exactly, be careful. He looks at me, just, I like your suit. I like the cut of your jib. Yeah, definitely. You gotta be careful of that kid, he's Hitler. But it's crazy to think about- Clip that to his internet. I mean, Quentin Tarantino said it to bed. I mean, in his script, personality goes a long way, dude. I mean, personality can usurp common sense and reason of the smartest people. These absolute smartest people can be hypnotized. It's sort of like a sexy woman. It's like, you can be tricked because we have such a blind spot for flattery. Yeah, I wonder, I think there's a BBC documentary on, I think it's called something like Charisma, Hitler's Charisma or something like that. There's quite, I mean, that one focused more about the power of his speeches. But I wonder if most of the success or the rise of Hitler and the Third Reich had to do with the charisma of Hitler when he's alone in a room with somebody, with the generals, just one-on-one. Like, I wonder if that's the essential element of just being able to just look into a person's eyes, like flatter them or whatever is needed to earn their trust and then convince them of anything you want. Right, yeah, I mean, you're right because that's the one piece of history we don't have. We don't know. We don't know. We do know that the kid crushed. I mean, he was a headliner. He got up there and his fucking hair would flop around. I mean, he crushed it. Yeah, there's certain elements about nationalism and pride that are really powerful. Like a lot of us humans, I think, long for that, for the feeling of belonging. And when some charismatic leader makes us feel like we belong to a group, the amount of evil we can do to other humans because of that is endless. Especially when you're dealing with scapegoat. Nobody wants to look in, nobody wants to do the work to be better or look at where they messed up. Why does it always have to be the Jews that are the scapegoat? You know, it's like, get over it, guys. I mean, it's like, they killed Jesus. You think, get over it. Okay, it's a long time ago. I mean, move on. I'm Jewish, I understand because we do run the central banks and- And the weather. And the weather. Yeah. Don't forget about the weather. That's a big one. That's a funny one that people created. Like, who gives a shit? Well, what is the weather? Like, what's the importance of the weather? All right, like Jews made it rain outside. Good, you got to fuck, you know, they made it snow. Okay, you get a day off. Thank the Jews. Yeah, it's like, there's certain conspiracies that make me like flat earth. Like, what's the motive? Like, what's the motivation for lying that the earth is round? Like, what's the conspiracy? Yeah, what does anyone get out of that? Yeah, what is exactly the profit? What's the, yeah, what's the strategy? Do you have any, from a historical perspective or just a human perspective, conspiracy theories you connect with? Or you're not necessarily conspiratorial? I'm not necessarily conspiratorial. Nobody cares that much. Like, they're, but then, you know, what happens is you find out this one or this two. And you start questioning everything. And you start questioning everything, man. It's like, you know, the Vietnam War started, that was a lie. That was a false flag. And then next thing you know, everything's a false flag. There are some strange things on 9-11. You know, there's some strange things from a scientific perspective. I'm no scientist, but it's like, you know, yeah, three steel-framed skyscrapers falling on the same day in the same way. A lot of people say, oh, it was, they were hit by planes. It's like, yeah, but that's not why they fell. They fell because of fires. And usually, not usually, all the time, except for three times. And there was buildings that have burned for longer than that. And there might be good explanations, but the lack of transparency, it's like, I feel like government. And building seven's weird. I mean, the way it kind of, just a neat, just a neat, the physical, I mean, you're a scientist, is that? Well, I don't, I, I, I. Is there resistance from the steel? No, it's, it's, it's. Free fall seems weird. Not all scientists know everything. I'm just a computer guy. Okay, because I had some questions I wanted to ask you about my biology, by the way. Yeah, so exactly, I don't understand biology. I don't understand the melting point of steel. I don't, but I'm just a common sense human that looks at government and institutions when they try to communicate. And there's a certain human element where you can sense that there's dishonesty going on. That dishonesty might not be deeply rooted in a conspiracy theory and something malevolent. It might just be rooted more likely to me in a basic fear of losing your job. Right. So when you have a bunch of people that are afraid of losing their job, you know, and they just don't want to, like the origins of the virus, whether it came from a lab or not, you know, that's a pretty, I know a lot of biologists behind closed doors that say it's very likely it was leaked from the lab. Right. But like, they don't want to talk about it because there's not good evidence either way. It's mostly, you're just using common sense. So they're waiting for good evidence to come out in either direction. But just like nobody in positions of institutional, like centralized power wants to just honestly say, we don't know, or on the point of masks or all those kinds of things to say, you know, here's the best evidence we have. We're not sure, we're trying to figure it out. We're desperately trying to figure that out. Or just like honesty, especially in the modern day, that's the hope I have for the 21st century is people seem to detect bullshit much, much better. Because the internet. Internet, yeah. Yeah, and we seem to- But they also believe crazy shit too. There's no Ying without a Yang, I guess. But I think the conspiracy theories arise only when the people in positions of power in government and institutions are full of shit. Like the air will be taken out of the conspiracy theories if the people in elected power would be much more honest. Like just like real. You have people like Andrew Yang, whatever you think about him, just more honest. He just like says whatever the hell comes to mind. By the way, he's running for New York mayor. Mayor, yeah. Do you have opinions? Yeah, it's no good. I like Andrew Yang and it's no good. I'd be honest with you, I'm a lifelong New Yorker. I mean, I'm a New Yorker. Well, you're a New Yorker, so nothing's good. Well, something is good. Okay. I mean, let's be honest about New York. It's a very socially liberal place. It is the head of the snake. New York is the country. If New York, when New York's not doing good, country's not doing good. It's the most important city, DC, New York. It's really Rome, be honest. It's, maybe I'm biased, I don't know. No. Yeah. We just, New Yorkers, we walk around everywhere and we go, this is just like New York, but not New York. It's, but New York needs, and I'm a guy who leans left. I just, I lean left and that's just what it is. A dictator, is that where you're going? No, we need, we need, it's a money town. Let's be, come on, man. I mean, New York is a money town. And Wall Street, and then when AOC and her cronies at the local level rejected that Amazon thing, you're going like, what do you think makes cities? What's gonna create jobs in the 21st century? What do we need, more nail salons, more pizza places? I mean, we're living in the tech revolution and whatever your opinions are about Jeff Bezos, that's the world, tech. And they want us to come here. Of course you give them tax breaks. That's why companies go anywhere. She's so fucking utopian and that progressive wing is so utopian and that always ends in disaster because it's not rooted in reality. It doesn't accept the reality that people are self-interested. Now they're gonna do this 14%, 15% tax hike on people making a million dollars more. In New York City, a million dollars is not that much. So people are gonna flee New York. The tax base is gonna flee. New York's gonna fall to shit like it did before. So you're saying it basically needs a more capitalist front, like capitalistic type of thinker. Bloomberg, Giuliani when he was still sane and his hair wasn't melting off his face. Prosecutor, you need a top. I mean, I don't know what's happened. That guy's lost it, but it's fun. Yeah, it's fun to watch. Yeah, it's fun to watch him be just like Trump's lackey. Like, yeah, boss, whatever you want, boss. I'll just say whatever you want, boss. But New York is a money town that needs a money guy and sort of more of a Republican. I have to say on the local level, as more of a guy who leans left, I'll just be honest. It's a tough city that needs a tough mayor, not some guy who's going like, I understand we all need free money. Andrew Yang, I think is right in the big picture because all the real jobs are somewhere else. And you look at those Asian cities, you go like, oh, that's what our cities used to look like at the Industrial Revolution. You know, there was like, there was jobs and people were making things here. But now you look at those cities in Asia and you're going like, wow. And then you go to Detroit and you're like, yeah, we're done. You go to Cleveland, you go, we're done. So I don't, actually, it's funny. The reason I really like Andrew Yang is I've learned a lot every time he talks. Like, it's not his opinions. He's just giving a lot of data, like information, which I- Just start a podcast, don't run for mayor. Well, yeah, that's true. He already has a podcast, I think. Yang speaks. Who doesn't? Who doesn't? Fucking who doesn't now? That's the way we communicate. I don't even talk to people unless it's on a podcast. Well, listen, man, I'm not gonna criticize that because there is something, like I talked to my dad on a podcast for four hours and I'm not sure I would ever talk to him in the way we talked without the podcast. What does he do? Physicist. Oh, shit. But like- Check that episode out. Yeah, it's episode 100 and, you know, the way I recorded that podcast is I tried to put my ego aside. It's actually really tough to talk to your dad, especially because you're giving him a platform. So at that time, there's already a bit of a platform for this podcast. And so there's this, as a son, you think like, oh, here it goes with this bullshit again. Like that's the natural son thought you have. But at the same time, I wanted to, the way I thought about it is in 20 years, when I look back, like I wanna do a conversation where I'm happy with it, you know? So I wanna make him shine. But I also called him out on like, why were you so distant? Like all of that kind of stuff. Yeah, it was very difficult to do, but it was really important to do. And I don't think I'd be able to do it without a microphone. Right. Listen, how often do we sit there and just focus our attention, just look at the other person? I don't know, man. This is not even recording right now. I just invited you over. Just so we could actually, you're right. The podcast does make, like I've been listening to every word you've been saying. And if we weren't doing a podcast, I might be looking at my phone or being self-conscious about something else or nervous or anxious. Especially with people close to you. I mean, that was, I recommend that actually for people to talk to their family on a podcast. Or like fake or not. That's really powerful. It made me realize that there's a clear distinction between the conversations we usually have with humans and those we have on a podcast that's being recorded. What the fuck were we talking on before that? I knew you were gonna lose your train of thought on that one because that's a big one. There's emotion behind that one. A podcast with dad is gonna take, that's gonna take you to a place. I took you to a place. It took you outside of interviewer. New York. I went to a place. New York and Yang. New York and Yang. So the data, one of the things that really surprised me about, I like the psychoanalysis you just threw in there. Yeah, I knew that. I mean, yeah, it took you to a place. So Angie Yang mentioned- Do you respect me now, dad? MIT, is it enough? Fucking million people listening to this. I've got 14 Rogans. Is that enough, dad? I'm creating robots. Is that enough for you? That's not enough. That's what drives you probably. That's probably what drives me. That's what gives meaning to life is it's never enough. And I hope to pass that on to my kids one day that nothing's ever enough. Whether they're robot or human, right? Your kids. Most likely, let's be honest. Robot. You might call one of your robot. Do you love your robot? Are you starting to love your, is it gonna be like that Pygmalion thing? You create them and then they kill you, but even while they're killing you, you got a tear rolling down your eye. The tear, a slow one tear, one tear. And just- Yeah, why are you doing this Frankenstein? They're going, oh! Why, why? But I loved you. Those would be the last words out of my mouth. But Angie Yang mentioned something on the, that it costs $400,000, over $400,000 per year to support one person in prison in New York. Like when I heard that number, it was really confusing to me. Like that it costs that much, 400K per person. And it was really refreshing to hear a politician describe a particular problem with data. That this is this prison industrial complex, whatever the hell it is. And whether the solution, it's unclear what the solution is. I think he has solutions, but just the honesty of presenting that information was refreshing. And I'm not sure a capitalistic person would solve that. Those kinds of problems he might make worse. And I'm not, you know, I'm a huge fan of capitalism. I think, I think the free market is the way we make progress in this world, but it seems to go wrong in certain directions. Like the military industrial complex, the prison, anything that ends with industrial complex. And so I'm not sure. I'm not sure if all of the problems, you're basically saying, let's put New York's problems aside. We need to have New York shine first to do what it does best. Essentially, yeah. And then the problems will fix them. Well, and then we can focus on the problems. But if you just say like, here's a problem, here's a problem, here's a problem. Let's make sure we have the safety net that protects us against all of these kinds of problems. That's not going to, that's going to kill the city, the spirit of the city that is, in your biased opinion, the Rome of the world. That said, a lot of people are fleeing New York. Yeah, that's why I say it. That's the reality of the situation is, you know, I'm all for the public good, but yeah, there needs to be, back to that Greek expression, pon metronariston. I also think the free market is responsible for progress. I think it's the most natural thing, the thing that's most aligned with human nature, which is self-interest. And which I, not to the extent that Ayn Rand would, but I do believe people are mostly self-interested, especially with one gun to the head. Morals are out the window. You know, it's about survival. So, you know, create a system that respects that and acknowledges that. But socialism works very well, at least right now, as a check, as to temper the excesses of capitalism. And in certain scenarios, is the more appropriate system, you know, in a vacuum. So one being prisons or, you know, governance, you know, parks. Maybe even, well, and this is a difficult one, but in healthcare. Healthcare. It's unclear what to write. There's a lot of debates there. Yeah, doctors want votes. So I guess you're voting for AOC, you're saying. No, I'm not voting for AOC, but I do. It's just a tough one. That's a tough one. But ultimately, the Hippocratic Oath, it's like, how do you turn people away, man? How do you do that to people? It's like, it's a tough thing to reconcile helping people, curing people with the marketplace. It's just, I can understand why that one's so tough. And then you got hypochondriacs, of course, who drain the system. You know, like people who have anxiety, like me, who had COVID and called 14, you know, I called 14 ambulances. So, and then of course, we're fat, and the free market made us fat because it played, the marketing made us want all this junk food, and that's a burden on the healthcare system. So we gotta do something about that. We gotta get creative. We need new thinkers. I'll be one of them. When you go to a fast food restaurant, you stand on a scale. If you're over a certain thing, you can't be served. It's good for the healthcare system. You know, you just hand them a salad and say, sorry, this burger's illegal for right now. If you achieve these certain BMI goals, then you can have this burger, but right now you can't. And that's where the state's important. Yeah. Okay, to regulate our freedoms. No slurpees, I'm with you, Bloomberg. Well, I'm with you. To go along, I think the salads are too expensive. They should be subsidized. If you go to like a fast food joint, the burger's always going to be cheaper than the salad. And this does not make sense. We should run this platform. I'll be your vice president. We'll ban burgers for people over a certain weight and make salads cheap. Three-day work weeks. Why has that not happened yet? Okay, where are you going with this one? Dude, good for the economy. Stimulates the economy, right? More shifts, creates more jobs, more people spending because they have more leisure time, boosts the leisure economy, you know? Why are we still doing the five-day work week? That was tempered from the seven-day work week. It used to be seven-day work week. It used to be like, and people who are just these libertarians, it's like, come on, dude. What is this? Are we freshmen in college? Yeah. We're going to talk about Ayn Rand next? Like, let's talk about reality, okay? And human nature. People are fucking greedy. They lie. You know, there's no end to up, which is one of my favorite expressions. No end to up. No end to up. There's no end to up. Can we dissect that from a Randian perspective? There's no end to up, which is, you just keep going. It's never enough. The human flaw, it's never enough. No end to up. More, more, more. And you know, you have to reconcile your fact that you're going to die. So like, there's no end to up thing, is that balance is just as valuable as progress. So we have to reconcile those two things and put them on a seesaw and figure out how to get two people who have the equal weight to keep it like that. And that's the goal. And it constantly vacillates according to the time. Sometimes you need a little more socialism. Sometimes you need a little more capitalism. You got to fly the plane, man. You got to fly the plane, dude. What's your, looking back at history, how you as, is there a moment, time period in history, a person in history that's most fascinating to you? You mentioned Bernie Madoff. Maybe second to Bernie Madoff. Is there, in the Battle of Crete, is there something that you've always been curious about? Even if it's something you haven't actually researched that well yet, just something that pulled at your curiosity that instructed the way you think about the world. An individual or an event? An event, individual, yeah, moment in history or a person in history. There's a few, but Queen Elizabeth, the Elizabethan era, the sun never sets in the British Empire, very successful empire. What an absolute success story that is for a leader and a woman. Can you tell a little bit about her story? Well, you know. I actually don't know much about the British Empire. Yeah, she had a good run. I think it's like 70 years, you know, Shakespeare, the, oh, I guess, what's the word, Pax Romana, the period of Rome that was at peace and they flourished, like a couple of emperors like Trajan or some good ones, and I think he was part of the Pax Romana, that sort of just a peace and a comfortable flourishing time and England had sort of that in their empire under her. Successful reign, she murdered her cousin. She, you know, the movies, there's, you know, Cate Blanchett plays her and does so, and she didn't win the Oscar because fucking Gwyneth Paltrow put a British accent on in Shakespeare in Love. It's a tragedy. Why do I know this? Because I'm not a full man. I'm a comedian, which means I do skits and I perform. And I, Cate Blanchett's an incredible actress, did great movies. She was just so, and here's the thing, she never got married. She was so astute at public relations and imagine how strong you gotta be as a woman to lead the greatest empire maybe known to man at the time and to do so so successfully. How Machiavellian you have to be, how idealist you have to be, how much of a good marketer you have to be. Propaganda machine was on point. She was married to England. She was adored the way she adorned herself. You walked in, you're like, holy man, God just walked in here. And of course she got fucked. I mean, who doesn't fuck? We all fuck. Even robots one day will fuck. But she did that propaganda thing. And historians aren't, they haven't decided this, but I believe she fucked. And I believe she did that as a tool of propaganda, a marriage to England. So you're directly referring to like using sex as a way to manipulate people. Well, she was known as like the virgin queen. And her thing was like, I'm married to England. Like I can't be distracted by man or woman, blah, blah, blah. She never had any kids, nothing. I think she did that as a tool of manipulation, which you need. Rulers need to, you know, Obama made you feel good and then he went and carpet bombed everywhere. You need to feel good about your guy no matter how evil they are. And she was fucking a dictator. But when you look back at her, everyone's like, oh my God, she was so great. The horror and the shit that she had to do, she didn't put that in the history books, but that's what probably was part of what made her successful. And she's a fascinating character to ponder on because she was so successful and England flourished so much. And it's just fascinating to me because she was the great virgin queen. And can you think of, there's no other woman who was that, I mean, Angela Merkel, I mean, come on. I mean, there's nobody who comes close and defeating the Spanish Armada, I think that happened under her. I mean, I'm no professional historian, but I mean, the woman crushed. Do you think it's more effective to lead by love, which it sounds like what she did from the PR perspective, or by fear? Where do you land on that with Merkel Valley? That's a great question. We gotta ask Joe. Well, yeah, this is interesting because I think leading in the 21st century in whatever ways is different. I think it's very difficult to lead by fear. I mean, that's why I find Putin fascinating and like really fascinating. Like, is he a relic of another era or is he something that will still be necessary in the coming decades for certain nations? I think he's a, I don't think he's a relic from another era. I think his background, I think he is who you think he is because his background was in espionage. His background was in subterfuge and espionage. I think I've said the word subterfuge maybe 10 times now. But he- You like big words, you're intellectuals. I just, I'm sitting here with you, it's time to flex. But he's very good at that, right? Like controlling people with psychology. And even if you look at the way he sort of used the internet and has sort of gotten into the citizens of other countries' opinions, and it's very KGB. He also looks great without a shirt on a pony. On a horse. On a horse, yeah, yeah. I thought he would choose a pony because a pony's smaller, makes him look better. Would you put Queen Elizabeth as the greatest leader of all time? Probably, yeah. I think as a woman, and you look at the length of the reign, I think it's like 70 something years or something like that, that she reigned. Success, man, success. She used the church, she used public psychology, Shakespeare, the greatest playwright of all time under her reign. People were going to plays and it was a success front and she was marauding everywhere else, marauding and culling resources for the empire. Just say absolute success. It's even a token of her success, we don't consider her a dictator. She's a dictator. She was queen. This is my thing I love about the feudal system, that these fucking countries still have feudal systems. They're celebrating a horrible thing, divine right of kings, oppression. Kings were dictators and now they have fucking ceremonial, why don't we have a ceremonial Führer? Why doesn't German, he doesn't do any of the bad stuff, he just rolls around and does this shit. I mean, it's like, what the fuck? There's no difference between a Hitler and a fucking king, they did the same horrible shit. Why not a fucking ceremonial conqueror? Alexander the Great walks in, rapes a little bit, but it's all fine, it's for ceremony. He represents the country, Macedonia. It's Greek. It's interesting to see that some, you're starting to see a bit of that in Russia with Stalin, actually, the celebration of a man that helped win the Great Patriotic War. Uh-oh, yeah. Right, so you're already starting to see that. It's very possible in history books, he'll be seen as maybe like a Genghis Khan type of character and you forget the millions that he tortured. So you're one of the most successful and brilliant people the world has ever seen, so you're the good person to ask for advice. You know, there's a lot of young people that look up to you. God bless their souls and hearts. Made the right choice. What advice would you give to a young person, maybe to yourself, to a young version of yourself? Just how to live a successful, a good life. Be doggedly you. I think the magic happens when you are stubbornly, doggedly you and you meet other people who are doing the same. And the real magic of life, the real true currency in this ephemeral life is sort of the communication that happens between people. That's the real currency. Friendships, love, it's cliche, but I think the meaning of life is to experience love. And I think people often mistake, maybe it's because of Hollywood films and things like that, that love is a feeling, but it's not, it's an action. So that took me a while to learn, and I think that's why I've made decisions since that I think have been good for me and healthy for me. Love is an action. People can say things, you can feel things. That doesn't mean they're necessarily real. It's all chemical reactions. It's all tied to our immaturity and psychological issues and survival. But action, when you do things, when you act out of love, that's what it's about. Is there times when you were younger where you were kind of dishonest with who you are to yourself? Yeah. In terms of like, what kind of things did you have to do to shake yourself up and be like, okay, I thought I'm gonna be a scientist, but instead I realized I'm gonna do this. Yeah, my parents were- I'm gonna make funny. My comedy is a hard thing to explain to an immigrant mother who came here under Nazi-occupied Crete and became a human rights lawyer and lawyer. And my brother's a lawyer, my father's a lawyer. Claude is way up. His dad was a- So you're a disappointment. I'm the black sheep. Yeah, my brother went to Oxford, Georgetown Law, Brown. You know, has a master's in law degrees. My mother has four law degrees, you know. She was on the Human Rights Commission in New York, up for a judgeship under Dinkins. Wrote a, you know, she was the editor of Unitar. She wrote a seminal piece on the human rights of children for the United Nations. And yeah, I was a comedian. I was always a fuck up. And the thing that I was best at, the only thing I was ever decent at was just like making people laugh. I don't know why, I don't know where that comes from. But- Was there ever a question, or was there a moment where you decided this is what I'm gonna do? There was a moment after I graduated college, yeah. But I was thinking about all types of stuff that other people imposed on me. And I was honest with myself. And once I figured out it was an actual career path, I wasn't even aware. Back then, the internet wasn't huge. You know, late 99, 2000, it wasn't big yet. So I thought Robin Williams was just like an actor. I didn't know there was comedy clubs and all. So once I learned that, I was just like, I tried it. I suffered from massive anxiety. I remember the first time I did comedy, my arms went numb. I started having a massive panic attack. I have my first set, I can show it to you. It's like, I suggest, I just- On video? Yeah, on video. Oh, nice. I kept going, thank you, thank you, thank you. And the reason why I kept saying thank you is because I forgot my whole joke, because I was so scared. And then they laughed because of the amount of times I said thank you. And then once they laughed, I remembered the whole thing. And I did the five minutes, and I remember getting off. And for a person who never felt like he had a place anywhere, nothing ever felt right, that felt like, okay, I found it. This is what I'm supposed to do. This is it. It was the only time in my life I felt that. I haven't felt it since, never felt it before. So it's the only thing I can do. Yeah, I had that. You know, it's funny, because I have a similar experience, like immigrant family. And the world tells you to do certain things, and you think that's right. But then you put yourself in situations, by luck probably, where it's like, oh, this feels right. This feels right. I don't know what this means, but this feels right. I think the biggest moment like that for me was, I don't know what to make of it exactly, but when I met Spot, the robot, the four-legged robot, it was like five years ago, it felt like the depth of fascinating ideas that are yet to be explored with this thing, this felt like a journey. It was like a door that opened. And I was like, I don't wanna be a professor. At that point, I realized I don't want to do sort of generic stuff. I want to do something crazy. I want to do something big. That's the reason I stepped away from MIT. That's the reason I have this burning desire to do a startup. That's the reason I came to Austin. Yeah, I don't know what the hell it all means, but you just kind of follow that. That's awesome. That sounds like you're following what's doggedly you. And also I think, just to piggyback off it, I think that means no matter what it is, because I think the American dream is sold like, hey, if you're not Beyonce or if you're not famous, you're not worth it. I hate that. And that's what I love so much about certain countries like Sweden, it's like where everyone has healthcare and stuff like that, because everyone is valued more. It's like whatever, if you wanna be a doorman, do it. It's all the same. Prince was not happy. There's no, just because you're rich or famous, you're still the same guy. Whether your possessions are a lot, little, it's like, I have met some doorman, I have met some tax gappers that, I lie to you not, are more fascinating. I have, comedians are horrible people. Some, I wanna get away from all of them. I have very few friends, Paul Verzi, Tim Dillon, who are comedians, because they're awful, awful people. Some of the people who you know the most, who are the most famous, are not who they say they are. Usually that's the case. They're putting on that public facade, because they're fucking sociopaths. They're horrible people. And some of the most beautiful people I've met and the most interesting people I've met have regular jobs. There's no shame in any fucking job. We don't all have to be rappers with like rims. It's just a weird thing. Yeah, fame is a drug. And yeah, comedians, I agree with you. There's some part of me that knows that there'll be a moment in my life when I'm standing there with like a sword or a knife in my stomach and looking at Tim Dillon's smiling face, saying, you shouldn't have trusted me, you stupid fuck. So on that note, Yanis, I've been a huge fan of yours. I love what you're doing with Long Days, now your new podcast. And I obviously love all the stuff you've done before with History of Hyenas. The chemistry you have with yourself is also fun to watch. So man, I'm a huge fan. It's a huge honor that you come down here. Thanks so much for talking to me. It means so much to me to hear you say that. I really appreciate it. I'm a big fan of yours and Have Me On has been amazing. And just thank you, man. Thank you for Have Me On. And people, if they want to watch my special, it's called Blowing the Light. It's on YouTube. And please come listen to Long Days, the podcast. And let's go eat some barbecue. Let's do it. Thanks for listening to this conversation with Yanis Papas. And thank you to Wine Access, Blinkist, Magic Spoon, and Indeed. Check them out in the description to support this podcast. And now let me leave you with some words from Karl Marx. Revolutions are the locomotives of history. Thank you for listening and hope to see you next time.

https://youtu.be/dmVqpx4YOY4

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Kate Darling: Social Robotics | Lex Fridman Podcast #98

The following is a conversation with Kate Darling, a researcher at MIT, interested in social robotics, robot ethics, and generally how technology intersects with society. She explores the emotional connection between human beings and lifelike machines, which for me, is one of the most exciting topics in all of artificial intelligence. As she writes in her bio, she's a caretaker of several domestic robots, including her PLEO dinosaur robots named Yo-Chai, Peter, and Mr. Spaghetti. She is one of the funniest and brightest minds I've ever had the fortune to talk to. This conversation was recorded recently, but before the outbreak of the pandemic. For everyone feeling the burden of this crisis, I'm sending love your way. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with Five Stars and Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now, and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. Quick summary of the ads. Two sponsors, Masterclass and ExpressVPN. Please consider supporting the podcast by signing up to Masterclass at masterclass.com slash Lex, and getting ExpressVPN at expressvpn.com slash Lex pod. This show is sponsored by Masterclass. Sign up at masterclass.com slash Lex to get a discount and to support this podcast. When I first heard about Masterclass, I thought it was too good to be true. For $180 a year, you get an all-access pass to watch courses from, to list some of my favorites, Chris Hadfield on space exploration, Neil deGrasse Tyson on scientific thinking and communication, Will Wright, creator of SimCity and Sims, love those games, on game design, Carlos Santana on guitar, Garry Kasparov on chess, Daniel Negrano on poker, and many more. Chris Hadfield explaining how rockets work and the experience of being launched into space alone is worth the money. By the way, you can watch it on basically any device. Once again, sign up on masterclass.com slash Lex to get a discount and to support this podcast. This show is sponsored by ExpressVPN. Get it at expressvpn.com slash Lex pod to get a discount and to support this podcast. I've been using ExpressVPN for many years. I love it. It's easy to use, press the big power on button and your privacy is protected. And if you like, you can make it look like your location's anywhere else in the world. I might be in Boston now, but I can make it look like I'm in New York, London, Paris, or anywhere else. This has a large number of obvious benefits. Certainly, it allows you to access international versions of streaming websites like the Japanese Netflix or the UK Hulu. ExpressVPN works on any device you can imagine. I use it on Linux. Shout out to Ubuntu, 2004, Windows, Android, but it's available everywhere else too. Once again, get it at expressvpn.com slash Lex pod to get a discount and to support this podcast. And now, here's my conversation with Kate Darling. You co-taught robot ethics at Harvard. What are some ethical issues that arise in the world with robots? Yeah, that was a reading group that I did when I, like, at the very beginning, first became interested in this topic. So I think if I taught that class today, it would look very, very different. Robot ethics, it sounds very science fiction-y, especially did back then, but I think that some of the issues that people in robot ethics are concerned with are just around the ethical use of robotic technology in general. So for example, responsibility for harm, automated weapon systems, things like privacy and data security, things like automation and labor markets. And then, personally, I'm really interested in some of the social issues that come out of our social relationships with robots. One-on-one relationship with robots. Yeah. I think most of the stuff we have to talk about is like one-on-one social stuff. That's what I love, and I think that's what you love as well and are expert in. But at societal level, there's like, there's a presidential candidate now, Andrew Yang, running. He's concerned about automation and robots and AI in general taking away jobs. He has a proposal of UBI, universal basic income, of everybody gets a thousand bucks. Yeah. As a way to sort of save you if you lose your job from automation, to allow you time to discover what it is that you would like to, or even love to do. Yes. So I lived in Switzerland for 20 years, and universal basic income has been more of a topic there, separate from the whole robots and jobs issue. So it's so interesting to me to see kind of these Silicon Valley people latch onto this concept that came from a very kind of left-wing socialists, you know, kind of a different place in Europe. But on the automation and labor markets topic, I think that it's very, so sometimes in those conversations, I think people overestimate where robotic technology is right now. And we also have this fallacy of constantly comparing robots to humans and thinking of this as a one-to-one replacement of jobs. So even like Bill Gates, a few years ago, said something about, you know, maybe we should have a system that taxes robots for taking people's jobs. And it just, I mean, I'm sure that was taken out of context. You know, he's a really smart guy, but that sounds to me like kind of viewing it as a one-to-one replacement versus viewing this technology as kind of a supplemental tool that of course is gonna shake up a lot of stuff, it's gonna change the job landscape. But I don't see, you know, robots taking all the jobs in the next 20 years. That's just not how it's gonna work. Right, so maybe drifting into the land of more personal relationships with robots and interaction and so on. I gotta warn you, I go, I may ask some silly philosophical questions, I apologize. Oh, please do. Okay, do you think humans will abuse robots in their interactions? So you've had a lot of, and what we'll talk about is sort of anthropomorphization and, you know, this intricate dance, emotional dance between human and robot, but there seems to be also a darker side where people, when they treat the other, as servants especially, they can be a little bit abusive or a lot abusive. Do you think about that? Do you worry about that? Yeah, I do think about that. So, I mean, one of my main interests is the fact that people subconsciously treat robots like living things, and even though they know that they're interacting with a machine, and what it means in that context to behave violently. I don't know if you could say abuse because you're not actually, you know, abusing the inner mind of the robot, the robot doesn't have any feelings. As far as you know. Well, yeah. It also depends on how we define feelings and consciousness, but I think that's another area where people kind of overestimate where we currently are with the technology. Like the robots are not even as smart as insects right now. And so I'm not worried about abuse in that sense, but it is interesting to think about what does people's behavior towards these things mean for our own behavior? Is it desensitizing the people to, you know, be verbally abusive to a robot or even physically abusive? And we don't know. Right, it's a similar connection from like, if you play violent video games, what connection does that have to desensitization to violence? That's like, I haven't read literature on that. I wonder about that. Because everything I've heard, people don't seem to any longer be so worried about violent video games. Correct. We've seemed, the research on it is, it's a difficult thing to research. So it's sort of inconclusive, but we seem to have gotten the sense, at least as a society, that people can compartmentalize. When it's something on a screen and you're like, you know, shooting a bunch of characters or running over people with your car, that doesn't necessarily translate to you doing that in real life. We do, however, have some concerns about children playing violent video games. And so we do restrict it there. I'm not sure that's based on any real evidence either, but it's just the way that we've kind of decided, you know, we wanna be a little more cautious there. And the reason I think robots are a little bit different is because there is a lot of research showing that we respond differently to something in our physical space than something on a screen. We will treat it much more viscerally, much more like a physical actor. And so it's totally possible that this is not a problem. And it's the same thing as violence in video games. You know, maybe, you know, restrict it with kids to be safe, but adults can do what they want. But we just need to ask the question again, because we don't have any evidence at all yet. Maybe there's an intermediate place to, I did my research on Twitter, by research I mean scrolling through your Twitter feed. You mentioned that you were going at some point to an animal law conference. So I have to ask, do you think there's something that we can learn from animal rights that guides our thinking about robots? Oh, I think there is so much to learn from that. I'm actually writing a book on it right now. That's why I'm going to this conference. So I'm writing a book that looks at the history of animal domestication and how we've used animals for work, for weaponry, for companionship. And, you know, one of the things the book tries to do is move away from this fallacy that I talked about of comparing robots and humans, because I don't think that's the right analogy. But I do think that on a social level, even on a social level, there's so much that we can learn from looking at that history, because throughout history, we've treated most animals like tools, like products. And then some of them we've treated differently, and we're starting to see people treat robots in really similar ways. So I think it's a really helpful predictor to how we're going to interact with the robots. Do you think we'll look back at this time, like 100 years from now, and see what we do to animals as like similar to the way we view like the Holocaust with the World War II? That's a great question. I mean, I hope so. I am not convinced that we will. But I often wonder, you know, what are my grandkids gonna view as, you know, abhorrent that my generation did, that they would never do? And I'm like, well, what's the big deal? You know, it's a fun question to ask yourself. It always seems that there's atrocities that we discover later. So the things that at the time people didn't see as, you know, you look at everything from slavery to any kinds of abuse throughout history, to the kind of insane wars that were happening, to the way war was carried out, and rape and the kind of violence that was happening during war, that we now, you know, we see as atrocities, but at the time perhaps didn't as much. And so now I have this intuition that, I have this worry, maybe I'm, you're going to probably criticize me, but I do anthropomorphize robots. I have, I don't see a fundamental philosophical difference between a robot and a human being in terms of once the capabilities are matched. So the fact that we're really far away doesn't in terms of capabilities and then that from natural language processing, understanding and generation, to just reasoning and all that stuff. I think once you solve it, I see the, this is a very gray area, and I don't feel comfortable with the kind of abuse that people throw at robots. Subtle, but I can see it becoming, I can see basically a civil rights movement for robots in the future. Do you think, let me put it in the form of a question, do you think robots should have some kinds of rights? Well, it's interesting because I came at this originally from your perspective. I was like, you know what? There's no fundamental difference between technology and human consciousness. We can probably recreate anything, we just don't know how yet. And so there's no reason not to give machines the same rights that we have once, like you say, they're kind of on an equivalent level. But I realized that that is kind of a far future question. I still think we should talk about it because I think it's really interesting, but I realized that it's actually, we might need to ask the robot rights question even sooner than that, while the machines are still, quote unquote, really dumb and not on our level because of the way that we perceive them. And I think one of the lessons we learned from looking at the history of animal rights, and one of the reasons we may not get to a place in a hundred years where we view it as wrong to eat or otherwise use animals for our own purposes is because historically we've always protected those things that we relate to the most. So one example is whales. No one gave a shit about the whales. Am I allowed to swear? Yeah. You can swear as much as you want. Freedom. Yeah, no one gave a shit about the whales until someone recorded them singing. And suddenly people were like, oh, this is a beautiful creature and now we need to save the whales. And that started the whole Save the Whales movement in the 70s. So as much as I, and I think a lot of people wanna believe that we care about consistent biological criteria, that's not historically how we formed our alliances. Yeah, so why do we believe that all humans are created equal? Killing of a human being, no matter who the human being is, that's what I meant by equality, is bad. And then, because I'm connecting that to robots and I'm wondering whether mortality, so the killing act is what makes something, that's the fundamental first right. So I am currently allowed to take a shotgun and shoot a Roomba, I think. I'm not sure, but I'm pretty sure. It's not considered murder, right? Or even shutting them off. So that's where the line appears to be, right? Is this mortality a critical thing here? I think here again, like the animal analogy is really useful because you're also allowed to shoot your dog, but people won't be happy about it. So we do give animals certain protections from like, you know, you're not allowed to torture your dog and set it on fire, at least in most states and countries, you know. But you're still allowed to treat it like a piece of property in a lot of other ways. And so we draw these, you know, arbitrary lines all the time. And, you know, there's a lot of philosophical thought on why viewing humans as something unique is just speciesism and not, you know, based on any criteria that would actually justify making a difference between us and other species. Do you think in general, people, most people are good? Do you think there's evil and good in all of us? That's revealed through our circumstances and through our interactions. I like to view myself as a person who like, believes that there's no absolute evil and good and that everything is, you know, gray. But I do think it's an interesting question. Like when I see people being violent towards robotic objects, you said that bothers you because the robots might someday, you know, be smart. And is that what? Well, it bothers me because it reveals, so I personally believe, because I've studied way too much, so I'm Jewish, I studied the Holocaust and World War II exceptionally well. I personally believe that most of us have evil in us. That what bothers me is the abuse of robots reveals the evil in human beings. Yeah. And I think it doesn't just bother me, I think it's an opportunity for roboticists to make, help people find the better sides that the angels of their nature, right? Yeah. That abuse isn't just the fun side thing, that's you revealing a dark part that you shouldn't, that should be hidden deep inside. Yeah, I mean, you laugh, but some of our research does indicate that maybe people's behavior towards robots reveals something about their tendencies for empathy generally, even using very simple robots that we have today that like clearly don't feel anything. So, Westworld is maybe, not so far off and it's like depicting the bad characters as willing to go around and shoot and rape the robots and the good characters as not wanting to do that, even without assuming that the robots have consciousness. So there's a opportunity, it's interesting, there's opportunity to almost practice empathy. Robots is an opportunity to practice empathy. I agree with you. Some people would say, why are we practicing empathy on robots instead of on our fellow humans or on animals that are actually alive and experience the world? And I don't agree with them because I don't think empathy is a zero-sum game and I do think that it's a muscle that you can train and that we should be doing that, but some people disagree. So the interesting thing, you've heard raising kids, sort of asking them or telling them to be nice to the smart speakers, to Alexa and so on, saying please and so on during the requests. I don't know if, I'm a huge fan of that idea because that's towards the idea of practicing empathy. I feel like politeness, I'm always polite to all the systems that we build, especially anything that's speech interaction-based, like when we talk to the car, I always have a pretty good detector for please. I feel like there should be a room for encouraging empathy in those interactions. Okay, so I agree with you, so I'm gonna play devil's advocate. Sure. Yeah, what is the devil's advocate argument there? The devil's advocate argument is that if you are the type of person who has abusive tendencies or needs to get some sort of behavior like that out, needs an outlet for it, that it's great to have a robot that you can scream at so that you're not screaming at a person. And we just don't know whether that's true, whether it's an outlet for people, or whether it just kind of, as my friend once said, trains their cruelty muscles and makes them more cruel in other situations. Oh boy, yeah, and that expands to other topics, which I don't know, there's a topic of sex, which is a weird one that I tend to avoid from a robotics perspective, and mostly the general public doesn't. They talk about sex robots and so on. Is that an area you've touched at all research-wise? Like the way, because that's what people imagine sort of any kind of interaction between human and robot that shows any kind of compassion. They immediately think from a product perspective in the near term is sort of expansion of what pornography is and all that kind of stuff. Yeah. Do researchers touch this? Well, that's kind of you to characterize it as, oh, they're thinking rationally about product. I feel like sex robots are just such a titillating news hook for people that they become the story. And it's really hard to not get fatigued by it when you're in the space, because you tell someone you do human-robot interaction, of course the first thing they wanna talk about is sex robots. Like you said, yeah, it happens a lot. And it's unfortunate that I'm so fatigued by it, because I do think that there are some interesting questions that become salient when you talk about sex with robots. See, what I think would happen when people get sex robots, like if you say, what's up guys? Okay, guys get female sex robots. What I think there's an opportunity for is an actual, like they'll actually interact, what I'm trying to say, they won't, outside of the sex would be the most fulfilling part. Like the interaction, it's like the folks who, there's movies on this, right? Who pay a prostitute and then end up just talking to her the whole time. So I feel like there's an opportunity. It's like most guys and people in general joke about the sex act, but really people are just lonely inside and they're looking for connection, many of them. And it'd be unfortunate if that connection is established through the sex industry. I feel like it should go into the front door of like people are lonely and they want a connection. Well, I also feel like we should kind of de-stigmatize the sex industry because even prostitution, like there are prostitutes that specialize in disabled people who don't have the same kind of opportunities to explore their sexuality. So I feel like we should like de-stigmatize all of that generally. But yeah, that connection and that loneliness is an interesting topic that you bring up because while people are constantly worried about robots replacing humans and oh, if people get sex robots and the sex is really good, then they won't want their partner or whatever. But we rarely talk about robots actually filling a hole where there's nothing and what benefit that can provide to people. Yeah, I think that's an exciting, there's a giant hole that's unfillable by humans. It's asking too much of your friends and people you're in a relationship with and your family to fill that hole. Because it's exploring the full, exploring the full complexity and richness of who you are. Like who are you really? People, your family doesn't have enough patience to really sit there and listen to who are you really. And I feel like there's an opportunity to really make that connection with robots. I just feel like we're complex as humans and we're capable of lots of different types of relationships. So whether that's with family members, with friends, with our pets, or with robots, I feel like there's space for all of that and all of that can provide value in a different way. Yeah, absolutely. So I'm jumping around. Currently most of my work is in autonomous vehicles. So the most popular topic among the general public is the trolley problem. So most, most, most roboticists kind of hate this question, but what do you think of this thought experiment? What do you think we can learn from it outside of the silliness of the actual application of it to the autonomous vehicle? I think it's still an interesting ethical question and that in itself, just like much of the interaction with robots has something to teach us. But from your perspective, do you think there's anything there? Well, I think you're right that it does have something to teach us because, but I think what people are forgetting in all of these conversations is the origins of the trolley problem and what it was meant to show us, which is that there is no right answer and that sometimes our moral intuition that comes to us instinctively is not actually what we should follow if we care about creating systematic rules that apply to everyone. So I think that as a philosophical concept, it could teach us at least that, but that's not how people are using it right now. Like we have, and these are friends of mine and like, I love them dearly and their project adds a lot of value, but if we're viewing the moral machine project as what we can learn from the trolley problems, the moral machine is, I'm sure you're familiar, it's this website that you can go to and it gives you different scenarios. Like, oh, you're in a car, you can decide to run over these two people or this child. You know, what do you choose? Do you choose the homeless person? Do you choose the person who's jaywalking? And so it pits these like moral choices against each other and then tries to crowdsource the quote unquote correct answer, which is really interesting and I think valuable data, but I don't think that's what we should base our rules in autonomous vehicles on because it is exactly what the trolley problem is trying to show, which is your first instinct might not be the correct one if you look at rules that then have to apply to everyone and everything. So how do we encode these ethical choices in interaction with robots? So for example, in autonomous vehicles, there is a serious ethical question of, do I protect myself? Does my life have higher priority than the life of another human being? Because that changes certain controlled decisions that you make. So if your life matters more than other human beings, then you'd be more likely to swerve out of your current lane. So currently automated emergency braking systems just break, they don't ever swerve. So swerving into oncoming traffic or no, just in a different lane can cause significant harm to others, but it's possible that it causes less harm to you. So that's a difficult ethical question. Do you have a hope that, like the trolley problem is not supposed to have a right answer? Do you hope that when we have robots at the table, we'll be able to discover the right answer for some of these questions? Well, what's happening right now, I think, is this question that we're facing of, what ethical rules should we be programming into the machines is revealing to us that our ethical rules are much less programmable than we probably thought before. And so that's a really valuable insight, I think, that these issues are very complicated and that in a lot of these cases, you can't really make that call, like not even as a legislator. And so what's gonna happen in reality, I think, is that car manufacturers are just gonna try and avoid the problem and avoid liability in any way possible, or they're gonna always protect the driver because who's gonna buy a car if it's programmed to kill you instead of someone else? So that's what's gonna happen in reality. But what did you mean by, like once we have robots at the table, like do you mean when they can help us figure out what to do? No, I mean when robots are part of the ethical decisions. So no, no, no, not they help us, well. Oh, you mean when it's like, should I run over a robot or a person? Right, that kind of thing. So what, no, no, no. So when you, it's exactly what you said, which is when you have to encode the ethics into an algorithm, you start to try to really understand what are the fundamentals of the decision-making process you make to make certain decisions. Should you, like capital punishment, should you take a person's life or not to punish them for a certain crime? Sort of, you can use, you can develop an algorithm to make that decision, right? And the hope is that the act of making that algorithm, however you make it, so there's a few approaches, will help us actually get to the core of what is right and what is wrong under our current societal standards. But isn't that what's happening right now? And we're realizing that we don't have a consensus on what's right and wrong. You mean in politics in general? Well, like when we're thinking about these trolley problems and autonomous vehicles and how to program ethics into machines and how to make AI algorithms fair and equitable, we're realizing that this is so complicated and it's complicated in part because there doesn't seem to be a one right answer in any of these cases. Do you have a hope for, like one of the ideas of the moral machine is that crowdsourcing can help us converge towards like democracy, can help us converge towards the right answer. Do you have a hope for crowdsourcing? Well, yes and no. So I think that in general, I have a legal background and policymaking is often about trying to suss out what rules does this particular society agree on and then trying to codify that. So the law makes these choices all the time and then tries to adapt according to changing culture. But in the case of the moral machine project, I don't think that people's choices on that website necessarily reflect what laws they would want in place. If given, I think you would have to ask them a series of different questions in order to get at what their consensus is. I agree, but that has to do more with the artificial nature of, I mean, they're showing some cute icons on a screen. That's almost, so if you, for example, we do a lot of work in virtual reality. And so if you put those same people into virtual reality where they have to make that decision, their decision would be very different, I think. I agree with that. That's one aspect. And the other aspect is, it's a different question to ask someone, would you run over the homeless person or the doctor in this scene? Or do you want cars to always run over the homeless people? I think, yeah. So let's talk about anthropomorphism. To me, anthropomorphism, if I can pronounce it correctly, is one of the most fascinating phenomena from both the engineering perspective and the psychology perspective, machine learning perspective, and robotics in general. Can you step back and define anthropomorphism, how you see it in general terms in your work? Sure, so anthropomorphism is this tendency that we have to project human-like traits and behaviors and qualities onto non-humans. And we often see it with animals, like we'll project emotions on animals that may or may not actually be there. We often see that we're trying to interpret things according to our own behavior when we get it wrong. But we do it with more than just animals. We do it with objects, you know, teddy bears. We see faces in the headlights of cars. And we do it with robots, very, very extremely. Do you think that can be engineered? Can that be used to enrich an interaction between an AI system and a human? Oh yeah, for sure. And do you see it being used that way often? Like, I don't, I haven't seen, whether it's Alexa or any of the smart speaker systems, often trying to optimize for the anthropomorphization. You said you haven't seen? No, I haven't seen. They keep moving away from that. I think they're afraid of that. They actually, so I only recently found out, but did you know that Amazon has like a whole team of people who are just there to work on Alexa's personality? So I know, depends on your personality. I didn't know that exact thing. But I do know that the, how the voice is perceived is worked on a lot. Whether that, if it's a pleasant feeling about the voice, but that has to do more with the texture of the sound and the audience on, but personality is more like. It's like, what's her favorite beer when you ask her? And the personality team is different for every country too. Like there's a different personality for German Alexa than there is for American Alexa. That said, I think it's very difficult to use the, or really, really harness the anthropomorphism with these voice assistants, because the voice interface is still very primitive. And I think that in order to get people to really suspend their disbelief and treat a robot like it's alive, less is sometimes more. You want them to project onto the robot and you want the robot to not disappoint their expectations for how it's going to answer or behave in order for them to have this kind of illusion. And with Alexa, I don't think we're there yet, or Siri, that just, they're just not good at that. But if you look at some of the more animal-like robots, like the baby seal that they use with the dementia patients, it's a much more simple design. It doesn't try to talk to you. It can't disappoint you in that way. It just makes little movements and sounds and people stroke it and it responds to their touch. And that is a very effective way to harness people's tendency to kind of treat the robot like a living thing. Yeah, so you bring up some interesting ideas in your paper chapter, I guess, Anthropomorphic Framing and Human-Robot Interaction that I read the last time we scheduled this. I don't remember that. Oh my God, that was a long time ago. What are some good and bad cases of anthropomorphism in your perspective? Like, when is it good, when is it bad? What are some cases? Well, I should start by saying that, while design can really enhance the anthropomorphism, it doesn't take a lot to get people to treat a robot like it's alive. Over 85% of Roombas have a name, which I don't know the numbers for your regular type of vacuum cleaner, but they're not that high, right? So people will feel bad for the Roomba when it gets stuck. They'll send it in for repair and wanna get the same one back. And that one is not even designed to make you do that. So I think that some of the cases where it's maybe a little bit concerning that anthropomorphism is happening is when you have something that's supposed to function like a tool and people are using it in the wrong way. And one of the concerns is military robots, where, so, gosh, in 2000, like early 2000s, which is a long time ago, iRobot, the Roomba company, made this robot called the Pakbot that was deployed in Iraq and Afghanistan with the bomb disposal units that were there. And the soldiers became very emotionally attached to the robots. And that's fine until a soldier risks his life to save a robot, which you really don't want. But they were treating them like pets. Like they would name them, they would give them funerals with gun salutes. They would get really upset and traumatized when the robot got broken. So in situations where you want a robot to be a tool, in particular, when it's supposed to do a dangerous job that you don't want a person doing, it can be hard when people get emotionally attached to it. That's maybe something that you would want to discourage. Another case for concern is maybe when companies try to leverage the emotional attachment to exploit people. So if it's something that's not in the consumer's interest, trying to sell them products or services or exploit an emotional connection to keep them paying for a cloud service for a social robot or something like that might be, I think that's a little bit concerning as well. Yeah, the emotional manipulation, which probably happens behind the scenes now with some social networks and so on, but making it more explicit. What's your favorite robot? Like a- Fictional or real? No, real. Real robot which you have felt a connection with or not like, not anthropomorphic connection, but I mean like you sit back and say, damn, this is an impressive system. Wow, so two different robots. So the Plio baby dinosaur robot that is no longer sold, that came out in 2007, that one I was very impressed with. But from an anthropomorphic perspective, I was impressed with how much I bonded with it, how much I wanted to believe that it had this inner life. Can you describe Plio? Can you describe what it is? How big is it? What can it actually do? Yeah, Plio is about the size of a small cat. It had a lot of like motors that gave it this kind of lifelike movement. It had things like touch sensors and an infrared camera. So it had all these like cool little technical features, even though it was a toy. And the thing that really struck me about it was that it could mimic pain and distress really well. So if you held it up by the tail, it had a tilt sensor that told it what direction it was facing and it would start to squirm and cry out. If you hit it too hard, it would start to cry. So it was very impressive in design. And what's the second robot that you were, you said there might've been two that you liked? Yeah, so the Boston Dynamics robots are just impressive feats of engineering. Have you met them in person? Yeah, I recently got a chance to go visit. And I was always one of those people who watched the videos and was like, this is super cool, but also it's a product video. Like, I don't know how many times that they had to shoot this to get it right. But visiting them, I'm pretty sure that, I was very impressed, let's put it that way. Yeah, in terms of the control, I think that was a transformational moment for me when I met Spot Mini in person. Because, okay, maybe this is a psychology experiment, but I anthropomorphized the crap out of it. So I immediately, it was like my best friend, right? I think it's really hard for anyone to watch Spot move and not feel like it has agency. Yeah, especially the arm on Spot Mini really obviously looks like a head. They say, no, we didn't mean it that way, but it obviously, it looks exactly like that. And so it's almost impossible to not think of it as almost like the baby dinosaur, but slightly larger. And this movement of the, of course, the intelligence is, their whole idea is that it's not supposed to be intelligent. It's a platform on which you build higher intelligence. It's actually really, really dumb. It's just a basic movement platform. Yeah, but even dumb robots can, like we can immediately respond to them in this visceral way. What are your thoughts about Sophia the robot? This kind of mix of some basic natural language processing and basically an art experiment. Yeah, an art experiment is a good way to characterize it. I'm much less impressed with Sophia than I am with Boston Dynamics. She said she likes you. She said she admires you. Is she, yeah, she followed me on Twitter at some point. Yeah. And she tweets about how much she likes you, so. So what does that mean? I have to be nice or? No, I don't know. See, I was emotionally manipulating you. No, how do you think of the whole thing that happened with Sophia is quite a large number of people kind of immediately had a connection and thought that maybe we're far more advanced with robotics than we are, or actually didn't even think much. I was surprised how little people cared that they kind of assumed that, well, of course AI can do this. Yeah. And then if they assume that, I felt they should be more impressed. Well, people really overestimate where we are. And so when something, I don't even think Sophia was very impressive or is very impressive. I think she's kind of a puppet, to be honest. But yeah, I think people are a little bit influenced by science fiction and pop culture to think that we should be further along than we are. So what's your favorite robots in movies and fiction? WALL-E. WALL-E. What do you like about WALL-E? The humor, the cuteness, the perception control systems operating on WALL-E that makes it all work, just in general? The design of WALL-E the robot. I think that animators figured out, starting in like the 1940s, how to create characters that don't look real, but look like something that's even better than real, that we really respond to and think is really cute. They figured out how to make them move and look in the right way. And WALL-E is just such a great example of that. You think eyes, big eyes, or big something that's kind of eye-ish. So it's always playing on some aspect of the human face, right? Often, yeah. So big eyes. Well, I think one of the first animations to really play with this was Bambi. And they weren't originally gonna do that. They were originally trying to make the deer look as lifelike as possible. They brought deer into the studio and had a little zoo there so that the animators could work with them. And then at some point, they were like, hmm, if we make really big eyes and a small nose and big cheeks, kind of more like a baby face, then people like it even better than if it looks real. Do you think the future of things like Alexa and the home has possibility to take advantage of that, to build on that, to create these systems that are better than real, that create a close human connection? I can pretty much guarantee you, without having any knowledge, that those companies are working on that, on that design behind the scenes. Like, I'm pretty sure. I totally disagree with you. Really? So that's what I'm interested in. I'd like to build such a company. I know a lot of those folks, and they're afraid of that because you don't, how do you make money off of it? Well, but even just like making Alexa look a little bit more interesting than just like a cylinder would do so much. It's an interesting thought, but I don't think people are, from Amazon perspective, are looking for that kind of connection. They want you to be addicted to the services provided by Alexa, not to the device. So the device itself, it's felt that you can lose a lot because if you create a connection, and then it creates more opportunity for frustration, for negative stuff than it does for positive stuff, is I think the way they think about it. That's interesting. I agree that it's very difficult to get right, and you have to get it exactly right, otherwise you wind up with Microsoft's Clippy. Okay, easy now. What's your problem with Clippy? You like Clippy? Is Clippy your friend? Yeah, I miss Clippy. I just talked to, we just had this argument, and they said, Microsoft CTO, and he said he's not bringing Clippy back. They're not bringing Clippy back, and that's very disappointing. I think it was, Clippy was the greatest assistance we've ever built. It was a horrible attempt, of course, but it's the best we've ever done, because it was a real attempt to have like a actual personality. And I mean, it was obviously technology was way not there at the time, of being able to be a recommender system for assisting you in anything, in typing, in Word, or any kind of other application, but it still was an attempt of personality that was legitimate. That's true. Which I thought was brave. Yes, yes, okay. You know, you've convinced me I'll be slightly less hard on Clippy. And I know I have like an army of people behind me who also miss Clippy, so. Really? I wanna meet these people. Who are these people? It's the people who like to hate stuff when it's there, and miss it when it's gone. So everyone. It's everyone, exactly. All right. So Enki and Jibo, the two companies, two amazing companies, social robotics companies, that have recently been closed down. Yes. Why do you think it's so hard to create a personal robotics company? So making a business out of essentially something that people would anthropomorphize, have a deep connection with. Why is it so hard to make it work? Is the business case not there, or what is it? I think it's a number of different things. I don't think it's going to be this way forever. I think at this current point in time, it takes so much work to build something that only barely meets people's minimal expectations. Because of science fiction and pop culture giving people this idea that we should be further than we already are. Like when people think about a robot assistant in the home, they think about Rosie from the Jetsons, or something like that. And Enki and Jibo did such a beautiful job with the design and getting that interaction just right. But I think people just wanted more. They wanted more functionality. I think you're also right that the business case isn't really there because there hasn't been a killer application that's useful enough to get people to adopt the technology in great numbers. I think what we did see from the people who did get Jibo is a lot of them became very emotionally attached to it. But that's not, I mean, it's kind of like the Palm Pilot back in the day. Most people are like, why do I need this? Why would I? They don't see how they would benefit from it until they have it or some other company comes in and makes it a little better. Yeah, like how far away are we, do you think? I mean, how hard is this problem? It's a good question. And I think it has a lot to do with people's expectations and those keep shifting depending on what science fiction that is popular. But also it's two things. It's people's expectation and people's need for an emotional connection. Yeah. And I believe the need is pretty high. Yes, but I don't think we're aware of it. That's right. There's like, I really think this is like the life as we know it. So we've just kind of gotten used to it. I've really, I hate to be dark because I have close friends, but we've gotten used to really never being close to anyone. All right. And we're deeply, I believe, okay, this is hypothesis. I think we're deeply lonely, all of us, even those in deep fulfilling relationships. In fact, what makes those relationships fulfilling, I think, is that they at least tap into that deep loneliness a little bit. But I feel like there's more opportunity to explore that that doesn't interfere with the human relationships you have. It expands more on the, yeah, the rich, deep, unexplored complexity that's all of us weird apes. Okay. I think you're right. Do you think it's possible to fall in love with a robot? Oh yeah, totally. Do you think it's possible to have a long-term, committed, monogamous relationship with a robot? Well, yeah, there are lots of different types of long-term, committed, monogamous relationships. I think monogamous implies like you're not going to see other humans sexually, or like you basically on Facebook have to say, I'm in a relationship with this person, this robot. I just don't, like, again, I think this is comparing robots to humans when I would rather compare them to pets. Like you get a robot, it fulfills, you know, this loneliness that you have in a, maybe not the same way as a pet, maybe in a different way that is even, you know, supplemental in a different way. But, you know, I'm not saying that people won't like, do this, be like, oh, I want to marry my robot, or I want to have like a, you know, sexual relation, monogamous relationship with my robot. But I don't think that that's the main use case for them. But you think that there's still a gap between human and pet. So between a husband and pet, there's a- It's a different relationship. It's an engineering, so that's a gap that can be closed through. I think it could be closed someday, but why would we close that? Like, I think it's so boring to think about recreating things that we already have when we could create something that's different. I know you're thinking about the people who like, don't have a husband and like, what could we give them? Yeah, but let's, I guess what I'm getting at is, maybe not. So like the movie, Her. Yeah. Right, so a better husband. Well, maybe better in some ways. Like it's, I do think that robots are gonna continue to be a different type of relationship, even if we get them like very human looking, or when the voice interactions we have with them feel very like natural and human-like. I think there's still gonna be differences. And there were in that movie too, like towards the end, it kind of goes off the rails. But it's just a movie. So your intuition is that, cause you kind of said two things, right? So one is, why would you want to basically replicate the husband? Yeah. Right? And the other is kind of implying that it's kind of hard to do. So like, anytime you try, you might build something very impressive, but it'll be different. I guess my question is about human nature. It's like, how hard is it to satisfy that role of the husband? So removing any of the sexual stuff aside, is the, it's more like the mystery, the tension, the dance of relationships, you think with robots that's difficult to build? What's your intuition? I think that, well, it also depends on how we're talking about robots now, in 50 years, in like indefinite amount of time, where like- I'm thinking like five to 10 years. Five or 10 years. I think that robots at best will be like, it's more similar to the relationship we have with our pets than relationship that we have with other people. I got it. So what do you think it takes to build a system that exhibits greater and greater levels of intelligence? Like, it impresses us with its intelligence. You know, a Roomba, so you talk about anthropomorphization, that doesn't, I think intelligence is not required. In fact, intelligence probably gets in the way sometimes, like you mentioned. But what do you think it takes to create a system where we sense that it has a human level intelligence? This is something that probably something conversational, human level intelligence. How hard do you think that problem is? It'd be interesting to sort of hear your perspective, not just purely, so I talk to a lot of people, how hard is the conversational agents? How hard is it to pass a Turing test? But my sense is it's easier than just solving, it's easier than solving the pure natural language processing problem, because I feel like you can cheat. Yeah. So yeah, so how hard is it to pass a Turing test in your view? Well, I think, again, it's all about expectation management. If you set up people's expectations to think that they're communicating with, what was it, a 13-year-old boy from the Ukraine? Yeah, that's right, yeah. Then they're not gonna expect perfect English, they're not gonna expect perfect understanding of concepts, or even being on the same wavelength in terms of conversation flow. So it's much easier to pass in that case. Do you think, you kind of alluded this too with audio, do you think it needs to have a body? I think that we definitely have, so we treat physical things with more social agency, because we're very physical creatures. I think a body can be useful. Does it get in the way? Is there a negative aspects like? Yeah, there can be. So if you're trying to create a body that's too similar to something that people are familiar with, like I have this robot cat at home that Hasbro makes, and it's very disturbing to watch because I'm constantly assuming that it's gonna move like a real cat, and it doesn't, because it's like a $100 piece of technology. So it's very disappointing, and it's very hard to treat it like it's alive. So you can get a lot wrong with the body too, but you can also use tricks, same as the expectation management of the 13-year-old boy from the Ukraine. If you pick an animal that people aren't intimately familiar with, like the baby dinosaur, like the baby seal that people have never actually held in their arms, you can get away with much more because they don't have these preformed expectations. Yeah, I remember you, I'm thinking of a TED Talk or something, that clicked for me, that nobody actually knows what a dinosaur looks like. So you can actually get away with a lot more. That was great. So what do you think about consciousness and mortality being displayed in a robot? So not actually having consciousness, but having these kind of human elements that are much more than just the interaction, much more than just, like you mentioned, with a dinosaur moving in interesting ways, but really being worried about its own death and really acting as if it's aware and self-aware and identity. Have you seen that done in robotics? What do you think about doing that? Is that a powerful, good thing? Well, I think it can be a design tool that you can use for different purposes. So I can't say whether it's inherently good or bad, but I do think it can be a powerful tool. The fact that the, you know, Plio mimics distress when you quote-unquote hurt it is a really powerful tool to get people to engage with it in a certain way. I had a research partner that I did some of the empathy work with named Pulasanandi, and he had built a robot for himself that had like a lifespan that would stop working after a certain amount of time just because he was interested in like whether he himself would treat it differently. And we know from, you know, Tamagotchis, those little games that we used to have that were extremely primitive, that like people respond to like this idea of mortality. And, you know, you can get people to do a lot with little design tricks like that. Now, whether it's a good thing depends on what you're trying to get them to do. Have a deeper relationship. Have a deeper connection, sorry, not a relationship. If it's for their own benefit, that sounds great. Okay. You could do that for a lot of other reasons. I see. So what kind of stuff are you worried about? So is it mostly about manipulation of your emotions for like advertisements and so on, things like that? Yeah, or data collection, or, I mean, you could think of governments misusing this to extract information from people. It's, you know, just like any other technological tool, it just raises a lot of questions. If you look at Facebook, if you look at Twitter and social networks, there's a lot of concern of data collection now. What's from the legal perspective or in general, how do we prevent the violation of sort of these companies crossing a line? It's a gray area, but crossing a line, they shouldn't in terms of manipulating, like we're talking about and manipulating our emotion, manipulating our behavior, using tactics that are not so savory. Yeah, it's really difficult because we are starting to create technology that relies on data collection to provide functionality. And there's not a lot of incentive, even on the consumer side to curb that because the other problem is that the harms aren't tangible. They're not really apparent to a lot of people because they kind of trickle down on a societal level and then suddenly we're living in like 1984, which sounds extreme, but that book was very prescient. And I'm not worried about these systems. I have Amazon's Echo at home and tell Alexa all sorts of stuff. And it helps me because Alexa knows what brand of diaper we use and so I can just easily order it again. So I don't have any incentive to ask a lawmaker to curb that. But when I think about that data then being used against low-income people to target them for scammy loans or education programs, that's then a societal effect that I think is very severe and legislators should be thinking about. But yeah, the gray area is the removing ourselves from consideration of explicitly defining objectives and more saying, well, we want to maximize engagement in our social network. And then just, because you're not actually doing a bad thing, it makes sense. You want people to keep a conversation going, to have more conversations, to keep coming back again and again to have conversations. And whatever happens after that, you're kind of not exactly directly responsible. You're only indirectly responsible. So I think it's a really hard problem. Are you optimistic about us ever being able to solve it? You mean the problem of capitalism? It's like, because the problem is that the companies are acting in the company's interests and not in people's interests. And when those interests are aligned, that's great. But the completely free market doesn't seem to work because of this information asymmetry. But it's hard to know how to, so say you were trying to do the right thing. I guess what I'm trying to say is it's not obvious for these companies what the good thing for society is to do. Like, I don't think they sit there and with, I don't know, with a glass of wine and a cat, like petting a cat, evil cat. And there's two decisions, and one of them is good for society, one is good for the profit, and they choose the profit. I think they actually, there's a lot of money to be made by doing the right thing for society. Like that, because Google, Facebook have so much cash that they actually, especially Facebook, would significantly benefit from making decisions that are good for society. It's good for their brand, right? So, but I don't know if they know what's good for society. That's the, I don't think we know what's good for society in terms of how, yeah, how we manage the conversation on Twitter, or how we design, we're talking about robots. Like, should we emotionally manipulate you into having a deep connection with Alexa or not? Yeah, yeah. Do you have optimism that we'll be able to solve some of these questions? Well, I'm gonna say something that's controversial, like in my circles, which is that I don't think that companies who are reaching out to ethicists and trying to create interdisciplinary ethics boards, I don't think that that's totally just trying to whitewash the problem, and so that they look like they've done something. I think that a lot of companies actually do, like you say, care about what the right answer is. They don't know what that is, and they're trying to find people to help them find them. Not in every case, but I think, you know, it's much too easy to just vilify the companies as, like you say, sitting there with their cat going, ha, ha, ha, $1 million. That's not what happens. A lot of people are well-meaning, even within companies. I think that what we do absolutely need is more interdisciplinarity, both within companies, but also within the policy-making space, because we're, you know, we've hurdled into the world where technological progress is much faster, it seems much faster than it was, and things are getting very complex, and you need people who understand the technology, but also people who understand what the societal implications are, and people who are thinking about this in a more systematic way to be talking to each other. There's no other solution, I think. So you've also done work on intellectual property. So if you look at the algorithms that these companies are using, like YouTube, Twitter, Facebook, so on, I mean, that's kind of, those are mostly secretive, the recommender systems behind these algorithms. Do you think about IP and the transparency of algorithms like this? Like what is the responsibility of these companies to open source the algorithms, or at least reveal to the public what's, how these algorithms work? So I personally don't work on that. There are a lot of people who do, though, and there are a lot of people calling for transparency. In fact, Europe's even trying to legislate transparency, maybe they even have at this point, where like if an algorithmic system makes some sort of decision that affects someone's life, that you need to be able to see how that decision was made. I, you know, it's a tricky balance because obviously companies need to have, you know, some sort of competitive advantage and you can't take all of that away, or you stifle innovation. But yeah, for some of the ways that these systems are already being used, I think it is pretty important that people understand how they work. What are your thoughts in general on intellectual property in this weird age of software, AI, robotics? Oh, that it's broken? I mean, the system is just broken. So can you describe, I actually, I don't even know what intellectual property is in the space of software, what it means to, I mean, so I believe I have a patent on a piece of software from my PhD. You believe? You don't know? No, we went through a whole process, yeah, I do. Do you get the spam emails? Like, we'll frame your patent for you. Yeah, it's much like a thesis. So, but that's useless, right? Or not? Where does IP stand in this age? What's the right way to do it? What's the right way to protect and own ideas when it's just code and this mishmash of something that feels much softer than a piece of machinery or an idea? I mean, it's hard because there are different types of intellectual property and they're kind of these blunt instruments. It's like, patent law is like a wrench. Like, it works really well for an industry like the pharmaceutical industry, but when you try and apply it to something else, it's like, I don't know, I'll just hit this thing with a wrench and hope it works. So software, you have a couple different options. Software, like any code that's written down in some tangible form is automatically copyrighted. So you have that protection, but that doesn't do much because if someone takes the basic idea that the code is executing and just does it in a slightly different way, they can get around the copyright. So that's not a lot of protection. Then you can patent software, but that's kind of, I mean, getting a patent costs, I don't know if you remember what yours cost or like, was it through an institution? Yeah, it was through a university. That's why they, it was insane. There were so many lawyers, so many meetings. It made me feel like it must've been hundreds of thousands of dollars. It must've been something crazy. It's insane, the cost of getting a patent. And so this idea of like protecting the like inventor in their own garage, like who came up with a great ideas, kind of, that's the thing of the past. It's all just companies trying to protect things and it costs a lot of money. And then with code, it's oftentimes like, by the time the patent is issued, which can take like five years, probably your code is obsolete at that point. So it's a very, again, a very blunt instrument that doesn't work well for that industry. And so at this point we should really have something better, but we don't. Do you like open source? Yeah, is open source good for society? You think all of us should open source code? Well, so at the Media Lab at MIT, we have an open source default because what we've noticed is that people will come in, they'll like write some code and they'll be like, how do I protect this? And we're like, that's not your problem right now. Your problem isn't that someone's gonna steal your project. Your problem is getting people to use it at all. Like there's so much stuff out there. Like we don't even know if you're gonna get traction for your work. And so open sourcing can sometimes help, get people's work out there, but ensure that they get attribution for it, for the work that they've done. So like I'm a fan of it in a lot of contexts. Obviously it's not like a one size fits all solution. So what I gleaned from your Twitter is you're a mom. I saw a quote, a reference to baby bot. What have you learned about robotics and AI from raising a human baby bot? Well, I think that my child has made it more apparent to me that the systems we're currently creating aren't like human intelligence. Like there's not a lot to compare there. It's just, he has learned and developed in such a different way than a lot of the AI systems we're creating that that's not really interesting to me to compare. But what is interesting to me is how these systems are gonna shape the world that he grows up in. And so I'm like even more concerned about kind of the societal effects of developing systems that rely on massive amounts of data collection, for example. So is he gonna be allowed to use like Facebook or? Facebook is over. Kids don't use that anymore. Snapchat, what do they use, Instagram? Snapchat's over too, I don't know. I just heard that TikTok is over, which I've never even seen, so I don't know. No. We're old, we don't know. I need to, I'm gonna start gaming and streaming my gameplay. So what do you see as the future of personal robotics, social robotics, interaction with other robots? Like what are you excited about if you were to sort of philosophize about what might happen in the next five, 10 years that would be cool to see? Oh, I really hope that we get kind of a home robot that makes it, that's a social robot and not just Alexa. Like it's, you know, I really love the Anki product. I thought Jibo was, had some really great aspects. So I'm hoping that a company cracks that. Me too. So Kate, it was wonderful talking to you today. Likewise, thank you so much. It was fun. Thanks for listening to this conversation with Kate Darling. And thank you to our sponsors, ExpressVPN and Masterclass. Please consider supporting the podcast by signing up to Masterclass at masterclass.com slash Lex and getting ExpressVPN at expressvpn.com slash LexPod. If you enjoy this podcast, subscribe on YouTube, review it with five stars on Apple Podcasts, support it on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some tweets from Kate Darling. First tweet is, the pandemic has fundamentally changed who I am. I now drink the leftover milk in the bottom of the cereal bowl. Second tweet is, I came on here to complain that I had a really bad day and saw that a bunch of you are hurting too. Love to everyone. Thank you for listening. I hope to see you next time.

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Cellular Automata and Rule 30 (Stephen Wolfram) | AI Podcast Clips

So in 2002, you published A New Kind of Science, to which, sort of on a personal level, I can credit my love for cellular automaton and computation in general. I think a lot of others can as well. Can you briefly describe the vision, the hope, the main idea presented in this 1200-page book? Sure, although it took 1200 pages to say in the book. So no, the real idea, it's kind of a good way to get into it is to look at sort of the arc of history and to look at what's happened in kind of the development of science. I mean, there was this sort of big idea in science about 300 years ago that was, let's use mathematical equations to try and describe things in the world. Let's use sort of the formal idea of mathematical equations to describe what might be happening in the world, rather than, for example, just using sort of logical augmentation and so on. Let's have a formal theory about that. And so there'd been this 300-year run of using mathematical equations to describe the natural world, which had worked pretty well. But I got interested in how one could generalize that notion. There is a formal theory, there are definite rules, but what structure could those rules have? And so what I got interested in was, let's generalize beyond the sort of purely mathematical rules, and we now have this sort of notion of programming and computing and so on. Let's use the kinds of rules that can be embodied in programs to as a sort of generalization of the ones that can exist in mathematics as a way to describe the world. And so my kind of favorite version of these kinds of simple rules are these things called cellular automata. And so a typical case, so wait, what are cellular automata? Fair enough. So typical case of a cellular automaton, it's an array of cells. It's just a line of discrete cells. Each cell is either black or white. And in a series of steps that you can represent as lines going down the page, you're updating the color of each cell according to a rule that depends on the color of the cell above it and to its left and right. So it's really simple. So a thing might be, you know, if the cell and its right neighbor are not the same and or the cell on the left is black or something, then make it black on the next step. And if not, make it white, typical rule. That rule, I'm not sure I said it exactly right, but a rule very much like what I just said has the feature that if you started off from just one black cell at the top, it makes this extremely complicated pattern. So some rules, you get a very simple pattern. Some rules, you have the rule is simple, you start them off from a sort of simple seed, you just get this very simple pattern. But other rules, and this was the big surprise when I started actually just doing the simple computer experiments to find out what happens, is that they produce very complicated patterns of behavior. So for example, this rule 30 rule has the feature you started from just one black cell at the top, makes this very random pattern. If you look like at the center column of cells, you get a series of values, you know, it goes back white, black, black, whatever it is. That sequence seems for all practical purposes random. So it's kind of like in math, you know, you compute the digits of pi, 3.1415926, whatever. Those digits once computed, I mean, the scheme for computing pi, you know, it's the ratio of the circumference diameter of a circle, very well defined, but yet when you are, once you've generated those digits, they seem for all practical purposes completely random. And so it is with rule 30, that even though the rule is very simple, much simpler, much more sort of computationally obvious than the rule for generating digits of pi, even with a rule that simple, you're still generating immensely complicated behavior. Yeah, so if we could just pause on that, I think you probably have said it and looked at it so long, you forgot the magic of it, or perhaps you don't, you still feel the magic. But to me, if you've never seen sort of, I would say, what is it? A one dimensional, essentially, coloratometer, right? And you were to guess what you would see if you have some sort of cells that only respond to its neighbors. If you were to guess what kind of things you would see, like my initial guess, like even when I first opened your book, A New Kind of Science, right? My initial guess is you would see, I mean, it would be very simple stuff. Right. And I think it's a magical experience to realize the kind of complexity, you mentioned rule 30, still your favorite cellular automaton? My favorite rule, yes. You get complexity, immense complexity. You get arbitrary complexity. Yes. And when you say randomness down the middle column, that's just one cool way to say that there's incredible complexity. And that's just, I mean, that's a magical idea. However you start to interpret it, all the reducibility discussions, all that, but it's just, I think that has profound philosophical kind of notions around it too. It's not just, I mean, it's transformational about how you see the world. I think for me it was transformational. I don't know, we can have all kinds of discussions about computation and so on, but just, I sometimes think if I were on a desert island and was, I don't know, maybe it was some psychedelics or something, but if I had to take one book and a new kind of science would be it because you could just enjoy that notion. For some reason it's a deeply profound notion, at least to me. I find it that way, yeah. I mean, look, it's been, it was a very intuition-breaking thing to discover. I mean, it's kind of like, you know, you point the computational telescope out there and suddenly you see, I don't know, you know, in the past it's kind of like, you know, moons of Jupiter or something, but suddenly you see something that's kind of very unexpected and Rule 30 was very unexpected for me. And the big challenge at a personal level was to not ignore it. I mean, people, you know, in other words, you might say, you know- The bug? What would you say? Yeah, what would you say? Yeah, I mean, I- What are we looking at, by the way? Well, I was just generating here, I'll actually generate a Rule 30 pattern. So that's the rule for Rule 30. And it says, for example, it says here, if you have a black cell in the middle and black cell to the left and white cell to the right, then the cell on the next step will be white. And so here's the actual pattern that you get starting off from a single black cell at the top there. And then- That's the initial state, initial condition. That's the initial thing. You just start off from that and then you're going down the page. And at every step, you're just applying this rule to find out the new value that you get. And so you might think, Rule that simple, you gotta get the, there's gotta be some trace of that simplicity here. Okay, we'll run it, let's say for 400 steps. It's what it does. It's kind of aliasing a bit on the screen there, but you can see there's a little bit of regularity over on the left, but there's a lot of stuff here that just looks very complicated, very random. And that's a big sort of shock to, was a big shock to my intuition, at least, that that's possible. The mind immediately starts, is there a pattern? There must be a repetitive pattern. Yeah, right. There must be. That's where the mind goes. And so indeed, that's what I thought at first. And I thought, well, this is kind of interesting, but if we run it long enough, we'll see something will resolve into something simple. And I did all kinds of analysis of using mathematics, statistics, cryptography, whatever, to try and crack it. And I never succeeded. And after I hadn't succeeded for a while, I started thinking, maybe there's a real phenomenon here that is the reason I'm not succeeding. Maybe, I mean, the thing that for me was sort of a motivating factor was looking at the natural world and seeing all this complexity that exists in the natural world. The question is, where does it come from? You know, what secret does nature have that lets it make all this complexity that we humans, when we engineer things, typically are not making? We're typically making things that at least look quite simple to us. And so the shock here was, even from something very simple, you're making something that complex. Maybe this is getting at sort of the secret that nature has that allows it to make really complex things, even though its underlying rules may not be that complex. How did it make you feel? If we look at the Newton apple, was there, you know, you took a walk and something, it profoundly hit you, or was this a gradual thing? A lobster being boiled? The truth of every sort of science discovery is it's not that gradual. I mean, I've spent, I happen to be interested in scientific biography kinds of things, and so I've tried to track down, you know, how did people come to figure out this or that thing? And there's always a long kind of sort of preparatory, you know, there's a need to be prepared and a mindset in which it's possible to see something. I mean, in the case of Rule 30, I was around June 1st, 1984, was kind of a silly story in some ways. I finally had a high-resolution laser printer. So I was able, so I thought, I'm gonna generate a bunch of pictures of the accelerometer, and I generate this one, and I put it on some plane flight to Europe, and I have this with me, and it's like, you know, I really should try to understand this. And this is really, you know, this is, I really don't understand what's going on, and that was kind of the, you know, slowly trying to see what was happening. It was not, it was depressingly unsudden, so to speak, in the sense that a lot of these ideas, like principle of computational equivalence, for example, you know, I thought, well, that's a possible thing. I didn't know if it's correct. Still don't know for sure that it's correct, but it's sort of a gradual thing, that these things gradually kind of become, seem more important than one thought. I mean, I think the whole idea of studying the computational universe of simple programs, it took me probably a decade, decade and a half to kind of internalize that that was really an important idea. And I think, you know, if it turns out we find the whole universe lurking out there in the computational universe, that's a good, you know, it's a good brownie point or something for the whole idea. But I think that the thing that's strange in this whole question about, you know, finding this different raw material for making models of things, what's been interesting sort of in the arc of history is, you know, for 300 years, it's kind of like the mathematical equations approach. It was the winner. It was the thing, you know, you want to have a really good model for something that's what you use. The thing that's been remarkable is just in the last decade or so, I think one can see a transition to using not mathematical equations, but programs as sort of the raw material for making models of stuff. And that's pretty neat. And it's kind of, you know, as somebody who's kind of lived inside this paradigm shift, so to speak, it is bizarre. I mean, no doubt in sort of the history of science that will be seen as an instantaneous paradigm shift, but it sure isn't instantaneous when it's played out in one's actual life, so to speak. It seems glacial. And it's the kind of thing where it's sort of interesting because in the dynamics of sort of the adoption of ideas like that into different fields, the younger the field, the faster the adoption typically, because people are not kind of locked in with the fifth generation of people who've studied this field. And it is the way it is, and it can never be any different. And I think that's been, you know, watching that process has been interesting. I mean, I think I'm fortunate that I do stuff mainly because I like doing it. And if I was, that makes me kind of thick-skinned about the world's response to what I do. But that's definitely, you know, and any time you write a book called something like A New Kind of Science, it's kind of the pitchforks will come out for the old kind of science. And it was interesting dynamics. I think that the, I have to say that I was fully aware of the fact that when you see sort of incipient paradigm shifts in science, the vigor of the negative response upon early introduction is a fantastic positive indicator of good long-term results. So in other words, if people just don't care, it's, you know, that's not such a good sign. If they're like, oh, this is great, that means you didn't really discover anything interesting. Um, what fascinating properties of Rule 30 have you discovered over the years? You've recently announced the Rule 30 prizes for solving three key problems. Can you maybe talk about interesting properties that have been kind of revealed, Rule 30 or other cellular automata, and what problems are still before us, like the three problems you've announced? Yeah, yeah, right. So I mean, the most interesting thing about cellular automata is that it's hard to figure stuff out about them. And that's some, in a sense, every time you try and sort of, you try and bash them with some other technique, you say, can I crack them? The answer is they seem to be uncrackable. They seem to have the feature that they are, that they're sort of showing irreducible computation. They're not, you're not able to say, oh, I know exactly what this is going to do. It's going to do this or that. But there's specific formulations of that fact. Yes, right. So I mean, for example, in Rule 30, in the pattern you get just starting from a single black cell, you get this sort of very, very sort of random looking pattern. And so one feature of that, just look at the center column. And for example, we've used that for a long time to generate randomness in Wolfram Language, just, you know, what Rule 30 produces. Now the question is, can you prove how random it is? So for example, one very simple question, can you prove that it'll never repeat? We haven't been able to show that it will never repeat. We know that if there are two adjacent columns, we know they can't both repeat, but just knowing whether that center column can ever repeat, we still don't even know that. Another problem that I sort of put in my collection of, you know, it's like $30,000 for three, you know, for these three prizes for about Rule 30, I would say that this is not one of those, this is one of those cases where the money is not the main point, but it's just, you know, helps motivate somehow the investigation. So there's three problems you propose, you get $30,000 if you solve all three, or maybe, I don't know. No, it's 10,000 for each. For each, right. My- The problem is, that's right, money's not the thing, the problems are themselves, they're just clean formulations of Java. It's just, you know, will it ever become periodic? Second problem is, are there an equal number of black and white cells? Down the middle column. Down the middle column. And the third problem is a little bit harder to state, which is, essentially, is there a way of figuring out what the color of a cell at position T down the center column is, in a, with a less computational effort than about T steps? So in other words, is there a way to jump ahead and say, I know what this is gonna do, you know, it's just some mathematical function of T. Or proving that there is no way. Or proving there is no way. Yes, but both, I mean, you know, for any one of these, one could prove that, you know, one could discover, you know, we know what rule 30 does for a billion steps, but, and maybe we'll know for a trillion steps before too very long. But maybe at a quadrillion steps, it suddenly becomes repetitive. You might say, how could that possibly happen? But so when I was writing up these prizes, I thought, and this is typical of what happens in the computational universe, I thought, let me find an example where it looks like it's just gonna be random forever, but actually it becomes repetitive. And I found one. And it's just, you know, I did a search, I searched, I don't know, maybe a million different rules with some criterion. And this is, what's sort of interesting about that is, I kind of have this thing that I say in a kind of silly way about the computational universe, which is, you know, the animals are always smarter than you are. That is, there's always some way one of these computational systems is gonna figure out how to do something, even though I can't imagine how it's gonna do it. And, you know, I didn't think I would find one that, you know, you would think after all these years that when I found sort of all possible things, funky things, that I would have gotten my intuition wrapped around the idea that, you know, these creatures are always, in the computational universe, are always smarter than I'm gonna be. But, you know. Well, they're equivalently as smart, right? That's correct. And that makes it, that makes one feel very sort of, it's humbling every time. Because every time the thing is, you know, you think it's gonna do this, or it's not gonna be possible to do this, and it turns out it finds a way. Of course, the promising thing is, there's a lot of other rules like Rule 30. It's just Rule 30 is- Oh, it's my favorite, because I found it first, and it's there. But the problems are focusing on Rule 30. It's possible that Rule 30 is repetitive after a trillion steps. It is possible. And that doesn't prove anything about the other rules. It does not. But this is a good sort of experiment of how you go about trying to prove something about a particular rule. Yes, and it also, all these things help build intuition. That is, if it turned out that this was repetitive after a trillion steps, that's not what I would expect. And so, we learn something from that. The method to do that, though, would reveal something interesting about the cellular- No doubt, no doubt. I mean, it's, although it's sometimes challenging, like the, you know, I put out a prize in 2007 for a particular Turing machine that I, that was the simplest candidate for being a universal Turing machine. And the young chap in England named Alex Smith, after a smallish number of months, said, I've got a proof. And he did. You know, it took a little while to iterate, but he had a proof. Unfortunately, the proof is very, it's a lot of micro details. It's not like you look at it and you say, aha, there's a big new principle. The big new principle is the simplest Turing machine that might have been universal actually is universal. And it's incredibly much simpler than the Turing machines that people already knew were universal before that. And so, that, intuitionally, is important because it says computation universality is closer at hand than you might have thought. But the actual methods are not, in that particular case, were not terribly illuminating. It would be nice if the methods would also be elegant. That's true. Yeah, no, I mean, I think it's one of these things where, I mean, it's like a lot of, we've talked about earlier, kind of, you know, opening up AIs and machine learning and things of what's going on inside. And is it just step by step, or can you sort of see the bigger picture more abstractly? It's unfortunate, I mean, with Fermat's last theorem proof, it's unfortunate that the proof to such an elegant theorem is not, I mean, it's not, it doesn't fit into the margins of a page. That's true. But there's no, one of the things is, that's another consequence of computational irreducibility. This fact that there are even quite short results in mathematics whose proofs are arbitrarily long. Yes. That's a consequence of all this stuff. And it makes one wonder, you know, how come mathematics is possible at all? Right. Why is, you know, why is it the case, how have people managed to navigate doing mathematics through looking at things where they're not just thrown into, it's all undecidable? That's its own separate story. And that would be, that would have a poetic beauty to it if people were to find something interesting about rule 30, because, I mean, there's an emphasis to this particular rule. It wouldn't say anything about the broad irreducibility of all computations, but it would nevertheless put a few smiles on people's faces of, yeah. Well, yeah, but to me, it's like, in a sense, establishing principle of computational equivalence, it's a little bit like doing inductive science anywhere. That is, the more examples you find, the more convinced you are that it's generally true. I mean, we don't get to, you know, whenever we do natural science, we say, well, it's true here that this or that happens. Can we prove that it's true everywhere in the universe? No, we can't. So, you know, it's the same thing here. We're exploring the computational universe. We're establishing facts in the computational universe. And that's sort of a way of inductively concluding general things.

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Katherine de Kleer: Planets, Moons, Asteroids & Life in Our Solar System | Lex Fridman Podcast #184

The following is a conversation with Catherine DeCleer, a professor of planetary science and astronomy at Caltech. Her research is on the surface environments, atmospheres, and thermochemical histories of the planets and moons in our solar system. Quick mention of our sponsors, Fundrise, Blinkist, ExpressVPN, and Magic Spoon. Check them out in the description to support this podcast. As a side note, let me say that this conversation and a few others, quite big ones actually, that are coming up were filmed in a studio where I was trying to outsource some of the work. Like all experiments, it was a learning experience for me. It had some positives and negatives. Ultimately, I decided to return back to doing it the way I was doing before, but hopefully with a team who can help me out and work with me long-term. The point is, I will always keep challenging myself, trying stuff out, learning, growing, and hopefully improving over time. My goal is to surround myself with people who love what they do, are amazing at it, and are obsessed with doing the best work of their lives. To me, there's nothing more energizing and fun than that. In fact, I'm currently hiring a few folks to work with me on very small projects. If this is something of interest to you, go to lexfriedman.com slash hiring. That's where I will always post opportunities for working with me. This is the Lex Friedman Podcast, and here is my conversation with Catherine DeCleer. Why is Pluto not a planet anymore? Does this upset you, or has justice finally been served? So I get asked this all the time. I think all planetary scientists get asked about Pluto, especially by kids who would just love for Pluto to still be a planet. But the reality is, when we first discovered Pluto, it was a unique object in the outer solar system, and we thought we were adding a planet to the inventory of planets that we had. And then over time, it became clear that Pluto was not a unique, large object in the outer solar system, that there were actually many of these. And as we started discovering more and more of them, we realized that the concept of Pluto being a planet didn't make sense unless maybe we added all the rest of them as planets. So you could have imagined actually a different direction that this could have gone, where all the other objects that were discovered in that belt, or at least all the ones, let's say, above a certain size, became planets instead of Pluto being declassified. But we're now aware of many objects out there in the outer solar system, and what's called the Kuiper Belt, that are of the same size, or in some cases, even larger than Pluto. So the declassification was really just a realization that it was not in the same category as the other planets in the solar system, and we basically needed to refine our definition in such a way that took into account that there's this belt of debris out there in the outer solar system of things with a range of sizes. Is there a hope for clear categorization of what is a planet and not? Or is it all just gray area? When you study planets, when you study moons, satellites of those planets, is there lines that could be cleanly drawn, or is it just a giant mess? Is it all like a fluid? Let's say not mess, but it's like fluid of what is a planet, what is a moon of a planet, what is debris, what is asteroids, all that kind of? So there are technically clear definitions that were set down by the IAU, the International Astronomy Union. Is it size related? Like what are the parameters based on what? So the parameters are that it has to orbit the sun, which was essentially to rule out satellites. Of course, this was a not very forward-thinking definition because it technically means that all extrasolar planets, according to that definition, are not planets. So it has to orbit the sun. It has to be large enough that its gravity has caused it to become spherical in shape, which also applies to satellites and also applies to Pluto. The third part of the definition is the thing that really rules out everything else, which is that it has to have cleared out its orbital path. And because Pluto orbits in a belt of material, it doesn't satisfy that stipulation. LUKE Why didn't it clear out the path? It's not big enough to knock everybody out of the way? DAVID And this actually is not the first time it has happened. So Ceres, when it was discovered, Ceres is the largest asteroid in the asteroid belt, and it was originally considered a planet when it was first discovered. And it went through exactly the same story, history, where people actually realized that it was just one of many asteroids in the asteroid belt region, and then it got declassified to an asteroid, and now it's back to a dwarf planet. So there is a lot of reclassification. So to me, as somebody who studies solar system objects, I just personally don't care. My level of interest in something has nothing to do with what it's classified as. So my favorite objects in the solar system are all moons. And frequently when I talk about them, I refer to them as planets because to me they are planets. They have volcanoes, they have geology, they have atmospheres, they're planet-like worlds. And so the distinction is not super meaningful to me, but it is important just for having a general framework for understanding and talking about things to have a precise definition. LUIS So you don't have a special romantic, like appreciation of a moon versus a planet versus an asteroid. It's just an object that flies out there and it doesn't really matter what the categorization is. Because there's movies about asteroids and stuff. And then there's movies about the moon, whatever, it's a really good movie. There's something about moons that's almost like an outlier. You think of a moon as a thing that's the secret part, and the planet is like the more vanilla, regular part. None of that? You don't have any of that? TESSA No, I actually do. Satellites, the moons are my favorite things in the solar system. And I think part of what you're saying, I agree from maybe a slightly different perspective, which is from the perspective of exploration. We've spent a lot of time sending spacecraft missions to planets. We had a mission to Jupiter, we had a mission to Saturn. We have plenty of missions to Mars and missions to Venus. I think the exploration of the moons in the outer solar system is the next frontier of solar system exploration. ED The belt of debris, just real quick, that's out there. Is there something incredible to be discovered there? Again, we tend to focus on the planets and the moons, but it feels like there's probably a lot of stuff out there. And it probably, what is it? It's like a garbage collector from outside of the solar system, isn't it? Doesn't it protect from other objects that kind of fly in? And it just feels like it's a cool, you know, when you like walk along the beach and look for stuff and like look for, it feels like that's that kind of place where you can find cool, weird things. Or I guess in our conversation today, when we think about tools and what science is studying, is there something to be studied out there? Or we just don't have maybe the tools yet or there's nothing to be found? MS. ALLAIN There's absolutely a lot to be found. So the material that's out there is remnant material from the formation of our solar system. We don't think it comes from outside the solar system, at least not most of it. But there are so many fascinating objects out there. And I think what you've hit on is exactly right, that we just don't have the tools to study them in detail. But we can look out there and we can see there are different species of ice on their surface that tells us about, you know, the chemical composition of the disk that formed our solar system. Some of these objects are way brighter than they should be, meaning they have some kind of geological activity. People have hypothesized that some of these objects have subsurface oceans. You could even stretch your imagination and say some of those oceans could be habitable. But we can't get very detailed information about them because they're so far away. And so I think if any of those objects were in the inner solar system, it would be studied intently and would be very interesting. So would you be able to design a probe in that, like, very dense debris field, be able to, like, hop from one place to another? Is that just outside of the realm of, like, how would you even design devices or sensors that go out there and take pictures and land? Do you have to land to truly understand a little piece of rock? Or can you understand it from remotely, like fly up close and remotely observe? You can learn quite a lot from just a flyby, and that's all we're currently capable of doing in the outer solar system. The New Horizons mission is a recent example which flew by Pluto, and then they had searched for another object that was out there in the Kuiper belt, any object that was basically somewhere that they could deflect their trajectory to actually fly by. And so they did fly by another object out there in the Kuiper belt, and they take pictures and they do what they can do. And if you've seen the images, and if you've seen the images from that mission of Pluto, you can see just how much detail we have compared to just the sort of reddish dot that we knew of before. So you do get an amazing amount of information, actually, from just essentially a high-speed flyby. It always makes me sad to think about flybys that we might be able to, we might fly by a piece of rock, take a picture, and think, oh, that looks pretty and cool and whatever, and that you could study certain, like composition of the surface and so on. But it's actually teeming with life, and we won't be able to see it at first. And it's sad, because you know, like when you're on a deserted island, you wave your hands and the thing flies by, and you're trying to get their attention, and they probably do the same, well, in their own way, bacteria probably, right? But, and we miss it. I don't know, some reason it makes me, it's the FOMO, it's fear of missing out. It makes me sad that there might be life out there, and we don't, we're not in touch with it. We're not talking. Yeah. Well, okay. So, a sad pause, a Russian philosophical pause. Okay. What are the tools available to us to study planets and their moons? Oh my goodness, that is such a big question. So, among the fields of astronomy, so planetary science, broadly speaking, well, it falls kind of at the border of astronomy, geology, climate science, chemistry, and even biology. So, it's kind of on the border of many things, but part of it falls under the heading of astronomy. And among the things that you can study with telescopes, like solar system moons and planets, the solar system is really unique in that we can actually send spacecraft missions to the objects and study them in detail. And so, I think that's the kind of thing that's the kind of type of tool that people are most aware of, that's most popularized, these amazing NASA missions that either you fly by the object, you orbit the object, you land on the object, potentially you can talk about digging into it, drilling, trying to detect tectonic tremors on its surface. The types of tools that I use are primarily telescopes. And so, my background is in astrophysics. And so, I actually got into solar system science from astronomy, not from a childhood fascination with spacecraft missions, which is actually what a lot of planetary scientists became planetary scientists because of childhood fascination with spacecraft missions, which is kind of interesting for me to talk to people and see that trajectory. I kind of came at it from the fascination with telescopes angle. All right. So, you like telescopes, not rockets, or at least you- When I was a kid, it was looking at the stars and playing with telescopes that really fascinated me. And that's how I got into this. But telescopes, it's amazing how much detail and how much information you can get from telescopes today. You can resolve individual cloud features and watch them kind of sheer out in the atmosphere of Titan. You can literally watch volcanoes on Io change from day to day as the lava flows expand. So, and then, you know, with spectroscopy, you get compositional information on all these things. And it's, when I started doing solar system astronomy, I was surprised by how much detail and how much information you can get even from Earth. And then as well as from orbit, like the Hubble Space Telescope or the James Webb. So, with a telescope, you can, I mean, how much information can you get about volcanoes, about storms, about sort of weather, just so we kind of get a sense, like what a resolution we're talking about? Well, in terms of resolution, so at a, you know, on a given night, if I go and take a picture of Io and it's volcanoes, you can sometimes see at least a dozen different volcanoes. You can see the infrared emission coming off of them and resolve them, separate them from one another on the surface and actually watch how the heat coming off of them changes with time. And I think this time variability aspect is one of the big advantages we get from telescopes. So you send a spacecraft mission there and you get an incredible amount of information over a very short time period. But for some science questions, you need to observe something for 30 years, 40 years. Like, let's say you wanna look at the moon Titan, which has one of the most interesting atmospheres in the solar system. Its orbital period is 29, 30 years. And so if you wanna look at how its atmospheric system and its atmospheric seasons work, you have to observe it over that long of a time period. And you're not gonna do that with a spacecraft, but you can do it with telescopes. Can we just zoom in on certain things like, let's talk about Io, which is the moon of Jupiter. Right. Okay, it's like epic. There's like volcanoes all over the place. It's from a distance, it's awesome. So can you tell me about this moon? And you're sort of a scholar of many planets and moons, but that one kind of stood out to me. So why is that an interesting one? For so many reasons, but Io is the most volcanically active object in the solar system. It has hundreds of active volcanoes on it. It has volcanic plumes that go hundreds of kilometers up above its surface. It puts out more volume of magma per volcano than volcanoes on earth today. But I think to me, the reason that it's most interesting is as a laboratory for understanding planetary processes. So one of the broad goals of planetary science is to put together a sort of more general and coherent framework for how planets work in general. Our current framework, it started out very earth centric. We start to understand how earth volcanoes work. But then when you try to transport that to somewhere like Io that doesn't have an atmosphere, which makes a very tenuous atmosphere, which makes a big difference for how the magma degasses for something that's really small, for something that has a different heat source, for something that's embedded in another object's magnetic field, the kind of intuition we have from earth doesn't apply. And so broadly planetary sciences is trying to broaden that framework so that you have a kind of narrative that all you can understand how each planet became different from every other planet. And I'm already making a mistake. When I say planet, I mean planets and moons. Like I said, I see the moons as planets. As planets. Yeah, I actually already noticed that you didn't introduce Io as the moon of Jupiter. You completely, you kind of ignored the fact that Jupiter exists. It's like, let's focus on the... Yeah. Okay, so, and you also didn't mention Europa, which I think is the... Is that the most famous moon of Jupiter? Is that the one that gets attention because it might have life? Exactly, yeah. But to you, Io is also beautiful. What's the difference between volcanoes on Io versus earth? You said atmosphere makes a difference. What... The heat source plays a big role. So many of the moons in the outer solar system are heated from gravitationally by tidal heating. And I'm happy to describe what that is or not. Well, yeah, please. What's tidal? Yes. So tidal heating is... If you want to understand and contextualize planets and moons, you have to understand their heat sources. So for earth, we have radioactive decay in our interior, as well as residual heat of formation. But for satellites, tidal heating plays a really significant role. And in particular, in driving geological activity on satellites and potentially making those subsurface oceans in places like Europa and Enceladus habitable. And so the way that that works is if you have multiple moons and their orbital periods are integer multiples of one another, that means that they're always encountering each other at the same point in the orbit. So if they were on just random orbits, they'd be encountering each other at random places. And the gravitational effect between the two moons would be canceling out over time. But because they're always meeting each other at the same point in the orbit, those gravitational interactions add up coherently. And so that tweaks them into eccentric orbits. What's an eccentric orbit? So eccentric orbit or elliptical orbit, it just means non-circular. So a deviation from a circular orbit. And that means that for Io or Europa, at some points in their orbit, they're closer to Jupiter. And at some points in the orbit, they're farther away. And so when they're closer, they're stretched out in a sense, but literally just not very stretched out, like a couple hundred meters, something like that. And then when they're farthest away, they're less stretched out. And so you actually have the shape of the object deforming over the course of the orbit. And these orbits are like just a couple of days. And so that in the case of Io, that is literally sufficient friction in its mantle to melt the rock of its mantle. And that's what generates the magma. LUIS That's the source of the magma. TANIA Okay. So why is Europa... I thought there was like ice and oceans underneath kind of thing. So why is Europa not getting the friction? TANIA It is. It's just a little bit farther away from Jupiter. And then Ganymede is also in the orbital resonance. So it's a three-object orbital resonance in the Jupiter system. But we have these sorts of orbital resonances all over the solar system. And also in exoplanets. So for Europa, basically, because it's farther from Jupiter, the effect is not as extreme. But you do still have heat generated in its interior in this way. And that may be driving, could be driving hydrothermal activity at the base of its ocean, which obviously would be a really valuable thing for life. LUIS Cool. So it's like heating up the ocean a little bit. TANIA Heating up the ocean a little bit. And specifically in these like hydrothermal vents where we see really interesting life evolve in the bottom of Earth's oceans. LUIS That's cool. Okay. So what's Io? What else? So we know the source is this friction, but there's no atmosphere. I'm trying to get a sense of what it's like if you and I were to visit Io. Like, what would that look like? What would it feel like? TANIA Is it, is this the entire thing covered in basically volcanoes? LUIS So it's interesting because there's very little atmosphere. The surface is actually really cold, very far below freezing on the surface when you're away from a volcano. But the volcanoes themselves are over a thousand degrees, or the magma when it comes out is over a thousand degrees. And so... LUIS But it does come to the surface, the magma? TANIA It does, yeah. LUIS In particular places. Whoa, that probably looks beautiful. So like, so it's frozen, not ice. Like, what is rock? It's really cold rock. And then you just have this like, what is, what does that look? What would that look like with no atmosphere? Would that, would it be smoke? What does it look like? What is just magma, like just red, yellow, like liquidy things? TANIA It's black. It's black and red, I guess. Like, think of the type of magma that you see in Hawaii. So different types of magma flow in different ways, for example. So in somewhere like Io, the magma is really hot. And so it will flow out in sheets because it has really low viscosity. And I think the lava flows that we've been having in Hawaii over the past couple of years are probably a decent analogy, although Io's magma's lavas are even more fluid and faster moving. LUIS How fast? Like, what, how fast? Like, if you, by the way, sorry, through the telescope, are you tracking at what time scale? Like, every frame is how far apart if you're looking through a telescope? Are we talking about seconds? Are we talking about days, months? When you kind of track, try to get a picture of what the surface might look like, what's the frequency? TANIA So it depends a little bit on what you want to do. Ideally, every night, but you could take a frame every second and see how things are changing. The problem with that is that for things to change on a one second time scale, to actually see something change that fast, you have to have super high resolution. The spatial resolution we have is a couple hundred kilometers. And so things are not changing on those scales over one second, unless you have something really crazy happening. LUIS So if you get a telescope closer to Io, if you get a camera closer to Io, would you be able to understand something? Is that something of interest to you? Would you be able to understand something deeper about these volcanic eruptions and how magma flows and just the, like the rate of the magma? Or is it basically enough to have the kilometer resolution? Do you get a sense? TANIA No way. We want to go there. LUIS You want to go to Io? TANIA I mean, I don't want to go there personally, but I want to send a spacecraft mission there. Absolutely. LUIS Why? Why are you scared? TANIA Why am I scared? LUIS Oh, you mean you don't? TANIA I don't want to go there as a human. LUIS As a human. TANIA I want to send a robot there to look at it. LUIS This is again, everybody's discriminating against robots. This is not, but it's fine. But it's not hospitable to humans in any way. Right. So it's very cold and very hot. TANIA It's very cold. The atmosphere is composed of sulfur dioxide. So you can breathe it. There's no pressure. I mean, it's kind of all the same things you talk about. One talks about Mars only worse. The atmosphere is still a thousand times less dense than Mars is. And the radiation environment is terrible because you're embedded deep within Jupiter's magnetic field. And Jupiter's magnetic field is full of charged particles that have all come out of Io's volcanoes, actually. So Jupiter's magnetic field strips all this material out of Io's atmosphere. And that populates its entire magnetosphere. And then that material comes back around and hits Io and spreads throughout the system. Actually, it's just it's like Io is the massive polluter of the Jupiter system. LUKE Okay, cool. So what does studying Io teach you about volcanoes on Earth or vice versa? Is in the difference of the two, what insights can you mine out? That might be interesting in some way. TANIA Yeah, it's we try to port the tools that we use to study Earth volcanism to Io and it works to some extent, but it is challenging because the situations are so different. And the compositions are really different. When you talk about outgassing, you know, Earth volcanoes outgassed primarily water and carbon dioxide and then sulfur dioxide is the third most abundant gas. And on Io, the water and carbon dioxide are not there. Either it didn't form with them or it lost them. We don't know. And so the chemistry of how the magma outgasses is completely different. But the kind of one to me, most interesting analogy to Earth is that so Io, as I've said, it has these really low viscosity magmas, the lava spreads really quickly across its surface, it can put out massive volumes of magma in relatively short periods of time. And that sort of volcanism is not happening anywhere else in the solar system today. But literally every terrestrial planet and the moon had this, what we call very effusive volcanism early in their history. Okay. So this is almost like a little glimpse into the early history of Earth. Yeah. Okay, cool. So what are the chances that a volcano on Earth destroys all of human civilization? Maybe I wanted to sneak in that question. Yeah, a volcano on Earth. Do you think about that kind of stuff when you just study volcanoes elsewhere? Because isn't it kind of humbling to see something so powerful and so hot, like so unpleasant for humans? And then you realize we're sitting on many of them here. Right. Yeah. Yellowstone as a classic example. I don't know what the chances are of that happening. My intuition would be that the chances of that are lower than the chances of us getting wiped out by some other means. That in the time, that maybe it'll happen eventually that there'll be one of these massive volcanoes on Earth, but we'll probably be gone by then by some other means. Not to sound bleak, but... That's very comforting. Okay. So can we talk about Europa? Is there... So maybe can you talk about the intuition, the hope that people have about life being on Europa, maybe also what are the things we know about it? What are the things to you that are interesting about that particular moon of Jupiter? Sure. Yeah, Europa is from many perspectives, one of the really interesting places in the solar system among the solar system moons. So there are a few... There's a lot of interest in looking for or understanding the potential for life to evolve in the subsurface oceans. I think it's fairly widely accepted that the chances of life evolving on the surfaces of really anything in the solar system is very low. The radiation environment is too harsh and there's just not liquids on the surface of most of these things and it's canonically accepted that liquids are required for life. And so the subsurface oceans, in addition to maybe Titan's atmosphere, the subsurface oceans of the icy satellites are one of the most plausible places in the solar system for life to evolve. Europa and Celadus are interesting because for many of the big satellites, so Ganymede and Callisto, also satellites of Jupiter, also are thought to have subsurface oceans. But they are... So they have these ice shells and then there's an ocean underneath the ice shell. But on those moons, or on Ganymede, we think that there's another ice shell underneath and then there's rock. And the reason that that is a problem for life is that your ocean is probably just pure water because it's trapped between two big shells of ice. So Europa doesn't have this ice shell at the bottom of the ocean, we think. And so the water and rock are in direct interaction. And so that means that you can basically dissolve a lot of material out of the rock. You potentially have this hydrothermal activity that's injecting energy and nutrients for life to survive. And so this rock-water interface is considered really important for the potential habitability. As a small aside, you kind of said that it's canonically assumed that water is required for life. Is it possible to have life like in the volcano? I remember people, like in that National Geographic program or something, kind of hypothesizing that you can really have life anywhere. So as long as there's a source of heat, a source of energy, do you think it's possible to have life in a volcano, like no water? I think anything's possible. I think it's so, water, it doesn't have to be water. That's sort of, you can tell as you identified, I phrased that really carefully. It's canonically accepted that because we recognize that, scientists recognize that we have no idea what broad range of life could be out there. And all we really have is our biases of life as we know it. But for life as we know it, it's very helpful to have, or even necessary to have some kind of liquid and preferably a polar solvent that can actually dissolve molecules, something like water. So the case of liquid methane on Titan is less ideal from that perspective. But you know, liquid magma, if it stays liquid long enough for life to evolve, you have a heat source, you have a liquid, you have nutrients. In theory, that checks your three classic astrobiology boxes. That'd be fascinating. It'd be fascinating if it's possible to detect it easily. How would we detect if there is life on Europa? Is it possible to do in a non-contact way from a distance through telescopes and so on? Or do we need to send robots and do some drilling? I think realistically, you need to do the drilling. There's, so Europa also has these long tectonic features on its surface where it's thought that there's potential for water from the ocean to be somehow making its way up onto the surface. And you could imagine some out there scenario where there's bacteria in the ocean, it's somehow working its way up through the ice shell, it's spilling out on the surface, it's being killed by the radiation, but your instrument could detect some spectroscopic signature of that dead bacterium. But that's, you know, that's many ifs and assumptions. That's a hope because then you don't have to do that much drilling, you can collect from the surface. Right, or even, I'm thinking even remotely. Oh, remotely. Yeah. That's sad that there's a single cell civilization living underneath all that ice trying to get up, trying to get out. So Enceladus gives you a slightly better chance of that because Enceladus is a moon of Saturn and it's broadly similar to Europa in some ways. It's an icy satellite, it has a subsurface ocean that's probably in touch with the rocky interior, but it has these massive geysers at its south pole where it's spewing out material that appears to be originating all the way from the ocean. And so in that case, you could potentially fly through that plume and scoop up that material and hope that at the velocities you'd be scooping it up, you're not destroying anything. You're not destroying any signature of the life you're looking for. But let's say that you have some ingenuity and can come up with a way to do that, it potentially gives you a more direct opportunity at least to try to measure those bacteria directly. Can you tell me a little more on, how do you pronounce it? Enceladus. Enceladus. Can you tell me a little bit more about Enceladus? People have been talking about, way too much about Jupiter. Saturn doesn't get enough love. Saturn doesn't get as much love. So what's Enceladus? Is that the most exciting moon of Saturn? Depends on your perspective. It's very exciting from a astrobiology perspective. I think Enceladus and Titan are the two most unique and interesting moons of Saturn. They definitely both get the most attention also from the life perspective. So what's more likely, Titan or Enceladus for life? If you were to bet all your money in terms of like investing, which to investigate, what are the difference between the two that are interesting to you? Yeah, so the potential for life in each of those two places is very different. So Titan is the one place in the solar system where you might imagine, again, all of this is so speculative, but you might imagine life evolving in the atmosphere. So from a biology perspective, Titan is interesting because it forms complex organic molecules in its atmosphere. It has a dense atmosphere. It's actually denser than Earth's. It's the only moon that has an atmosphere denser than Earth's. It's got tons of methane in it. What happens is that methane gets irradiated. It breaks up and it reforms with other things in the atmosphere. It makes these complex organic molecules and it's effectively doing prebiotic chemistry in the atmosphere. While it's still being freezing cold? Yes. Okay. What would that be like? Would that be pleasant for humans to hang out there? It's just really cold? There's nowhere in the solar system that would be pleasant for humans. It would be cold. You couldn't breathe the air. So colonization wise, if there's an atmosphere, is that a big plus? Or still a ton of radiation? Okay. So Titan, that's a really nice feature that the life could be in the atmosphere because then it might be remotely observable or certainly is more accessible if you visit. So what about Enceladus? So that would be still in the ocean? Right. Enceladus has the advantage, like I said, of spewing material out of its south pole so you could collect it. But it has the disadvantage of the fact that we don't actually really understand how its ocean could stay frozen or sorry, could stay globally liquid over the age of the solar system. And so there are some models that say that it's going through this cyclical evolution where the ocean freezes completely and thaws completely and the orbit sort of oscillates in and out of these eccentricities. And in that case, the potential for life ever occurring there in the first place is a lot lower because if you only have an ocean for 100 million years, is that enough time? And it also means there might be mass extinction events if it does occur. Right. And it just freezes. Again, very sad. This is very depressing. All the slaughter of life elsewhere. How unlikely do you think life is on Earth? So when you look, when you study other planets and you study the contents of other planets, does that give you a perspective on the origin of life on Earth? Which again is full of mystery in itself. Not the evolution, but the origin. The first springing to life, like from nothing to life, from the basic ingredients to life. I guess another way of asking it is how unique are we? Yeah, it's a great question. And it's one that just scientifically we don't have an answer to. We don't even know how many times life evolved on Earth, if it was only once or if it happened independently a thousand times in different places. We don't know whether it's happened anywhere else in the universe, although it feels absurd to believe that we are the only life that evolved in the entire universe, but it's conceivable. We just have just no real information. We don't understand really how life came about in the first place on Earth. I mean, so if you look at the Drake equation, that tries to estimate how many alien civilizations are out there. Scientists have a big part to play in that equation. If you were to bet money in terms of the odds of origins of life on Earth, I mean, this all has to do with how special and unique is Earth. What you land in terms of the number of civilizations has to do with how unique the rare Earth hypothesis is. How rare, special is Earth? How rare and special is the solar system? If you had to bet all your money on a completely unscientific question, well, no, it's actually rigorously scientific. We just don't know a lot of things in that equation. There's a lot of mysteries about that. It's slowly becoming better and better understood in terms of exoplanets, in terms of how many solar systems are out there, where there's planets, there are Earth-like planets. It's getting better and better understood. Makes your sense from that perspective, how many alien civilizations out there? Zero or one plus? You're right that the equation is being better understood, but you're really only talking about the first three parameters in the equation or something. How many stars are there? How many planets per star? Then we're just barely scratching the surface of what fraction of those planets might be habitable. The rest of the terms in the equation are like, how likely is life to evolve given habitable conditions? How likely is it to survive? All these things. There are all these huge unknowns. Actually, I remember when I first saw that equation, I think it was my first year of college and I thought, this is ridiculous. This is A, common sense that didn't need to give a name, and B, just a bunch of unknowns. It's like putting our ignorance together in one equation. Now I understand this equation, it's not something we ever necessarily have the answer to. It just gives us a framework for having the exact conversation we're having right now. I think that's how it was intended in the first place when it was put into writing, was to give people a language to communicate about the factors that go into the potential for aliens to be out there and for us to find them. I would put money on there being aliens. I would not put money on us having definitive evidence of them in my lifetime. Well, definitive is a funny word. My sense is, this is the saddest part for me, is my sense in terms of intelligent alien civilizations, I feel like we're so self-obsessed that we literally would not be able to determine or detect them, even when they're in front of us. Trees could be aliens, but just their intelligence could be realized on a scale, on a time scale or physical scale that we're not appreciating. Trees could be way more intelligent than us. I don't know. It's just a dumb example. It could be rocks, or it could be things like, I love this, this is Dawkins memes. It could be the ideas we have. Where do ideas come from? Where do thoughts come from? Maybe thoughts are the aliens, or maybe thoughts is the actual mechanisms of communication in physics. We think of thoughts as something that springs up from neurons firing. Where the hell did they come from? Now, what about consciousness? Maybe consciousness is the communication. It sounds ridiculous, but we're so self-centered on this space-time communication in physical space using written language, spoken with audio on a time scale that's very specific, on a physical scale that's very specific. I tend to think that bacteria will probably recognize, moving organisms will probably recognize, but when that forms itself into intelligence, most likely it'll be robots of some kind, because we won't be meeting the origins. We'll be meeting the creations of those intelligences. We just would not be able to appreciate it. That's the saddest thing to me. We're too dumb to see aliens. We kind of think, look at the progress of science. We've accomplished so much. The sad thing, it could be that we're just in the first.0001% of understanding anything. It's humbling. I hope that's true, because I feel like we're very ignorant as a species, and I hope that our current level of knowledge only represents the.001% of what we will someday achieve. That actually feels optimistic to me. I feel like that's easier for us to comprehend in the space of biology, and not as easy to comprehend in the space of physics, for example, because we have a sense that... If you talk to theoretical physicists, they have a sense that we understand the basic laws that form the nature of reality of our universe. Physicists are much more confident. Biologists are like, this is a squishy mess. We're doing our best. It would be fascinating to see if physicists themselves would also be humbled by their being like, what the hell is dark matter and dark energy? What the hell is the... Not just the origin, not just the Big Bang, but everything that happened since the Big Bang. A lot of things that happened since the Big Bang, we have no ideas about except basic models of physics. Right. Or what happened before the Big Bang. Yeah. Yeah. What happened before. Or what's happening inside a black hole. Is there a black hole at the center of our galaxy? Can somebody answer this? A super massive black hole. Nobody knows how it started. They seem to be in the middle of all galaxies. That could be a portal for aliens to communicate through consciousness. Okay. All right. Back to planets. What's your favorite, outside of Earth, what's your favorite planet or moon? Maybe outside of the ones... Well, first, have we talked about it already? And then if we did mention it, what's the one outside of that? Oh, gosh. I have to come up with another favorite that's not Io. Oh, Io is the favorite. Oh, absolutely. Why is Io the favorite? I mean, basically everything I've already said. It's just such an amazing and unique object. But on, I guess, a personal note, it's probably the object that made me become a planetary scientist. It's the first thing in the solar system that really deeply captured my interest. And when I started my PhD, I wanted to be an astrophysicist working on things like galaxy evolution. And slowly, I had done some projects in the solar system, but Io was the thing that really caught me into doing solar system science. Okay. Let's leave moons aside. What's your favorite planet? It sounds like you like moons better than planets. So let's... That's accurate. But the planets are fascinating. I think, I find the planets in the solar system really fascinating. What I like about the moons is that there's so much less that is known. There's still a lot more discovery space and the questions that we can ask are still the bigger questions. Gotcha. Which, you know, maybe I'm being unfair to the planets because we're still trying to understand things like, was there ever life on Mars? And that is a huge question and one that we've sent numerous robots to Mars to try to answer. So maybe I'm being unfair to the planets. But there is certainly quite a bit more information that we have about the planets than the moons. But, I mean, Venus is a fascinating object. So I like the objects that lie at the extremes. I think that if we can make a sort of theory or like I've been saying, framework for understanding planets and moons that can incorporate even the most extreme ones, then, you know, those are the things that really test your theory and test your understanding. And so they've always really fascinated me. Not so much the nice habitable places like Earth, but these extreme places like Venus that have sulfuric acid clouds and just incredibly hot and dense surfaces. And Venus, of course, I love volcanism for some reason. And Venus has probably has volcanic activity, definitely has in their recent past, maybe has ongoing today. What do you make of the news? Maybe you can update it in terms of life being discovered in the atmosphere of Venus. Is that sorry? OK, you have an opinion. I can already tell you have opinions. Was that fake news? I got excited when I saw that. What's the what's the final? Is there a life on Venus? So the detection that was reported was the detection of the molecule phosphine. And they said that they tried every other mechanism they could think of to produce phosphine. And they none of no mechanism worked. And then they said, well, we know that life produces phosphine. And so that was sort of the train of logic. And I don't personally believe that phosphine was detected in the first place. OK, so I mean, this is just one study, but I as a layman am skeptical a little bit about tools that sense the contents of an atmosphere like contents of an atmosphere from remotely and making conclusive statements about life. Oh, yeah, well, that connection that you just made, the contents of the atmosphere to the life. Yeah, is is a tricky one. And yeah, I know that that claim received a lot of criticism for the lines of logic that went from detection to to claim of life. Even the detection itself, though, doesn't doesn't meet the sort of historical scientific standards of a detection. It was a very tenuous detection and only one line of the species was detected. And a lot of really complicated data analysis methods had to be applied to even make that weak detection. Yeah. So it could be it could be noise, it could be polluted data, it could be all all those things. I don't know, it doesn't have it doesn't meet the the level of rigor that you would hope. But of course, I mean, we're doing our best. And it's clear that the human species are hopeful to find life. Clearly. Yes. Everyone is so excited about that possibility. All right, let's let me ask you about Mars. So there's a guy named Elon Musk, and he seems to want to take something called Dogecoin there. First of the moon. I'm just kidding about the Dogecoin. I don't even know what the heck is up with that whole. I think humor has power in the 21st century, in a way to spread ideas in the most positive way. So I love that kind of humor, because it makes people smile. But it also kind of sneak, it's like a Trojan horse for cool ideas. You open with humor, and you like the humor is the appetizer, and then the main meal is the science and the engineering. Anyway, do you think it's possible to colonize Mars? Or other planets in the solar system, but we're especially looking to Mars. Is there something about planets that make them very harsh to humans? Or something in particular you think about? And maybe in a high, like big picture perspective, do you have a hope we do, in fact, become a multi planetary species? I do think that if our species survives long enough, and we don't wipe ourselves out or get wiped out by some other means that we will eventually be able to colonize other planets. I do not expect that to happen in my lifetime. I mean, tourists may go to Mars, tourists, people who commit years of their life to go into Mars as a tourist may go to Mars. I don't think that we will colonize it. Is there a sense why it's just too harsh on the environment? Like it's too costly to build something habitable there for a large population? I think that we need to do a lot of work in learning how to use the resources that are on the planet already to do the things we need. So if you're talking about someone going there for a few months, so back up a little bit. There are many things that make Mars not hospitable temperature, you can't breathe the air, you need a pressure suit. Even if you're on the surface, the radiation environment is, you know, even in all those things, the radiation environment is too harsh for the human body. All of those things seem like they could eventually have technological solutions. The challenge, the real significant challenge to me seems to be the creation of a self-sustaining civilization there. You know, you can bring pressure suits, you can bring oxygen to breathe, but those are all in limited supply. And if we're going to colonize it, we need to find ways to make use of the resources that are there to do things like produce food, produce the air that humans need to keep breathing. Just in order to make it self-sustaining, there's a tremendous amount of work that has to be done. And people are working on these problems, but I think that's going to be a major obstacle in going from visiting where we can bring everything we need to survive in the short term to actually colonizing. Yeah, I find that whole project of the human species quite inspiring, these like huge moonshot projects. Somebody, I was reading something in terms of the source of food that may be the most effective on Mars, is you could farm insects. That's the easiest thing to farm. So we'll be eating like cockroaches before living on Mars, because that's the easiest thing to actually, as a source of protein. So growing a source of protein is the easiest thing as insects. I just imagine this giant, for people who are afraid of insects, this is not a pleasant, maybe you're not supposed to even think of it that way. It would be like a cockroach milkshake or something like that. Right. I wonder, have people been working on the genetic engineering of insects to make them more... Radiation friendly? Right. To make them more radiation resistant or whatever, and make them more... What can possibly go wrong? What can cockroaches make them radiation resistant? They're already like survived everything. Plus I took an allergy test in Austin, so everybody's like the allergy levels are super high there. And one of the things apparently, I'm not allergic to any insects except cockroaches. It's hilarious. So maybe, well, I'm going to use that as, you know how people use an excuse that I'm allergic to cats, to not have cats? I'm going to use that as an excuse to not go to Mars as one of the first batch of people. I was going to ask, if you had the opportunity, would you go? Yeah, I'm joking about the cockroach thing. I would definitely go. I love challenges. I love doing things where the possibility of death is not insignificant, because that makes me appreciate it more. Meditating on death makes me appreciate life. And when the meditation on death is forced on you because of how difficult the task is, I enjoy those kinds of things. Most people don't, it seems like. But I love the idea of difficult journeys for no purpose whatsoever, except exploration, going into the unknown, seeing what the limits of the human mind and the human body are. It's like, what the hell else is this whole journey that we're on for? But it could be because I grew up in the Soviet Union. There's a kind of love for space, like the space race, the Cold War created. I don't know if still it permeates American culture as much, but especially with the dad as a scientist, I think I've loved the idea of humans striving out towards the stars, always, like from the engineering perspective. Has been really exciting. I don't know if people love that as much in America anymore. I think Elon is bringing that back a little bit, that excitement about rockets and going out there. But so that's hopeful. For me, I always loved that idea. From an alien scientist perspective, if you were to look back on Earth, is there something interesting you could say about Earth? How would you summarize Earth? Like in a report, like Hitchhiker's Guide to the Galaxy, if you had to report, write a paper on Earth or a letter, like a one pager, summarizing the contents of the surface and the atmosphere, is there something interesting? Do you ever take that kind of perspective on it? I know you like volcanism, so volcanoes, that'll probably be in the report. I was going to say, that's where I was going to go first. There are a few things to say about the atmosphere, but in terms of the volcanoes, so one of the really interesting puzzles to me in planetary science is, so we can look out there and we've been talking about surfaces and volcanoes and atmospheres and things like that, but that is just this tiny little veneer on the outside of the planet. And most of the planet is completely sort of inaccessible to telescopes or to spacecraft missions. You can drill a meter into the surface, but that's still really the veneer. And one of the cool puzzles is looking at what's going on on the surface and trying to figure out what's happening underneath or just any kind of indirect means that you have to study the interior, because you can't dig into it directly, even on Earth, you can't dig deep into Earth. So from that perspective, looking at Earth, one thing that you would be able to tell from orbit given enough time is that Earth has tectonic plates. So you would see that volcanoes follow the edges. If you trace where all the volcanoes are on Earth, they follow these lines that trace the edges of the plates. And similarly, you would see things like the Hawaiian string of volcanoes that you could infer just like we did as people actually living on Earth, that the plates are moving over some plume that's coming up through the mantle. And so you could use that to say, if the aliens could look at where the volcanoes are happening on Earth and say something about the fact that Earth has plate tectonics, which makes it really unique in the solar system. Oh, really? So the other planets don't have plate tectonics? It's the only one that has plate tectonics. Yeah. What about Io and the friction and all that that's not plate tectonics? What's the difference between... Oh, it's plate tectonics, like another layer of like solid rock that moves around and there's cracks? Exactly. So Earth has plates of solid rock sitting on top of a partially molten layer, and those plates are kind of shifting around. On Io, it doesn't have that. And the volcanism is what we call heat pipe volcanism. It's the magma just punches a hole through the crust and comes out on the surface. I mean, that's a simplification, but that's effectively what's happening. Through the freezing cold crust? Yes. Very cold, very rigid crust. Yeah. How does that look like, by the way? I don't think we've mentioned, so the gas that's expelled, if we were to look at it, is it beautiful or is it boring? The gas? Like the whole thing, like the magma punching through the icy... Oh my gosh. Yes, I'm sure it would be beautiful. And the pictures we've seen of it are beautiful. You have... So the magma will come out of the lava, will come out of these fissures, and you have these curtains of lava that are maybe even a kilometer high. So if you looked at videos, I don't know how many volcano videos you've looked at on earth, but you sometimes see a tiny, tiny version of this in Iceland. You see just these sheets of magma coming out of a fissure when you have this really low viscosity magma, sort of water-like coming out at these sheets. And the plumes that come out, because there's no atmosphere, all the plume molecules are just plume particles, where they end up is just a function of the direction that they left the vent. So they're all following ballistic trajectories. And you end up with these umbrella plumes. You don't get these sort of complicated plumes that you have on earth that are occurring because of how that material is interacting with the atmosphere that's there. You just have these huge umbrellas. And it's been hypothesized actually that the atmosphere is made of sulfur dioxide. And that you could have these kind of ash particles from the volcano and the sulfur dioxide would condense onto these particles and you'd have sulfur dioxide snow coming out of these volcanic plumes. And there's not much light though, right? So you wouldn't be able to, like, it would not make a good Instagram photo because you have to, would you see the snow? Sure. There's light. It depends. Oh, okay. So you could, okay. It depends on what angle you're looking at it, where the sun is, all the things like that. You know, the sunlight is much weaker, but it's still there. It's still there. And how big is Io in terms of gravity? Is it smaller? Is it a pretty small moon? It's quite a bit smaller than earth anyway. It's smaller than earth. Okay. Okay, cool. So they float out for a little bit. So the floats, yeah, no, you're right. That would be, that would be, that would be gorgeous. What else about earth is interesting besides volcanoes? So plate tectonics, I didn't realize that that was the unique element of a planet in the solar system. Because that, I wonder what, I mean, we experience as human beings, it's quite painful because of earthquakes and all those kinds of things, but I wonder if there's nice features to it. Yeah. So coming back to habitability again, things like tectonics and plate tectonics are thought to play an important role in the surface being habitable. And that's because you have a way of recycling materials. So if you have a stagnant surface, everything, you know, you use up all the free oxygen, everything reacts until you no longer have reactants that life can extract energy from. And so if nothing's changing on your surface, you kind of reach this stagnation point. But something like plate tectonics recycles material, you bring up new fresh material from the interior, you bring down material that's up on the surface, and that can kind of refresh your nutrient supply in a sense, or the sort of raw materials that the surface has to work with. So from a kind of astrobiologist perspective, looking at Earth, you would see that recycling of material because the plate tectonics, you would also see how much oxygen is in Earth's atmosphere. And between those two things, you would identify Earth as a reasonable candidate for a habitable environment, in addition to, of course, the, you know, pleasant temperature and liquid water. But the abundance of oxygen and the plate tectonics both play a role as well. And also see like tiny dot satellites flying around and rockets. Well, sure, yes. I wonder if they would be able to, I really think about that, like if they, if aliens were to visit, I mean, would they really see humans as the thing they should be focusing on? I think it would take a while, right? Because it's so obvious that that should, because there's like so much incredible, in terms of biomass, humans are a tiny, tiny, tiny fraction. There's like ants. They would probably detect ants, right? Or they probably would focus on the water and the fish. Because there's like a lot of water. I was surprised to learn that there's more species on land than there is in the sea. Like there's 90, I think 90 to 95% of the species are on land. Are on land? Not in the sea. Not in the sea. I thought like there's so much going on in the sea, but no, the variety that like the branches created by evolution, apparently it's probably a good answer from evolutionary biology perspective, why land created so much diversity, but it did. So like the sea, there's so much not known about the sea, about the oceans, but it's not diversity friendly. What can I say? It needs to improve its diversity. What can you say? Do you think the aliens would come? I mean, the first thing they would see is, I suppose, are cities. Assuming that they had some idea of what a natural world looked like, they would see cities and say, these don't belong. Which of these many species created these? Yeah. I mean, if I were to guess, it would... It's a good question. I don't know if you do this when you look at the telescope, whether you look at geometric shapes. If it's... Because to me, hard corners, what do we think is engineered? Things that have kind of straight lines and corners and so on, they will probably detect those in terms of buildings would stand out to them because that goes against the basic natural physics of the world. But I don't know if electricity and lights and so on. It could be. Honestly, it could be the plate tectonics. It could be like, hmm, the volcanoes. That'd be okay. That's a source of heat. And then they would focus. They might literally... I mean, depending on how alien life forms are, they might notice the microorganisms before they notice the big... Notice the ant before the elephant. Because there's a lot more of them, depending what they're measuring. We think size matters, but maybe with their tools of measurement, they would look for quantity versus size. Why focus on the big thing? Focus on the thing that there's a lot of. And when they see humans, depending on their measurement devices, they might see... We're made up of billions of organisms. The fact that we're very human-centric. We think we're one organism, but that may not be the case. They might see, in fact, they might also see a human city as one organism. What is this thing that... Clearly this organism gets aroused at night because the lights go on. And then it sleeps during the day. I don't know. What perspective do you take on the city? Is there something interesting about Earth or other planets in terms of weather patterns? We talked a lot about volcanic patterns. Is there something else about weather that's interesting, like storms or variations in temperature, all those kinds of things? Yeah. So there's sort of... Every planet and moon has a kind of interesting and unique weather pattern, and those weather patterns are really... We don't have a good understanding of them. We don't even have a good understanding of the global circulation patterns of many of these atmospheres, why the storm systems occur. So the composition and occurrence of storms and clouds and these objects is another one of these kind of windows into the interior that I was talking about with surfaces, one of these ways that we can get perspective in what the composition is of the interior and how the circulation is working. So circulation will bring some species up from deeper in the atmosphere of the planet to some altitude that's a little bit colder, and that species will condense out and form a cloud at that altitude. And we can detect in some cases what those clouds are composed of. And looking at where those occur can tell you how the circulation cells are, whether the atmospheric circulation is, say, coming up at the equator and going down at the poles, or whether you have multiple cells in the atmosphere. And I mean, Jupiter's atmosphere is just insane. There's so much going on. You look at these pictures, and there's all these vortices and anti-vortices, and you have these different bands that are moving in opposite directions that may be giving you information about the deep, like deep in the atmosphere, physically deep properties of Jupiter's interior and circulation. What are these vortices? What's the basic material of the storms? It's condensed molecules from the atmosphere, so ammonia ice particles. In the case of Jupiter, it's methane ice. In the case of, let's say, Uranus and Neptune and other species, you can kind of construct a chemical model for which species can condense where. And so you see a cloud at a certain altitude within the atmosphere, and you can make a guess at what that cloud is made of, and sometimes measure it directly. And different species make different colors as well. Oh, cool. Ice storms. Okay. I mean, the climate of Uranus has always been fascinating to me because it orbits on its side, and it has a 42-year orbital period. And so, you know, with Earth, our seasons are because our equator is tipped just a little bit to the plane that we orbit in. So sometimes the sunlight's a little bit above the equator, and sometimes it's a little bit below the equator. But on Uranus, it's like for 10 years, the sunlight is directly on the North Pole, and then it's directly on the equator, and then it's directly on the South Pole. And it's actually kind of amazing that the atmosphere doesn't look crazier than it does. But understanding how, taking again, like one of these extreme examples, if we can understand why that atmosphere behaves in the way it does, it's kind of a test of our understanding of how atmospheres work. So it like heats up one side of the planet for 10 years, and then freezes it the next, and that, you're saying, should probably lead to some chaos. And it doesn't. The fact that it doesn't tells you something about the atmosphere. So atmospheres have a property that surfaces don't have, which is that they can redistribute heat a lot more effectively. Right. So they have a stabilizing, like self-regulating aspect to them, that they're able to deal with extreme conditions. But predicting how that complex system unrolls is very difficult, as we know, about predicting the weather on Earth, even. Oh my goodness. Even with the little variation we have on Earth. You know, people have tried to put together global circulation models. You know, we've done this for Earth. People have tried to do these for other planets as well. And it is a really hard problem. So Titan, for example, like I said, it's one of the best studied atmospheres in the solar system and people have tried to make these global circulation models and actually predict what's going to happen moving into sort of the next season of Titan. And those predictions have ended up being wrong. And so then, you know, I don't know, it's always exciting when a prediction is wrong, because it means that there's something more to learn, like your theory wasn't sufficient. And then you get to go back and learn something by how you have to modify the theory to make it fit. I'm excited by the possibility of one day there'll be for various moons and planets, there'll be like news programs reporting the weather with the fake confidence of like, as if you can predict the weather. We talked quite a bit about planets and moons. Can we talk a little bit about asteroids? For sure. What is, what's an asteroid and what kind of asteroids are there? So the asteroids, let's talk about just the restricted to the main asteroid belt, which is the region, it's a region of debris, basically, between Mars and Jupiter. And the, these sort of belts of debris throughout the solar system, the outer solar system, you know, the Kuiper belt that we talked about, the asteroid belt, as well as certain other populations where they accumulate because they're gravitationally more favored, are remnant objects from the origin of the solar system. And so one of the reasons that we are so interested in them, aside from potentially the fact that they could come hit Earth, but scientifically, it's, it gives us a window into understanding the composition of the material from which Earth and the other planets formed and how that material was kind of redistributed over the history of the solar system. So the asteroids, one could classify them in two different ways. Some of them are ancient objects. So they accreted out of the sort of disk of material that the whole solar system formed out of and have kind of remained ever since, more or less the same. They've probably collided with each other and we see all these collisional fragments. And you can actually look and based on their orbits, say, you know, like these 50 objects originated as the same object. You can see them kind of dynamically moving apart after some big collision. And so some of them are these ancient objects, maybe that have undergone collisions. And then there's this other category of object that is the one that I personally find really interesting, which is remnants of objects that could have been planets. So early on, a bunch of potential planets accreted that we call planetesimals and they formed and they formed with a lot of energy and they had enough time to actually differentiate. So some of these objects differentiated into cores and mantles and crusts. And then they were subsequently distracted in these massive collisions and now we have these fragments, we think fragments floating around the asteroid belt that are like bits of mantle, bits of core, bits of crust, basically. So it's like puzzle pieces that you might be able to stitch together. Or I guess it's all mixed up so you can't stitch together the original planet candidates. Or is that possible to try to see if they kind of, I mean, there's too many objects in there to... I think that there are cases where people have kind of looked at objects and by looking at their orbits, they say these objects should have originated together, but they have very different compositions. And so then you can hypothesize maybe they were different fragments of a differentiated object. But one of the really cool things about this is, you know, we've been talking about getting clues into the interiors of planets. We've never seen a planetary core or deep mantle directly. Some mantle material comes up on our surface and then we can see it, but you know, in sort of in bulk. We haven't seen these things directly and these asteroids potentially give us a chance to like look at what our own core and mantle is like, or at least would be like if it had been also floating through space for a few billion years and getting irradiated and all that. But it's a cool potential window or like analogy into the interior of our own planet. Well, how do you begin studying some of these asteroids? What if you were to put together a study, like what are the interesting questions to ask that are a little bit more specific? Do you find a favorite asteroid that could be tracked and try to track it through telescopes? Or do you, is it has to be, you have to land on those things to study it? So when it comes to the asteroids, there's so many of them and the big pictures or the big questions are answered. So some questions can be answered by zooming in in detail on individual object, but mostly you're trying to do a statistical study. So you want to look at thousands of objects, even hundreds of thousands of objects and figure out what their composition is and look at how many big asteroids there are of this composition versus how many small asteroids of this other composition and put together these kind of statistical properties of the asteroid belt. And those properties can be directly compared with the results of simulations for the formation of the solar system. What do we know about the surfaces of asteroids or the contents of the insides of asteroids and what are still open questions? So I would say that we don't know a whole lot about their compositions. Most of them are small and so you can't study them in such detail with telescopes as you could a planet or moon and at the same time because there are so many of them, you could send a spacecraft to a few, but you can't really get a statistical survey with spacecraft. And so a lot of what has been done comes down to classification. You look at how bright they are, you look at whether they're red or blue, simply whether their spectrum is sloped towards long wavelengths or short wavelengths. There are certain, if you point a spectrograph at their surfaces, there are certain features you can see. So you can tell that some of them have silicates on them. But these are the sort of, they're pretty basic questions. We're still trying to classify them based on fairly basic information in kind of combination with our general understanding of the material the solar system formed from. And so you're coming in with prior knowledge, which is that you more or less know what the materials are the solar system formed from, and then you're trying to classify them into these categories. There's still a huge amount of room for understanding them better and for understanding how their surfaces are changing in the space environment. Is it hard to land on an asteroid? Is this a dumb question? It feels like it would be quite difficult to actually operate a spacecraft in such a dense field of debris. Oh, the asteroid belt. There's a ton of material there, but it's actually not that dense. It is mostly open space. So mentally do picture like mostly open space with some rocks. The problem is some of them are not thought to be solid. So some of these asteroids, especially these core mantle fragments, you can think of as sort of solid like a planet, but some of them are just kind of aggregates of material. We call them rubble piles. And so there's not necessarily... Might look like a rock. Do a lot of them have kind of clouds around them, like a dust cloud thing? Or do you know what you're stepping on when you try to land on it? Like what are we supposed to be visualizing here? There's like very few have water, right? There's some water in the outer part of the asteroid belt, but they're not quite like comets in the sense of having clouds around them. There are some crazy asteroids that do become active like comets. That's the whole other category of thing that we don't understand. But their surfaces, I mean, we have visited some. You can find pictures the spacecraft have taken of them. We've actually scooped up material off of the surface of some of these objects. We're bringing it back to analyze it in the lab. And there's a mission that's launching next year to land on one of these supposedly core fragment objects to try to figure out what the heck it is and what's going on with it. But the surfaces, you can picture a solid surface with some little grains of sand or pebbles on it and occasional boulders, maybe some fine dusty regions, dust kind of collecting in certain places. Do you worry about this? Is there any chance that one of these fellas destroys all of human civilization by an asteroid kind of colliding with something, changing its trajectory and heading its way towards Earth? That is definitely possible. And it doesn't even have to necessarily collide with something and change its trajectory. We're not tracking all of them. We can't track all of them yet. You know, there's still... A lot of them. People are tracking a lot of them and we are doing our best to track more of them. But there are a lot of them out there and it would be potentially catastrophic if one of them impacted Earth. Are you aware of this Apophis object? So there's an asteroid, a near-Earth object called Apophis that people thought had a decent probability of hitting Earth in 2029 and then potentially again in 2036. So they did a lot of studies. It's not actually going to hit Earth, but it is going to come very close. It's going to be visible in the sky in a relatively dark, I mean, not even that dark, probably not visible from Los Angeles. And it's going to come a tenth of the way between the Earth and the Moon. It's going to come closer, apparently, than some geosynchronous communication satellites. Oh, wow. So that is a close call, but people have studied it and apparently are very confident it's not actually going to hit us. But it wasn't. I'm going to have to look into this because I'm very sure, I'm very sure what's going to happen if an asteroid actually hits Earth, that the scientific community and government will confidently say that we have nothing to worry about, it's going to be a close call. And then last minute, they'll be like, there was a miscalculation. They're not lying. It's just like the space of possibilities, because it's very difficult to track these kinds of things. And there's a lot of kind of, there's complexities involved to this. There's a lot of uncertainties. Something tells me that human civilization will end with, we'll see it coming. And then last minute, there'll be a, oops. We'll see it coming and we'll be like, no, this is threatening, but no problem, no problem. And last minute, it'll be like, oops, that was a miscalculation. And then it's all over in a matter of like a week. So, we're just very positive and optimistic today. Is there any chance that Bruce Willis can save us in the sense that from what you know about asteroids, is there something that you can catch them early enough to change volcanic eruptions, right? Sort of drill, put a nuclear weapon inside and break up the asteroid or change its trajectory? There is potential for that if you catch it early enough in advance. I think in theory, if you knew five years in advance, depending on the objects and how close, how much you would need to deflect it, you could deflect it a little bit. I don't know that it would be sufficient in all cases. And this is definitely not my specific area of expertise, but my understanding is that there is something you could do. But it also, how you would carry that out depends a lot on the properties of the asteroid. If it's a solid object versus a rubble pile. So let's say you planted some bomb in the middle of it and it blew up, but it was just kind of a pile of material anyway, and then that material comes back together and then you kind of just have the same thing. Presumably its trajectory would be altered, but it's... It's like Terminator 2, when it's like the thing that just like you shoot it and it splashes and then comes back together. It would be very useless. That's fascinating. What's fascinating, I've gotten a lot of hope from watching SpaceX rockets that land. There's so much, it's like, oh wow, from an AI perspective, from a robotics perspective, wow, we can do a hell of an amazing job with control. But then we have an understanding about surfaces here on earth, we can map up a lot of things. I wonder if we can do that some kind of detail of being able to have that same level of precision in landing on surfaces with as wide of a variety as asteroids have. So be able to understand the exact properties of the surface and be able to encode that into whatever rocket that lands sufficiently to, I presume humans, unlike the movies, humans would likely get in the way. Like it should all be done by robots. Like land, drill, place the explosive, that should all be done through control, through robots. And then you should be able to dynamically adjust to the surface. The flip side of that for a robotics person, I don't know if you've seen these, it's been very heartbreaking. The I know well, Russ Tedrick at MIT led the DARPA Robotics Challenge team for the Humanoid Robot Challenge. For DARPA, I don't know if you've seen videos of robots on two feet falling, but you're talking about millions, several years of work with some of the most brilliant roboticists in the world, millions of dollars. And the final thing is a highlight video on YouTube of robots falling, but they had a lot of trouble with uneven surfaces. That's basically what you have to do with the challenge involves you're mostly autonomous with some partial human communication, but that human communication is broken up. Like you don't get a, you get a noisy channel. So you can, humans can, which is very similar to what it would be like in humans remotely operating a thing on an asteroid. And so with that robots really struggle. There's some hilarious, painful videos of like a robot not able to like open the door and then it tries to open the door without like, it misses the handle and in doing so like falls. I mean, it's painful to watch. So like that there's that, and then there's SpaceX. So I have hope from SpaceX and then I have less hope from Bipedal Robotics. But it's fun to kind of imagine. And I think the planetary side of it comes into play in understanding the surfaces of these asteroids more and more that, you know, forget sort of destruction of human civilization. It'd be cool to have like spacecraft just landing on all these asteroids to study them at scale and being able to figure out dynamically what, you know, whether it's a rubble pile or whether it's a solid objects. Do you see that kind of future of science maybe a hundred, 200, 300 years from now where there's just robots expanding out through the solar system, like sensors essentially, some of it taking pictures from a distance, some of them landing, just exploring and giving us data? Because it feels like we're working with very little data right now. Sure, I do see exploration going that way. I think the way that NASA is currently or historically has been doing missions is putting together these really large missions that do a lot of things and are extremely well tested and have a very low rate of failure. But now that these sort of CubeSat technologies are becoming easier to build, easier to launch, they're very cheap. And, you know, NASA is getting involved in this as well. There's a lot of interest in these missions that are relatively small, relatively cheap and just do one thing so you can really optimize it to just do this one thing. And maybe you could build a hundred of them and send them to different asteroids and they would just collect this one piece of information from each asteroid. It's a kind of different, more distributed way of doing science, I guess. And there's a ton of potential there. I agree. Let me ask you about objects or one particular object from outside our solar system. We don't get to study many of these, right? We don't get stuff that just flies in out of nowhere from outside the solar system and flies through. Apparently there's been two recently in the past few years. One of them is Amoamua. What are your thoughts about Amoamua? So fun to say. Could it be space junk from a distant alien civilization or is this just a weird shaped comet? I like the way that's phrased. So Amoamua is a fascinating object. Just the fact that we have started discovering things that are coming in from outside our solar system is amazing and can start to study them. And now that we have seen some, we can design now, kind of thinking in advance, the next time we see one, we will be much more ready for it. We will know which telescopes we want to point at it. We will have explored whether we could even launch a fast turnaround mission to actually like get to it before it leaves the solar system. In terms of Amoamua, yeah, it's for an object in our solar system, it's really unusual in two particular ways. One is the dimensions that we don't see natural things in our solar system that are kind of long and skinny. The things we see in our solar system don't deviate from spherical by that much. And then that it showed these strange properties of accelerating as it was leaving the solar system, which was not understood at first. So in terms of the alien space junk, you know, as a scientist, I cannot rule out that possibility. I have no evidence to the contrary. However... So you're saying there's a chance. I cannot as a scientist honestly say that I can rule out that it's alien space junk. However, I see the kind of alien explanation as following this, the Sagan's extraordinary claims require extraordinary evidence. If you are going to actually claim that something is aliens, you need to carefully evaluate, one needs to carefully evaluate the other options and see whether it could just be something that we know exists that makes sense. In the case of Amoamua, there are explanations that fit well within our understanding of how things work. There are a couple, there are two hypotheses for what it could be made of. They're both basically just ice shards. In one case, it's a nitrogen ice shard that came off of something like Pluto in another solar system. That Pluto got hit with something and broke up into pieces and one of those pieces came through our solar system. In the other scenario, it's a bit of a failed solar system. So our solar system formed out of a collapsing molecular cloud, sometimes those molecular clouds are not massive enough and they sort of collapse into bits, but they don't actually form a solar system, but you end up with these kind of chunks of hydrogen ice apparently. And so one of those chunks of hydrogen ice could have got ejected and passed through our solar system. So both cases explain these properties in about the same way. So those ices will sublimate once they've passed the sun and so as they're moving away from the sun, you have the hydrogen or nitrogen ice sublimating off the sunward part of it and so that is responsible for the acceleration. The shape also, because you have all this ice sublimating off the surface, if you take something, the analogy that works pretty well here is for a bar of soap. Your bar of soap starts out sort of close to spherical, at least from a physicist's perspective and as you use it over time, you eventually end up with this long thin shard because it's been just by sort of weathering as we would call it. And so in the same way, if you just sublimate material off of one of these ice shards, it ends up long and thin and it ends up accelerating out of the solar system. And so given that these properties can be reasonably well explained that way, we should be extremely skeptical about attributing things to aliens. See, the reason I like to think that it's aliens is because it puts a lot of priority on us not being lazy and we need to catch this thing next time it comes around. I like the idea that there's objects, it almost saddens me, they come out of the darkness really fast and just fly by and go and leave. It just seems like a wasted opportunity not to study them. It's the easiest way to do space travel outside of the solar system, is having the things come to us. Right? I like that way of putting it. And it would be nice to just land on it. And first of all, really importantly, detect it early. And then land on it with a really nice spacecraft and study the hell out of it. And if there's a chance it's aliens, alien life, it just feels like such a cheap way, inexpensive way to get information about alien life or something interesting that's out there. And I'm not sure if a nice shard from another planetary system will be interesting, but it very well could be. It could be totally new sets of materials, it could be, tell us about composition of planets we don't quite understand. And it's just nice when, especially in the case of a Momoa, I guess it was pretty close to Earth, it would have been nice to, you know, it's like, don't go there, they come to us. I don't know. That's what makes me, that's what makes me quite sad. It's a missed opportunity. Well, yeah. And whether you think it's aliens or not, it's a missed opportunity, but we weren't prepared and we will be prepared for the next ones. And as so there's been a movement in astronomy more towards what's called time domain astronomy. So kind of monitoring the whole sky all the time at all wavelengths, that's kind of the goal. And so we expect to detect many more of these in the future, even though these were the first two we saw, our potential to detect them is only increasing with time. And so there will be more opportunities. And you know, based on these two, we now can actually sit and think about what we'll do when the next one shows up. I also, what it made me realize, I know I didn't really think through this, but it made me realize if there is alien civilizations out there, the thing we're most likely to see first would be space junk, my stupid understanding of it. And the second would be really dumb kind of, you could think of maybe like relay nodes or something, objects that you need to have a whole lot of for particular purposes of like space travel and so on, like speed limit signs or something. I don't know, whatever we have on earth, a lot of that's dumb. It's not aliens in themselves. It's like artifacts that are useful to the engineering in the systems that are engineered by alien civilizations. So like we would see a lot of stuff in terms of SETI, in terms of looking for alien life and trying to communicate with it. Maybe we should be looking not for like smart creatures or systems to communicate with. Maybe we should be looking for artifacts or even as dumb as like space junk. It just kind of reframed my perspective of like what are we looking for as signs. There could be a lot of stuff that doesn't have intelligence, but gives us really strong signs that there's somewhere is life or intelligent life. And yeah, that made me kind of, I know it might be dumb to say, but reframe the kind of thing that we should be looking for. Yeah, it's so the benefit of looking for intelligent life is that we perhaps have a better chance of recognizing it. We couldn't necessarily recognize what an alien stop sign looked like. And maybe, you know, the theorists or the people who sort of model and try to understand solar system objects are pretty good at coming up with models for anything. I mean, maybe a muamua was a stop sign, but were clever enough that we could come up with some physical explanations for it. And then, you know, we all want to go with the simplest possible. We all want to believe the sort of most skeptical possible explanation. And so we missed it because we're too good at coming up with alternate explanations for things. And it's such an outlier, such a rare phenomenon that we can't study, you know, 100 or 1000 of these objects. We have to, we had just one. And so the science almost destroys the possibility of something special being there. It's like a Johnny Ive, this designer of Apple. I don't know if you know who that is. He's the lead designer. He's the person who designed the iPhone and all the major things. He talked about, he's brilliant, one of my favorite humans on earth and one of the best designers in the history of earth. He talked about like when he had this origins of an idea, like in his baby stages, he would not tell Steve Jobs because Steve would usually like trample all over it. He would say, this is a dumb idea. And so I sometimes think of the scientific community in that sense, because the weapon of the scientific method is so strong at its best that it sometimes crushes the out of the box outlier evidence. You know, we don't get a lot of that evidence because we don't have, we're not lucky enough to have a lot of evidence. So we have to deal with just special cases. And special cases could present an inkling of something much bigger, but the scientific method user tramples all over. And it's hard to know what to do with that because the scientific method works. But at the same time, every once in a while, it's like a balance. You have to do 99% of the time, you have to do like scientific rigor, but every once in a while, this is not you saying, me saying, smoke some weed and sit back and think, I wonder, you know, it's the Joe Rogan thing. It's entirely possible that it's alien space junk. Anyway. Yeah, I think so. I completely agree. And I think that most scientists do speculate about these things. It's just, at what point do you act on those things? So you're right that the scientific method has inherent skepticism. And for the most part, that's a good thing, because it means that we're not just believing crazy things all the time. But it's an interesting point that requiring that high level of rigor occasionally means that you will miss something that is truly interesting, because you needed to verify it three times, and it wasn't verifiable. I also think like when you communicate with the general public, I think there's power in that 1% speculation of just demonstrating authenticity as a human being, as a curious human being. I think too often, I think this is changing, but I saw, I've been quite disappointed in my colleagues throughout 2020 with the coronavirus. There's too much speaking from authority, as opposed to speaking from curiosity. There's some of the most incredible science has been done in 2020, especially on the virology, biology side. And the kind of being talked down to by scientists is always really disappointing to me, as opposed to inspiring. Like the things we, there's a lot of uncertainty about the coronavirus, but we know a lot of stuff. And we speak from scientists from various disciplines speak from data in the face of that uncertainty. And we're curious, we don't know what the hell is going on. We don't know if this virus is going to evolve, mutate. We don't know if this virus or the next one might destroy all of human civilization. You can't speak with certain, in fact, I was on a survey paper about masks. I don't talk much about it because I don't like politics, but we don't know if masks work, but there's a lot of evidence to show that they work for this particular virus. The transmission of the virus is fascinating, actually. The biomechanics of the way viruses spread is fascinating. If it wasn't destructive, it would be beautiful. And we don't know, but it's inspiring to apply the scientific method to the best of our ability, but also to show that you don't always know everything and to perhaps not about the virus as much, but other things speculate. What if, you know, what if it's the worst case and the best case? And because that's ultimately what we are, descendants of apes that are just curious about the world around us. Yeah, I'll just add to that, not on the topic of masks, but on the topic of curiosity. I mean, I think that's astronomy and planetary sciences, a field are a little are unique because for better and for worse, they don't directly impact humanity. So you know, we're not studying virology to prevent transmission of, you know, illness amongst humans. We're not characterizing volcanoes on Earth that could destroy cities. We, and it really is a more curious and in my opinion, playful scientific field than many. So for better and worse, we can kind of afford to pursue some of the speculation more because human lives are not in danger if we speculate a little bit too freely and get something wrong. Yeah, definitely. In the space of AI, I am worried that we're sometimes too eager, speaking for myself, to like flip the switch to on just to see like what happens. Maybe sometimes we want to be a little bit careful about that, because bad things might happen. Is there books or movies in your life long ago or recently that were inspiring, had an impact on you that you would recommend? Yeah, absolutely. So many that I just don't know where to start with it. So I love reading. I read obsessively. I've been reading fiction and a little bit of nonfiction, but mostly fiction obsessively since I was a child and just never stopped. So I have some favorite books. None of them are easy readings. So I definitely, I mean, I recommend them for somebody who likes an intellectual challenge in the books that they read. So maybe I should go chronologically. I have at least three. I'm not going to go through 50 here. Yeah, I'd love to also like maybe ideas that you took away from, as you mentioned. Yeah, yeah. Why they were so compelling to me. One of the first books that really captured my fascination was Nabokov's book Pale Fire. Are you familiar with it? So I read it actually for a class. It's one of the few books I've ever read for a class that I actually really liked. And the book is, it's in some sense a puzzle. He's a brilliant writer, of course. But the book is like it's formatted like a poem. So there's an introduction, a very long poem and footnotes. And you get partway through it before realizing that the whole thing is actually a novel, unless you sort of read up on it going in. But the whole thing is a novel. And there's a story that slowly reveals itself over the course of all of this. And kind of reveals this just fascinating character, basically, and how his mind works in this story. The idea of a novel also being a kind of intellectual puzzle and something that slowly reveals itself over the course of reading was really fascinating to me. And I have since found a lot more writers like that. In a contemporary example that comes to mind is Kazuo Ishiguro, who's pretty much all of his books are like slow reveals over the course of the book. And like nothing much happens in the books, but you keep reading them because you just want to know like what the reality is that he's slowly revealing to you. The kind of discovery oriented reading maybe. What's the second one? Perhaps my favorite writer is Renier Maria Rilke. Wow. Are you familiar with him? You're hitting hitting ones. I mean, I know in the book of well, but I've never read Pale Fire. But Rilke I've never I know it's a very difficult read. I know that much. Yeah, right. All of these are difficult reads. I think I just I read for in part for an intellectual challenge, but Rilke so he wrote one thing that might be characterizable as a novel, but he wrote a lot of poetry. I mean, he wrote this series of poems called the Duino Elegies that were very impactful for me personally, just emotionally. Which actually it kind of ties in with astronomy in that there's there's a sense, you know, in which we're all going through our lives alone. And there's just this sense of kind of profound loneliness in the existence of every individual human. And I think I was drawn to astronomy in part because the sort of vast spaces, the kind of loneliness and desolateness of space made the sort of internal loneliness feel okay. In a sense, it like gave companionship. And that's how I feel about Rilke's poetry. He turns the kind of desolation and loneliness of human existence into something joyful and almost meaningful. Yeah, there's something about melancholy. I don't know about Rilke in general, but like contemplating the melancholy nature of our of the human condition that makes it okay. I get into from an engineering perspective, think that there is so much loneliness we haven't explored within ourselves yet. And that's my hope is to build AI systems that help us explore our own loneliness. I think that's kind of what love is and friendship is, is somebody who in a very small way helps us explore our own loneliness. Like they listen. We connect like two lonely creatures connect for time. It's like, oh, like acknowledge that we exist together, like for a brief time, but in a somewhat shallow way, I think relative to how much it's possible to truly connect those two consciousnesses. So AI might be able to help on that front. So what's the third one? Actually, I hadn't realized until this moment, but it's yet another one of these kind of slow reveal books. It's a contemporary Russian, I think, Russian American writer named Olga Grushin, G-R-U-S-H-I-N. And she wrote this just phenomenal book called The Dream Life of Sukhonov that I read this year, maybe it was last year for the first time. And it's just a really beautiful, this one you could call a character study, I think, of a Russian father coming to terms with himself and his own past as he potentially slowly loses his mind. Slow reveal. Slow reveal. Well, that's apparent from the beginning. I hope I don't think it's a spoiler. Declining to madness. Spoiler alert. So all of these are really heavy. I don't know. I just I don't have anything lighter to recommend. Pretty gross, the light version of this. Okay. Well, heavy has a certain kind of beauty to it in itself. Is there advice you would give to a young person today that looks up to the stars and wonders what the heck they want to do with their life? So career, science, life in general. You've for now chosen a certain kind of path of curiosity. What insights do you draw from that that you can give us advice to others? I think for somebody, I would not presume to speak to giving people advice on life and humanity overall, but for somebody thinking of being a scientist. So there are a couple of things, one sort of practical thing, which is career wise, I hadn't appreciated this going into science, but you need to. So the questions you're working on and the techniques you use are both of very high importance, maybe equal importance for being happy in your career. If there are questions you're interested in, but the techniques that you need to use to do them are tedious for you, then your job is going to be miserable, even if the questions are inspiring. So you have to find, but if the techniques that you use are things that excite you, then your job is fun every day. So for me, I'm fascinated by the solar system and I love telescopes, and I love doing data analysis, playing with data from telescopes, coming up with new ways to use telescopes. And so that's where I have found that mesh. But if I was interested in the dynamical evolution of the solar system, how the orbits of things evolve, then I would need to do a different type of work that I would just not find as appealing and so it just wouldn't be a good fit. And so it sort of seems like an unromantic thing to have to think about the techniques being the thing you want to work on also, but it really makes a profound difference for I think your happiness in your scientific career. I think that's really profound. It's like the thing, the menial tasks, if you enjoy those, that's a really good sign that that's the right path for you. I think David Foster Wallace said that the key to life is to be unboreable. So basically everything should be exciting. I don't think that's feasible, but you should find an area where everything is exciting. I mean, depending on the day, but you could find the joy in everything, not just the big exciting quote unquote things that everyone thinks is exciting, but the details, the repetitive stuff, the menial stuff, the stuff that takes years, the stuff that involves a lot of failure and all those kinds of things that you find that enjoyable. That's actually really profound to focus on that because people talk about like dreams and passion and goals and so on, the big thing, but that's not actually what takes you there. It takes you there every single day, putting in the hours and that's what actually makes up life is the boring bits. If the boring bits aren't boring, then that's an exciting life. Let me, because when you were talking so romantically and passionately about IO, I remember the poem by Robert Frost. So let me ask you, let me read the poem and ask what your opinion is. It's called Fire and Ice. Oh yeah. I could almost recite this from memory. Some say the world will end in fire, some say in ice. From what I've tasted of desire, hold with those who favor fire. But if I had to perish twice, I think I know enough of hate to say that for destruction, ice is also great and will suffice. So let me ask, if you had to only choose one, would you choose the world to end in fire, in volcanic eruptions, in heat and magma or in ice frozen over? Fire or ice? Fire. Excellent choice. I've always been a fan of chaos and the idea of things just slowly getting cold and stopping and dying is just so depressing to me. So much more depressing than things blowing up or burning or getting covered by a lava flow. So the activity of it endows it with more meaning to me, maybe. I've just now had this vision of you in action films where you're walking away without looking back and there's explosions behind you and you put on shades and then it goes to credits. So, Katherine, this was awesome. I think your work is really inspiring. The kind of things we'll discover about planets in the next few decades is super cool and I hope, I know you said there's probably not life in one of them, but there might be and I hope we discover just that. And perhaps even on Io, within the volcanic eruptions, there's a little creature hanging on that we'll one day discover. Thank you so much for wasting all your valuable time with me today. It was really awesome. Yeah, likewise. Thank you for having me here. Thanks for listening to this conversation with Katherine DeCleer and thank you to Fundrise, Blinkist, ExpressVPN and Magic Spoon. Check them out in the description to support this podcast. And now let me leave you with some words from Carl Sagan. On Titan, the molecules that have been raining down like mana from heaven for the last four billion years might still be there, largely unaltered, deep frozen, awaiting for the chemists from Earth. Thank you for listening and hope to see you next time.

https://youtu.be/85F0FDsPHf8

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Tesla AI Day Highlights | Lex Fridman

Tesla AI day presented the most amazing real-world AI and engineering effort I have ever seen in my life. I wrote this and I meant it. Why was it amazing to me? No, not primarily because of the Tesla bot. It was amazing because I believe the autonomous driving task and the general real-world robotics perception and planning task is a lot harder than people generally think and I also believed the scale of effort in algorithm data annotation simulation inference compute and training compute required to solve these problems is something no one would be able to do in the near term. Yesterday was the first time I saw in one place just the kind and the scale of effort that has a chance to solve this, the autonomous driving problem and the general real-world robotics perception and planning problem. This includes the neural network architecture and pipeline, the autopilot compute hardware in the car, dojo compute hardware for training, the data and the annotation, the simulation for rare edge cases, and yes, the generalized application of all of the above beyond the car robot to the humanoid form. Let's go through the big innovations. The neural network. Each of these is a difficult and I would say brilliant design idea that is either a step or a leap forward from the state-of-the-art in machine learning. First is to predict a vector space, not an image space. This alone is a big leap beyond what is usually done in computer vision that usually operates in the image space in the two-dimensional image. The thing about reality is that it happens out there in the three-dimensional world and it doesn't make sense to be doing all the machine learning on the 2D projections of it onto images. Like many good ideas, this is an obvious one, but a very difficult one. Second is the fusion of camera sensor data before the detections. The detection is performed by the different heads of the multitask neural network. For now, the fusion is at the multi-scale feature level. Again, in retrospect, an obvious but a very difficult engineering step of doing the detection and the machine learning on all of the sensors combined as opposed to doing them individually and combining only the decisions. Third is using video context to model not just vector space, but time. At each frame, concatenating positional encodings, multicam features, and ego kinematics. Using a pretty cool spatial recurrent neural network architecture that forms a 2D grid around the car where each cell of the grid is a RNN, recurrent neural network. The other cool aspect of this is that you can then build a map in the space of RNN features and then perhaps do planning in that space, which is a fascinating concept. Andrzej Karpathy, I think, also mentioned some future improvements performing the fusion earlier and earlier in the neural network. So currently the fusion of space and time are late in the network. Moving the fusion earlier on takes us further toward full end-to-end driving with multiple modalities. Seamlessly fusing, integrating the multiple sources of sensory data. Finally, the place where there's currently, from my understanding, the least amount of utilization of neural networks is planning. So obviously optimal planning in action space is intractable so that you have to come up with a bunch of heuristics. You can do those manually or you could do those through learning. So the idea that was presented is to use neural networks as heuristics in a similar way that neural networks were used as heuristics in the Monte Carlo tree search for mu0 and alpha0 to play different games, to play Go, to play chess. This allows you to significantly prune the search through action space for a plan that doesn't get stuck in the local optima and gets pretty close to the global optima. I really appreciated that the presentation didn't dumb anything down. But maybe in all the technical details, it was easy to miss just how much brilliant innovation that was here. The move to predicting in vector space is truly brilliant. Of course, you can only do that if you have the data and you have the annotation for it. But just to take that step is already taking a step outside the box of the way things are currently done in computer vision. Then fusing seamlessly across many camera sensors, incorporating time into the whole thing in a way that's differentiable with these spatial RNNs, and then of course using that beautiful mess of features both on the individual image side and the RNN side to make plans using neural network architecture for as a heuristic. I mean, all of that is just brilliant. The other critical part of making all of this work is the data and the data annotation. First is the manual labeling. So to make the neural networks that predict in vector space work, you have to label in vector space. So you have to create in-house tools and as it turns out, Tesla hired in-house team of annotators to use those tools to then perform the labeling of vector space and then project it out into the image space. First of all, that saves a lot of work and second of all, that means you're directly performing the annotation in the space in which you're doing the prediction. Obviously, as was always the case, as is the case with self-supervised learning, auto labeling is the key to this whole thing. One of the interesting thing that was presented is the use of clips of data that includes video, IMU, GPS, odometry, and so on for multiple vehicles at the same location in time to generate labels of both the static world and the moving objects and their kinematics. That's really cool. You have these little clips, these buckets of data from different vehicles and they're kind of annotating each other. You're registering them together to then combine a solid annotation of that particular part of road at that particular time. That's amazing because the more the fleet grows, the stronger that kind of auto labeling becomes and the more edge cases you're able to catch that way. Speaking of edge cases, that's what Tesla is using simulation for, is to simulate rare edge cases that are not going to appear often in the data, even when that data set grows incredibly large. Also, they're using it for annotation of ultra complex scenes where accurate labeling of real-world data is basically impossible, like a scene with like a hundred pedestrians, which I think is the example they used. So I honestly think the innovations on the neural network architecture and the data annotation is really just a big leap. Then there's the continued innovation on the autopilot computer side, the neural network compiler that optimizes latency and so on. There's, I think I remember, really nice testing and debugging tools for like variants of candidate trained neural networks to be deployed in the future, where you can compare different neural networks together. That's almost like developer tools for to be deployed neural networks. And it was mentioned that almost 10,000 GPUs are currently being used to continually retrain the network. I forget what the number was, but I think every week or every two weeks the network is fully retrained end to end. The other really big innovation, but unlike the neural network and the data annotation, this is in the future. So to be deployed still, it's still under development, is the dojo computer, which is used for training. So the autopilot computer is the computer on the car that is doing the inference and dojo computer is the thing that you would have in a data center that performs the training of the neural network. There's a, what they're calling a single training tile that is nine flops. It's made up of D1 chips that are built in-house by Tesla. Each chip with super fast I.O. Each tile also with super fast I.O. So you can basically connect an arbitrary number of these together, each with a power supply and cooling. And then I think they connected like a million nodes to have a compute center. I forget what the name is, but it's 1.1 exaflop. So combined with the fact that this can arbitrarily scale, I think this is basically contending to be the world's most powerful neural network training computer. Again, the entire picture that was presented on AI day is amazing because the, what would you call it? The Tesla AI machine can improve arbitrarily through the iterative data engine process of auto labeling plus manual labeling of edge cases. So like that labeling stage plus a data collection, retraining, deploying. And then again, you go back to the data collection, the labeling, retraining and deploying. And you can go through this loop as many times as you want to arbitrarily improve the retrieval. Arbitrarily improve the performance of the network. I still think nobody knows how difficult the autonomous driving problem is. But I also think this loop does not have a ceiling. I still think there's a big place for driver sensing. I still think you have to solve the human robot interaction problem to make the experience more pleasant. But damn it, this loop of manual and auto labeling that leads to retraining, at least the deployment goes back to the data collection and the auto labeling and the manual labeling is incredible. Second reason this whole effort is amazing is that Dojo can essentially become an AI training as a service directly taken on AWS and Google Cloud. So there's no reason it needs to be utilized specifically for the autopilot computer. The simplicity of the way they describe the deployment of PyTorch across these nodes, you can basically use it for any kind of machine learning problem, especially one that requires scale. Finally, the third reason all of this was amazing is that the neural network architecture and data engine pipeline is applicable to much more than just roads and driving. It can be used in the home, in the factory, and by robots, basically any form as long as it has cameras and actuators, including, yes, the humanoid form. As someone who loves robotics, the presentation of a humanoid Tesla bot was truly exciting. Of course, for me personally, the lifelong dream has been to build the mind, the robot that becomes a friend and a companion to humans, not just a servant that performs boring and dangerous tasks. But to me, these two problems should, and I think will be solved in parallel. The Tesla bot, if successful, just might solve the latter problem of perception, movement, and object manipulation. And I hope to play a small part in solving the former problem of human-robot interaction, and yes, friendship. I'm not going to mention love when talking about robots. Either way, all of this, to me, paints a picture of an exciting future. Thanks for watching. Hope to see you next time.

https://youtu.be/ABbDB6xri8o

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Cumrun Vafa: String Theory | Lex Fridman Podcast #204

The following is a conversation with Kamran Vafa, a theoretical physicist at Harvard specializing in string theory. He is the winner of the 2017 Breakthrough Prize in Fundamental Physics, which is the most lucrative academic prize in the world. Quick mention of our sponsors, Headspace, Jordan Harmer-Deschaux, Squarespace, and Allform. Check them out in the description to support this podcast. As a side note, let me say that string theory is a theory of quantum gravity that unifies quantum mechanics and general relativity. It says that quarks, electrons, and all other particles are made up of much tinier strings of vibrating energy. They vibrate in 10 or more dimensions, depending on the flavor of the theory. Different vibrating patterns result in different particles. From its origins, for a long time, string theory was seen as too good not to be true, but has recently fallen out of favor in the physics community, partly because over the past 40 years, it has not been able to make any novel predictions that could then be validated through experiment. Nevertheless, to this day, it remains one of our best candidates for a theory of everything, or a theory that unifies the laws of physics. Let me mention that a similar story happened with neural networks in the field of artificial intelligence, where it fell out of favor after decades of promise and research, but found success again in the past decade as part of the deep learning revolution. So I think it pays to keep an open mind, since we don't know which of the ideas in physics may be brought back decades later and be found to solve the biggest mysteries in theoretical physics. String theory still has that promise. This is the Lex Friedman Podcast, and here's my conversation with Kamran Vafa. What is the difference between mathematics and physics? Well, that's a difficult question, because in many ways, math and physics are unified in many ways. So to distinguish them is not an easy task. I would say that perhaps the goals of math and physics are different. Math does not care to describe reality. Physics does. That's the major difference. But a lot of the thoughts, processes, and so on, which goes to understanding the nature and reality, are the same things that mathematicians do. So in many ways, they are similar. Mathematicians care about deductive reasoning, and physicists or physics in general, we care less about that. We care more about interconnection of ideas, about how ideas support each other, or if there's a puzzle, discord between ideas. That's more interesting for us. And part of the reason is that we have learned in physics that the ideas are not sequential. And if we think that there's one idea which is more important, and we start with there and go to the next idea, next one, and deduce things from that, like mathematicians do, we have learned that the third or fourth thing we deduce from that principle turns out later on to be the actual principle, and from a different perspective, starting from there leads to new ideas, which the original one didn't lead to, and that's the beginning of a new revolution in science. So this kind of thing we have seen again and again in the history of science, we have learned to not like deductive reasoning, because that gives us a bad starting point to think that we actually have the original thought process should be viewed as the primary thought, and all these are deductions, like the way mathematicians sometimes does. So in physics, we have learned to be skeptical of that way of thinking. We have to be a bit open to the possibility that what we thought is a deduction of a hypothesis actually the reason that's true is the opposite, and so we reverse the order. And so this switching back and forth between ideas makes us more fluid about deductive fashion. Of course, it sometimes gives a wrong impression, like physicists don't care about rigor, they just say random things, they are willing to say things that are not backed by the logical reasoning, that's not true at all. So despite this fluidity in seeing which one is a primary thought, we are very careful about trying to understand what we have really understood in terms of relationship between ideas. So that's an important ingredient, and in fact, solid math being behind physics is I think one of the attractive features of a physical law. So we look for beautiful math underpinning it. Can we dig into that process of starting from one place and then ending up at like the fourth step and realizing all along that the place you started at was wrong? So is that happen when there's a discrepancy between what the math says and what the physical world shows? Is that how you then can go back and do the revolutionary idea for different starting place altogether? Perhaps I give an example to see how it goes, and in fact, the historical example is Newton's work on classical mechanics. So Newton formulated the laws of mechanics, you know, the force F equals to ma and his other laws, and they look very simple, elegant, and so forth. Later, when we studied more examples of mechanics and other similar things, physicists came up with the idea that the notion of potential is interesting. Potential was an abstract idea which kind of came, you could take its gradient and relate it to the force, so you don't really need a a priori, but it solved, helped some thoughts. And then later, Euler and Lagrange reformulated Newtonian mechanics in a totally different way in the following fashion. They said if you take, if you wanna know where a particle at this point and at this time, how does it get to this point at the later time, is the following. You take all possible paths connecting this particle from going from the initial point to the final point, and you compute the action, and what is an action? Action is the integral over time of the kinetic term of the particle minus its potential. So you take this integral, and each path will give you some quantity, and the path it actually takes, the physical path, is the one which minimizes this integral or this action. Now, this sounded like a backwards step from Newton's. Newton's formula seemed very simple, F equals to MA, and you can write F is minus the gradient of the potential. So why would anybody start formulating such a simple thing in terms of this complicated looking principle? You have to study the space of all paths and all things and find the minimum, and then you get the same equation, so what's the point? So Euler and Lagrange's formulation of Newton, which was kind of recasting in this language, is just a consequence of Newton's law. F equals to MA gives you the same fact that this path is a minimum action. Now, what we learned later, last century, was that when we deal with quantum mechanics, Newton's law is only an average correct, and the particle going from one to the other doesn't take exactly one path. It takes all the paths with the amplitude, which is proportional to the exponential of the action times an imaginary number, I. And so this fact turned out to be the reformulation of quantum mechanics. We should start there as the basis of the new law, which is quantum mechanics, and Newton is only an approximation on the average correct. When we say amplitude, do you mean probability? Yes, the amplitude means if you sum up all these paths with exponential i times the action, if you sum this up, you get the number, complex number. You square the norm of this complex number, gives you a probability to go from one to the other. Is there ways in which mathematics can lead us astray when we use it as a tool to understand the physical world? Yes, I would say that mathematics can lead us astray as much as all physical ideas can lead us astray. So if you get stuck in something, then you can easily fool yourself that just like the thought process, we have to free ourselves of that. Sometimes math does that role. Like say, oh, this is such a beautiful map. I definitely wanna use it somewhere. And so you just get carried away and you just get maybe carried too far away. So that is certainly true, but I wouldn't say it's more dangerous than old physical ideas. To me, new math ideas is as much potential to lead us astray as old physical ideas, which could be long-held principles of physics. So I'm just saying that we should keep an open mind about the role that math plays, not to be antagonistic towards it and not to over-welcoming it. We should just be open to possibilities. What about looking at a particular characteristics of both physical ideas and mathematical ideas, which is beauty? Do you think beauty leads us astray? Meaning, and you offline showed me a really nice puzzle that illustrates this idea a little bit. Now maybe you can speak to that or another example where beauty makes it tempting for us to assume that the law and the theory we found is actually one that perfectly describes reality. I think that beauty does not lead us astray because I feel that beauty is a requirement for principles of physics. So beauty is fundamental in the universe? I think beauty is fundamental. At least that's the way many of us view it. It's not emergent. It's not emergent. I think Hardy is the mathematician who said that there's no permanent place for ugly mathematics. And so I think the same is true in physics, that if we find a principle which looks ugly, we are not going to be, that's not the end stage. So therefore, beauty is going to lead us somewhere. Now, it doesn't mean beauty is enough. It doesn't mean if you just have beauty, if I just look at something is beautiful, then I'm fine. No, that's not the case. Beauty is certainly a criteria that every good physical theory should pass. That's at least the view we have. Why do we have this view? That's a good question. It is partly, you could say, based on experience of science over centuries, partly is a philosophical view of what reality is or should be. And in principle, it could have been ugly and we might have had to deal with it, but we have gotten maybe confident through examples after examples in the history of science to look for beauty. And our sense of beauty seems to incorporate a lot of things that are essential for us to solve some difficult problems, like symmetry. We find symmetry beautiful and the breaking of symmetry beautiful. Somehow, symmetry is a fundamental part of how we conceive of beauty at all layers of reality, which is interesting. In both the visual space, where we look at art, we look at each other as human beings, the way we look at creatures in the biological space, the way we look at chemistry, and then to the physics world as the work you do. It's kind of interesting. It makes you wonder, like, which one is the chicken or the egg? Is symmetry the chicken in our conception of beauty, the egg, or the other way around? Or somehow, the fact that the symmetry is part of reality, it somehow creates a brain that then is able to perceive it? Or maybe this is just because we, maybe it's so obvious, it's almost trivial, that symmetry, of course, will be part of every kind of universe that's possible. And then, any kind of organism that's able to observe that universe is going to appreciate symmetry. Well, these are good questions. We don't have a deep understanding of why we get attracted to symmetry. Why do laws of nature seem to have symmetries underlying them? And the reasoning, the examples of whether, if it wasn't symmetric, we would have understood it or not. We could have said that, yeah, if there were things which didn't look that great, we could understand them. For example, we know that symmetries get broken, and we have appreciated nature in the broken symmetry phase as well. The world we live in has many things which do not look symmetric, but even those have underlying symmetry when you look at it more deeply. So, we have gotten maybe spoiled, perhaps, by the appearance of symmetry all over the place, and we look for it. And I think this is perhaps related to the sense of aesthetics that scientists have, and we don't usually talk about it among scientists. In fact, it's kind of a philosophical view of why do we look for simplicity or beauty or so forth. And I think, in a sense, scientists are a lot like philosophers. Sometimes, I think, especially modern science seems to shun philosophers and philosophical views, and I think at their peril. I think, in my view, science owes a lot to philosophy, and, in my view, many scientists, in fact, probably all good scientists, are perhaps amateur philosophers. They may not state that they are philosophers, or they may not like to be labeled philosophers, but in many ways, what they do is philosophical takes of things. Looking for simplicity or symmetry is an example of that, in my opinion, or seeing patterns. You see, for example, another example of the symmetry is like how you come up with new ideas in science. You see, for example, an idea A is connected with an idea B. Okay, so you study this connection very deeply, and then you find the cousin of an idea A, let me call it A prime, and then you immediately look for B prime. If A is like B, and if there's an A prime, then you look for B prime. Why? Because it completes the picture. Why? Well, it's philosophically appealing to have more balance in terms of that, and then you look for B prime, and lo and behold, you find this other phenomenon, which is a physical phenomenon, which you call B prime. So this kind of thinking motivates asking questions and looking for things, and it has guided scientists, I think, through many centuries and I think it continues to do so today. And I think if you look at the long arc of history, I suspect that the things that will be remembered is the philosophical flavor of the ideas of physics and chemistry and computer science and mathematics. Like, I think the actual details will be shown to be incomplete or maybe wrong, but the philosophical intuitions will carry through much longer. There's a sense in which, if it's true that we haven't figured out most of how things work, currently, that it'll all be shown as wrong and silly, it'll almost be a historical artifact. But the human spirit, whatever, like the longing to understand the way we perceive the world, the way we conceive of it, of our place in the world, those ideas will carry on. I completely agree. In fact, I believe that almost, well, I believe that none of the principles or laws of physics we know today are exactly correct. All of them are approximations to something. They're better than the previous versions that we had, but none of them are exactly correct and none of them are gonna stand forever. So I agree that that's the process we are heading, we are improving, and yes, indeed, the thought process and that philosophical take is common. So when we look at older scientists, or maybe even all the way back to Greek philosophers and the things that the way they thought and so on, almost everything they said about nature was incorrect. But the way they thought about it and many things that they were thinking is still valid today. For example, they thought about symmetry breaking. They were trying to explain the following. This is a beautiful example, I think. They had figured out that the Earth is round and they said, okay, Earth is round. They have seen the length of the shadow of a meter stick and they have seen that if you go from the equator upwards north, they find that depending on how far away you are, that the length of the shadow changes and from that they had even measured the radius of the Earth to good accuracy. That's brilliant, by the way, the fact that they did that. Very brilliant, very brilliant. So these Greek philosophers are very smart. And so they had taken it to the next step. They asked, okay, so the Earth is round, why doesn't it move? They thought it doesn't move. They were looking around, nothing seemed to move. So they said, okay, we have to have a good explanation. It wasn't enough for them to be there. So they really wanna deeply understand that fact and they come up with a symmetry argument. And the symmetry argument was, oh, if the Earth is a spherical, it must be at the center of the universe for sure. So they said the Earth is at the center of the universe. That makes sense. And they said, you know, if the Earth is going to move, which direction does it pick? Any direction it picks, it breaks that spherical symmetry because you have to pick a direction and that's not good because it's not symmetrical anymore. So therefore, the Earth decides to sit put because it would break the symmetry. So they had the incorrect science. They thought Earth doesn't move and they, but they had this beautiful idea that symmetry might explain it. But they were even smarter than that. Aristotle didn't agree with this argument. He said, why do you think symmetry prevents it from moving? Because the preferred position? Not so. He gave an example. He said, suppose you are a person and we put you at the center of a circle and we spread food around you on a circle around you, loaves of bread, let's say. And we say, okay, stay at the center of the circle forever. Are you going to do that just because of the symmetric point? No, you are going to get hungry. You're going to move towards one of those loaves of bread despite the fact that it breaks the symmetry. So from this way, he tried to argue being at the symmetric point may not be the preferred thing to do. And this idea of spontaneous symmetry breaking is something we just use today to describe many physical phenomena. So spontaneous symmetry breaking is the feature that we now use. But this idea was there thousands of years ago, but applied incorrectly to the physical world, but now we are using it. So these ideas are coming back in different forms. So I agree very much that the thought process is more important and these ideas are more interesting than the actual applications that people may find today. Did they use the language of symmetry and the symmetry breaking and spontaneous symmetry? But that's really interesting. Because I could see a conception of the universe that kind of tends towards perfect symmetry and is stuck there. Like, not stuck there, but achieves that optimal and stays there. The idea that you would spontaneously break out of symmetry, like have these perturbations, jump out of symmetry and back. That's a really difficult idea to load into your head. Like, where does that come from? And then the idea that you may not be at the center of the universe. That is a really tough idea. Right, so symmetry sometimes is an explanation of being at the symmetric point is sometimes a simple explanation of many things. Like, if you have a ball, circular ball, then the bottom of it is the lowest point. So if you put a pebble or something, it will slide down and go there at the bottom and stays there at the symmetric point, because the preferred point, the lowest energy point. But if that same symmetric circular ball that you had had a bump on the bottom, the bottom might not be at the center, it might be on a circle on the table. In which case, the pebble would not end up at the center, it would be the lower energy point. Symmetrical, but it breaks the symmetry once it picks a point on that circle. So we can have symmetry reasoning for where things end up, or symmetry breakings, like this example would suggest. We talked about beauty. I find geometry to be beautiful. You have a few examples that are geometric in nature in your book. How can geometry in ancient times or today be used to understand reality? And maybe, how do you think about geometry as a distinct tool in mathematics and physics? Yes, geometry is my favorite part of math as well. And Greeks were enamored by geometry. They tried to describe physical reality using geometry and principles of geometry and symmetry. Platonic solids, the five solids they had discovered, had these beautiful solids. They thought it must be good for some reality. They must be explaining something. They attached one to air, one to fire, and so forth. They tried to give physical reality to symmetric objects. These symmetric objects are symmetries of rotation and discrete symmetry groups, we call today, of rotation group in three dimensions. Now, we know now, we kind of laugh at the way they were trying to connect that symmetry to the laws of the realities of physics. But actually, it turns out, in modern days, we use symmetries in not too far away, exactly in these kind of thought processes in the following way. In the context of string theory, which is the field light study, we have these extra dimensions. And these extra dimensions are compact, tiny spaces, typically, but they have different shapes and sizes. We have learned that if these extra shapes and sizes have symmetries which are related to the same rotation symmetries that the Greek were talking about, if they enjoy those discrete symmetries, and if you take that symmetry and quotient the space by it, in other words, identify points under these symmetries, you get properties of that space at the singular points which force emanates from them. What forces? Forces like the ones we have seen in nature today, like electric forces, like strong forces, like weak forces. So these same principles that were driving them to connect geometry and symmetries to nature is driving today's physics, now much more modern ideas, but nevertheless, the symmetries connecting geometry to physics. In fact, often we sometimes we have, we ask the following question, suppose I want to get this particular physical reality, I wanna have this particles with these forces and so on, what do I do? It turns out that you can geometrically design the space to give you that. You say, oh, I put the sphere here, I will do this, I will shrink them. So if you have two spheres touching each other and shrinking to zero size, that gives you strong forces. If you have one of them, it gives you the weak forces. If you have this, you get that. And if you want to unify forces, do the other thing. So these geometrical translation of physics is one of my favorite things that we have discovered in modern physics in the context of strength theory. The sad thing is when you go into multiple dimensions and we'll talk about it is we start to lose our capacity to visually intuit the world we're discussing. And then we go into the realm of mathematics and we'll lose that. Unfortunately, our brains are such that we're limited. But before we go into that mysterious, beautiful world, let's take a small step back. And you also in your book have this kind of, through the space of puzzles, through the space of ideas, have a brief history of physics, of physical ideas. Now, we talked about Newtonian mechanics, are leading all through different Lagrangian, Hamiltonian mechanics. Can you describe some of the key ideas in the history of physics, maybe lingering on each from electromagnetism to relativity to quantum mechanics and to today as we'll talk about with quantum gravity and strength theory? Sure, so I mentioned the classical mechanics and the Euler-Lagrange formulation. One of the next important milestones for physics were the discoveries of laws of electricity and magnetism. So Maxwell put the discoveries all together in the context of what we call the Maxwell's equations. And he noticed that when he put these discoveries that Faraday's and others had made about electric and magnetic phenomena in terms of mathematical equations, it didn't quite work. There was a mathematical inconsistency. Now, one could have two attitudes. One would say, okay, who cares about math? I'm doing nature, electric force, magnetic force, math I don't care about. But it bothered him. It was inconsistent. The equations he were writing, the two equations he had written down did not agree with each other. And this bothered him. But he figured out, if you add this jiggle, this equation by adding one little term there, it works. At least it's consistent. What is the motivation for that term? He said, I don't know. Have we seen it in experiments? No. Why did he add it? Well, because of mathematical consistency. So he said, okay, math forced him to do this term. He added this term, which we now today call the Maxwell term. And once he added that term, his equations were nice, differential equations, mathematically consistent, beautiful, but he also found a new physical phenomena. He found that because of that term, he could now get electric and magnetic waves moving through space at a speed that he could calculate. So he calculated the speed of the wave. And lo and behold, he found it's the same as the speed of light, which puzzled him because he didn't think light had anything to do with electricity and magnetism. But then he was courageous enough to say, well, maybe light is nothing but these electric and magnetic fields moving around. And he wasn't alive to see the verification of that prediction, and indeed it was true. So this mathematical inconsistency, which we could say, this mathematical beauty drove him to this physical, very important connection between light and electric and magnetic phenomena, which was later confirmed. So then physics progresses and it comes to Einstein. Einstein looks at Maxwell's equation, says, beautiful, these are nice equation, except we get one speed light. Who measures this light speed? And he asked the question, are you moving? Are you not moving? If you move, the speed of light changes, but Maxwell's equation has no hint of different speeds of light. It doesn't say, oh, only if you're not moving, you get the speed. It's just you always get the speed. So Einstein was very puzzled and he was daring enough to say, well, you know, maybe everybody gets the same speed for light. And that motivated his theory of special relativity. And this is an interesting example, because the idea was motivated from physics, from Maxwell's equations, from the fact that people tried to measure the properties of ether, which was supposed to be the medium in which the light travels through. And the idea was that only in that medium, the speed of, if you're at rest with respect to the ether, the speed of light, then if you're moving, the speed changes. And people did not discover it. Michelson and Morley's experiments showed there is no ether. So then Einstein was courageous enough to say, you know, light is the same speed for everybody, regardless of whether you're moving or not. And the interesting thing is about special theory of relativity is that the math underpinning it is very simple. It's linear algebra, nothing terribly deep. You can teach it at high school level, if not earlier. Okay, does that mean Einstein's special relativity is boring? Not at all. So this is an example where simple math, you know, linear algebra, leads to deep physics. Einstein's theory of special relativity, motivated by this inconsistency of Maxwell's equation would suggest for the speed of light, depending on who observes it. What's the most daring idea there, that the speed of light could be the same everywhere? That's the basic, that's the guts of it. That's the core of Einstein's theory. That statement underlies the whole thing. Speed of light is the same for everybody, it's hard to swallow, and it doesn't sound right. It sounds completely wrong on the face of it. And it took Einstein to make this daring statement. It would be laughing in some sense. How could anybody make this possibly ridiculous claim? And it turned out to be true. How does that make you feel? Because it still sounds ridiculous. It sounds ridiculous until you learn that our intuition is at fault about the way we conceive of space and time. The way we think about space and time is wrong, because we think about the nature of time as absolute. And part of it is because we live in a situation where we don't go with very high speeds, that our speeds are small compared to the speed of light, and therefore the phenomena we observe does not distinguish the relativity of time. The time also depends on who measures it. There's no absolute time. When you say it's noon today now, it depends on who's measuring it, and not everybody would agree with that statement. And to see that, you would have to have fast observer moving close to the speed of light. So this shows that our intuition is at fault. And a lot of the discoveries in physics precisely is getting rid of the wrong old intuition. And it is funny, because we get rid of it, but it always lingers in us in some form. Like even when I'm describing it, I feel like a little bit like, isn't it funny? As you're just feeling the same way. It is, it is. But we kind of replace it by an intuition. And actually there's a very beautiful example of this, how physicists do this, try to replace their intuition. And I think this is one of my favorite examples about how physicists develop intuition. It goes to the work of Galileo. So again, let's go back to Greek philosophers, or maybe Aristotle in this case. Now again, let's make a criticism. He thought that objects, the heavier objects fall faster than the lighter objects. Makes sense. It kind of makes sense. And people say about the feather and so on, but that's because of the air resistance. But you might think like if you have a heavy stone and a light pebble, the heavy one will fall first. If you don't do any experiments, that's the first gut reaction. I would say, everybody would say that's the natural thing. Galileo did not believe this, and he kind of did the experiment. Famously it said he went on the top of Pisa Tower and he dropped these heavy and light stones and they fell at the same time when he dropped it at the same time, from the same height. Okay, good. So he said, I'm done. I've showed that the heavy and lighter objects fall at the same time, I did the experiment. Scientists at that time did not accept it. Why was that? Because at that time, science was not just experimental. The experiment was not enough. They didn't think that they have to soil their hands in doing experiments to get to the reality. They said, why is it the case? Why? So Galileo had to come up with an explanation of why heavier and lighter objects fall at the same rate. This is the way he convinced them, using symmetry. He said, suppose you have three bricks, the same shape, the same size, same mass, everything. And we hold these three bricks at the same height and drop them. Which one will fall to the ground first? Everybody said, of course, we know that symmetry tells you, you know, they're all the same shape, same size, same height. Of course, they fall at the same time. Yeah, we know that, next, next. It's trivial. He said, okay, what if we move these bricks around with the same height? Does it change the time they hit the ground? They said, if it's the same height, again, by the symmetry principle, because the height translation, horizontal translation is the symmetry. No, it doesn't matter. They all fall at the same rate. Good, doesn't matter how close I bring them together? No, it doesn't. Okay, suppose I make the two bricks touch and then let them go. Do they fall at the same rate? Yes, they do. But then he said, well, the two bricks that touch are twice more mass than this other brick. And you just agreed that they fall at the same rate. They say, yeah, yeah, we just agreed. That's right, that's strange. Yes, so he confused them by the symmetry reasoning. So this way of repackaging some intuition, a different intuition, when the intuitions clash, then you side on the, you replace the intuition. That's brilliant. In some of these more difficult physical ideas, physics ideas in the 20th century and the 21st century, it starts becoming more and more difficult to then replace the intuition. You know, what does the world look like for an object traveling close to the speed of light? You start to think about like the edges of supermassive black holes. And you start to think like, what's that look like? Or I've been into gravitational waves recently. It's like when the fabric of space-time is being morphed by gravity. Like what's that actually feel like? If I'm riding a gravitational wave, what's that feel like? I mean, I think some of those are more sort of hippie, not useful intuitions to have. But if you're an actual physicist or whatever the particular discipline is, I wonder if it's possible to meditate, to sort of escape through thinking, prolonged thinking and meditation on a world, like live in a visualized world that's not like our own in order to understand a phenomena deeply. So like replace the intuition, like through rigorous meditation on the idea in order to conceive of it. I mean, if we talk about multiple dimensions, I wonder if there's a way to escape with a three-dimensional world in our mind in order to then start to reason about it. It's the more I talk to topologists, the more they seem to not operate at all in the visual space. They really trust the mathematics, which is really annoying to me because topology and differential geometry feels like it has a lot of potential for beautiful pictures. Yes, I think they do. Actually, I would not be able to do my research if I don't have an intuitive feel about geometry. And we'll get to it, as you mentioned before, that how, for example, in string theory, you deal with these extra dimensions. And I'll be very happy to describe how we do it because without intuition, we will not get anywhere. And I don't think you can just rely on formalism. I don't. I don't think any physicist just relies on formalism. That's not physics. That's not understanding. So we have to intuit it. And that's crucial. And there are steps of doing it, and we learned. It might not be trivial, but we learned how to do it. Similar to this Galileo picture I just told you, you have to build these gradually. But- You have to connect the bricks. You have to connect the, yeah, exactly. You have to connect the bricks, literally. So yeah, so then, so going back to your question about the path of the history of the science, so I was saying about the refusal of magnetism and the special relativity were simple idea led to special relativity. But then he went further, thinking about acceleration in the context of relativity, and he came up with general relativity, where he talked about the fabric of space-time being curved and so forth, and matter affecting the curvature of the space and time. So this gradually became a connection between geometry and physics. Namely, he replaced Newton's gravitational force with a very geometrical, beautiful picture. It's much more elegant than Newton's, but much more complicated mathematically. So when we say it's simpler, we mean in some form it's simpler, but not in pragmatic terms of equation solving. The equations are much harder to solve in Einstein's theory, and in fact, so much harder that Einstein himself couldn't solve many of the cases. He thought, for example, he couldn't solve the equation for a spherical symmetric matter, like if you had a symmetric sun. He didn't think you can actually solve his equation for that, and a year after he said that, it was solved by Schwarzschild. So it was that hard that he didn't think it's gonna be that easy. So yeah, the formalism is hard. But the contrast between the special relativity and general relativity is very interesting, because one of them has almost trivial math, and the other one has super complicated math. Both are physically amazingly important. And so we have learned that the physics may or may not require complicated math. We should not shy from using complicated math like Einstein did. Nobody, Einstein wouldn't say, I'm not gonna touch this math because it's too much tensors or curvature, and I don't like the four-dimensional space time because I can't see four dimensions. He wasn't doing that. He was willing to abstract from that because physics drove him in that direction. But his motivation was physics. Physics pushed him. Just like Newton pushed to develop calculus because physics pushed him, that he didn't have the tools, so he had to develop the tools to answer his physics questions. So his motivation was physics, again. So to me, those are examples which show that math and physics have this symbiotic relationship which kind of reinforce each other. Here I'm giving you examples of both of them, namely Newton's work led to development of mathematics, calculus. And in the case of Einstein, he didn't develop Riemannian geometry, he just used them. So it goes both ways, and in the context of modern physics, we see that again and again it goes both ways. Let me ask a ridiculous question. You talk about your favorite soccer player at a bar. I'll ask the same question about Einstein's ideas, which is, which one do you think is the biggest leap of genius? Is it the E equals MC squared? Is it Brownian motion? Is it special relativity? Is it general relativity? Which of the famous set of papers he's written in 1905, and in general his work, was the biggest leap of genius? In my opinion, it's special relativity. The idea that speed of light is the same for everybody is the beginning of everything he did. The beginning is the speed. The beginning, it's the same. Once you embrace that weirdness, all the rest of it. I would say that's, even though he says the most beautiful moment for him, he says that is when he realized that if you fall in an elevator, you don't know if you're falling, or whether you're in the falling elevator, or whether you're next to the Earth's gravitational field. That, to him, was his aha moment, which inertial mass and gravitational mass being identical geometrically and so forth as part of the theory, not because of some funny coincidence. That's for him. But I feel, from outside at least, it feels like the speed of light being the same is the really aha moment. The general relativity to you is not like a conception of space-time. In a sense, the conception of space-time already was part of spatial relativity when you talk about length contraction. So general relativity takes that to the next step. But beginning of it was already space-length contracts, time dilates. So once you talk about those, then yeah, you can dilate more or less different places than its curvature. So you don't have a choice. So it kind of started just with that same simple thought. Speed of light is the same for all. Where does quantum mechanics come into view? Exactly, so this is the next step. So Einstein's developed general relativity and he's beginning to develop the foundation of quantum mechanics at the same time, the photoelectric effects and others. And so quantum mechanics overtakes, in fact, Einstein in many ways because he doesn't like the probabilistic interpretation of quantum mechanics and the formalism that's emerging. But physicists march on and try to, for example, combine Einstein's theory of relativity with quantum mechanics. So Dirac takes spatial relativity, tries to see how is it compatible with quantum mechanics. Can we pause and briefly say what is quantum mechanics? Oh yes, sure. So quantum mechanics, so I discussed briefly when I talked about the connection between Newtonian mechanics and the Euler-Lagrange reformulation of the Newtonian mechanics and interpretation of this Euler-Lagrange formalism in terms of the paths that the particle take. So when we say a particle goes from here to here, we usually think it classically follows a specific trajectory, but actually in quantum mechanics, it follows every trajectory with different probabilities. And so there's this fuzziness. Now, most probable, it's the path that you actually see. And the deviation from that is very, very unlikely and probabilistically very minuscule. So in everyday experiment, we don't see anything deviated from what we expect, but quantum mechanics tells us that things are more fuzzy. Things are not as precise as the line you draw. If things are a bit like cloud. So if you go to microscopic scales, like atomic scales and lower, these phenomena become more pronounced. You can see it much better. The electron is not at the point, but the cloud spread out around the nucleus. And so this fuzziness, this probabilistic aspect of reality is what quantum mechanics describes. Can I briefly pause on that idea? Do you think this is, quantum mechanics is just a really damn good approximation, a tool for predicting reality? Or does it actually describe reality? Do you think reality's fuzzy at that level? Well, I think that reality is fuzzy at that level, but I don't think quantum mechanics is necessarily the end of the story. So quantum mechanics is certainly an improvement over classical physics. That much we know by experiments and so forth. Whether I'm happy with quantum mechanics, whether I view quantum mechanics, for example, the thought, the measurement description of quantum mechanics, am I happy with it? Am I thinking that's the end stage or not? I don't. I don't think we're at the end of that story, and many physicists may or may not view this way. Some do, some don't. But I think that it's the best we have right now, that's for sure. It's the best approximation for reality we know today, and so far we don't know what it is the next thing that improves it or replaces it and so on. But as I mentioned before, I don't believe any of the laws of physics we know today are fragmentary. It's exactly correct. And it doesn't bother me. I'm not like dogmatic, saying I have figured out, this is the law of nature, I know everything. No, no. That's the beauty about science, that we are not dogmatic. And we are willing to, in fact we are encouraged to be skeptical of what we ourselves do. So you were talking about Dirac. Yes, I was talking about Dirac. So Dirac was trying to now combine this Schrodinger's equations, which was described in the context of trying to talk about how these probabilistic waves of electrons move for the atom, which was good for speeds which were not too close to the speed of light, to what happens when you get to the near the speed of light. So then you need relativity. So then Dirac tried to combine Einstein's relativity with quantum mechanics. So he tried to combine them and he wrote this beautiful equation, the Dirac equation, which roughly speaking, take the square root of the Einstein's equation in order to connect it to Schrodinger's time evolution operator, which is first order in time derivative, to get rid of the naive thing that Einstein's equation would have given, which is second order. So you have to take a square root. Now square root usually has a plus or minus sign when you take it. And when he did this, he originally didn't notice this, didn't pay attention to this plus or minus sign, but later physicists pointed out to Dirac, says look, there's also this minus sign, and if you use this minus sign, you get negative energy. In fact, it was very, very annoying that somebody else tells you this obvious mistake you make. Pauli, famous physicist, told Dirac, this is nonsense. You're gonna get negative energy with your equation, which negative energy without any bottom. You can go all the way down to negative infinite energy, so it doesn't make any sense. Dirac thought about it, and then he remembered Pauli's exclusion principle. Just before him, Pauli had said, you know, there's this principle called the exclusion principle that two electrons cannot be on the same orbit. And so Dirac said, okay, you know what? All these negative energy states are filled orbits, occupied. So according to you, Mr. Pauli, there's no place to go, so therefore they only have to go positive. Sounded like a big cheat. And then Pauli said, oh, you know what? We can change orbits from one orbit to another. What if I take one of these negative energy orbits and put it up there? Then it seems to be a new particle, which has opposite properties to the electron. It has positive energy, but it has positive charge. What is that? Dirac was a bit worried. He said, maybe that's proton, because proton has plus charge. He wasn't sure. But then he said, oh, maybe it's proton. But then they said, no, no, no, no. It has the same mass as the electron. It cannot be proton, because proton is heavier. Dirac was stuck. He says, well, then maybe another particle we haven't seen. By that time, Dirac himself was getting a little bit worried about his own equation and his own crazy interpretation. Until a few years later, Anderson, in the photographic place that he had gotten from these cosmic rays, he discovered a particle which goes in the opposite direction that the electron goes when there's a magnetic field, and with the same mass, exactly like what Dirac had predicted. This was what we call now positron. In fact, beginning with the work of Dirac, we know that every particle has an antiparticle. This idea that there's an antiparticle came from this simple math. There's a plus and a minus from the Dirac's quote-unquote mistake. So again, trying to combine ideas, sometimes the math is smarter than the person who uses it to apply it, and we try to resist it, and then you're kind of confronted by criticism, which is the way it should be. So physicists come and say, no, no, that's wrong, and you correct it, and so on. So that is a development of the idea there's particle, there's antiparticle, and so on. So this is the beginning of development of quantum mechanics and the connection with relativity, but the thing was more challenging, because we had to also describe how electric and magnetic fields work with quantum mechanics. This was much more complicated, because it's not just one point. Electric and magnetic fields were everywhere, so you had to talk about fluctuating and a fuzziness of electrical field and magnetic fields everywhere, and the math for that was very difficult to deal with. And this led to a subject called quantum field theory. Fields, like electric and magnetic fields, had to be quantum, had to be described also in a wavy way. Feynman, in particular, was one of the pioneers, along with Schrodinger and others, to try to come up with a formalism to deal with fields, like electric and magnetic fields, interacting with electrons in a consistent quantum fashion, and they developed this beautiful theory, quantum electrodynamics, from that, and later on, that same formalism, quantum field theory, led to the discovery of other forces and other particles, all consistent with the idea of quantum mechanics. So that was how physics progressed, and so basically, we learned that all particles and all the forces are, in some sense, related to particle exchanges. And so, for example, electromagnetic forces are mediated by a particle we call a photon, and so forth, and same for other forces that they discovered, strong forces and the weak forces. So we got the sense of what quantum field theory is. Is that a big leap of an idea that particles are fluctuations in a field, like the idea that everything is a field? Is the old Einstein, light is a wave, both a particle and a wave, kind of idea? Is that a huge leap in our understanding of conceiving the universe as fields? I would say so. I would say that viewing the particles, this duality that Bohr mentioned between particles and waves, that waves can behave sometimes like particles, sometimes like waves, is one of the biggest leaps of imagination that quantum mechanics made physics do. So I agree that that is quite remarkable. Is duality fundamental to the universe, or is it just because we don't understand it fully? Like, will it eventually collapse into a clean explanation that doesn't require duality? Like, that a phenomena could be two things at once and both to be true. That seems weird. So in fact, I was going to get to that when we get to string theory, but maybe I can comment on that now. Duality turns out to be running the show today, is the whole thing that we are doing is string theory. Duality is the name of the game. So it's the most beautiful subject, and I want to talk about it. Let's talk about it in the context of string theory. Let's talk about the context of string theory, yes. So we, do you want to take a next step into, because we mentioned general relativity, we mentioned quantum mechanics, is there something to be said about quantum gravity? Yes, that's exactly the right point to talk about. So namely, we have talked about quantum fields, and I talked about electric forces, photon being the particle carrying those forces. So for gravity, quantizing gravitational field, which is this curvature of space-time, according to Einstein, you get another particle called graviton. So, what about gravitons? Should be there, no problem. So then you start computing it. What do I mean by computing it? Well, you compute scattering of one graviton off another graviton, maybe a graviton with an electron, and so on, see what you get. Feynman had already mastered this quantum electrodynamics, he said, no problem, let me do it. Even though these are such weak forces, the gravity is very weak, so therefore to see them, these quantum effects of gravitational waves was impossible, it's even impossible today. So Feynman just did it for fun. He usually had this mindset that I wanna do something which I will see in experiment, but this one, let's just see what it does. And he was surprised because the same techniques he was using for doing the same calculations, quantum electrodynamics, when applied to gravity, failed. The formulas seemed to make sense, but he had to do some integrals, and he found that when he does those integrals, he got infinity, and it didn't make any sense. Now, there were similar infinities in the other pieces, but he had managed to make sense out of those before. This was no way he could make sense out of it, he just didn't know what to do. He didn't feel it's an urgent issue because nobody could do the experiment, so he was kind of said, okay, there's this thing, but okay, we don't know how to exactly do it, but that's the way it is. So in some sense, a natural conclusion from what Feynman did could have been like, gravity cannot be consistent with quantum theory, but that cannot be the case because gravity is in our universe, quantum mechanics is in our universe, they're both together, somehow it should work. So it's not acceptable to say they don't work together. So that was a puzzle, how does it possibly work? It was left open. And then we get to the string theory. So this is the puzzle of quantum gravity, the particle description of quantum gravity failed. So the infinity shows up, what do we do with infinity? Let's get to the fun part, let's talk about string theory. Yes. Let's discuss some technical basics of string theory. What is string theory? What is a string? How many dimensions are we talking about? What are the different states? How do we represent the elementary particles and the laws of physics using this new framework? So string theory is the idea that the fundamental entities are not particles, but extended higher dimensional objects, like one dimensional strings, like loops. These loops could be open, like two ends, like an interval or a circle without any ends. So, and they're vibrating and moving around in space. So how big they are? Well, you can of course stretch it and make it big, or you can just let it be whatever it wants, it can be as small as a point because the circle can shrink to a point, and be very light, or you can, you know, stretch it and becomes very massive, or it could oscillate and become massive that way. So it depends on which kind of state you have. In fact, the string can have infinitely many modes, depending on which kind of oscillation it's doing, like a guitar has different harmonics, string has different harmonics, but for the string, each harmonic is a particle. So each particle will give you, ah, this is a more massive harmonic, this is a less massive. So the lightest harmonic, so to speak, is no harmonics, which means like the string shrunk to a point, and then it becomes like a massless particles, or light particles, like photon, and graviton, and so forth. So when you look at tiny strings, which are shrunk to a point, the lightest ones, they look like the particles that we think of, they're like particles. In other words, from far away, they look like a point. But of course, if you zoom in, there's this tiny little, you know, little circle that's there, that's shrunk to almost a point. Should we be imagining, this is to the visual intuition, should we be imagining literally strings that are potentially connected as a loop, or not? When you, and when somebody outside of physics, is imagining a basic element of string theory, which is a string, should we literally be thinking about a string? Yes, you should literally think about string, but string with zero thickness. With zero thickness. So notice, it's a loop of energy, so to speak, if you can think of it that way. And so, there's a tension, like a regular string, if you pull it, there's, you know, you have to stretch it. But it's not like a thickness, like you're made of something, it's just energy. It's not made of atoms, or something like that. But, and it is very, very tiny. Very tiny. Much smaller than elementary particles of physics. Much smaller. So we think if you let the string to be, by itself, the lowest state, there'll be like, a fuzziness, or a size of that tiny little circle, which is like a point, about, could be anything between, we don't know the exact size, but different models have different sizes, but something of the order of 10 to the minus, let's say 30 centimeters. So, 10 to the minus 30 centimeters, just to compare with the size of the atom, which is 10 to the minus eight centimeters, is 22 orders of magnitude smaller. So, so it's- Unimaginably small, I would say. Very small, very small. So we basically think, from far away, string is like a point particle. And that's why a lot of the things that we learned about point particle physics carries over directly to strings. So therefore, there's not much of a mystery why particle physics was successful, because a string is like a particle when it's not stretched. But it turns out having this size, being able to oscillate, get bigger, turned out to be resolving this puzzle that Feynman was having in calculating his diagrams, and it gets rid of those infinities. So when you're trying to do those infinities, the regions that give infinities to Feynman, as soon as you get to those regions, then this string starts to oscillate, and these oscillation structure of the strings resolves those infinities to find the answer at the end. So the size of the string, the fact that it's one-dimensional, gives a finite answer at the end, resolves this paradox. Now, perhaps it's also useful to recount of how string theory came to be. Because it wasn't like somebody say, well, let me solve the problem of Einstein's, solve the problem that Feynman had with unifying Einstein's theory with quantum mechanics by replacing the point by a string. No, that's not the way the thought process, the thought process was much more random. Physicist, Venetiano in this case, was trying to describe the interactions they were seeing in colliders, in accelerators. And they were seeing that some process, in some process when two particles came together and joined together and when they were separately, in one way, and the opposite way, they behave the same way. In some way, there was a symmetry, a duality, which he didn't understand. The particles didn't seem to have that symmetry. He said, I don't know what it is, what's the reason that these colliders and experiments we're doing seems to have the symmetry, but let me write the mathematical formula which exhibits that symmetry. He used gamma functions, beta functions, and all that complete math, no physics, other than trying to get symmetry out of his equation. He just wrote down a formula as the answer for a process, not a method to compute it. Just say, wouldn't it be nice if this was the answer? Yes. Physicist looked at this formula, that's intriguing, it has this symmetry, all right, but what is this, where is this coming from? Which kind of physics gives you this? So I don't know. A few years later, people saw that, oh, the equation that you're writing, the process that you're writing in the intermediate channels that particles come together seems to have all the harmonics. Harmonics sounds like a string. Let me see if what you're describing has anything to do with the strings, and people try to see if what he's doing has anything to do with the strings. Oh, yeah, indeed, if I study scattering of two strings, I get exactly the formula you wrote down. That was the reinterpretation of what he had written in the formula as a string, but still had nothing to do with gravity. It had nothing to do with resolving the problems of gravity with quantum mechanics. It was just trying to explain a process that people were seeing in hadronic physics collisions. So it took a few more years to get to that point. They noticed that, physicists noticed that whenever you try to find the spectrum of strings, you always get a massless particle, which has exactly the properties that a graviton is supposed to have, and no particle in hadronic physics that had that property. You are getting a massless graviton as part of the scattering without looking for it. It was forced on you. People were not trying to solve quantum gravity. Quantum gravity was pushed on them. I don't want this graviton, get rid of it. They couldn't get rid of it. They gave up trying to get rid of it. Physicists said, Sherkin and Schwartz said, you know what, string theory is theory of quantum gravity. They changed the perspective altogether. We are not describing the hadronic physics. We are describing this theory of quantum gravity, and that's when string theory probably got exciting, that this could be the unifying theory. Exactly, it got exciting, but at the same time, not so fast. Namely, it should have been fast, but it wasn't, because particle physics through quantum field theory were so successful at that time. This is mid-70s. Standard model of physics, electromagnetism and unification of electromagnetic forces with all the other forces were beginning to take place without the gravity part. Everything was working beautifully for particle physics, and so that was the shining golden age of quantum field theory and all the experiments, standard model, this and that, unification, and spontaneous symmetry breaking was taking place. All of them was nice. This was kind of like a side show, and nobody was paying so much attention. This exotic string is needed for quantum gravity. Ah, maybe there's other ways. Maybe we should do something else. So, anyway, it wasn't paid much attention to, and this took a little bit more effort to try to actually connect it to reality. There are a few more steps. First of all, there was a puzzle that you were getting extra dimensions. String was not working well with three spatial dimensions at one time. It needed extra dimension. Now, there are different versions of strings, but the version that ended up being related to having particles like electron, what we call fermions, needed 10 dimensions, what we call superstring. Now, why super? Why the word super? It turns out this version of the string, which had fermions, had an extra symmetry, which we call supersymmetry. This is a symmetry between a particle and another particle with exactly the same properties, same mass, same charge, et cetera. The only difference is that one of them has a little different spin than the other one. And one of them is a boson, one of them is a fermion, because of that shift of spin. Otherwise, they're identical. So there was this symmetry. String theory had this symmetry. In fact, supersymmetry was discovered through string theory, theoretically. So theoretically, the first place that this was observed when you were describing these fermionic strings. So that was the beginning of the study of supersymmetry was via string theory. And then it had remarkable properties that the symmetry meant and so forth that people began studying supersymmetry after that. And that was a kind of a tangent direction at the beginning for string theory. But people in particle physics started also thinking, oh, supersymmetry is great. Let's see if we can have supersymmetry in particle physics and so forth. Forget about strings. And they developed on a different track as well. Supersymmetry in different models became a subject on its own right, understanding supersymmetry and what does this mean. Because it unified bosons and fermions, unifies some ideas together. So photon is a boson, electron is a fermion. Could things like that be somehow related? It was a kind of a natural kind of a question to try to kind of unify because in physics, we love unification. Now, gradually string theory was beginning to show signs of unification. It had graviton, but people found that you also have things like photons in them. Different excitations of string behave like photons. Another one behave like electron. So a single string was unifying all these particles into one object. That's remarkable. It's in 10 dimensions though. It is not our universe because we live in three plus one dimension. How could that be possibly true? So this was a conundrum. It was elegant, it was beautiful, but it was very specific about which dimension you're getting, which structure you're getting. It wasn't saying, oh, you just put D equals to four, you'll get your space time dimension that you want. No, it didn't like that. It said, I want 10 dimensions and that's the way it is. So it was very specific. Now, so people try to reconcile this by the idea that maybe these extra dimensions are tiny. So if you take three macroscopic spatial dimensions on one time and six extra tiny spatial dimensions, like tiny spheres or tiny circles, then it avoids contradiction with manifest fact that we haven't seen extra dimensions in experiments today. So that was a way to avoid conflict. Now, this was a way to avoid conflict, but it was not observed in experiments. A string observed in experiments? No, because it's so small. So it's beginning to sound a little bit funny. Similar feeling to the way perhaps Dirac had felt about this positron, plus or minus. You know, it was beginning to sound a little bit like, oh yeah, not only I have to have 10 dimension, but I have to also this and, and so conservative physicists would say, hmm, you know, I haven't seen these in experiments. I don't know if they are really there. Are you pulling my leg? Do you want me to imagine things that are not there? So this was an attitude of some physicists just towards string theory, despite the fact that the puzzle of gravity and quantum mechanics merging together work, but still was this skepticism. You're putting all these things that you want me to imagine there are these extra dimensions that I cannot see, uh-huh, uh-huh, and you want me to believe that string theory, you have not even seen the experiments that are real, uh-huh, okay, what else do you want me to believe? So this kind of beginning to sound a little funny. Now, I will pass forward a little bit further. A few decades later, when string theory became the mainstream of efforts to unify the forces and particles together, we learned that these extra dimensions actually solved problems. They weren't a nuisance the way they originally appeared. First of all, the properties of these extra dimensions reflected the number of particles we got in four dimensions. If you took these six dimensions to have like six, five holes or four holes, it changed the number of particles that you see in four dimensional space time. You get one electron and one muon if you had this, but if you did the other J shape, you get something else. So geometrically, you could get different kinds of physics. So it was kind of a mirroring of geometry by physics down in the macroscopic space. So these extra dimension were becoming useful. Fine, but we didn't need extra dimensions to just write an electron in three dimensions. We did, we wrote it, so what? Was there any other puzzle? Yes, there were. Hocking. Hocking had been studying black holes in mid 70s, following the work of Bekenstein, who had predicted that black holes have entropy. So Bekenstein had tried to attach entropy to the black hole. If you throw something into the black hole, the entropy seems to go down because you had something entropy outside the black hole and you throw it. Black hole was unique, so the entropy did not have any, black hole had no entropy, so the entropy seemed to go down. And so that's against the laws of thermodynamics. So Bekenstein was trying to say, no, no, therefore black hole must have an entropy. So he was trying to understand that. He found that if you assign entropy to be proportional to the area of the black hole, it seems to work. And then Hocking found not only that's correct, he found the correct proportionality factor of a one quarter of the area in Planck units is the correct amount of entropy. And he gave an argument using quantum, semi-classical arguments, which means basically using a little bit of quantum mechanics, because he didn't have the full quantum mechanics of strength theory, he could do some aspects of approximate quantum arguments. So heuristic quantum arguments led to this entropy formula. But then he didn't answer the following question. He was getting a big entropy for the black hole, the black hole with the size of the horizon of a black hole is huge, has a huge amount of entropy. What are the microstates of this entropy? When you say, for example, the gas has entropy, you count where the atoms are, you count this bucket or that bucket, there's information about there and so on, you count them. For the black hole, the way Hocking was seeing it, there was no degree of freedom. You throw them in and there was just one solution. So where are these entropy? What are these microscopic states? They were hidden somewhere. So later in string theory, the work that we did with my colleague Strominger in particular showed that these ingredients in string theory of black hole arise from the extra dimensions. So the degrees of freedom are hidden in terms of things like strings, wrapping these extra circles in this hidden dimensions. And then we started counting how many ways like the strings can wrap around this circle and the extra dimension or that circle and counted the microscopic degrees of freedom. And lo and behold, we got the microscopic degrees of freedom that Hocking was predicting four dimensions. So the extra dimensions became useful for resolving a puzzle in four dimensions. The puzzle was where are the degrees of freedom of the black hole hidden? The answer, hidden in the extra dimensions, the tiny extra dimensions. So then by this time, it was beginning to, we see aspects that extra dimensions are useful for many things. It's not a nuisance. It wasn't to be kind of, you know, be shamed of. It was actually in the welcome features. New feature nevertheless. How do you intuit the 10 dimensional world? So yes, it's a feature for describing certain phenomena like the entropy in black holes. But what, you said that to you a theory becomes real or becomes powerful when you can connect it to some deep intuition. So how do we intuit 10 dimensions? Yes, so I will explain how some of the analogies work. First of all, we do a lot of analogies. And by analogies, we build intuition. So I will start with this example. I will try to explain that if we are in 10 dimensional space, if we have a seven dimensional plane and eight dimensional plane, we ask typically in what space do they intersect each other in what dimension? That might sound like how do you possibly give an answer to this? So we start with lower dimensions. We start with two dimensions. We say if you have one dimension and a point, do they intersect typically on a plane? The answer is no. So a line one dimensional, a point zero dimension on a two dimensional plane, they don't typically meet. But if you have a one dimensional line, another line, which is one plus one on a plane, they typically intersect at a point. Typically means if you're not parallel, typically they intersect at a point. So one plus one is two. And in two dimension, they intersect at the zero dimensional point. So you see two dimension, one and one, two, two minus two is zero. So you get point out of intersection. Okay, let's go to three dimension. You have a plane, two dimensional plane and a point. Do they intersect? No, two and zero. How about the plane and a line? A plane is two dimensional and a line is one, two plus one is three. In three dimension, a plane and a line meet at points, which is zero dimensional, three minus three is zero. Okay, so plane and a line intersect at a point in three dimension. How about the plane and a plane in 3D? A plane is two and this is two, two plus two is four. In 3D, four minus three is one, they intersect on a one dimensional line. Okay, we're beginning to see the pattern. Okay, now come to the question. We're in 10 dimension, now we have the intuition. We have a seven dimensional plane and an eight dimensional plane in 10 dimension. They intersect on a plane. What's the dimension? Well, seven plus eight is 15 minus 10 is five. We draw the same picture as two planes and we write seven dimension, eight dimension, but we have gotten the intuition from the lower dimensional one. What to expect? It doesn't scare us anymore. So we draw this picture. We cannot see all the seven dimensions by looking at this two dimensional visualization of it, but it has all the features we want. It has, so we draw this picture, which is seven, seven, and they meet at the five dimensional plane. This is five. So we have built this intuition. Now, this is an example of how we come up with intuition. Let me give you more examples of it because I think this will show you that people have to come up with intuitions to visualize it. Otherwise, we will be a little bit lost. So what you just described is kind of in these high dimensional spaces, focus on the meeting place of two planes in high dimensional spaces. Exactly, how the planes meet, for example. What's the dimension of their intersection and so on? So how do we come up with intuition? We borrow examples from lower dimensions, build up intuition and draw the same pictures as if we are talking about 10 dimensions, but we are drawing the same as a two dimensional plane because we cannot do any better. But our words change, but not our pictures. So your sense is we can have a deep understanding of reality by looking at its slices, a lower dimensional slices. Exactly, exactly. And this brings me to the next example I wanna mention, which is sphere. Let's think about how do we think about the sphere? Well, the sphere is a sphere, the round nice thing, but sphere has a circular symmetry. Now, I can describe the sphere in the following way. I can describe it by an interval, which is, think about this going from the north of the sphere to the south. And at each point, I have a circle attached to it. So you can think about the sphere as a line with a circle attached with each point, the circle shrinks to a point at end points of the interval. So I can say, oh, one way to think about the sphere is an interval, where at each point on that interval, there's another circle I'm not drawing. But if you like, you can just draw it. Say, okay, I won't draw it. So from now on, there's this mnemonic. I draw an interval when I wanna talk about the sphere and you remember that the end points of the interval mean a strong circle, that's all. And then you say, yeah, I see, that's a sphere, good. Now, we wanna talk about the product of two spheres. That's four dimensional, how can I visualize it? Easy, you just take an interval and another interval, that's just gonna be a square. Yeah. A square is a four dimensional space? Yeah, why is that? Well, at each point on the square, there's two circles, one for each of those directions you drew. And when you get to the boundaries of each direction, one of the circles shrink on each edge of that square. And when you get to the corners of the square, all both circles shrink. This is a sphere times a sphere, I have defined interval. I just described for you a four dimensional space. Do you want a six dimensional space? No problem. Take a corner of a room. In fact, if you want to have a sphere times a, take sphere times a sphere times a sphere. Take a cube, a cube is a rendition of this six dimensional space. It's two sphere times another sphere times another sphere, where three of the circles I'm not drawing for you. For each one of those direction, there's another circle. But each time you get to the boundary of the cube, one circle shrinks. When the boundaries meet, two circles shrink. When three boundaries meet, all the three circles shrink. So I just give you a picture. Now, mathematicians come up with amazing things, like, you know what, I wanna take a point in space and blow it up. You know, these concepts like topology and geometry, complicated, how do you do? In this picture, it's very easy. Blow it up in this picture means the following. You think about this cube, you go to the corner, and you chop off a corner. Chopping off the corner replaces a point. Yeah. Replace the point by a triangle. Yes. That's called blowing up a point, and then this triangle is what they call P2, projective two space. But these pictures are very physical and you feel it. There's nothing amazing. I'm not talking about six dimension. Four plus six is 10, the dimension of string theory. So we can visualize it, no problem. Okay, so that's building the intuition to a complicated world of string theory. Nevertheless, these objects are really small. And just like you said, experimental validation is very difficult because the objects are way smaller than anything that we currently have the tools and accelerators and so on to reveal through experiment. So there's a kind of skepticism that's not just about the nature of the theory because of the 10 dimensions, as you've explained, but in that we can't experimentally validate it. And it doesn't necessarily, to date, maybe you can correct me, predict something fundamentally new. So it's beautiful as an explaining theory, which means that it's very possible that it is a fundamental theory that describes reality and unifies the laws. But there's still a kind of skepticism. And me, from sort of an outside observer perspective, have been observing a little bit of a growing cynicism about string theory in the recent few years. Can you describe the cynicism about, sort of by cynicism I mean a cynicism about the hope for this theory of pushing theoretical physics forward? Yes. Can you describe why this is cynicism and how do we reverse that trend? Yes, first of all, the criticism for string theory is healthy in a sense that in science we have to have different viewpoints and that's good. So I welcome criticism. And the reason for criticism, and I think that is a valid reason, is that there has been zero experimental evidence for string theory. That is, no experiment has been done to show that there's this little loop of energy moving around. And so that's a valid objection and valid worry. And if I were to say, you know what, string theory can never be verified or experimentally checked that's the way it is, they would have every right to say what you're talking about is not science. Because in science we will have to have experimental consequences and checks. The difference between string theory and something which is not scientific is that string theory has predictions. The problem is that the predictions we have today of string theory is hard to access by experiments available with the energies we can achieve with the colliders today. It doesn't mean there's a problem with string theory, it just means technologically we're not that far ahead. Now, we can have two attitudes. You say, well, if that's the case why are you studying this subject? Because you can't do experiment today. Now, this is becoming a little bit more like mathematics in that sense. You say, well, I want to learn, I want to know how the nature works even though I cannot prove it today that this is it because of experiments. That should not prevent my mind not to think about it. That's right. So that's the attitude many string theorists follow that it should be like this. Now, so that's an answer to the criticism but there's actually a better answer to the criticism I would say. We don't have experimental evidence for string theory but we have theoretical evidence for string theory. And what do I mean by theoretical evidence for string theory? String theory has connected different parts of physics together. It didn't have to. It has brought connections between part of physics although, suppose you're just interested in particle physics. Suppose you're not even interested in gravity at all. It turns out there are properties of certain particle physics models that string theory has been able to solve using gravity, using ideas from string theory, ideas known as holography, which is relating something which has to do with particles to something having to do with gravity. Why did it have to be this rich? The subject is very rich. It's not something we were smart enough to develop. It came at us. As I explained to you, the development of string theory came from accidental discovery. It wasn't because we were smart enough to come up with the idea, oh yeah, string of course has gravity. No, it was accident discovery. So some people say it's not fair to say we have no evidence for string theory. Graviton, gravity is an evidence for string theory. It's predicted by string theory. We didn't put it by hand, we got it. So there's a qualitative check. Okay, gravity is a prediction of string theory. It's a postdiction because we know gravity existed. But still, logically it is a prediction because really we didn't know it had, it's a graviton and we later learned that, oh, that's the same as gravity. So literally that's the way it was discovered. It wasn't put in by hand. So there are many things like that, that there are different facets of physics, like questions in condensed matter physics, questions of particle physics, questions about this and that have come together to find beautiful answers by using ideas from string theory at the same time as a lot of new math has emerged. That's an aspect which I wouldn't emphasize as evidence to physicists necessarily because they would say, okay, great, you got some math, but what's it do with reality? But as I explained, many of the physical principles we know of have beautiful math underpinning them. So certainly leads further confidence that we may not be going astray, even though that's not the full proof as we know. So there are these aspects that give further evidence for string theory, connections between each other, connection with the real world, but then there are other things that come about and I can try to give examples of that. So these are further evidences and these are certain predictions of string theory. They are not as detailed as we want, but there are still predictions. Why is the dimension of space and time three plus one? Say, I don't know, just deal with it, three plus one. But in physics, we want to know why. Well, take a random dimension from one to infinity. What's your random dimension? A random dimension from one to infinity would not be four. It would most likely be a humongous number if not infinity. I mean, if you choose any reasonable distribution which goes from one to infinity, three or four would not be your pick. The fact that we are in three or four dimension is already strange. The fact that strings, sorry, I cannot go beyond 10 or maybe 11 or something. The fact that there's this upper bound, the range is not from one to infinity, it's from one to 10 or 11 or whatnot. It already brings a natural prior, oh yeah, three or four is, you know, it's just on the average, if you pick some of the compactifications, then it will easily be that. So in other words, it makes it much more possible that it could be theory of our universe. So the fact that the dimension already is so small, it should be surprising. We don't ask that question. We should be surprised. Because we could have conceived of universes with our predimension. Why is it that we have such a small dimension? That's number one. So, oh, so good theory of the universe should give you an intuition of the why it's four or three plus one. And it's not obvious that it should be. That should be explained. We take that as an assumption, but that's a thing that should be explained. Yeah, so we haven't explained that in string theory. Actually, I did write a model within string theory to try to describe why we end up with three plus one space-time dimensions, which are big compared to the rest of them. And even though this has not been, the technical difficulties to prove it is still not there, but I will explain the idea. Because the idea connects to some other piece of elegant math, which is the following. Consider a universe made of a box, a three-dimensional box. Or in fact, if we start in string theory, nine-dimensional box, because we have nine spatial dimensions at one time. So imagine a nine-dimensional box. So we should imagine the box of a typical size of the string, which is small. So the universe would naturally start with a very tiny nine-dimensional box. What do strings do? Well, strings go around the box and move around and vibrate and all that, but also they can wrap around one side of the box to the other, because I'm imagining a box with periodic boundary conditions, so what we call the torus. So the string can go from one side to the other. This is what we call a winding string. The string can wind around the box. Now, suppose you now evolve the universe. Because there's energy, the universe starts to expand. But it doesn't expand too far. Why is it? Well, because there are these strings which are wrapped around from one side of the wall to the other. When the universe, the walls of the universe are growing, it is stretching the string, and the strings are becoming very, very massive. So it becomes difficult to expand. It kind of puts a halt on it. In order to not put a halt, a string which is going this way and a string which is going that way should intersect each other and disconnect each other and unwind. So a string which winds this way and a string which winds the opposite way should find each other to reconnect and this way disappear. So if they find each other, they disappear. But how can strings find each other? Well, the string moves, and another string moves. A string is one-dimensional, one plus one is two, and one plus one is two, and two plus two is four. In four-dimensional space-time, they will find each other. In a higher-dimensional space-time, they typically miss each other. Oh, interesting. So if the dimension were too big, they would miss each other, they wouldn't be able to expand. So in order to expand, they have to find each other, and three of them can find each other, and those can expand, and the other one would be stuck. So that explains why, within string theory, these particular dimensions are really big and full of exciting stuff. That could be an explanation. That's a model we suggested with my colleague Brandenberger. But it turns out to be related to a deep piece of math. You see, for mathematicians, manifolds of dimension bigger than four are simple. Four-dimension is the hardest dimension for math, it turns out. And it turns out the reason it's difficult is the following. It turns out that in higher dimension, you use what's called surgery in mathematical terminology, where you use these two-dimensional tubes to maneuver them off of each other. So you have two plus two becoming four. In higher than four dimension, you can pass them through each other without them intersecting. In four dimension, two plus two doesn't allow you to pass them through each other. So the same techniques that work in higher dimension don't work in four dimension, because two plus two is four. The same reasoning I was just telling you about strings finding each other in four ends up to be the reason why four is much more complicated to classify for mathematicians as well. So there might be these things. So I cannot say that this is the reason that string theory is giving you three plus one, but it could be a model for it. And so there are these kinds of ideas that could underlie why we have three extra dimensions which are large and the rest of them are small. But absolutely, we have to have a good reason. We cannot leave it like that. Can I ask a tricky human question? So you are one of the seminal figures in string theory. You got the Breakthrough Prize. You've worked with Edward Witten. There's no Nobel Prize that has been given on string theory. You know, credit assignment is tricky in science. It makes you quite sad, especially big, like LIGO, big experimental projects when so many incredible people have been involved and yet the Nobel Prize is annoying in that it's only given to three people. Who do you think gets the Nobel Prize for string theory at first? If it turns out that it, if not in full, then in part is a good model of the way the physics of the universe works. Who are the key figures? Maybe let's put Nobel Prize aside. Who are the key figures? Okay, I like the second version of the question. I think to try to give a prize to one person in string theory doesn't do justice to the diversity of the subject. That to me is. So there was quite a lot of incredible people in the history of string theory. Quite a lot of people. I mean, starting with Ferenciano who wasn't talking about strings. I mean, he wrote down the beginning of a string. So we cannot ignore that for sure. And so you start with that and you go on with various other figures and so on. So there are different epochs in string theory and different people have been pushing it. So for example, the early epoch, we just told you people like Veneziano and Nambu and the Suskind and others were pushing it. Green and Schwartz were pushing it and so forth. So this was, or Sherk and so on. So these were the initial periods of pioneers, I would say, of string theory. And then there were the mid 80s that Edward Witten was the major proponent of string theory and he really changed the landscape of string theory in terms of what people do and how we view it. And I think his efforts brought a lot of attention to the community about high energy community to focus on this effort as the correct theory of unification of forces. So he brought a lot of research as well as of course the first rate work he himself did to this area. So that's in mid 80s and onwards and also in mid 90s where he was one of the proponents of the duality revolution in string theory. And with that came a lot of these other ideas that led to breakthroughs involving, for example, the example I told you about black holes and holography and the work that was later done by Maldacena about the properties of duality between particle physics and quantum gravity and the connections, deeper connections of holography and it continues. And there are many people within this range which I haven't even mentioned. They have done fantastic important things. How it gets recognized I think is secondary in my opinion than the appreciation that the effort is collective. That in fact, that to me is the more important part of science that gets forgotten. For some reason humanity likes heroes and science is no exception. We like heroes. But I personally try to avoid that trap. I feel in my work, most of my work is with colleagues. I have much more collaborations than sole author papers and I enjoy it and I think that that's to me one of the most satisfying aspects of science is to interact and learn and debate ideas with colleagues because that influx of ideas enriches it and that's why I find it interesting. To me science, if I was in an island and if I was developing string theory by myself and had nothing to do with anybody, it would be much less satisfying in my opinion. Even if I could take credit, I did it, it won't be as satisfying. Sitting alone with a big metal drinking champagne. No, I think to me the collective work is more exciting and you mentioned my getting the breakthrough. When I was getting it, I made sure to mention that it is because of the joint work that I've done with colleagues at that time. It was around 180 or so collaborators and I acknowledged them in the webpage for them. I write all of their names and the collaborations that led to this. So to me, science is fun when it's collaboration and yes, there are more important and less important figures as in any field and that's true, that's true in string theory as well but I think that I would like to view this as a collective effort. So setting the heroes aside, the Nobel Prize is a celebration of, what's the right way to put it? That this idea turned out to be right. So like you look at Einstein didn't believe in black holes and then black holes got their Nobel Prize. Do you think string theory will get its Nobel Prize, Nobel Prizes? If you were to bet money, if this was an investment meeting and we had to bet all our money, do you think you'd guess the Nobel Prizes? I think it's possible that none of the living physicists will get the Nobel Prize in string theory but somebody will. Because unfortunately, the technology available today is not very encouraging in terms of seeing directly evidence for string theory. Do you think it ultimately boils down to the Nobel Prize will be given when there is some direct or indirect evidence? There would be but I think that part of this breakthrough prize was precisely the appreciation that when we have sufficient evidence, theoretical as it is, not experiment, because of this technology lag, you appreciate what you think is the correct path. So there are many people who have been recognized precisely because they may not be around when it actually gets experimented even though they discovered it. So there are many things like that that's going on in science. So I think that I would want to attach less significance to the recognitions of people. And I have a second review on this which is there are people who look at these works that people have done and put them together and make the next big breakthrough. And they get identified with, perhaps rightly, with many of these new visions. But they are on the shoulders of these little scientists which don't get any recognition. You know, yeah, you did this little work. Oh yeah, you did this little work. Oh yeah, yeah, five of you. Oh yeah, this showed this pattern and then somebody else. It's not fair. To me, those little guys which kind of like seem to do a little calculation here, a little thing there which doesn't rise to the occasion on this grandiose kind of thing, doesn't make it to the New York Times headlines and so on, deserve a lot of recognition. And I think they don't get enough. I would say that there should be this Nobel Prize for, you know, they have these Doctors Without Borders, they're a huge group, they should do similar thing. The Strength Years Without Borders kind of, everybody's doing a lot of work. And I think that I would like to see that effort to recognize. I think in the long arc of history, we're all little guys and girls standing on the shoulders of each other. I mean, it's all going to look tiny in retrospect. If we celebrate the New York Times, you know, as a newspaper, or the idea of a newspaper in a few centuries from now will be long forgotten. Yes, I agree with that. Especially in the context of strength theory, we should have very long term view. Yes, exactly. Just as a tiny tangent, we mentioned Edward Witten, and he, in a bunch of walks of life for me as an outsider, comes up as a person who is widely considered as like one of the most brilliant people in the history of physics, just as a powerhouse of a human. Like the exceptional places that a human mind can rise to. You've gotten a chance to work with him. What's he like? Yes, more than that. He was my advisor, PhD advisor. So I got to know him very well, and I benefited from his insights. In fact, what you said about him is accurate. He's not only brilliant, but he's also multifaceted in terms of the impact he has had in not only physics, but also in mathematics. He's gotten the Fields Medal because of his work in mathematics, and rightly so, he has used his knowledge of physics in a way which impacted deep ideas in modern mathematics, and that's an example of the power of these ideas in modern high-energy physics and string theory, that the applicability of it to modern mathematics. So he's quite an exceptional individual. We don't come across such people a lot in history. So I think, yes, indeed, he's one of the rare figures in this history of subject. He has had great impact on a lot of aspects of not just string theory, a lot of different areas in physics, and also, yes, in mathematics as well. So I think what you said about him is accurate. I had the pleasure of interacting with him as a student, and later on as colleagues, writing papers together and so on. What impact did he have on your life? Like, what have you learned from him? If you were to look at the trajectory of your mind, of the way you approach science and physics and mathematics, how did he perturb that trajectory? Yes, he did, actually. So I can explain, because when I was a student, I had the biggest impact by him, clearly as a grad student at Princeton. So I think that was a time where I was a little bit confused about the relation between math and physics. I got a double major in mathematics and physics at MIT, because I really enjoyed both, and I liked the elegance and the rigor of mathematics, and I liked the power of ideas in physics and its applicability to reality and what it teaches about the real world around us. But I saw this tension between rigorous thinking in mathematics and lack thereof in physics, and this troubled me to no end. I was troubled by that. So I was at crossroads when I decided to go to graduate school in physics, because I did not like some of the lack of rigors I was seeing in physics. On the other hand, to me, mathematics, even though it was rigorous, I think it sometimes were, I didn't see the point of it. In other words, when I see, the math theorem by itself could be beautiful, but I really wanted more than that. I wanted to say, okay, what does it teach us about something else, something more than just math? So I wasn't that enamored with just math, but physics was a little bit bothersome. Nevertheless, I decided to go to physics, and I decided to go to Princeton, and I started working with Edward Witten as my thesis advisor. And at that time, I was trying to put physics in rigorous mathematical terms. I took quantum field theory, I tried to make rigorous out of it, and so on. And no matter how hard I was trying, I was not being able to do that, and I was falling behind from my classes. I was not learning much physics, and I was not making it rigorous. And to me, it was this dichotomy between math and physics. What am I doing? I like math, but this is not exactly this. There comes Edward Witten as my advisor, and I see him in action, thinking about math and physics. He was amazing in math. He knew all about the math. It was no problem with him. But he thought about physics in a way which did not find this tension between the two. It was much more harmonious. For him, he would draw the Feynman diagrams, but he wouldn't view it as a formalism. He would view it, oh yeah, the particle goes over there, and this is what's going on. And so wait, you're thinking really, is this particle, this is really electron going there? Oh yeah, yeah, it's not the form of a result perturbation. No, no, no. You just feel like the electron, you're moving with this guy and do that and so on, and you're thinking invariantly about physics, or the way he thought about relativity. Like I was thinking about this momentum system. He was thinking invariantly about physics, just like the way you think about invariant concepts in relativity, which don't depend on the frame of reference. He was thinking about the physics in invariant ways, the way that gives you a bigger perspective. So this gradually helped me appreciate that interconnections between ideas and physics replaces mathematical rigor. That the different facets reinforce each other. We say, oh, I cannot rigorously define what I mean by this, but this thing connects with this other physics I've seen, and this other thing, and they together form an elegant story. And that replaced for me what I believed as a solidness, which I found in math as a rigor, you know, solid, I found that replaced the rigor and solidness in physics. So I found, okay, that's the way you can hang on to. It is not wishy-washy. It's not like somebody is just not being able to prove it, just making up a story. It was more than that, and it was no tension with mathematics. In fact, mathematics was helping it, like friends. And so much more harmonious and gives insights to physics. So that's, I think, one of the main things I learned from interactions with Witten. And I think that now perhaps I have taken that to a far extreme. Maybe he wouldn't go this far as I have. Namely, I use physics to define new mathematics in a way which would be far less rigorous than a physicist might necessarily believe, because I take the physical intuition, perhaps literally in many ways, that could teach us math. So now I've gained so much confidence in physical intuition that I make bold statements that sometimes, you know, takes math friends off guard. So an example of it is mirror symmetry. So we were studying these compactification of string geometries. This is after my PhD now. By the time I'd come to Harvard, we were studying these aspects of string compactification on these complicated manifolds, six-dimensional spaces, called Calabi-Yau manifolds, very complicated. And I noticed with a couple other colleagues that there was a symmetry in physics suggested between different Calabi-Yau's. It suggested that you couldn't actually compute the Euler characteristic of a Calabi-Yau. Euler characteristic is counting the number of points minus the number of edges plus the number of faces minus. So you can count the alternating sequence of properties of the space, which is the topological property of a space. So Euler characteristic of the Calabi-Yau was a property of the space. And so we noticed that from the physics formalism, if string moves in a Calabi-Yau, you cannot distinguish, we cannot compute the Euler characteristic. You can only compute the absolute value of it. Now this bothered us because how could you not compute the actual sign unless the both sides were the same? So I conjectured maybe for every Calabi-Yau with the Euler characteristic is positive, there's one with negative. I told this to my colleague Yao, whose namesake is Calabi-Yau, that I'm making this conjecture. Is it possible that for every Calabi-Yau, there's one with the opposite Euler characteristic? Sounds not reasonable. I said, why? He said, well, we know more Calabi-Yau's with negative Euler characteristics than positive. I said, but physics says we cannot distinguish them, at least I don't see how. So we conjectured that for every Calabi-Yau with one sign, there's the other one, despite the mathematical evidence. Despite the mathematical evidence. Despite the expert telling us it's not the right idea. A few years later, this symmetry, mirror symmetry between the sign with the opposite sign was later confirmed by mathematicians. So this is actually the opposite view. That is, physics is so sure about it that you're going against the mathematical wisdom, telling them they better look for it. So taking the physical intuition literally and then having that drive the mathematics. Exactly, and by now we are so confident about many such examples that has affected modern mathematics in ways like this, that we are much more confident about our understanding of what string theory is. These are other aspects of why we feel string theory is, is doing these kinds of things. I've been hearing your talk quite a bit about string theory, landscape and the swampland. What the heck are those two concepts? Okay, very good question. So let's go back to what I was describing about Feynman. Feynman was trying to do these diagrams for graviton and electrons and all that. He found that he's getting infinities he cannot resolve. Okay, the natural conclusion is that field theories and gravity and quantum theory don't go together and he cannot have it. So in other words, field theories and gravity are inconsistent with quantum mechanics, period. String theory came up with examples, but didn't address the question more broadly that is it true that every field theory can be coupled to gravity in a quantum mechanical way? It turns out that Feynman was essentially right. Almost all particle physics theories, no matter what you add to it, when you put gravity in it, doesn't work. Only rare exceptions work. So string theory are those rare exceptions. So therefore the general principle that Feynman found was correct. Quantum field theory and gravity and quantum mechanics don't go together, except for Joule's exceptional cases. There are exceptional cases. Okay, the total vastness of quantum field theories that are there, we call the set of quantum field theories, possible things. Which ones can be consistently coupled to gravity? We call that subspace the landscape. The rest of them, we call the swampland. It doesn't mean they are bad quantum field theories, they are perfectly fine. But when you couple them to gravity, they don't make sense, unfortunately. And it turns out that the ratio of them, the number of theories which are consistent with gravity to the ones which without, the ratio of the area of the landscape to the swampland, in other words, is measure zero. And so the swampland is infinitely large? The swampland's infinitely large. So let me give you one example. Take a theory in four dimension with matter, with maximum amount of supersymmetry. Can you get, it turns out a theory in four dimension with maximum amount of supersymmetry is characterized just with one thing, a group. What we call the gauge group. Once you pick a group, you have to find the theory. Okay, so does every group make sense? Yeah. As far as quantum field theory, every group makes sense. There are infinitely many groups, there are infinitely many quantum field theories. But it turns out there are only finite number of them which are consistent with gravity out of that same list. So you can take any group but only finite number of them, the ones who's what we call the rank of the group, the ones whose rank is less than 23. Any one bigger than rank 23 belongs to the swampland. There are infinitely many of them. They're beautiful field theories, but not when you include gravity. So then this becomes a hopeful thing. So in other words, in our universe, we have gravity, therefore we are part of that dual subset. Now, is this dual subset small or large? It turns out that subset is humongous, but we believe still finite. The set of possibilities is infinite, but the set of consistent ones, I mean the set of quantum field theories are infinite, but the consistent ones are finite, but humongous. The fact that they're humongous is the problem we are facing in string theory because we do not know which one of these possibilities is the universe we live in. If we knew, we could make more specific predictions about our universe. We don't know. And that is one of the challenges when string theory, which point on the landscape, which corner of this landscape do we live in? We don't know. So what do we do? Well, there are principles that are beginning to emerge. So I will give you one example of it. You look at the patterns of what you're getting in terms of these good ones, the ones which are in the landscape compared to the ones which are not. You find certain patterns. I'll give you one pattern. You find in all the ones that you get from string theory, gravitational force is always there, but it's always, always the weakest force. However, you could easily imagine field theories for which gravity is not the weakest force. For example, take our universe. If you take mass of the electron, if you increase the mass of electron by a huge factor, the gravitational attraction of the electrons will be bigger than the electric repulsion between two electrons. And the gravity will be stronger, that's all. It happens that it's not the case in our universe because electron is very tiny in mass compared to that. Just like our universe, gravity is the weakest force. We find in all these other ones which are part of the good ones, the gravity is the weakest force. This is called the weak gravity conjecture. We conjecture that all the points in the landscape have this property. Our universe being just an example of it. So there are these qualitative features that we are beginning to see. But how do we argue for this? Just by looking patterns? Just by looking string theory as this? No, that's not enough. We need more better reasoning, and it turns out there is. The reasoning for this turns out to be studying black holes. Ideas of black holes turn out to put certain restrictions of what a good quantum filter should be. It turns out using black hole, the fact that the black holes evaporate, the fact that the black holes evaporate gives you a way to check the relation between the mass and the charge of elementary particle. Because what you can do, you can take a charged particle and throw it into a charged black hole and wait it to evaporate. And by looking at the properties of evaporation, you find that if it cannot evaporate, particles whose mass is less than their charge, then it will never evaporate, you'll be stuck. And so the possibility of a black hole evaporation forces you to have particles whose mass is sufficiently small so that the gravity is weaker. So you connect this fact to the other fact. So we begin to find different facts that reinforce each other. So different parts of the physics reinforce each other, and once they all kind of come together, you believe that you're getting the principle correct. So weak gravity conjecture is one of the principles we believe in as a necessity of these conditions. So these are the predictions strength you are making. Is that enough? Well, it's qualitative. It's a semi quantity, it's just that mass of the electron should be less than some number. But that number is, if I call that number one, the mass of the electron turns out to be 10 to the minus 20 actually. So it's much less than one, it's not one. But on the other hand, there's a similar reasoning for a big black hole in our universe. And if that evaporation should take place, gives you another restriction, tells you the mass of the electron is bigger than 10 to the, is now in this case, bigger than something. It shows bigger than 10 to the minus 30 in the Planck unit. So you find, aha, the mass of the electron should be less than one, but bigger than 10 to the minus 30. In our universe, the mass of the electron is 10 to the minus 20. Okay, now this kind of you could call postdiction, but I would say it follows from principles that we now understand from strength theory, first principle. We are beginning to make these kinds of predictions, which are very much connected to aspects of particle physics that we didn't think are related to gravity. We thought, just take any electron mass you want. What's the problem? It has a problem with gravity. And so that conjecture has also a happy consequence that it explains that our universe, like why the heck is gravity so weak as a force? And that's not only an accident, but almost a necessity if these forces are to coexist effectively. Exactly, so that's the reinforcement of what we know in our universe, but we are finding that as a general principle. So we want to know what aspects of our universe is forced on us, like the weak gravity conjecture and other aspects. How much of them do we understand? Can we have particles lighter than neutrinos? Or maybe that's not possible. You see, the neutrino mass, it turns out to be related to dark energy in a mysterious way. Naively, there's no relation between dark energy and the mass of a particle. We have found arguments from within the swampland kind of ideas why it has to be related. And so there are beginning to be these connections between consistency of quantum gravity and aspects of our universe gradually being sharpened. But we are still far from a precise quantitative prediction like we have to have such and such, but that's the hope, that we are going in that direction. Coming up with a theory of everything that unifies general relativity and quantum field theories is one of the big dreams of human civilization, us descendants of apes wondering about how this world works. So a lot of people dream. What are your thoughts about sort of other out there ideas, theories of everything, or unifying theories? So there's quantum loop gravity. There's also more sort of, like a friend of mine, Eric Weinstein, beginning to propose something called geometric unity. So these kinds of attempts, whether it's through mathematical physics or through other avenues, or with Stephen Wolfram, a more computational view of the universe. Again, in his case, it's these hypergraphs that are very tiny objects as well, similarly as string theory, in trying to grapple with this world. What do you think, is there any of these theories that are compelling to you, that are interesting, that may turn out to be true, or at least may turn out to contain ideas that are useful? Yes, I think the latter. I would say that the containing ideas that are true, is my opinion, was what some of these ideas might be. For example, loop quantum gravity is to me not a complete theory of gravity in any sense, but they have some nuggets of truth in them, and typically what I expect to happen, and I have seen examples of this within string theory, aspects which we didn't think are part of string theory come to be part of it. For example, I'll give you one example. String was believed to be 10 dimensional, and then there was this 11 dimensional super gravity, and nobody know what the heck is that. Why are we getting 11 dimensional super gravity, whereas string is saying it should be 10 dimensional? 11 was the maximum dimension you can have a super gravity, but string was saying, sorry, we're 10 dimensional. So for a while, we thought that theory is wrong, because how could it be? Because string theory is definitely theory of everything. We later learned that one of the circles of string theory itself was tiny, that we had not appreciated that fact, and we discovered by doing thought experiments in string theory that there's gotta be an extra circle, and that circle is connected to an 11 dimensional perspective, and that's what later on got called M-theory. So there are these kind of things that we do not know what exactly string theory is, we're still learning. So we do not have a final formulation of string theory. It very well could be that different facets of different ideas come together, like loop quantum gravity or whatnot, but I wouldn't put them on par. Namely, loop quantum gravity is a scatter of ideas about what happens to space when they get very tiny. For example, you replace things by discrete data and try to quantize it and so on, and it sounds like a natural idea to quantize space. If you were naively trying to do quantum space, you might think about trying to take points and put them together in some discrete fashion in some way that is reminiscent of loop quantum gravity. String theory is more subtle than that. For example, I will just give you an example, and this is the kind of thing that we didn't put in by hand, we got it out. And so it's more subtle than, so what happens if you squeeze the space to be smaller and smaller? Well, you think that after a certain distance, the notion of distance should break down. When it goes smaller than Planck's scale, should break down. What happens in string theory? We do not know the full answer to that, but we know the following. Namely, if you take a space and bring it smaller and smaller, if the box gets smaller than the Planck's scale by a factor of 10, it is equivalent by the duality transformation to a space which is 10 times bigger. So there's a symmetry called T-duality which takes L to one over L. Well, L is measured in Planck units or more precisely, string units. This inversion is a very subtle effect. And I would not have been, or any physicist would not have been able to design a theory which has this property, that when you make the space smaller, it is as if you're making it bigger. That means there is no experiment you can do to distinguish the size of the space. This is remarkable. For example, Einstein would have said, of course I can measure the size of the space. What do I do? Well, I take a flashlight, I send the light around, measure how long it takes for the light to go around the space and bring back and find the radius or circumference of the universe. What's the problem? I said, well, suppose you do that and you shrink it. He said, well, it gets smaller and smaller. So what? I said, well, it turns out in string theory, there are two different kinds of photons. One photon measures one over L, the other one measures L. And so this duality reformulates. And when the space gets smaller, it says, oh no, you better use the bigger perspective because the smaller one is harder to deal with. So you do this one. So these examples of loop quantum gravity have none of these features. These features that I'm telling you about, we have learned from string theory. But they nevertheless have some of these ideas like topological gravity aspects are emphasized in the context of loop quantum gravity in some form. And so these ideas might be there in some kernel, in some corners of string theory. In fact, I wrote a paper about topological string theory and some connections potentially loop quantum gravity, which could be part of that. So there are little facets of connections. I wouldn't say they're complete, but I would say most probably what will happen to some of these ideas, the good ones at least, they will be absorbed to string theory, if they are correct. Let me ask a crazy out there question. Can physics help us understand life? So we spoke so confidently about the laws of physics being able to explain reality, but and we even said words like theory of everything, implying that the word everything is actually describing everything. Is it possible that the four laws we've been talking about are actually missing, they are accurate in describing what they're describing, but they're missing the description of a lot of other things like emergence of life and emergence of perhaps consciousness. So is there, do you ever think about this kind of stuff where we would need to understand extra physics to try to explain the emergence of these complex pockets of interesting, weird stuff that we call life and consciousness in this big homogeneous universe that's mostly boring and nothing is happening? So first of all, we don't claim that string theory is the theory of everything in the sense that we know enough what this theory is. We don't know enough about string theory itself. We are learning it. So I wouldn't say, okay, give me whatever, I will tell you how it works, no. However, I would say by definition, by definition, to me physics is checking all reality. Any form of reality, I call it physics. That's my definition. I mean, I may not know a lot of it, like maybe the origin of life and so on, maybe a piece of that, but I would call that as part of physics. To me, reality is what we are after. I don't claim I know everything about reality. I don't claim string theory necessarily has the tools right now to describe all the reality either, but we are learning what it is. So I would say that I would not put a border to say, no, you know, from this point onwards, it's not my territory, it's somebody else's. But whether we need new ideas in string theory to describe other reality features, for sure I believe, as I mentioned, I don't believe any of the laws we know today is final. So therefore, yes, we will need new ideas. This is a very tricky thing for us to understand. And be precise about. But just because you understand the physics doesn't necessarily mean that you understand the emergence of chemistry, biology, life, intelligence, consciousness. So those are built, it's like you might understand the way bricks work, but to understand what it means to have a happy family, you don't get from the bricks. So directly, in theory you could, if you ran the universe over again, but just understanding the rules of the universe doesn't necessarily give you a sense of the weird, beautiful things that emerge. Right, no, so let me describe what you just said. So there are two questions. One is whether or not the techniques I use in let's say quantum field theory and so on will describe how the society works. Yes. Okay, that's far distance, far different scales of questions that we're asking here. The question is, is there a change of, is there a new law which takes over that cannot be connected to the older laws that we know or more fundamental laws that we know? Do you need new laws to describe it? I don't think that's necessarily the case in many of these phenomena like chemistry or so on you mentioned. So we do expect in principle chemistry can be described by quantum mechanics. We don't think there's gonna be a magical thing, but chemistry is complicated. Yeah, indeed there are rules of chemistry that chemists have put down which has not been explained yet using quantum mechanics. Do I believe that they will be something described by quantum mechanics? Yes, I do. I don't think they are going to be sitting there in the shelves forever, but maybe it's too complicated and maybe we'll wait for very powerful quantum computers or whatnot to solve those problems. I don't know. But I don't think in that context we have new principles to be added to fix those. So I'm perfectly fine in the intermediate situation to have rules of thumb or principles that chemists have found which are working which are not founded on the basis of quantum mechanical laws which does the job. Similarly as biologists do not found everything in terms of chemistry, but they think there's no reason why chemistry cannot. They don't think necessarily they're doing something amazingly not possible with chemistry. Coming back to your question, does consciousness, for example, bring this new ingredient? If indeed it needs a new ingredient, I will call that new ingredient part of physical law. We have to understand it. To me that, so I wouldn't put a line to say, okay, from this point onwards, it's disconnected. It's totally disconnected from strength or whatever. We have to do something else. It's not a line. What I'm referring to is can physics of a few centuries from now that doesn't understand consciousness be much bigger than the physics of today where the textbook grows? It definitely will. I would say it will grow. I don't know if it grows because of consciousness being part of it or we have different view of consciousness. I do not know where the consciousness will fit. It's gonna be hard for me to guess. I mean, I can make random guesses now which probably most likely is wrong, but let me just do just for the sake of discussion. I could say, you know, brain could be their quantum computer, classical computer. Their arguments against this being a quantum thing, so it's probably classical, and if it's classical, it could be like what we are doing in machine learning, slightly more fancy and so on. Okay, people can go to this argument to no end and to say whether consciousness exists or not, or life, does it have any meaning? Or is there a phase transition where you can say, does electron have a life? At what level does a particle become life? Maybe there's no definite definition of life in that same way that, you know, we cannot say electron. I like this example quite a bit. You know, we distinguish between liquid and a gas phase, like water is liquid or vapor is gas, we say they're different, you can distinguish them. Actually, that's not true. It's not true because we know from physics that you can change temperatures and pressure to go from liquid to the gas without making any phase transition. So there is no point that you can say this was a liquid and this was a gas. You can continuously change the parameters to go from one to the other. So at the end, it's very different looking, like, you know, I know that water is different from vapor, but you know, there's no precise point this happens. I feel many of these things that we think, like consciousness, clearly, dead person is not conscious and the other one is, so there's a difference, like water and vapor. But there's no point you could say that this is conscious. There's no sharp transition. So it could very well be that what we call heuristically in daily life, consciousness is similar, or life is similar to that. I don't know if it's like that or not. I'm just hypothesizing it's possible, like there's no... There's no discrete phase. There's no discrete phase transition like that. Yeah, yeah, but there might be, you know, concepts of temperature and pressure that we need to understand to describe what the heck consciousness in life is that we're totally missing. I think that's not a useless question. Even those questions that, back to our original discussion of philosophy, I would say consciousness and free will, for example, are topics that are very much so in the realm of philosophy currently. But I don't think they will always be. I agree with you. I agree with you, and I think I'm fine with some topics being part of a different realm than physics today because we don't have the right tools. Just like biology was. I mean, before we had DNA and all that, genetics and all that gradually began to take hold. I mean, when people were beginning with various experiments with biology and chemistry and so on, gradually they came together. So it wasn't like together. So yeah, I have a perfectly understanding of a situation where we don't have the tools. So do these experiments that you think defines the consciousness in a different form and gradually we'll build it and connect it. And yes, we might discover new principles of nature that we didn't know. I don't know, but I would say that if they are, they'll be deeply connected with the else. We have seen in physics, we don't have things in isolation. You cannot compartmentalize, you know, this is gravity, this is electricity, this is that. We have learned they all talk to each other. There's no way to make them in one corner and don't talk. So the same thing with anything, anything which is real. So consciousness is real, so therefore, we have to connect it to everything else. So to me, once you connect it, you cannot say it's not reality and once it's reality, it's physics. I call it physics. It may not be the physics I know today, for sure it's not, but I would be surprised if there's disconnected realities that you cannot imagine them as part of the same soup. So I guess God doesn't have a biology or chemistry textbook and mostly, or maybe he or she reads it for fun, biology and chemistry, but when you're trying to get some work done, it'll be going to the physics textbook. Okay, what advice, let's put on your wise, visionary hat, what advice do you have for young people today? You've dedicated your book, actually, to your kids, to your family. What advice would you give to them? What advice would you give to young people today thinking about their career, thinking about life, of how to live a successful life, how to live a good life? Yes, I have three sons and in fact, to them, I have tried not to give too much advice. So even though I've tried to kind of not give advice, maybe indirectly, there has been some impact. My oldest one is doing biophysics, for example, and the second one is doing machine learning and the third one is doing theoretical computer science. So there are these facets of interest which are not too far from my area, but I have not tried to impact them in that way, but and they have followed their own interests. And I think that's the advice I would give to any young person, follow your own interests and let that take you wherever it takes you. And this I did in my own case that I was planning to study economics and electrical engineering when I started at MIT. And I discovered that I'm more passionate about math and physics. And at that time, I didn't feel math and physics would make a good career. And so I was kind of hesitant to go in that direction, but I did because I kind of felt that that's what I'm driven to do. So I don't regret it. I'm lucky in the sense that society supports people like me who are doing these abstract stuff, which may or may not be experimentally verified even let alone applied to the daily technology in our lifetime. I'm lucky I'm doing that. And I feel that if people follow their interests, they will find a niche that they're good at. And this coincidence of hopefully their interests and abilities are kind of aligned, at least some extent to be able to drive them to something which is successful. And not to be driven by things like, this doesn't make a good career, or this doesn't do that, and my parents expect that, or what about this? And I think ultimately you have to live with yourself and you only have one life and it's short, very short. I can tell you I'm getting there. So I know it's short. So you really want not to do things that you don't want to do. So I think following your interests is my strongest advice to young people. Yeah, it's scary when your interest doesn't directly map to a career of the past or of today. So you're almost anticipating future careers that could be created. It's scary. But yeah, there's something to that, especially when the interest and the ability align, that you will pave a path. That we'll find a way to make money. Especially in this society, in the capitalistic United States society, it feels like ability and passion paves the way. Yes. At the very least you can sell funny T-shirts. Yes. You've mentioned life is short. Do you think about your mortality? Are you afraid of death? I don't think about my mortality. I think that I don't think about my death. I don't think about death in general too much. First of all, it's something that I care too much about. And I think it's something that it doesn't drive my everyday action. It is natural to expect that it's somewhat like the time reversal situation. So we believe that we have this approximate symmetry in nature, time reversal. Going forward we die, going backwards we get born. So what was it to get born? It wasn't such a good or bad thing. I have no feeling of it. So who knows what the death will feel like, the moment of death or whatnot. So I don't know. It is not known. But in what form do we exist before or after? Again, it's something that it's partly philosophical maybe. I like how you draw comfort from symmetry. It does seem that there is something asymmetric here, a breaking of symmetry, because there's something to the creative force of the human spirit that goes only one way. That it seems the finiteness of life is the thing that drives the creativity. And so it does seem that at least the contemplation of the finiteness of life, of mortality, is the thing that helps you get your stuff together. Yes, I think that's true. But actually I have a different perspective on that a little bit. Namely, suppose I told you you're immortal. Yes. I think your life would be totally boring after that. Because you will not, I think part of the reason we have enjoyment in life is the finiteness of it. Yes. And so I think mortality might be a blessing, and immortality may not. So I think that we value things because we have that finite life. We appreciate things, we wanna do this, we wanna do that, we have motivation. If I told you, you know, you have infinite life, oh, I don't need to do this today, I have another billion or trillion or infinite life, so why do I do now? There is no motivation. A lot of the things that we do are driven by that finiteness, the finiteness of these resources. So I think it is a blessing in disguise. I don't regret it that we have more finite life. And I think that the process of being part of this thing, that you know, the reality, to me, part of what attracts me to science is to connect to that immortality kind of, namely the loss, the reality beyond us. To me, I'm resigned to the fact that not only me, everybody's going to die. So this gives a little bit of a consolation. None of us are going to be around. So therefore, okay, and none of the people before me are around, so therefore, yeah, okay, this is something everybody goes through. So taking that minuscule version of, okay, how tiny we are and how short time it is and so on, to connect to the deeper truth beyond us, the reality beyond us, is what sense of, quote unquote, immortality I would get. Namely, at least I can hang on to this little piece of truth, even though I know, I know it's not complete. I know it's going to be imperfect. I know it's going to change and it's going to be improved. But having a little bit deeper insight than just the naive thing around us, little Earth here and little galaxy and so on, makes me feel a little bit more pleasure to live this life. So I think that's the way I view my role as a scientist. Yeah, the scarcity of this life helps us appreciate the beauty of the immortal, the universal truths of that physics present us. And maybe one day physics will have something to say about that beauty in itself, explaining why the heck it's so beautiful to appreciate the laws of physics, and yet why it's so tragic that we die so quickly. Yes, we die so quickly. So that can be a bit longer, that's for sure. It would be very nice. Maybe physics will help out. Well, Carmen, it was an incredible conversation. Thank you so much once again for painting a beautiful picture of the history of physics. And it kind of presents a hopeful view of the future of physics. So I really, really appreciate that. It's a huge honor that you would talk to me and waste all your valuable time with me. I really appreciate it. Thanks, Lex. It was a pleasure and I love talking with you. And this is wonderful set of discussions. I really enjoyed my time with this discussion. Thank you. Thanks for listening to this conversation with Comrade Wafa. And thank you to Headspace, Jordan Homer just show, Squarespace and Allform. Check them out in the description to support this podcast. And now let me leave you with some words from the great Richard Feynman. Physics isn't the most important thing, love is. Thank you for listening and hope to see you next time.

https://youtu.be/j4_VyRDOmN4

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Daniel Kahneman: How Hard is Autonomous Driving? | AI Podcast Clips

is it seems that almost every robot-human collaboration system is a lot harder than people realize. So do you think it's possible for robots and humans to collaborate successfully? We talked a little bit about semi-autonomous vehicles, like in the Tesla, Autopilot, but just in tasks in general. If you think we talked about current neural networks being kind of system one, do you think those same systems can borrow humans for system two type tasks and collaborate successfully? Well, I think that in any system where humans and the machine interact, the human will be superfluous within a fairly short time. That is, if the machine is advanced enough so that it can really help the human, then it may not need the human for a long time. Now, it would be very interesting if there are problems that for some reason the machine doesn't, cannot solve, but that people could solve. Then you would have to build into the machine an ability to recognize that it is in that kind of problematic situation and to call the human. That cannot be easy without understanding. That is, it must be very difficult to program a recognition that you are in a problematic situation without understanding the problem. That's very true. In order to understand the full scope of situations that are problematic, you almost need to be smart enough to solve all those problems. It's not clear to me how much the machine will need the human. I think the example of chess is very instructive. I mean, there was a time at which Kasparov was saying that human machine combinations will beat everybody. Even stockfish doesn't need people. And alpha zero certainly doesn't need people. The question is, just like you said, how many problems are like chess and how many problems are the ones where are not like chess? Well, every problem probably in the end is like chess. The question is, how long is that transition period? I mean, you know, that's a question I would ask you in terms of, I mean, autonomous vehicle, just driving is probably a lot more complicated than Go to solve that. And that's surprising. Because it's open. No, I mean, you know, that's not surprising to me because there is a hierarchical aspect to this, which is recognizing a situation and then within the situation bringing up the relevant knowledge. And for that hierarchical type of system to work, you need a more complicated system than we currently have. A lot of people think because as human beings, this is probably the cognitive biases, they think of driving as pretty simple because they think of their own experience. This is actually a big problem for AI researchers or people thinking about AI because they evaluate how hard a particular problem is based on very limited knowledge, based on how hard it is for them to do the task. And then they take for granted, maybe you can speak to that because most people tell me driving is trivial. And humans, in fact, are terrible at driving is what people tell me. And I see humans and humans are actually incredible at driving and driving is really terribly difficult. So is that just another element of the effects that you've described in your work on the psychology side? No, I mean, I haven't really, you know, I would say that my research has contributed nothing to understanding the ecology and to understanding the structure of situations and the complexity of problems. So all we know is very clear that that goal, it's endlessly complicated, but it's very constrained. So and in the real world, far fewer constraints and many more potential surprises. So that's obvious because it's not always obvious to people, right? So when you think about Well, I mean, you know, people thought that reasoning was hard and perceiving was easy, but, you know, they quickly learned that actually, modeling vision was tremendously complicated and modeling, even proving theorems was relatively straightforward. To push back on that a little bit on the quickly part, Evan, it took several decades to learn that and most people still haven't learned that. I mean, our intuition, of course, AI researchers have, but you drift a little bit outside the specific AI field, the intuition is still perceptible. Oh, yeah. No, I mean, that's true. Intuitions, the intuitions of the public haven't changed radically. And they are, as you said, they're evaluating the complexity of problems by how difficult it is for them to solve the problems. And that's got very little to do with the complexities of solving them in AI.

https://youtu.be/owGn_BS--Hs

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Ariel Ekblaw: Space Colonization and Self-Assembling Space Megastructures | Lex Fridman Podcast #271

We think that self-assembly, this modular reconfigurable algorithm for constructing space structures in orbit is gonna give us this promise of space architecture that's actually worth living in. You see, do believe we might one day become intergalactic civilization? I have a hope, yeah. The following is a conversation with Ariel Edblaw, director of MIT Space Exploration Initiative. She's especially interested in autonomously self-assembling space architectures, basically giant space structures that can sustain human life and that assemble themselves out in space and then orbit Earth, Moon, Mars, and other planets. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, dear friends, here's Ariel Edblaw. When did you first fall in love with space exploration and space in general? My parents are both ex-Air Force, so my dad's an A-10 fighter pilot and my mom trained and had qualified to be a fighter pilot, but it was early enough that women were not allowed in combat at that time. And so I grew up with these two pilots and although they themselves did not become astronauts, there's a really rich legacy of Air Force pilots becoming astronauts and this loomed large in my childhood. What does it mean to be courageous, to be an explorer, to be at the vanguard of something hard and challenging? And to couple with that, my dad was a huge fan of science fiction. And so I, as a kid, read Heinlein and Isaac Asimov, all these different classics of science fiction that he had introduced me to, and that just started a love affair with space exploration and really thinking about civilization scale space exploration. So did they themselves dream about going to the stars as opposed to flying here in Earth's atmosphere, just looking up? Yeah, my dad always said he was absolutely convinced because he was a child of the Apollo years that he would get to go in his lifetime, really thought it was gonna happen. And so it was a challenge and sad for many people when to their view on the outside, space exploration slowed down for a period of time. In reality, we were just catching up. I think we leapt so far ahead with Apollo more than the rest of society was ready for. And now we're coming back to this moment for space exploration where we actually have an economy and we have the other accoutrement that society needs to be able to make space exploration more real. And my dad's thrilled because finally, not nearly, I hope not anywhere near the end of his life, but as he's an older man, he now can see still within his lifetime, people really getting a chance to build a sustainable lunar settlement on the moon or maybe even go to Mars. So settlement, civilizations and other planets, that's the cool thing to dream about in the future. It certainly is. What was the favorite sci-fi authors when you were growing up? Pablo Isaac Asimov Foundation Trilogy. This is an amazing story of Harry Seldon, this foundation that he forms at different ends of the, well, according to the story, different ends of the universe and has this interesting focus on society. So it's not just space exploration for the sake of space exploration or novel technology, which is a lot of what I work on day to day at MIT, but how do you structure a society across those vast expanses of distance and time? And so I'd say absolutely a favorite. Now though, my favorite is Neil Stevenson and Seveneves. It's a book that inspired my own PhD research and some ongoing work that we're doing with NASA now for the future of swarm robotics for spacecraft. We were saying offline about Neil Stevenson because I just recently had a conversation with him. And I said that not until I was doing the research for him that I realized he also had a role to play in Blue Origin. So it's like sci-fi actually having a role to play in the design, engineering, just the implementation of ideas that kind of percolate out from the sci-fi world and actually become reality. It's kind of a fascinating figure in that way. So do you also think about him beyond just his work in science fiction, but his role in coming up with wild, crazy ideas that actually become reality? Yes, I think it's a great example of this cycle between authors and scientists and engineers that we can be inspired in one generation by what authors dream up. We build it, we make it a reality, and then that inspires another generation of really wild and crazy thought for science fiction. I think Neil Stevenson does a beautiful job of being what we'd call a hard science fiction author. So it's really grounded in a lot of science, which makes it very compelling for me as a scientist and engineer to read and then be challenged to make that vision a reality. The other community that Neil's involved with and some of my other mentors are involved with that we are thinking about more and more in the work that we do at MIT is the Long Now Foundation. And this focus on what does society need to take in terms of steps at this juncture, this particular inflection point in human history to make sure that we're setting ourselves up for a long and prosperous horizon for humanity's horizons. There's a lot of examples of what the Long Now Foundation does and thinks about. But when I think about this in my own work, it's what does it take to scale humanity's presence in orbit? We are seeing some additional investment in commercial space habitats. So it'll no longer be just NASA running the International Space Station, but to really democratize access to space, to have, like Bezos wants to have millions of people living and working in space, you need architecture that's bigger and grander and can actually scale. That means you need to be thinking about how can you construct things for long-time horizons that are really sustainable in orbit or on a surface of a celestial body that are bigger than the biggest rocket payload fairing that we currently have available. And that's what led me to self-assembly and other models of in-space construction. Okay, every time you speak, I get like a million tangent ideas. But let me- You can cut me off, keep going. No, no, no, no, no, no, no, no, please keep talking, this is amazing. I just, there's like a million ideas. So one sort of on the dark side, let me ask. Do you think about the threats to human civilization that kind of motivate the scaling of the expansion of humans in space and on other planets? What are you worried about? Nuclear war, pandemics, super intelligent artificial intelligence systems, more not existential crises, but ones that have significant, potentially significant detrimental effects on society like climate change, those kinds of things. And then there's of course the fun ass story coming out from the darkness and hitting all Earth. There's been a few movies on that. Anyway, is there something that you think about that threatens us in this century? I mean, as an ex-military family, we used to talk about all of this. We would say that luck favors the prepared. And so growing up, we had a plan, actually a family plan for what we would do in a pandemic. Didn't think we were gonna have to put that plan into place and here we are. We do, certainly among my own family and my friends and then our work at MIT, we do think about existential threats and risks to humanity and what role does space exploration and getting humans off world have to play in a resilient future for humanity. But what I actually find more compelling recently is instead of thinking about a need to ever abandon Earth through a path of space exploration or space voyaging is to see how we can use space technology to keep Earth livable. The obvious direct ways of doing this would be satellite technology that's helping us learn more about climate change or emitters or CO2. But there's also a future for geoengineering that might be space-based. A lot of questions that would have to be answered around that, but these are examples of pivoting our focus away from maybe the Hollywood vision of, oh, an asteroid's gonna come, we're all gonna have to escape Earth to let's use our considerable technology prowess and use space technology to save Earth and be very much focused on how we can have a worthwhile life for Earth's citizens, even as some of us wanna go out and further venturing. Right, just the desire to explore the mysterious, yes. But also it does seem that by placing us in harsh conditions, the harsh conditions of space, the harsh conditions of planets, and the biology, the chemistry, the engineering, the robotics, the materials, all of that, that's just a nice way to come up with cool new things. Great forcing function, yeah. Yeah, it's a forcing, exactly, it's a forcing function like survival, you don't get this right, you die. So, and that you can bring back to Earth and it will improve, like figuring out food in space will make you figure out how to eat, live healthier lives here on Earth. So true, I mean, some of the technologies that we're directly looking at right now for space habitats, it's hard to keep humans alive in this really fragile little pocket against the vacuum and all of the dangers that the space environment presents. Some of the technologies we are gonna have to figure out is energy efficient cooling and air conditioning, air filtration, scrubbing CO2 from the air, being able to have habitats that are themselves resilient to extremes of space weather and radiation. And some of these are direct translational opportunities for areas from financial disasters. You know, people in California a decade ago would never have had to think about having an airtight house but now with wildfires, maybe you do want something close to an airtight house, how do you manage that? There's a lot of technologies from the space habitation world that we are hoping we can actually bring back down to benefit life on Earth as well in these extreme environment contexts. Okay, so you mentioned to go back to swarm. Yeah. So that was interesting to you, first of all, in your own work, but also I believe you said something that was inspiring from Neil Stephenson as well. So when you say swarm, are you thinking about architectures or are you thinking about artificial intelligence like robotics or are those kind of intermixed? I think the future that we're seeing is that they're going to be intermixed, which is really exciting. So the future of space habitats are one of intelligent structures, maybe not all the way to how, and the 2001 Space Odyssey reference that scares people about the habitat having a mind of its own. But certainly we're building systems now where the habitat has sensing technology that allows it to communicate its basic functions, you know, maintaining life support for the astronauts, but could also communicate in symbiosis with these swarm robots that would be on the outside of the spacecraft, whether it's in a microgravity orbiting environment or on the surface. And these little robots, they crawl, just a la Neil Stephenson and Seveneves, they crawl along the outside of the spacecraft looking for micrometeorite punctures or gas leaks or other faults and defects. And right now we're just working on the diagnosis. So can the swarm with its collective intelligence act in symbiosis with the spacecraft and detect things? But in the future, we'd also love for these little micro robots to repair in situ and really be like ants living in a tree all together connected to the spacecraft. Do you envision the system to be fully distributed and just like an ant colony, if one of them is damaged or, you know, whatever, loses control and all those kinds of things that that doesn't affect the performance of the complete system or doesn't need to be centralized? This is more like almost a technical question. Do you think we could- Good architecture question. Right, from the ground up, it's so scary to go fully distributed. Yes. But it's also exceptionally powerful, right? Robust, resilient to the harsh conditions of space. What do you, if you look into the next 10, 20, 100 years, starting from scratch, do you think we should be doing architecture-wise distributed systems? For space, yes, because it gives you this redundancy and safety profile that's really critical. So whether it's small swarm robots, where it doesn't matter if you lose a few of them, to habitats that instead of having a central monolithic habitat, you might actually be able to have a decentralized node of a space station so that you can kind of right out of Star Wars, you can shut a blast door if there's a fire or if there's a conflict in a certain area and you can move the humans and the crew into another decentralized node of the spacecraft. There's another idea out of Neil Stephenson's Seveneves actually where these arclets, which were decentralized spacecraft that could form and dock little temporary space stations with each other and then separate and go off on their way and have a decentralized approach to living in space. So the self-assembly component of that too, so this is your PhD work and beyond, you explored autonomously self-assembling space architecture for future space tourist habitats and space stations in orbit around Earth, Moon and Mars. There's few things I personally find sexier than self-assembling space, autonomously self-assembling space architecture. In general, it doesn't even need to be space. The idea of self-assembling architectures is really interesting, like building a bridge or something like that through self-assembling materials. It feels like incredibly efficient way to do it because optimization is built in. So you can build the most optimal structures. Given dynamic, uncertain changing conditions. So maybe can you talk about your PhD work, about this work, about Tesserae, what is it in general? Any cool stuff, because this is super cool. Yeah, yeah, absolutely. So Tesserae is my PhD research. It's this idea that we could take tiles that construct a large structure like a buckyball. Yeah, this is exactly what we're looking at here, which is the tiles that are packed flat in a rocket. They're released to float in microgravity. Magnets, pretty powerful electropermanent magnets on their edges draw them together for autonomous docking. So there's no human in the loop here, and there's no central agent coordinating, saying tile one, go to tile two. It's completely decentralized system. They find each other on their own. What we don't show in this video is what happens if there's an error, right? So what happens if they bond incorrectly? The tiles have sensing, so proximity sensing, magnetometer, other sensors that allow them to detect a good bond versus a bad bond, and pulse off and self-correct, which anybody who works in the field of self-assembly will tell you that error detection and correction, just like error detection in a DNA sequence or protein folding, is really important part of the system for that robustness. And so we've done a lot of work to engineer that ability for the tiles to be self-determining. They know whether they're forming the structure that they're supposed to form or not. They know if they're in a toxic relationship and they need to get out. Right, right, if they need to separate, exactly, yeah. All right, this is so amazing. And for people who are just listening to this, yeah, there's, I mean, how large are these tiles? So the size that we use in the lab, they can really be any size, because we can scale them down to do testing in microgravity. So we sent tiles that were about three inches wide to the International Space Station a couple years ago to test the code, test the state machine, test the algorithm of self-assembly. But now we're actually building our first ever human scale tiles. They're me-human size, so a little smaller than maybe your average human, but they're 2.5 feet on edge length. The larger scale that we would love to build in the future would actually be tiles that are big enough to form a buckyball, big open spherical volume, spherical approximation volume, that'd be about 10 meters in diameter, so 30 feet, which is much bigger and grander in terms of open space than any current module on the ISS. And one of the goals of this project was to say, what's the purpose of next generation space architecture? Should it be something that really inspires and delights people when you float into that space? Can you get goosebumps in the way that you do when you walk into a really stunning piece of architecture on Earth? And so we think that self-assembly, this modular reconfigurable algorithm for constructing space structures in orbit is gonna give us this promise of space architecture that's actually worth living in. Living in, oh, I thought you also meant from outside artistic perspective, when you see the whole thing, it's just. With the aesthetics of it, absolutely. You know when you go into Vegas or something, whenever you go into a city and it over the hill appears in front of you, and I mean, there's something majestic about seeing like, wow, humans created that. It gives you hope about like, if these a bunch of ants were able to figure out how to build skyscrapers that light up. And in general, the design of these tiles and the way you envision it are pretty scalable. Yes, and they're inspired by exactly what you mentioned a moment ago, which is we have these patterns of self-assembly on Earth, and there's a lot of fantastic MIT research that we're building this concept on. So like Daniela Rus at CSAIL and Pebbles taking the power of magnets to create units that are themselves interchangeable, this notion of programmable matter. And so we're interested in going really big with it to build big scale space structures with programmable tiles. But there's also a really fascinating, you know, end of that on the other side of the spectrum, which is how small can you go with matter that's programmable and stacks and builds itself and creates a bridge or something in the future. What do you envision the thing would look like? Like when you imagine a thing far into the future where there's, so we're not even thinking about like small space, well, let's not call them small, but are currently sized space stations, but like something gigantic. What do you envision? Is this something with symmetry, or is this something we can't even come up with yet? Is there beautiful structures that you imagine in your mind? I've got three candidates that I would love to build. If we're talking about monumental space architecture, one is, what does a space cathedral look like? It can be a secular cathedral, doesn't necessarily have to be about religion, but that notion of long sight lines, inspiring, stunning architecture when you go in. And you can imagine floating, instead of being on the ground and only looking up, in space, you could be in a central node and each direction you look at, all the cardinal directions are spires going off in a really large and long way. So that's concept number one. Number two would be something more organic that's not just geometric. So here, one of the ideas that we're working on at MIT in my lab is to say, could you, instead of the tesserae model, right? Which is self-assembling a shell, could you define a module that's a node, a small node that someone can live in, and you self-assemble a lot of those together? They're called a plesiohedrons, like space-filling solids, and you dock a bunch of them together and you can create a really organic structure out of that. So the same way that muscles accrete to appear, you can have these nodes that dock together. And one shape that I would love to form out of this is something like a nautilus, a seashell, that beautiful Fibonacci spiral sequence that you get in that shape, which I think would be a stunning and fabulous aggregated space station. You said so many cool words, plesiohedron. Yeah, plesiohedron. So that's a space-filling- Solid. The simplest thing to think of is like a cube. Oh, cubes. A cube, right? So you can stack cubes together, and if you had an infinite number of cubes, you'd fill all that space. There's no gaps in between the cubes. They stack and fill space. Another plesiohedron is a truncated octahedron, and that's actually one of the candidate structures that we think would be great for space stations. What's the truncated part? Ah, so you cut off an octahedron, actually has little pointy areas. You truncate certain sections of it, and you get surfaces that are on the structure that are cubes and I think hexagons. I have to remind myself exactly what the faces are. But overall, a truncated octahedron can be bonded to other truncated octahedrons, and just like a cube, it fills all the gaps as you build it out. So you can imagine two truncated octahedrons, they come together at an airlock, which is what we space people call doors in space, and you dock them on all sides, and you've basically created this decentralized network of space nodes that make a big space station. And once you have enough of them, and you're growing with enough big units, you can do it in any macro shape you want. That's where the nautilus comes in. It's could we design an organically inspired shape for a space station? Can I just say how awesome it is to hear you say, we space people? I know you meant people that are doing research on space exploration, space technology, but it also made me think of a future. There's Earth people, and there's those space people. And then there's the Mars people. I'd love to unite those two. Yeah, no, no, for sure, for sure. But it's like New Yorkers, and Texans, or something like that. Yeah, of course, you live for a time in New York, and then you go up to Boston, but for a time, you're the space people. Oh, I know those space people. They're kind of wild up there. Let's see how that dynamic evolves. Yeah, exactly. There's that culture, culture forms, and I would love to see what kind of culture, once you have sort of more and more civilians. I mean, there's a human. I mean, I love psychology and sociology, and I'll maybe ask you about that too, which is like the dynamic between humans. You have to kind of start considering that, and you start spending more and more time up in space, and start sending civilians, start sending bigger and bigger groups of people, and then, of course, the beautiful and the ugly emerges from the human nature that we haven't been able to escape up to this point. But when you say the plesiohedrons, these kinds of shapes, are they multifunctional? Like, is the idea you'd be able to, humans can occupy them safely, and some of them, and some others have some other purposes? Exactly. One could be sleeping quarters. One could be a greenhouse or an agricultural unit. One could be a storage depot. Essentially, all of the different rooms or functions that you might need in a space station could be subdivided into these nodes, and then stacked together. And one of the promises of both Tesserae, my original PhD research, which is these shells, and then this follow-on node concept, is that right now, we build space stations, and once they're built, they're done. You can't really change them profoundly, but the benefit of a modular self-assembling system is you can disassemble it. You can completely reconfigure it. So if your mission changes, or the number of people in space that you wanna host, if you have a space conference happening, like South by Southwest. I was thinking space party, but space conference is good, too. Then maybe all of a sudden, you want to change out what were window tiles yesterday, cupola tiles, and make them into a birthing port so that you can welcome five new spaceships to come and join you in space. That's what this promise of reconfigurable space architecture might allow us to explore. I've been hanging out with Grimes recently, and I just feel like she belongs up in space. This is like design for artists, essentially. I imagine, I mean, this is what South by keeps introducing me to, is there's like the weird and the beautiful people, and like the artists. And it feels like there's a lot of opportunities for art and design. 100%. I feel like space is a combination of arts, design, and great engineering. It's safety critical with the highest of stakes. So you can't mess it up. And is there, first of all, you're talking about tiling. So Neil Stephens is obsessed about tile. I don't know if it's related to any of this, but he seems to be obsessed with how do you tile a space. That's like a geometric notion. Like the tessellation. And it's a beautiful idea for architecture that you can self-assemble these different shapes, and you can have probably some centralized guidance of the kind of thing you want to build. But they also kind of figure stuff out themselves in terms of the low level details, in terms of figuring out when everything fits just right. For the OCD people, like, what's that subreddit? Pleasantly, it's like really fun. Everything, they have videos of everything's just pleasant when everything just fits perfectly. Very pleasing. All the tolerances come together. So they figure that out on themselves, and the local robotics problem. But by the way, was Daniela Rose Pebbles, was the Pebbles Project? Yeah, the Pebbles Project are little cubes that have EPMs in them, electropermanent magnets, and they can self-disassemble. So they'll turn off, and so you'll have this little structure that all of a sudden can flip the little pebbles over and essentially just disaggregate. They have to make some pleasing sounds. Yes. Like, pew, pew. And that's gonna, so I'm supposed to talk to Daniela, so I'll probably spend an hour just discussing the sounds on the pebbles. Okay, what were we talking about? So that's, because you mentioned two, I think. Right, my third one. Yeah, is there a third one? My third one is The Ringworld, just because every science fiction book ever that's worth anything has a Ringworld in it. Is it a donut? A donut, yeah. So a really big torus that could encircle a planet or encircle another celestial body, maybe an asteroid or a small moon. And the promise here is just the beauty of being able to have that geometry in orbit and all that surface area for solar panels and docking and essentially just all of what that enables to have a Ringworld at that scale in orbit. By the way, for the viewers, we're looking at Figure 11. What paper is this from? This is a hexagonal tiling of a torus generated in Mathematica, referencing code and approach from two citations. So we're looking at a tiled donut, and I'm now hungry. So this is the, is this from your thesis or no? This is probably, I mean, this is in my thesis. This looks like it was one of my earlier papers. This was an approach to say, great, we've come up with this tessellation approach for a buckyball. And we picked the buckyball because it is the most efficient surface area to volume shape, and what's expensive in space, the surface area, shipping up all that material. So we wanted something that would maximize the volume. But if we think about Ringworlds and other shapes, we wanted to look at how do you tile a torus, and this is one example with hexagons, to be able to say, could we take this same tesseray approach of self-assembling tiles and create other geometries? This is so freaking cool. That's awesome. So you mentioned microgravity, and I saw, I believe that there's a picture of you floating in microgravity. When did you get to experience that? What was that like? Ah, so I've flown nine times. Wow. On the affectionately known as the vomit comet. It's the parabolic flight, and essentially it does what you'd want a plane never to do. It pitches really steeply upwards at 45 degrees. Oh, that's a picture of you. Yeah, yeah. That's tesseray, that's super early in my PhD. Some of just the passive tiles, before we even put electronics in, we were just testing the magnet polarity and the, essentially, is it an energy favorable structure to self-assemble on its own? So we tweaked a lot of things between. Are we looking at a couple of them? Yeah, you're looking at a bunch of them there. It's almost 32 of them. Yeah, they're clumping. Can you comment on what's the difference between microgravity and zero gravity? Yes, so there is. Is that an important difference? It's an important difference. There is no zero gravity. There's no, nothing, there's, in the universe, there is no such thing as zero gravity. So Newton's law of gravity tells us that there's always gravity attraction between any two objects. So zero g is a shorthand that some of us fall into using, where it's a little easier to communicate to the public. The accurate term is microgravity, where you are essentially floating, you're weightless, but generally in free fall. So on the parabolic flights, the vomit comet, you're in free fall at the end of the parabola, and in orbit around the Earth, when you're floating, you're also in free fall. So that's microgravity. What was it like? So affectionately called vomit comet, I'm sure there's a reason why it's called affectionately. So what's it like? What's your first time, so both philosophically, spiritually, and biologically? What's it like? It's profound. It is unlike anything else you will experience on Earth, because it is this true feeling of weightlessness with no drag. So the closest experience you can think of would be floating in a pool, but you move slowly when you float in a pool, and your motion is restricted. When you're floating, it's just you and your body flying, like in a dream. It takes the littlest amount of energy, like a finger tap against the wall of the plane to shoot all the way across the fuselage. Wow, and you can move at full speed. You can move your arms. Exactly. So your muscles work. There's no, yeah. There's no resistance. There's no resistance. They actually tell you to make a memory when you're on the plane, because it's such a fleeting experience for your body that even a few days later, you've already forgotten exactly what it felt like. It's so foreign to the human experience. They kind of suggest that you explicitly try to really form this into a memory, and then you can do the replay. Is that for training? Cognitively freeze it, yeah. Cognitively. Yeah. Save. Right. When we have Neuralink, we can replay that. There you go. Replay that memory. So in terms of how much stress it has on your body, is it biologically stressful? You do feel a 2G pullout, right? So the cost of getting those micro G parabolas is you then have a 2G pullout, and that's hard. You have to train for it. If you move your neck too quickly in that 2G pullout, you can strain muscles, but I wouldn't say that it's actually a profound, tough thing on the body. It's really just an incredibly novel experience, and when you're in orbit, and you're not having to go through the ups and downs of the parabolic plane, there's a real grace and elegance, and you see the astronauts learn to operate in this completely new environment. What are some interesting differences between the parabolic plane and when you're actually going up in orbit? Is it that with orbit you can look out and see that blue little planet of ours? You can see the blue marble, the stunning overview effect, which is something I hope to see one day. What's also really different is if you're in orbit for any significant period of time, there's gonna be a lot more physiological changes to your body than if you just did an afternoon flight on the Vomit Comet. Everything from your bones, your muscles, your eyeballs change shape. There's a lot of different things that happen for long-duration spaceflight, and we still have to, as scientists, we still have to solve a lot of these interesting challenges to be able to keep humans thriving in microgravity or deep-duration space missions. Deep-duration space missions. Okay, let's talk about this. I was just gonna ask a bunch of dumb questions. So approximately how long does it take to travel to Mars? Asking for a friend. Asking for a friend, as we all do. About three years for a round trip. And that's not that it actually takes that long. Why the round trip? Is that? Well, you're just asking just for one way. The friend was asking about the one-way trip. Got it, got it, got it. So okay, cool. So for just like literally flying to Mars in a round, it takes three years. There's some interstitial time there because you really can only go between Earth and Mars at certain points in their orbits where it's favorable to make that journey. And so part of that three years is you take the journey to Mars a few months, six to nine months. You're there for a period of time until the orbits find a favorable alignment again, and then you come back another six to nine months. So one-way travel, six to nine months. They hang out there on vacation and come back. Forced vacation. Forced vacation. You come back. Well, me, who loves working all the time, all vacation is forced vacation. All right. So, okay, so that gives us a sense of duration, and we can maybe also talk about longer and longer and longer duration as well. What are the hardest aspects of living in space for many days, for let's say 100 days, 200 days? Maybe there's a threshold when it gets really tough. What are some stupid little things or big things that are very difficult for human beings to go through? So one big thing and one little thing. There's two classic problems that we're trying to solve in the space industry. One is radiation. It's not as much of a problem for us right now on the International Space Station because we're still protected by part of Earth's magnetosphere. But as soon as you get farther out into space and you don't have that protection once you leave the Van Allen Belt area of the Earth and the cocoon around the Earth, we have really serious concerns about radiation and the effect on human health long-term. That's the big one. The small one, and I say it's small because it seems mundane, but it actually is really big in its own way, is mental health and how to keep people happy and balanced. And you were alluding to some of the psychological challenges of having humans together on missions, and especially as we try to scale the number of humans in orbit or in space. So that's another big challenge, is how to keep people happy and balanced and cooperating. That's not an issue on Earth at all. At all. Okay, so we'll talk about each of those in a bit more detail, but let me continue on the chain of dumb questions. What about food? What's a good source for food in space? And what are some sort of standard go-to meals, menus? Right now, your go-to menu is gonna be mostly freeze-dried. Every so often, NASA will arrange for a fun stunt or fresh food to get up to station. So they did bake double tree cookies with Hilton a couple of years ago, as I recall, I think sometime before the pandemic. But there's work actually in our lab at MIT, Maggie Koblentz, one of my staff researchers, is looking at the future of fermentation. Everybody loves beer, right? Beer and wine and kimchi and miso, these foods that have just been really important to human cultures for eons, because we love the umami and the better flavor in them. But it turns out they also have a good shelf life, if done properly. And they also have an additional health benefit for the microbiome, for probiotics and prebiotics. So we're trying to work with NASA and convince them to be more open-minded to fermented food for long-duration deep space missions. That we think is one of the future elements, in addition to in-situ growing your own food. Okay, this is essential for the space party, is the space beer. Yes, it's the fermented product, yes. Okay, cool. In terms of water, what's a good source of drinkable water? Like where do you get water? Do you have to always bring it on board with you? And is there a compressed, efficient way of storing it? So to steal a line from Charlie Bolden, who's the former administrator of NASA, this morning's fresh water is yesterday's coffee. So if you think about what that means, you drank the coffee yesterday. Right, as a child. It goes fully through the body. Fully through the body as the recycling system. And then you drink what you peed out, as clarified, refined, fresh water the next day. That is one source of water. Another source of water in the near neighborhood of our solar system would be on the moon. So water ice deposits, there's also water on Mars. This is one of the big things that's bringing people to want to develop infrastructure on the moon, is once you've gotten out of the gravity well of earth, if you can find water on the moon and refine it, you can either make it into propellant or drinkable water for humans. And so that's really valuable as a potential gateway out into the rest of the solar system to be able to get propellant without always having to ship it up from earth. So how much water is there on Mars? It's a great question, I do not know. We don't know this yet, right? I know there's water at the caps. I suspect NASA, from all of the satellite studies that they've done at Mars, have a decent idea of what the water deposits look like, but I don't know to what degree they have characterized those. I really hope there's life or traces of previous life on Mars. This is a special spot in my heart because I got to work on SHERLOCK, which is the astrobiology experiment that's on Mars right now, searching for what they would say in a very cautious way is signs of past habitability. They want to be careful not to get people overly excited and say we're searching for signs of life. They're searching to see if there would have been organics on the surface of Mars or water in certain areas that would have allowed for life to flourish. And I really love this prospect. I do think within our lifetimes, we'll get a better answer about finding life in our solar system if it's there. If not on Mars, maybe Europa, one of the icy worlds. So you like astrobiology. I do. This is part of the, so it's not just about human biology, it's also other extraterrestrial alien biology. Search for life in the universe. Okay. Does that scare you or excite you? It excites me, profoundly excites me. That there's other alien civilizations potentially very different than our own? I think there's gotta be some humility there and certainly from science fiction, we have plenty of reasons to fear that outcome as well. But I do think as a scientist, it would be profoundly exciting if we were to find life, especially in the near neighborhood of our solar system. Right now, we would expect it to be most likely microbial life, but we have a real serious challenge in astrobiology, which is it may not even be carbon-based life. And all of our detectors, we only know to look for DNA or RNA. How would you even build a detector to look for silicon-based life or different molecules than what we know to be the fundamental molecules for life? And then you mentioned offline Sarah Walker. I mean, the question that she's obsessed with is even just defining life. What is life to look outside the carbon-based? I mean, to look outside of basically anything we can even imagine chemically, to look outside of any kind of notions that we think of as biology. Yeah, it's really weird. So you now get into this land of complexity, of measuring of how many assembly steps it takes to build that thing. Right. And maybe dynamic movement or some maintenance of some kind of membrane structures. We don't even know which properties life should have, whether it should be able to reproduce and all those kinds of things or pass information, genetic type of information. We don't know. And it's like, it's so humbling. I mean, I tend to believe that there could be something like alien life here on Earth, and we're just too human biology obsessed to even recognize it. The shadow biosphere, I remember you and Sarah were talking about. I mean, that's like, speaking of beer, I mean, that's something I wanted to make sure, in all of science, to shake ourselves out of reminding ourselves constantly how little we know. Because it might be right in front of our nose. I wouldn't be surprised if trees are orders of magnitude more intelligent than humans. They're just operating at a much slower scale, and they're talking shit about us the whole time, about silly humans that take everything seriously, and we start all kinds of nuclear wars, and we quarrel and we tweet about it. But the trees are always there, just watching us silly humans. Like the Ents in Lord of the Rings. Exactly. So, I mean, I don't know. I mean, obviously I'm joking on that one, but there could be stuff like that. Well, let me ask you the Drake equation, the big question. How many, like, obviously nobody knows, but what's your gut, what's your hope, as a scientist, as a human, how many alien civilizations are out there? As a ex-physicist, I'm now much more on the aerospace engineering side for space architecture, but as an ex-physicist, I hope it is prolific. I think the challenge is, if it's as prolific as we would hope, if there are many, many, many civilizations, then the question is, where are they? Why haven't we heard from them? And the Fermi paradox is there's some great filter that life only gets to some level of sophistication and then kills itself off through war, or through famine, or through different challenges that filter that society out of existence. And it would be an interesting question to try to understand, if the universe was teeming with life, why haven't we found it or heard from it yet, to our knowledge? Yeah, I personally believe that it's teeming with life, and you're right, I think that's a really useful, productive engineering and scientific question of what kind of great filter can just be destroying all of that life, or preventing it from just constantly talking to us silly descendants of apes. That's a really nice question. What are the ways civilizations can destroy themselves? And- There's too many, sadly. Well, I don't think we've come up with most of them yet. That's also probably true. That's the thing, it's... I mean, and if you look at nuclear war, some of it is physics, but some of it is game theory. It's human nature, it's how societies build themselves, how they interact, how we create and resolve conflict. And it gets back to the human question on when you're doing long-term space travel, how do you maintain this dynamical system of flawed, irrational humans such that it persists throughout time, to not just maintain the biological body, but get people from not murdering each other. Had like like each other sufficiently to where you kind of fit well. But I think if songs or poetry or books taught me anything, if you like each other a little too much, I mean, the problems arise, because then there's always a third person who also likes, and then there's the drama. It's like, I can't believe you did that and then last night, whatever. So, and then there's beer. Gets complicated quickly. It gets complicated quickly. Okay, anyway, back to the dumb questions, because you answered this. There's an interview where you answer a bunch of cool little questions from young students and so on about like space. One of them was playing music in space. Yeah. And you mentioned something about what kind of instruments you could use to play music in space. Could you mention about like does Spotify work in space? And if I wanted to do a live performance, what kind of instruments would I need? Yeah, I mean, you referenced culture before, and I think this is one of the most exciting things that we have at our fingertips, which is to define a new culture for space exploration. We don't just have to import cultural artifacts from Earth to make life worth living in space. And this musical instrument that you referenced was a design of an object that could only be performed in microgravity. Oh, cool. So it doesn't sound the same way when it's a percussive instrument, when it's rattled or moved in a gravity environment. It's unique. Can we look it up? It's called the telemetron. Yeah, it's created by. Of course it's called the telemetron. That is so awesome. Created by Sans Fish and Nicole Wouliere, two amazing graduate students and staff researchers on my team. What does it look like? It looks steampunk, actually. That's awesome. Yeah, it's a pretty cool design. It looks like it's a geometric solid that has these interesting artifacts on the inside. And it has a lot of sensors actually, additionally on the inside, like IMUs, inertial measurement sensors, that allow it to detect when it's floating and when it's not floating, and provides this really kind of ethereal, they later sonify it. So they use electronic music to turn it into a symphony or turn it into a piece. And yeah, this is the object, the telemetron. How does the human interact with it? By tossing it. So it's an interactive musical instrument. It actually requires another partner. So the idea was that it's something like a dance or just like something like a choreography in space. Got it. And then speaking of which, you also talked about sports and like ball sports, like playing soccer. So what, you mentioned that, so your muscles can move at full speed. And then if you push off the wall lightly, you fly across, zoom across. So how does the physics of that work? Can you still play soccer, for example, in space? You can, but one of the most intuitive things that we all learn as babies, right, is whenever you throw something, if I was gonna toss something to you, I'd toss it up. Because I know that it has to compensate for the fact that that Keplerian arc is gonna drop down. So equations of motion are gonna drop down. I would, in space, I would just shoot something directly towards you. So like straight line of sight. And so that would be very different for any type of ball sport, is to retrain your human mind to have that as your intuitive arc of motion or lack of arc. From your experience, from understanding how astronauts get adjusted to this stuff, how long does it take to adjust to the physics of this world, this other world? So even after one or two parabolic flights, you can gain a certain facility with moving in that environment. I think most astronauts would say maybe several days on station or a week on station, and their brain flips. It's amazing, the plasticity of the human brain and how quickly they are able to adapt. And so pretty quickly, they become creatures of this new environment. Okay, so that's cool. It's creating a little bit of an experience. What about if you go for more than 100 days for one year, for two years, for three years, what challenges start to emerge in that case? So Scott Kelly wrote this amazing book after he spent a year in space, and he's a twin. It's absolutely fantastic that NASA got to do a twin study. It's perfect. So he wrote a lot about his experience on the health side of what changed. Things like bone density, muscle atrophy, eyesight changing because the shape of your eyeball changes, which changes your lens, which changes how you see. If we're then thinking about the challenges between a year and three years, especially if we're doing that three-year trip to Mars for your friend who asked earlier, then you have to think about nutrition. And so how are you keeping all of these different needs for your body alive? How are you protecting astronauts against radiation? Either having some type of a shell on the spacecraft, which is expensive because it's heavy. If it's something like lead, a really effective radiation shell, it's gonna be a lot of mass. Or is there a pill that could be taken to try to make you less in danger of some of the radiation effects? A lot of this has not yet been answered, but radiation is a really significant challenge for that three-year journey. And what are the negative effects of radiation on the human body out in space? A higher likelihood to develop cancer at a younger age. So you'd probably be able to get there and get back, but you'd find yourself in the same way if you were exposed to significant radiation on Earth, you'd find significant bad health effects as you age. What do you think about decades? Do you think about decades? Or is this an entire human lifetime? I think about centuries. Centuries? For my space workers, but yeah, for decades. I think as soon as we get past the three-year mark, we'll absolutely want, somewhere between three years and a decade, we'll want artificial gravity. And we know how to do that, actually. The engineering questions still need to be tweaked for how we'd really implement it, but the science is there to know how we would spin habitats in orbit, generate that force, so even if the entire habitat's not spinning, you at least have a treadmill part of the space station that is spinning, and you can spend some fraction of your day in a near to 1G environment and keep your body healthy. Wait, literally from just spinning? From spinning, yes, centripetal force. That's fascinating. So you generate this force. If you've ever been in those carnival rides, the Gravitrons that spin you up around the side, that's the concept. And this is actually one of the reasons why we are spinning out a new company from my MIT lab. Spinning out, ha. Spinning out, ha. That was an accidental but well-noted space pun. It's like impossible to avoid. Dad jokes, all right. But yeah, we're spinning out a new company to look at next-generation space architecture and how do we actually scale humanity's access to space. And one of the areas that we wanna look at is artificial gravity. Is there a name yet? Yep, there's a name. We are brand new. We are just exiting stealth mode. So your podcast listeners will literally be among some of the first to hear about it. It's called Aurelia Institute. Beautiful. Aurelia is an old English word for chrysalis. And the idea with this is that we, humanity, collectively, are at this next stage of our metamorphosis, like a chrysalis, into a space-faring species. And so we felt that this was a good time, a necessary time, to think about next-generation space architecture, but also Starfleet Academy, if you know that reference from Star Trek. Yes, so let me ask a silly-sounding, ridiculous-sounding, but probably extremely important question. Sex in space, including intercourse, conception, procreation, birth, like being a parent, like raising the baby. So basically, from birth, well, from the before-birth part, like the birds and the bees and stuff, and then the whole thing. How complicated is that? I remember looking at the, thank you. I remember looking at this exact Wikipedia page, actually. And I remember being, the Wikipedia page is Sex in Space, and fascinated how difficult of an engineering problem the whole thing is. Is that something you think about, too, how to have generations of humans, self-replicating organisms? Societies, yes, societies, essentially. I guess with micro, if you solve the gravity problem, you solve a lot of these problems. That's the hope, yeah, is the central challenge of microgravity to human reproduction. But we do host a workshop every year at Beyond the Cradle, which is the space event that we run at MIT, and we always do one on pregnancy in space, or motherhood, or raising children in space, because there are huge questions. There have been a few mammal studies that have looked at reproduction in space, but there are still really major questions about how does it work, how does the fetus evolve in microgravity if you were pregnant in space? And I think the near-term answer is just gonna be, we need to be able to give humans a 1G environment for that phase of our development. Yeah, so there's some studies on mice in microgravity. And it's interesting, I think the mice, like one of them, the mice weren't able to walk, or their understanding of physics, I guess, is off, or something like that. Yeah, the mental model, when you're really young, and you're kind of getting your mental model of physics, we do think that that would change kids' abilities to if they were born in microgravity, their ability to have that intuition around an Earth-based 1G environment might be missing, because a lot of that is really crystallized in early development, early childhood development. So that makes sense that they would see that in mice, yeah. So what about life when we choose to park our vehicles on another planet, on the moon, but let's go to Mars. First of all, does that excite you, humans going to Mars, like stepping foot on Mars? And when do you think it'll happen? It does excite me. I think visionaries like Elon are working to make that happen in terms of building the road to space. We are really excited about building out the human lived experience of space once you get there. So how are you gonna grow your food? What is your habitat gonna look like? I think it's profoundly exciting, but I do think that there's a little bit of a misunderstanding of Mars anywhere in the near future being anything like a replacement for Earth. So it is good for humanity to have these other pockets of our civilization that can expand out beyond Earth, but Mars is not in its current state a good home for humanity. Too many perchlorates in the soil, you can't use that soil to grow crops. Atmosphere is too thin, certainly can't breathe it, but it's also just really thin compared to our atmosphere. A lot of different challenges that would have to be fundamentally changed on that planet to make it a good home for a large human civilization. How does a large civilization of humans get built on Mars? And where do you think it starts being difficult? So can you have a small base of like 10 people, essentially, kind of like the International Space Station kind of situation? And then can you get it to 100, to 1,000, to a million? Are there some interesting challenges there that worry you, saying that Mars is just not a good backup at this time for Earth? I think small outposts, absolutely, like McMurdo, right? So we have these models of really extreme environments on Earth, in Antarctica, for example, where humans have been able to go and make a sustainable settlement. McMurdo-style life on Mars, probably feasible in the 2030s. So we wanna send the first human missions to Mars and maybe as early as the end of this decade, more likely early 2030s. Moving anywhere beyond that, in terms of a place where like an entire human life would be lived, where it's not just you go for a three-month deployment and you come back, that is actually the big challenge line, is just saying, is there enough technological sophistication that can be brought that far out into space? If you imagine your electronics break, there's no Radio Shack. This dates me a little bit, that my mind jumps to Radio Shack. But there's no supply chains on Mars that can supply the level of technological sophistication for all the products that we rely on on day-to-day life. So you'd be going back to actually a very simple existence, more like pioneer life out West in the story of the US, for example. And I think that the future of larger scale gatherings of humans in orbit, or sorry, in space, is actually gonna be in microgravity, floating space cities, not so much trying to establish settlements on the surface. So you think sort of a significant engineering investment in terms of our efforts and money should be on large spaceships, that perhaps are doing this kind of self-assembly, all these kinds of things, and doing an orbit, maybe building a giant donut around the planet over time. Yeah, that is the goal. And I think the current political climate is such that you can't get the trillion dollar investment to build, to start from scratch, and build the sci-fi megastructure. But if you can build it in fits and starts, in little different pieces, which is another advantage of self-assembly, it's much more like how nature works. So it's biomimicry-inspired way for humanity to scale out in space. Yeah, whether it's out in space or on Mars, the idea that sort of two people fall in love, they have sex, a child is born, and then that couple has to teach that child that they came from Earth. I just love the idea that somebody's born on Mars or out in space, and you have to be like, this is not actually the original home. Just them looking at Earth and being like, this is where we came from. I don't know, that's really inspiring to me. And the child being really confused and then wanting to go back to TikTok, or whatever they do. Whatever they do in that era. I mean, there's great sci-fi, right, about people being born on Mars, and because it's a lower gravity environment, they're taller, they're more gangly, if they were actually able to develop there, and then they come back to Earth and they're like second-class citizens because they can't function here in the same way because the gravity's too strong for them. You see this in series like The Expanse with the Belters and these different societies that if we were to succeed in having human societies grow up in different pockets, it's not necessarily going to be easy for them to always come back to Earth as their home. Yeah, different cultures form, which is the positive way of phrasing it, but it's also this human history teaches us that we like to form the other. So there's this kind of conflict that naturally emerges. Let me ask another sort of dark question. What do you think about coming from a military family? There's still, sadly, wars in the world. Do you think wars, military conflicts, will follow us into space? Wars between nations. Like from my perspective currently, it just seems like space is a place for scientists and engineers to explore ideas, but the more and more progress you make, does it worry you that nations start to step in and form, you know, that go out, unfold out military conflict, whether it's in cyberspace, in space, or actual hot war? I am really concerned about that. And I do think for decades, the scientific community in space has hung on to this notion from the 1967 Outer Space Treaty, which is space is the province of all humankind, peaceful uses of outer space only. But I do think the rise in tensions and the geopolitical scene that we're seeing, I do, yeah, I do harbor a lot of concern about hot wars following humanity out into space. And it's worth trying to tie nations together with more collaboration to avoid that happening. The International Space Station is a great example. I think it's something like 18 countries are party to this treaty. It might be less, it might be more. And then of course, there's a smaller number of countries that actually send astronauts. But even at the fall of the Soviet Union and through some tense times with Russia, the ISS had been a place where the US and Russia were actually able to collaborate between Mir and ISS. I think it'd be really important right now in particular to find other platforms where these hegemonic powers in the world and developing world nations can come and collaborate on the future of space and purposefully intertwine our success so that there's a danger to multiple parties if somebody is a bad actor. So we're now talking as there's a war in Ukraine and I haven't been sleeping much. I have family, friends, colleagues in both countries and I'm just talking to a lot of people, many of whom are crying, refugees. And there's a basic human compassion and love for each other that I believe technology can help catalyze and accelerate. But there's also science. There's something about rockets. There's something about, and I mean like space exploration that inspires the world about the positive possibilities of the human species. So in terms of Ukraine and Russia and China and India and the United States and Europe and everywhere else, it seems like collaborating on giant space projects is one way to escape these wars, to escape these sort of geopolitical conflicts. I mean, there's so much camaraderie to the whole thing. And even in this little period of human history we're living through, it seems like that's essential. Even through this pandemic, there's something so inspiring about those like SpaceX rockets going up, for example. It's true. This reinvigoration of the space exploration efforts by the commercial sector. I don't know. I had some, as many of us have sort of some dark times during this pandemic, just like loneliness and sometimes emotion and anger and just hopelessness and politics. And then you look at those rockets going up and it just gives you hope. So I think that's an understated sort of value of space exploration is the thing that unites us and gives us hope. Obviously also inspires young generations of young minds to also contribute in not necessarily in space exploration, but in all of science and literature and poetry. There's something about when you look up to the stars that makes you dream. Very true. And so that's a really good reason to sort of invest in this, whether it's building giant megastructure, which is so freaking cool, but also colonizing Mars. Yeah, it's something to look forward to, something that, and not make it a domain of war, but a domain of human collaboration and human compassion, I think. Yeah. You're the founder and director of the MIT Space Exploration Initiative. It includes a ton of projects. So I just wanted to, they're focused, I guess, on life in space from astrobiology, like we talked about, to habitats. Are there some other interesting projects part of this initiative that you are, that pop to mind that you find particularly cool? Absolutely. One is the future of in-space manufacturing. So if we're gonna build large-scale space structures, yes, it's great to ship them up from Earth and self-assemble them. But what about extrusion in orbit? It's one of the best technologies to leverage in microgravity because you can extrude a particularly long beam that would sag in a normal gravity environment, but might be able to become the basis of a truss or a large-scale space structure. So we're doing miniature tests of extrusion and are excited to fly this on the International Space Station in a few months. We are working on swarm robots. We have just announced, actually, MIT's return to the moon. So my organization is leading this mission for MIT, going back to the surface of the moon as early as the end of this year, 2022, maybe early 2023, and trying to take data from our research payloads at this historic South Pole site where NASA's supposed to send the first humans back on the Artemis III mission. So our hope is to directly support that human mission with our data. How does that connect to the swarm aspects? Does it connect? Yes, yeah. So we're actually gonna fly one of the little astro-ants, that's the current plan, one of the little swarm robots on the top of a rover. That's part of the mission. Ants riding a rover? Yes, exactly, an ant riding a rover. That rover gets packed in a lander. That lander gets packed in a SpaceX rocket, so it's a whole nesting dolls situation to get to the moon. Mother of robot dragons. Yes, yeah, exactly. So this one, a swarm of one? Swarm of one, exactly. We're testing out, it's a tech demonstration mission, not a true swarm. Yeah, there they are. Those are the astro-ants. Wow, and this was a distributed system, and in theory, you could have a ton of these. Yes, these could also be centralized. So they have wireless technology that could also talk to a central base station, and we'll be assessing, kind of case by case, whether it makes sense to operate them in a decentralized swarm, or to command them in a centralized swarm. Each robot is equipped with four magnetic wheels, which enable the robot to attach to any magnetic surface, so you can operate basically in any environment. He tested the, we tested the mobility of all robots on different materials in a microgravity environment. On the vomit comet, prior to going to the moon. That must look so cool. So they're basically moving along different metallic surfaces. Yeah, exactly. It's interesting when you, just a minute ago, talking about the reflection of how space can be so aspirational and so uniting. There's a great quote from Bill Anders from the Apollo 8 mission to the moon, which is he, it's the Earthrise photo that was taken, where you see the Earth coming up over the horizon of the moon, and the quote is something along the lines of, we came all the way to discover the moon, and what we really discovered was the Earth, this really powerful image looking back. And so we're also trying to think for our lunar mission, we realize we're a very privileged group at MIT to get the opportunity to do this. How could we bring humanity along with us? And so one of the things we're still testing out, I don't know if we're gonna be able to swing it, would be to do something like a Twitch plays Pokemon, but with the robot. So let a lot of people on Earth actually control the robot, or at least benefit from the data that we're gathering and try to release the data openly. So we're exploring a couple different ideas for how do we engage more people in this mission. That would be surreal to be able to interact in some way with the thing that's out there. Exactly. On another surface. Direct connection. Direct connection. I think about artificial intelligence in that same way, which is like building robots puts a mirror to us humans. Certainly. It makes us like wonder about like, what is intelligence, what is consciousness, and what is actually valuable about human beings? When an AI system learns to play chess better than humans, you start to let go of this idea that humans are special because of intelligence. It's something else. Maybe the flame of human consciousness. It's the capacity to feel deeply, to sort of both suffer and to love, all those things. And somehow AI to me sort of puts a mirror to that. You mentioned HAL 9000, you have to bring it up, with these swarm bots crawling on the surface of your cocoon in space. I mean, all right, let me steel man the HAL 9000 perspective here. Okay. The poor guy just wanted to maintain the mission and the astronauts were, I mean, I don't know if people often talk about that, but like doctors have to make difficult decisions too. When there's limited resources, you actually do have to sacrifice human life often because you have to make decisions. And I think HAL was probably making that kind of decision about what's more important, the lives of individual astronauts or- The mission. The mission. And I feel like AI, when other humans will need to make these decisions, and it also feels like AI systems will need to help make those decisions. I don't know. I guess my question is about greater and greater collective intelligence by systems. Do you worry about that? What is the right way to sort of solve this problem, keeping a human in the loop? Do you think about this kind of stuff? Or are they sufficiently dumb now, the robots that's not yet on the horizon to think about? I think it should be on the horizon. It's always good to think about these things early because we make a lot of technical design decisions at this phase, working with swarm robots, that it would be better to have thought about some of these questions early in the life cycle of a project. There is a real interest in NASA right now, thinking about the future of human robot interaction, HRI, and what is the right synergy in terms of level of control for the human versus level of dependence or control for the robot. And we're beginning to test out more of these scenarios. For example, the Gateway Space Station, which is meant to be in orbit around the moon as a staging base for the surface operations, is meant to be able to function autonomously with no humans in it for months at a time, because they think it's gonna be seasonal. They think we might not be constantly staffing it. So this would be a really great test of, I don't know that anybody's yet worried about HAL 9000 evolving, but certainly just the robustness of some of these AI systems that might be asked to autonomously maintain the station while the humans are away. Or detection algorithms that are gonna say, if you had a human pilot, they might see debris in orbit and steer around it. There'll be a lot of autonomous navigation that has to happen. That'll be one of the early test beds where we'll start to get a little bit closer to that future. Well, the HRI component is really interesting to me, especially when the I includes almost friendship, because people don't realize this, I think, that we humans long for connection. And when you have even a basic interaction that's just supposed to be just serving you or something, you still project, it's still a source of meaning and connection. And so you do have to think about that. I mean, HAL 9000, the movie maybe doesn't portray it that way, but I'm sure there's a relationship there between the astronauts and the robot, especially when you have greater and greater level of intelligence. Maybe that addresses the happiness question too. Yeah, I think there's a great book by Kate Darling, who's one of my colleagues at MIT. Yeah, she's amazing. She's already been on this podcast, but we talk all the time and we're supposed to talk and we've been missing each other and we're gonna make it happen soon. Yeah. Come down to Texas, Kate. All right. Anyway, yeah, she's amazing. And she has this book, her whole work is about this. Connection with robots, yeah. This beautiful connection that we have with robots, but I think it's greater and greater importance when it's out in space because it could help alleviate some of the loneliness. Right. One of the projects in the book that I gave you, which is a catalog of the projects that we've worked on over the last five years is the social robot that was developed at the Media Lab. And one of the first years in 2017 that we flew a zero-g flight, we took the social robot along and tried to do a little bit of a very scaled down human study to look at these questions because you do imagine that we would form a bond, a real bond with the social robots that might be not just serving us on a mission, but really be our teammates on a future mission. And I do think that that could have a powerful role in the mental health and just the stability of a crew is to have some other robot friends come along. What do you, by the way, the book you mentioned is Into the Anthropocosmos, a whole space catalog from the space catalog. Get that reference. Yeah, so call out to Earth catalog, a whole space catalog from the MIT Space Exploration Initiative. What about the happiness? You said that that's one of the problems of when you're out in space. How do you keep humans happy? Again, asking for a friend. Yes. I mean, one of the big challenges is you can't just open a window or walk out a door and blow off steam, right? You can't just go somewhere to clear your head. And in that sense, you need to build habitats that are homes that really care for the humans inside them and have, whether it's biophilia and a place where you can go and feel like you're in nature or a VR headset, which for some people is a poor simulcrum, but is maybe better than nothing. You need to be thinking about these technological interventions that are gonna have to be part of your home and be part of your maybe day-to-day ritual to keep you steady and balanced and happy or feeling fulfilled. What about other humans, relationship with other humans? Do those get weird when you get past a certain number of humans? I'm not an expert in this area, but an anecdote that I'll share, my understanding is that NASA has still not decided whether it's better to send married couples or single crew members in terms of you want some level of stability, you don't wanna have the drama of romantic relationships like you're alluding to before, but they can't decide because married couples also fight and have a really tough dynamic. And so there's a lot of open questions still to answer about what is the ideal psychological makeup of a crew? And we're starting to test some of these things with the civilian crews that are going up with Inspiration4, like last fall with SpaceX and Axe-1 that's gonna fly in a few days here in March. As we begin to lengthen the time of those civilian crews, I think we'll start to learn a little bit more about just average everyday human-to-human dynamics and not the astronauts that are themselves selected to be perfect human specimens, very good to work with, easy to get along with. I wish we collected more data about this pandemic because I feel like it's a good rough simulation of what it'd be like out in space. A lot of people were in lockdown, some married couples. I think a lot of marriages broke up, a lot of marriages got closer together. And then the single people, some of them went off the cliff and some of them discovered their new happiness and meaning and so on. It's a beautiful little experiment, a painful one. Is there a thorough way to really test that? Because it's such a costly experiment to send humans up there, but I guess you can always return back to Earth if it's not working out. That's what we hope. That's what we hope. You don't have like a Apollo 13 situation that doesn't quite make it back. But yeah, this is also why Mars is such a challenge. The moon is only three days away. That's a lot quicker to recover from if there's a psychological problem with the crew or any type of maintenance problem, anything. Three years is such a challenge compared to these other domains that we've been getting more used to in terms of human space flight. So this is a question that we will need to have explored more before we start really sending crews to Mars. So you're a young scientist. Do you think in your lifetime, you will go out into orbit, you will go out beyond into deep space and potentially step, you, I don't know if you can call yourself a civilian. I don't know if that's what you count as, but you as a curious aunt from MIT, land, step on Mars. Yes. That's a firm- Are you coming back? Firm yes. Yeah, I'm coming back. I don't want that one-way mission. I want the two-way mission. But yes. I think we're already talking about a pretty near-term opportunity where I could send graduate students to the International Space Station. Yeah, yeah, yeah. So no, not a sacrifice. No, but send graduate students- For the experience. For the experience. Send graduate students to the ISS to do their research. I do think you and I both would have an opportunity to go to a lunar base of some sort within our lifetime. And there's a good chance if we really wanted to, we might have to really advocate for it, apply to an astronaut program. There will be some avenues for humans in our lifetime to go to Mars. What's the bar for health? Do you think that bar will keep getting lower and lower in terms of how healthy, how athletic, like how the psychological profile, all those kinds of things? Yeah, for one, we're gonna build more robust habitats that don't depend on astronauts being so impeccably well-trained. So we're gonna make it better for inclusion and just opening access to space. But there's a fantastic group called Astra Access that is already helping disabled space flyers do zero-G flights and potentially get access to the ISS. And some of the things that we think of as disabilities on Earth are hyper abilities in space. You don't need really powerful legs in space. What you'd really benefit from having is a third arm, more ways to kind of move yourself around and grip and interact. So we are already seeing a much more open-minded approach to who gets to go to space and Astra Access is a wonderful organization doing some of that work. I'm hoping introversion will also be a superpower in space. Okay, well, first I'd love to get your opinion on commercial space flight, what SpaceX, what Blue Origin are doing. And also another question on top of that is, because you've worked with a lot of different kinds of people, culturally, what's the difference between SpaceX or commercial type of efforts? NASA and MIT. And academia. Academia. Yeah, so the first part of your question, I am thrilled by all of the commercial activity in space. It has really empowered our program. So instead of me waiting for five years to get a grant and get the money from the grant and only then can you send a project to space, I got my fundraise a lot like a startup founder and I directly buy access to space on the International Space Station through SpaceX or NanoRacks, same with Blue Origin and their suborbital craft, same with Axiom now, Axiom's making plans for their own commercial space station. It's not out of the realm of possibility, but in a few years, I will rent lab space in orbit. I will rent a module from the Axiom space station or the orbital reef, which is the Blue Origin space station, or NanoRacks is thinking about Starlab Oasis. There's probably some other companies that I'm not even aware of yet that are doing commercial space habitat. So I think that's fabulous and really empowering for our research. Is it affordable? So like loosely speaking, does it become affordable for like MIT type of research lab? Does it, you know, or does it need to be a multi-university, like a gigantic effort? A consortium thing. A consortium thing. One of the reasons we're spinning out Aurelia is we actually realized it's cheap enough, it doesn't even have to be MIT. And we wanted to start democratizing access to these spaceflight opportunities to a much broader swath of humanity. Could you take a, you know, Khan Academy educational course about, hey, students around the world, this is how you get ready for a zero-g flight. And by the way, come fly with us next year, which is something we're gonna do with Aurelia. We're gonna bring, you know, much more just kind of day-to-day folks on zero-g flights and get them access to engaging in the space industry. So it's become cheap enough and the prices have dropped enough to consider even that. So that's amazing. It definitely doesn't have to be a consortium of universities anymore. Depends on what you wanna fly. If you wanna fly James Webb, a huge telescope that's decades in the making, sure, you need a NASA allocation budget. You need billions. But for a lot of the stuff in the book and our research portfolio, it's actually becoming far more accessible. So that's commercial. What about NASA and MIT academia? Yeah, I think, you know, people have been worried about NASA the last few years because in some people's minds, they are ceding ground to these commercial efforts, but that's really not what's happening. NASA empowered these commercial efforts because they wanna free themselves up to go to Mars and go to Europa and continue being that really aspirational force for humanity of pushing the boundary, always pushing the boundary. And if they were anchored in low-Earth orbit, maintaining a space station indefinitely, that's so much a part of their budget that it was keeping them from being able to do more. So it actually is really fantastic for NASA to have grown this commercial ecosystem and then that frees NASA up to go further. And in academia, we like to think that we will be able to do the provocative next-generation research that is going to unlock things at that frontier. And we can partner with NASA. We can go through a program if we wanna send a probe out really far, but we can also partner with SpaceX and see what human life in a SpaceX-Mars settlement might look like and how we could design for that. Speaking of projects, maybe are there other projects that pop to mind from the Space Exploration Initiative or maybe stuff from the book that you can mention? Something super cool? I mean, everything we've been talking about is cool, but just something that pops to mind again? Yeah, so we talked about life in space and you might need more arms than legs. One of the projects by Valentina Sumini was an air-powered robotics tail. So it's a soft robotics tail that essentially has a little camera on the back end of it, can do computer vision, and knows where to grapple, so it's behind you. It grapples onto something and holds you in space and then you can actually free up both of your hands to work so we're already starting to think about the design of bionic humans or prosthetics or things that would make you kind of like a cyborg to augment your capabilities when you're in a space environment. How would you control something like that? So it's kind of like a, I mean, you can't call it a leg, but whatever, it's a- An additional appendage. Appendage, so how would you, what are ideas for controlling something like that? Yeah, so right now it's super, yeah, there you go. That's cool. Right now it's super manual. It's basically just like a kind of a set pattern of inflating as we're testing it, but in the future, if we had a Neuralink, I mean, this is something that you could imagine directly controlling, just thinking thoughts and controlling it. That's a ways away. Yeah, so we talked about on the biology side, astrobiology, there's probably agriculture stuff. Is there other things that kind of feed the ecosystem of out in space for survival, or the robotics architectures, the self-assembly stuff? So kind of combining something we were talking about, you can form these relationships with objects and anthropomorphize. One of the things that we're thinking about for agriculture created by Manwe and Somu, so two students at MIT, was this little, it looks like a planet, but it's inspired by, I think, a mandala or Nepalese spinning wheel, and you plant plants on the inside and the astronaut has to spin it every day to help the plant survive. So it's a way to give the astronaut something to care about, something that they are responsible for keeping alive and can really invest themselves in. And it's not necessary, right? We have other ways to grow in orbit, hydroponics, liquid medium, trying to keep the liquid around the plant roots is hard because there's no gravity to pull it down in a particular direction. But what I loved about this project was they said, sure, we have ways that the plants could grow on their own, but the astronauts might wanna care for it in the same way that we have little plants that come to be important to us, little plant friends. Yeah, so there's agri-fuge, that's an early model of this manually spinning plant habitat. I guess this is the best of academic research is you can do these kinds of wild ideas. Wild ideas, yeah. Well, I get to spend quite a bit of time with Mr. Elon Musk and he's very stressed, especially about Starship and all those kinds of engineering efforts. Yeah. What do you think about how damn hard it is to get out of space? Like, are we humans gonna be able to do this? I don't know, I think it feels like it's an engineering problem, it's a scientific problem, but it's also just a motivation problem for the entire human species. And you also need to have superstar researchers and engineers working on it. So you have to get the best people in the world, inspire them, and starting from a young age and kinda- It's inculcating us into why we do it. I mean, I guess this way it's exciting. You don't know if we're gonna be able to pull this off. Like, we could fail miserably. And that, I suppose, I mean, that's where the best of engineering is done, is like success is not guaranteed. And even if it happens, it might be very painful. I think that's what's so special about what Elon is doing with SpaceX is he takes these risks and he tests iteratively and he'll see the spectacular failures on the path to a successful Starship. It's something that people have said, why isn't NASA doing that? Well, that's because NASA is doing that with taxpayer dollars and we would all revolt if we saw NASA failing at all these different stages. But that level of spiral engineering theory of development isn't super impressive. And it's a really interesting approach that SpaceX has taken. And I think between people like Elon and Jeff Bezos and Firefly and NASA and ESO, we are gonna get there. They're building the road to space. These trailblazers are doing it. And now part of the challenge is to get the rest of the public to understand that it's happening. A lot of people don't know that we're going back to the moon, that we're gonna send the first woman to the moon within a few years. A lot of people don't know that there are commercial space stations in orbit, that it's not just NASA that does space stuff. So we have a big challenge to get more of humanity excited and educated and involved again, kind of like in the Apollo era where it was a big deal for everybody. Well, a lot of that is also one of the big, impressive things that Elon does, I think, extremely well is the social media, is the getting people excited. And I think that actually, he's helped NASA step their game up in terms of social media. There's something about, yeah, the storytelling, but also not like authentic and just real and raw engineering. There's a lot of excitement for that. Humor and fun also. All of those things you realize, the thing that make up the virality of the meme is beautiful. You have to kind of embrace that. And to me, this kind of, I criticize a lot of companies based on this. I talked to a bunch of CEOs and so on, and it's just like, there's a caution. Like, let us do this press conference thing where when the final product is ready and it's overproduced as opposed to the raw, the gritty, just show it off. And it's something that I think MIT is very good at doing, is just showing the raw by nature, the mess of it. And the mess of it is beautiful, and people get really excited, and failure is really exciting. When the thing blows up and you're like, oh shit, that makes it even more exciting when it doesn't blow up. And doing all of that on social media and showing also the humans behind it, the individual young researchers or the engineers or the leaders where everything's at stake. I don't know. I think I'm really excited about that. I do want MIT to do that more for students to show off their stuff and not be pressured to do this kind of generic official presentation, but show their, become a YouTuber also. Like, show off your raw research as you're working on it in the early days. I hope that's the future. Things like, I was teasing about TikTok earlier, but these kinds of things, I think, inspire young people to show off their stuff, to show their true self, the rawness of it. Because I think that's where engineering is best. And I think that will inspire people about all the cool stuff we could do in space. I should say, I couldn't agree more. And I actually think that this is why we need a real life Starfleet Academy right now. It was the place where the space cadets got to go to learn about how to engage in a future of life in space. And we can do it in a much better way. There are a bunch of groups that traditionally haven't thought that they could engage in aerospace. Whether it's because you were told you had to be into math and science. Now we need space lawyers, we need space artists like Grimes, right? We need really creative, profoundly interesting people to want to see themselves in that future. And I think it's a big challenge to us in the space industry to also do some more diversity, equity, and inclusion, and show a broader swath of society that there's a future for them in this space exploration vision. Let me push back on one thing. We don't need space lawyers. I'm just kidding. Okay, it's a joke. We do, we do, we do. Okay, we do. The lawyers are great, I love them. Okay, let me ask a big, ridiculous question. What is the most beautiful idea to you about space exploration? Whether it's the engineering, the astrobiology, the science, the inspiration, the human happiness, or aliens, I don't know. What do you, like, inspires you every day in terms of its beauty, in terms of its awe? As a ex-physicist, what I've always found so profound is just that at really, really small scales, like particle physics, and really, really big scales, like astrophysics, there are similarities in the way that those systems behave and look, and there's a certain beautiful symmetry in the universe that's just kind of waiting for us to tie together the physics and really understand it. That is something that just really captivates me, and I would love to, even though I'm now much more on the applied space exploration side, I really try to keep up with what's happening in those physics areas, because I think that will be a huge answer for humanity along the lines of, are we alone in the universe? One of the fascinating things about you is you have a degree in physics, mathematics, and philosophy, and now, I don't know, what do you wanna, what would you call it, aerospace engineering maybe kind of thing? So you have it afoot in all of these worlds, the theoretic, the beauty of that world, and the philosophy somehow is in there, and now the very practical, pragmatic implementation of all these wild ideas, plus your incredible communicator, all of those things. What did you pick up from those different disciplines? Or maybe I'm just romanticizing all those different disciplines. But what did you pick up from the variety of that physics, mathematics, philosophy? What I loved about having this chance to do a liberal arts education was trying to understand the human condition, and I think more designers for space exploration should be thinking about that, because there's so much depth of, like we were talking about, issues and opportunities around human connection, human life, meaning in life, how do you find fulfillment or happiness? And I think if you approach these questions just purely from the standpoint of an engineer or a scientist, you'll miss some of what makes it a life worth living. And so I love being able to combine some of this notion of philosophy and the human condition with my work. But I'm also a pragmatist, and I didn't wanna stay just purely in these big picture questions about the universe. I wanted to have an impact on society, and I also felt like I had such a wonderful childhood and a really fantastic setup that I owe society some work to really make a positive impact for a broader swath of citizens. And so that kind of led me from the physics domain to thinking about engineering and practical questions for life in space. In physics, was there a dream? Are you also captivated by this search for the theory of everything that kind of unlocks the deeper and deeper, in the simple, elegant way, the function of our universe? Do you think that'll be useful for us for the actual practical engineering things that you're working on now? It could be. I mean, I worked at CERN for two summers in undergrad, and we were looking for supersymmetry, which was one of these alternatives to the standard model. And it was sad because my professors were getting sadder and sadder because they weren't finding it. They were excluding what we would call this parameter space of finding these supersymmetric particles. But the search for what that theory of everything could be, or a grand unified theory that kind of answers some of the holes within the standard model of physics, would presumably kind of unlock a better understanding of certain fundamental physical laws that we should be able to build a better understanding of engineering and day-to-day services from that. It might not be an immediately obvious thing. When we discovered the Higgs, the Higgs boson, I was there at CERN that day. It was July 4th, 2012 that it was announced. We all waited like nerds overnight in line to get into the announcement chamber. I'd never waited for even like a Harry Potter premiere in my life, but we waited for this like announcement of the Higgs boson to get into the chamber overnight. But did that immediately translate to technology for engineering? No, but it's still a really important part of our understanding of these fundamental laws of physics. And so I don't know that it's always immediate, but I think it is really critical knowledge for humanity to seek. It might just shake up understanding of the world. What scares me is it might help us create more dangerous weapons. So, and then we'll figure out that great filter situation. And I still believe that human compassion and love is actually the way to defend against all these greater and greater and more impressive weapons. Let me ask a weird question in terms of you disagreeing with others. What important idea do you believe is true that many others don't agree with you on? Maybe it's a tough question. You might have to think about that one, but it was very specific, like which material to use or something about a particular project, or it could be grand priorities on missions. I think one you actually mentioned is interesting is like the thing we should be looking for is like colonization of space versus colonization of planets, meaning like- Yes, that's probably my best hot take that people would disagree with me on is life in floating cities as opposed to life on the surface. How do you envision that like spread of humans? Because you said at the beginning of the conversation something about like scale, increasing the scale, basically humans in space. Are they just like in, they're in orbit, and then they get a little farther and farther out? Like do you see these kind of floating cities just getting farther and farther from Earth that can always kind of return? But like if you look a few centuries from now, do you just see all these like floating cities? Like Namibia? Yeah, and it just kind of envelops the space around us in these like neighborhoods. Yeah, yeah, in these neighborhoods. It's like rural, and there's like giant structures, and there's small pirate structures and that kind of stuff. Pirate structures, yeah. I think low Earth orbit might come to look like that, and it's a really interesting regulatory challenge to make sure that there's some cross purposes. So the more cool space cities we have in orbit, the more shiny objects in the night sky, the worse it is for astronomers in a really kind of overly simplified case. So there's some pushback to this like amoeba-ing where we just grow kind of incongruously or indiscriminately as an amoeba in low Earth orbit. Beyond that though, I think we'll grow in pockets where there are resources. So we won't just expand around the gravity well of Earth. We'll do some development around the moon, some development around asteroids, some development around Mars, because there'll always be purposes for which we wanna go down to a physical object and study it or extract something or learn from it. But I think we'll grow in fits and starts in pockets. Some of the coolest pockets are the gravity balanced pockets like the Lagrange points, which is where we just sent, we, not me personally, but NASA just sent James Webb, the big telescope, I think it's at L2. What's the nice feature about those pockets? So it's a stable orbit. There are several different Lagrange points. And so it just requires less energy to stay where you're trying to stay. Yeah, that's fascinating. What's also fascinating is the interaction between nations. That was gonna be- On that regard, like who owns that? Would you say in those floating cities, do you envision independent governments? That was gonna be my next answer to you, which pushed me harder for a more provocative question where I might disagree with other people. I don't yet have my own opinions fully formed on this, but we are trying to figure out right now what happens to the moon with all of these first come first served actors just arriving and setting precedents that might really affect future access. And one example is property rights. We do want companies that have the expertise to go to the moon and mine stuff that will help us develop a human settlement there or a gateway, but companies need to know generally that they have rights to a certain area or that they have some legal right to sell things that they're getting. Does that mean we're gonna grant property rights on the moon to companies? Who has the right to give that right away? So there's a bunch of really kind of gnarly questions that we have to think about, which is why I think we need space lawyers. Maybe that's the true provocative answer is I think we need space lawyers. True. I mean, yeah, yeah. But those questions again, as you said eloquently, will help us answer questions about here. We hope so, yeah. It is a little strange. I mean, it's obvious, but it's also strange if you look at the big picture of it all that we draw these borders around geographical areas and we say, this is mine. And then we fight wars over what's mine and not. It seems like there's possible alternatives, but also it seems like there needs to be a public ownership of some parts. Something. Like, what is it, Central Park in New York? Is there something like preserving? The commons. Yeah, the commons. The commons. That's why we titled the book Into the Anthropocosmos. We know it's a long and kind of a mouthful, but this notion of the Anthropocene. We have a lot of commons problems in humanity. How are we treating the earth? Global climate change. How are we gonna treat and behave in space? How can we be responsible stewards of the space commons? And I would love to see an approach to the moon that is commons-based, but it's hard to know who would be the protector or the enforcer of that. And if it's, which it will be probably in the early days, a lot of companies sort of working on the moon, working on Mars, working out in space, it feels like there still needs to be a civilian representation of like the greater effort or something like that. Like where there should be a president, there should be a democracy of some kind where people can vote. Some representative government. Those are all again, the same human questions. What advice would you give to a young person today thinking about what they wanna do with their life, career? So somebody in high school, somebody in college, maybe somebody that looks up to the stars and dreams to one day take a one-way ticket to Mars or to contribute something to the effort. I'd say you should feel empowered because it's really the first time in human history that we're at this cusp of interplanetary civilization. And I don't think we're gonna lapse back from it. So the future is incredibly bright for young people that even younger than you and I who will actually really get a chance to go to Mars for certain. The other thing I would say is be open-minded about what your own interests are. I don't think you anymore have to be shoehorned into a particular career to be welcomed into the future of space exploration. If you are an artist and that is your passion, but you would love to do space art, or if not space art, use your artistry to communicate a feeling or a message about space, that's a role that we desperately need just as much as we need space scientists and space engineers. Well, when you look at your own life, you're an incredibly accomplished scientist, young scientist, and you hopped around from physics to aerospace. So going from the biggest theoretical ideas to the biggest practical ideas, is there something from your own journey you can give advice to, like how to end up doing incredible research at MIT? Maybe the role of the university and college and education and learning, all that kind of stuff. I'd say one piece of advice is find really good teammates because I get to be the one that's talking to you, but there are 50 graduate students, staff, and faculty that are part of my organization back at MIT. And I'm actually, you guys can't see it on camera, but I'm sitting here with my co-founder and COO, Danielle DeLatte. And that is really what makes these large-scale challenges for humanity possible, is really fantastic teams working together to scale more than what I could do alone. So I think that that's an important model that we don't talk about enough in academia. There's a big push for this lone wolf genius figure in academia, but that's certainly not been the case in my life. I've had wonderful collaborators and people that I work with along the team. Also cross-disciplinary. Absolutely, yeah, cross-disciplinary, interdisciplinary, whatever you wanna call it. Artists, where do artists come in? Do you work with artists? We do, we have an arts curator on the Space Exploration Initiative side. She helps make sure, partly around that communication challenge that we talked about, that we're not just doing zero-G flights and space missions, but that we take our artifacts of this sci-fi space future to museums and galleries and exhibits. She pushed me to make sure, her name is Xing Liu, she pushed me for our first ISS mission. I was just gathering all the engineering payloads that I wanted to support for the students to fly, including my own work. And she said, you know what, we should do an open call internationally for artists to send something to the ISS. And we found out it was the first time. We were the first ever international open call for art to go to the ISS. And that was thanks to Xing, an artist, bringing a perspective that I might not have thought about prioritizing. Yeah, that's awesome. So when you look out there, it's the flame of human consciousness. There does seem to be something quite special about us humans. Well, first of all, what do you think it is? What's consciousness? What are we trying to preserve here? What is it about humans that should be preserved or life here on earth? What gives you hope to try to expand it out farther and farther? What makes you sad if it was all gone? I think we're a remarkable species. I think we're a remarkable species that we are aware of our own thoughts. We are meta aware of our own thoughts and of ourselves. And are able to speak on a podcast about a meta awareness about our own thoughts. About our own thoughts, yeah, turtles all the way down. I think that that is a really special gift that we have been given as a species and that there's a worth to expanding our circles of awareness. So we're very aware of as an earth-based species, we've become a little bit more aware of the fragility of earth and how special a place it is when we go to the moon and we look back. What would it mean for us to have a presence and our purpose in life as a inter-solar system species or eventually an intergalactic species? I think it's a really profound opportunity for exploration for the sake of exploration. A real gift for the human mind. Yeah, for anything we're curious creatures. So you do believe we might one day become intergalactic civilization? Long, long time from now. We have a lot of propulsion challenges to answer to get that far. So you have a hope for this. Yeah. Another big ridiculous question building on top of that, what do you think is the meaning of life? This individual life of ours, your life, that unfortunately has to come to an end as far as we know for now. Yeah. And our life here together. Is there a why? Or do we just kinda let our curiosity carry us away? Oh, interesting. Is there a single kind of driving purpose why or can it just be curiosity based? I certainly feel, and this is not the scientist in me talking but just more of like a human soul talking, I certainly feel some sense of purpose and meaning in my life. And there's a version of that that's a very local level within my family, which is funny because this whole conversation has been big, grand space exploration themes, but you asked me this question and my first thought is what really matters to me, my family, my biological reproducing unit. But then there's also another purpose, like another version of the meaning in my life that is trying to do good things for humanity. So that sense that we can be individual humans and have our local meaning, and we can also be global humans, maybe someday like the Star Trek Utopia will all be global citizens. I don't wanna sound too naive, but there is, I think, that beauty to a meaning and a purpose of your life that's bigger than yourself, working on something that's bigger and grander than just yourself. The deepest meaning is from the local biological reproduction unit, and then it goes to the engineering, scientific, what is it, corporate, like company unit that can actually produce and compete and interact with the world. And then there's the giant human unit that's struggling with pandemics. And commons. And together struggling against the forces of nature that keeps wanting to kill us. Yeah, there'd be nothing like an alien invasion to unite the planet, we think. I can't wait, bring it on, aliens. Listen, your work, you're an incredible communicator, incredible young scientist, Sarah, it's a huge honor that you would spend your time with me. I can't wait what you do in the future. And thank you for representing MIT so beautifully, so masterfully, you're an incredible person. Thank you for talking to me. Thank you so much for having me. It's been an absolute pleasure, it's a great conversation. Thanks for listening to this conversation with Ariel Ekblom. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Seneca, the Roman Stoic philosopher. There is no easy way from earth to the stars. Thank you for listening and hope to see you next time.

https://youtu.be/KW8Vjs84Fxg

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Ayanna Howard: Human-Robot Interaction & Ethics of Safety-Critical Systems | Lex Fridman Podcast #66

The following is a conversation with Ayana Howard. She's a roboticist, professor at Georgia Tech, and director of the Human Automation Systems Lab, with research interests in human-robot interaction, assistive robots in the home, therapy gaming apps, and remote robotic exploration of extreme environments. Like me, in her work, she cares a lot about both robots and human beings, and so I really enjoyed this conversation. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcast, follow on Spotify, support it on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. I recently started doing ads at the end of the introduction. I'll do one or two minutes after introducing the episode, and never any ads in the middle that can break the flow of the conversation. I hope that works for you, and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. I personally use Cash App to send money to friends, but you can also use it to buy, sell, and deposit Bitcoin in just seconds. Cash App also has a new investing feature. You can buy fractions of a stock, say $1 worth, no matter what the stock price is. Brokerage services are provided by Cash App Investing, a subsidiary of Square and member SIPC. I'm excited to be working with Cash App to support one of my favorite organizations called FIRST, best known for their FIRST Robotics and Lego competitions. They educate and inspire hundreds of thousands of students in over 110 countries, and have a perfect rating, a charity navigator, which means that donated money is used to maximum effectiveness. When you get Cash App from the App Store or Google Play, and use code LEXPODCAST, you'll get $10, and Cash App will also donate $10 to FIRST, which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world. And now here's my conversation with Ayana Howard. What or who is the most amazing robot you've ever met, or perhaps had the biggest impact on your career? I haven't met her, but I grew up with her. But of course, Rosie. So, and I think it's because also- Who's Rosie? Rosie from the Jetsons. She is all things to all people, right? Think about it, like anything you wanted, it was like magic, it happened. So people not only anthropomorphize, but project whatever they wish for the robot to be onto. Onto Rosie. But also, I mean, think about it. She was socially engaging. She every so often had an attitude, right? She kept us honest. She would push back sometimes when, you know, George was doing some weird stuff. But she cared about people, especially the kids. She was like the perfect robot. And you've said that people don't want the robots to be perfect. Can you elaborate that? What do you think that is? Just like you said, Rosie pushed back a little bit every once in a while. Yeah, so I think it's that. So if you think about robotics in general, we want them because they enhance our quality of life. And usually that's linked to something that's functional. Right? Even if you think of self-driving cars, why is there a fascination? Because people really do hate to drive. Like there's the, like Saturday driving where I can just speed, but then there's the, I have to go to work every day and I'm in traffic for an hour. I mean, people really hate that. And so robots are designed to basically enhance our ability to increase our quality of life. And so the perfection comes from this aspect of interaction. If I think about how we drive, if we drove perfectly, we would never get anywhere. Right? So think about how many times you had to run past the light because you see the car behind you is about to crash into you. Or that little kid kind of runs into the street and so you have to cross on the other side because there's no cars. Right? Like if you think about it, we are not perfect drivers. Some of it is because it's our world. And so if you have a robot that is perfect in that sense of the word, they wouldn't really be able to function with us. Can you linger a little bit on the word perfection? So from the robotics perspective, what does that word mean? And how is sort of the optimal behavior as you're describing different than what we think of as perfection? Yeah. So perfection, if you think about it in the more theoretical point of view, it's really tied to accuracy. Right? So if I have a function, can I complete it at 100% accuracy with zero errors? And so that's kind of, if you think about perfection in the sense of the word. And in the self-driving car realm, do you think from a robotics perspective, we kind of have to be able to do that? From a robotics perspective, we kind of think that perfection means following the rules perfectly, sort of defining, staying in the lane, changing lanes, when there's a green light, you go, when there's a red light, you stop. And that's the, and be able to perfectly see all the entities in the scene. That's the limit of what we think of as perfection. And I think that's where the problem comes is that when people think about perfection for robotics, the ones that are the most successful are the ones that are quote unquote perfect. Like I said, Rosie is perfect, but she actually wasn't perfect in terms of accuracy, but she was perfect in terms of how she interacted and how she adapted. And I think that's some of the disconnect is that we really want perfection with respect to its ability to adapt to us. We don't really want perfection with respect to 100% accuracy, with respect to the rules that we just made up anyway. Right? So I think there's this disconnect sometimes between what we really want and what happens. And we see this all the time, like in my research, right? Like the optimal quote unquote optimal interactions are when the robot is adapting based on the person, not 100% following what's optimal based on the rules. Just to linger on autonomous vehicles for a second, just your thoughts, maybe off the top of your head, how hard is that problem do you think based on what we just talked about? There's a lot of folks in the automotive industry that are very confident from Elon Musk to Waymo to all these companies. How hard is it to solve that last piece? The last mile. The gap between the perfection and the human definition of how you actually function in this world. Yeah, so this is a moving target. So I remember when all the big companies started to heavily invest in this, and there was a number of, even roboticists, as well as folks who were putting in the VCs and corporations, Elon Musk being one of them, that said, self-driving cars on the road with people within five years. That was a little while ago. And now people are saying, five years, 10 years, 20 years. Some are saying never, right? I think if you look at some of the things that are being successful is these basically fixed environments where you still have some anomalies. You still have people walking, you still have stores, but you don't have other drivers, like other human drivers. It's a dedicated space for the cars. Because if you think about robotics in general, where it's always been successful is in, I mean, you can say manufacturing, like way back in the day. It was a fixed environment. Humans were not part of the equation. We're a lot better than that. But when we can carve out scenarios that are closer to that space, then I think that it's where we are. So a closed campus where you don't have self-driving cars and maybe some protection so that the students don't jet in front just because they wanna see what happens. Having a little bit, I think that's where we're gonna see the most success in the near future. And be slow moving. Right, not 55, 60, 70 miles an hour, but the speed of a golf cart, right? So that said, the most successful in the automotive industry robots operating today in the hands of real people are ones that are traveling over 55 miles an hour and in unconstrained environments, which is Tesla vehicles, so Tesla autopilot. So I would love to hear sort of your, just thoughts of two things. So one, I don't know if you've gotten to see, you've heard about something called Smart Summon, where Tesla system, autopilot system, where the car drives zero occupancy, no driver in the parking lot, slowly sort of tries to navigate the parking lot to find itself to you. And there's some incredible amounts of videos and just hilarity that happens as it awkwardly tries to navigate this environment. But it's a beautiful nonverbal communication between machine and human that I think is a, it's some of the work that you do in this kind of interesting human-robot interaction space. So what are your thoughts in general about it? So I do have that feature. Do you drive a Tesla? I do. Mainly because I'm a gadget freak, right? So I've seen, it's a gadget that happens to have some wheels. And yeah, I've seen some of the videos. But what's your experience like? I mean, you're a human-robot interaction roboticist. You're a legit sort of expert in the field. So what does it feel for a machine to come to you? It's one of these very fascinating things, but also I am hyper, hyper alert, right? Like I'm hyper alert. Like my thumb is like, oh, okay, I'm ready to take over. Even when I'm in my car, or I'm doing things like automated backing into, so there's like a feature where you can do this automated backing into a parking space, or bring the car out of your garage, or even, you know, pseudo autopilot on the freeway, right? I am hypersensitive. I can feel like as I'm navigating, I'm like, yeah, that's an error right there. Like I am very aware of it, but I'm also fascinated by it. And it does get better. Like I look and see, it's learning. From all of these people who are cutting it on, like every time I cut it on, it's getting better, right? And so I think that's what's amazing about it is that. This nice dance of you're still hyper vigilant. So you're still not trusting it at all. And yet you're using it. What on the highway, if I were to, like what, as a roboticist, we'll talk about trust a little bit. How do you explain that? You still use it. Is it the gadget? Freak part, like where you just enjoy exploring technology or is that the right actually balance between robotics and humans is where you use it, but don't trust it. And somehow there's this dance that ultimately is a positive. Yeah, so I think I'm, I just don't necessarily trust technology, but I'm an early adopter, right? So when it first comes out, I will use everything, but I will be very, very cautious of how I use it. Do you read about it or do you explore it by just try it? Do you do like crudely, to put it crudely, do you read the manual or do you learn through exploration? I'm an explorer. If I have to read the manual, then I do design. Then it's a bad user interface. It's a failure. Elon Musk is very confident that you kind of take it from where it is now to full autonomy. So from this human robot interaction, where you don't really trust, and then you try and then you catch it when it fails to, it's going to incrementally improve itself into full, where you don't need to participate. What's your sense of that trajectory? Is it feasible? So the promise there is by the end of next year, by the end of 2020, it's the current promise. What's your sense about that journey that Tesla's on? So there's kind of three things going on now. I think in terms of will people go, like as a user, as a adopter, will you trust going to that point? I think so, right? Like there are some users and it's because what happens is when you're hypersensitive at the beginning, and then the technology tends to work, your apprehension slowly goes away. And as people, we tend to swing to the other extreme, right? Because like, oh, I was like hyper, hyper fearful or hypersensitive and it was awesome. And we just tend to swing. That's just human nature. And so you will have, I mean, and I- It's a scary notion because most people are now extremely untrusting of autopilot. They use it, but they don't trust it. And it's a scary notion that there's a certain point where you allow yourself to look at the smartphone for like 20 seconds, and then there'll be this phase shift where it'll be like 20 seconds, 30 seconds, one minute, two minutes. It's a scary proposition. But that's people, right? That's just, that's humans. I mean, I think of even our use of, I mean, just everything on the internet, right? Like think about how reliant we are on certain apps and certain engines, right? 20 years ago, people have been like, oh yeah, that's stupid. Like that makes no sense. Like, of course that's false. Like now it's just like, oh, of course I've been using it. It's been correct all this time. Of course, aliens, I didn't think they existed, but now it says they do, obviously. 100%, earth is flat. So, okay, but you said three things. So one is the human. Okay, so one is the human. And I think there will be a group of individuals that will swing, right? Teenagers. Teenage, I mean, it'll be teenage, it'll be adults. There's actually an age demographic that's optimal for technology adoption. And you can actually find them. And they're actually pretty easy to find. They're actually pretty easy to find. Just based on their habits, based on... So someone like me who wasn't a roboticist would probably be the optimal kind of person, right? Early adopter, okay with technology, very comfortable, and not hypersensitive, right? I'm just hypersensitive because I designed this stuff. So there is a target demographic that will swing. The other one though is you still have these humans that are on the road. That one is a harder thing to do. And as long as we have people that are on the same streets, that's gonna be the big issue. And it's just because you can't possibly, I won't say, you can't possibly map some of the silliness of human drivers, right? Like as an example, when you're next to that car that has that big sticker called student driver, right? Like you are like, oh, either I am going to like go around. Like we know that that person is just gonna make mistakes that make no sense, right? How do you map that information? Or if I'm in a car and I look over and I see two fairly young looking individuals, and there's no student driver bumper, and I see them chit-chatting to each other, I'm like, oh, that's an issue, right? So how do you get that kind of information and that experience into basically an autopilot? Yeah, and there's millions of cases like that where we take little hints to establish context. I mean, you said kind of beautifully poetic human things, but there's probably subtle things about the environment, about it being maybe time for commuters to start going home from work, and therefore you can make some kind of judgment about the group behavior of pedestrians, blah, blah, blah, and so on and so on. Or even cities, right? Like if you're in Boston, how people cross the street, like lights are not an issue versus other places where people will actually wait for the crosswalk. Seattle or somewhere peaceful. But what I've also seen sort of just even in Boston that intersection to intersection is different. So every intersection has a personality of its own. So certain neighborhoods of Boston are different. So we're kind of, and based on different timing of day, at night, it's all, there's a dynamic to human behavior that we kind of figure out ourselves. We're not able to introspect and figure it out, but somehow our brain learns it. We do. And so you're saying, is there a shortcut? Is there a shortcut though for, is there something that could be done you think that, that's what we humans do. It's just like bird flight, right? That's the example they give for flight. Do you necessarily need to build a bird that flies or can you do an airplane? Is there a shortcut? So I think the shortcut is, and I kind of, I talk about it as a fixed space. Where, so imagine that there's a neighborhood that's a new smart city or a new neighborhood that says, you know what, we are going to design this new city based on supporting self-driving cars. And then doing things, knowing that there's anomalies, knowing that people are like this, right? And designing it based on that assumption that like, we're going to have this, that would be an example of a shortcut. So you still have people, but you do very specific things to try to minimize the noise a little bit. As an example. And the people themselves become accepting of the notion that there's autonomous cars, right? Right, like they move into, so right now you have like a, you will have a self-selection bias, right? Like individuals will move into this neighborhood knowing like this is part of like the real estate pitch. Right? And so I think that's a way to do a shortcut. One, it allows you to deploy. It allows you to collect then data with these variances and anomalies because people are still people, but it's a safer space and is more of an accepting space. I.e. when something in that space might happen because things do, because you already have this self-selection, like people would be, I think, a little more forgiving than other places. And you said three things, did we cover all of them? The third is legal law. Oh, no. Liability, which I don't really want to touch, but it's still of concern. And the mishmash with like, with policy as well, sort of government, all that whole- That big ball of stuff. Mess, yeah. Gotcha. So that's, so we're out of time now. Do you think from a robotics perspective, if you're kind of honest of what cars do, they kind of threaten each other's life all the time. So cars are very, I mean, in order to navigate intersections, there's an assertiveness, there's a risk taking. And if you were to reduce it to an objective function, there's a probability of murder in that function, meaning you killing another human being and you're using that. First of all, it has to be low enough to be acceptable to you on an ethical level as an individual human being, but it has to be high enough for people to respect you, to not sort of take advantage of you completely and jaywalk in front of you and so on. So, I mean, I don't think there's a right answer here, but what's, how do we solve that? How do we solve that from a robotics perspective when danger and human life is at stake? Yeah, as they say, cars don't kill people, people kill people. People kill people. Right. So I think- And now robotic algorithms would be killing people. Right, so it will be robotics algorithms that are, no, it will be robotic algorithms don't kill people, developers of robotic algorithms kill people. Right, I mean, one of the things is people are still in the loop and at least in the near and midterm, I think people will still be in the loop at some point, even if it's a developer. Like we're not necessarily at the stage where robots are programming autonomous robots with different behaviors. Robots with different behaviors quite yet. That's a scary notion, sorry to interrupt, that a developer has some responsibility in the death of a human being. That's a heavy burden. I mean, I think that's why the whole aspect of ethics in our community is so, so important, right? Like, because it's true. If you think about it, you can basically say, I'm not going to work on weaponized AI, right? Like people can say, that's not what I'm gonna do. But yet you are programming algorithms that might be used in healthcare algorithms that might decide whether this person should get this medication or not. And they don't and they die. Okay, so that is your responsibility, right? And if you're not conscious and aware that you do have that power when you're coding and things like that, I think that's just not a good thing. Like, we need to think about this responsibility as we program robots and computing devices much more than we are. Yeah, so it's not an option to not think about ethics. I think it's a majority, I would say, of computer science. Sort of, it's kind of a hot topic now, I think, about bias and so on. But it's, and we'll talk about it, but usually it's kind of, it's like a very particular group of people that work on that. And then people who do like robotics are like, well, I don't have to think about that. There's other smart people thinking about it. It seems that everybody has to think about it. It's not, you can't escape the ethics, whether it's bias or just every aspect of ethics that has to do with human beings. Everyone. So think about, I'm gonna age myself, but I remember when we didn't have like testers, right? And so what did you do? As a developer, you had to test your own code, right, like you had to go through all the cases and figure it out. And then they realized that, we probably need to have testing because we're not getting all the things. And so from there, what happens is like most developers, they do a little bit of testing, but it's usually like, okay, did my compiler bug out? Let me look at the warnings. Okay, is that acceptable or not? Right, like that's how you typically think about as a developer, and you'll just assume that it's going to go to another process and they're gonna test it out. But I think we need to go back to those early days when you're a developer, you're developing, there should be like this, a, okay, let me look at the ethical outcomes of this because there isn't a second like testing ethical testers, right? It's you. We did it back in the early coding days. I think that's where we are with respect to ethics. Like let's go back to what was good practices and only because we were just developing the field. Yeah, and it's a really heavy burden. I've had to feel it recently in the last few months, but I think it's a good one to feel. Like I've gotten a message more than one from people. You know, I've unfortunately gotten some attention recently, and I've gotten messages that say that I have blood on my hands because of working on semi-autonomous vehicles. The idea that you have semi-autonomy means people would lose vigilance and so on. That's actually be humans as we described. And because of that, because of this idea that we're creating automation, there'll be people be hurt because of it. And I think that's a beautiful thing. I mean, it's, you know, it's many nights where I wasn't able to sleep because of this notion. You know, you really do think about people that might die because of this technology. Of course, you can then start rationalizing and saying, well, you know what? 40,000 people die in the United States every year, and we're trying to ultimately try to save lives. But the reality is your code you've written might kill somebody. And that's an important burden to carry with you as you design the code. I don't even think of it as a burden if we train this concept correctly from the beginning. And I use, and not to say that coding is like being a medical doctor, but think about it. Medical doctors, if they've been in situations where their patient didn't survive, right? Do they give up and go away? No, every time they come in, they know that there might be a possibility that this patient might not survive. And so when they approach every decision, like that's in their back of their head. And so why isn't that we aren't teaching, and those are tools though, right? They are given some of the tools to address that so that they don't go crazy. But we don't give those tools so that it doesn't happen. It does feel like a burden versus something of, I have a great gift and I can do great, awesome good, but with it comes great responsibility. I mean, that's what we teach in terms of, if you think about the medical schools, right? Great gift, great responsibility. I think if we just change the messaging a little, great gift, being a developer, great responsibility. And this is how you combine those. But do you think, I mean, this is really interesting. It's outside, I actually have no friends who are sort of surgeons or doctors. I mean, what does it feel like to make a mistake in a surgery and somebody to die because of that? Like, is that something you could be taught in medical school, sort of how to be accepting of that risk? So, because I do a lot of work with healthcare robotics, I have not lost a patient, for example. The first one's always the hardest, right? But they really teach the value, right? So, they teach responsibility, but they also teach the value. Like, you're saving 40,000, but in order to really feel good about that, when you come to a decision, you have to be able to say at the end, I did all that I could possibly do, right? Versus a, well, I just picked the first widget and did, right, so every decision is actually thought through. It's not a habit, it's not a, let me just take the best algorithm that my friend gave me, right? It's a, is this it, is this the best? Have I done my best to do good, right? And so- You're right, and I think burden is the wrong word. It's a gift, but you have to treat it extremely seriously. Correct. So, on a slightly related note, in a recent paper, the ugly truth about ourselves and our robot creations, you discuss, you highlight some biases that may affect the function of various robotic systems. Can you talk through, if you remember, examples of some? There's a lot of examples. I usually- What is bias, first of all? Yeah, so bias is this, and so bias, which is different than prejudice. So bias is that we all have these preconceived notions about particular, everything from particular groups to habits to identity, right? So we have these predispositions, and so when we address a problem, we look at a problem, we make a decision, those preconceived notions might affect our outputs, our outcomes. So there, the bias could be positive or negative, and then is prejudice the negative kind of bias? Prejudice is the negative, right? So prejudice is that not only are you aware of your bias, but you are then take it and have a negative outcome, even though you are aware. And there could be gray areas too. There's always gray areas. That's the challenging aspect of all ethical questions. So I always like, so there's a funny one, and in fact, I think it might be in the paper, because I think I talk about self-driving cars. But think about this. For teenagers, right, typically, insurance companies charge quite a bit of money if you have a teenage driver. So you could say that's an age bias, right? But no one will, I mean, parents will be grumpy, but no one really says that that's not fair. That's interesting. We don't, that's right, that's right. It's everybody in human factors and safety research almost, I mean, is quite ruthlessly critical of teenagers. And we don't question, is that okay? Is that okay to be ageist in this kind of way? It is, and it is ageist, right? It's definitely age, there's no question about it. And so this is the gray area, right? Because you know that teenagers are more likely to be in accidents, and so there's actually some data to it. But then if you take that same example, and you say, well, I'm going to make the insurance higher for an area of Boston, because there's a lot of accidents. And then they find out that that's correlated with socioeconomics. Well, then it becomes a problem, right? Like that is not acceptable, but yet the teenager, which is age, it's against age, is, right? So- So you figure that out as a society by having conversations, by having discourse. I mean, throughout history, the definition of what is ethical or not has changed, and hopefully always for the better. Correct, correct. So in terms of bias or prejudice in algorithms, what examples do you sometimes think about? So I think about quite a bit the medical domain, just because historically, right, the healthcare domain has had these biases, typically based on gender and ethnicity, primarily, a little in age, but not so much. Historically, if you think about FDA and drug trials, it's harder to find women that aren't childbearing, and so you may not test on drugs at the same level, right? So there's these things. And so if you think about robotics, right, something as simple as, I'd like to design an exoskeleton, right? What should the material be? What should the weight be? What should the form factor be? Are you, who are you gonna design it around? I will say that in the US, women average height and weight is slightly different than guys. So who are you gonna choose? Like, if you're not thinking about it from the beginning, as, you know, okay, when I design this, and I look at the algorithms, and I design the control system, and the forces, and the torques, if you're not thinking about, well, you have different types of body structure, you're gonna design to, you know, what you're used to. Oh, this fits in my, all the folks in my lab, right? So think about it from the very beginning is important. What about sort of algorithms that train on data kind of thing? Sadly, our society already has a lot of negative bias. And so if we collect a lot of data, even if it's a balanced weight, it's going to contain the same bias that our society contains. And so, yeah, is there things there that bother you? Yeah, so you actually said something. You had said how we have biases, but hopefully we learn from them and we become better, right? And so that's where we are now, right? So the data that we're collecting is historic. So it's based on these things when we knew it was bad to discriminate, but that's the data we have, and we're trying to fix it now, but we're fixing it based on the data that was used in the first place to discriminate. Fix it in post. Right, and so the decisions, and you can look at everything from the whole aspect of predictive policing, criminal recidivism. There was a recent paper that had the healthcare algorithms which had a kind of a sensational titles. I'm not pro sensationalism in titles, but you read it, right? So it makes you read it, but I'm like, really? Like, ah, you could have- What's the topic of the sensationalism? I mean, what's underneath it? What's, if you could sort of educate me on what kind of bias creeps into the healthcare space. Yeah, so- I mean, you already kind of mentioned. Yeah, so this one was, the headline was racist AI algorithms. Okay, like, okay, that's totally a clickbait title. And so you looked at it, and so there was data that these researchers had collected. I believe, I wanna say it was either science or nature. It just was just published, but they didn't have a sensational title. It was like the media. And so they had looked at demographics, I believe between black and white women, right? And they showed that there was a discrepancy in the outcomes, right? And so, and it was tied to ethnicity, tied to race. The piece that the researchers did actually went through the whole analysis, but of course- I mean, the journalists with AI are problematic across the board, let's say. And so this is a problem, right? And so there's this thing about, oh, AI, it has all these problems. We're doing it on historical data, and the outcomes aren't even based on gender or ethnicity or age. But I'm always saying is like, yes, we need to do better, right? We need to do better. It is our duty to do better, but the worst AI is still better than us. Like, you take the best of us, and we're still worse than the worst AI, at least in terms of these things. And that's actually not discussed, right? And so I think, and that's why the sensational title, right, and so it's like, so then you can have individuals go like, oh, we don't need to use this AI. I'm like, oh, no, no, no, no. I want the AI instead of the doctors that provided that data, because it's still better than that, right? I think that's really important to linger on. Is the idea that this AI is racist, it's like, well, compared to what? Sort of, I think we set, unfortunately, way too high of a bar for AI algorithms. And in the ethical space where perfect is, I would argue, probably impossible. Then if we set the bar of perfection, essentially, of it has to be perfectly fair, whatever that means, is it means we're setting it up for failure. But that's really important to say what you just said, which is, well, it's still better than some things. And one of the things I think that we don't get enough credit for, just in terms of as developers, is that you can now poke at it, right? So it's harder to say, you know, is this hospital, is this city doing something, right, until someone brings in a civil case, right? Well, with AI, it can process through all this data and say, hey, yes, there was an issue here, but here it is, we've identified it, and then the next step is to fix it. I mean, that's a nice feedback loop versus like waiting for someone to sue someone else before it's fixed, right? And so I think that power, we need to capitalize on a little bit more, right? Instead of having the sensational titles, have the, okay, this is a problem, and this is how we're fixing it, and people are putting money to fix it because we can make it better. I look at like facial recognition, how Joy, she basically called out a couple of companies and said, hey, and most of them were like, oh, embarrassment. And the next time it had been fixed, right? It had been fixed better, right? And then it was like, oh, here's some more issues. And I think that conversation then moves that needle to having much more fair and unbiased and ethical aspects, as long as both sides, the developers are willing to say, okay, I hear you, yes, we are going to improve, and you have other developers who are like, hey, AI, it's wrong, but I love it, right? Yes, so speaking of this really nice notion that AI is maybe flawed but better than humans, so just made me think of it, one example of flawed humans is our political system. Do you think, or you said judicial as well, do you have a hope for AI sort of being elected for president or running our Congress or being able to be a powerful representative of the people? So I mentioned, and I truly believe that this whole world of AI is in partnerships with people. And so what does that mean? I don't believe, or maybe I just don't, I don't believe that we should have an AI for president, but I do believe that a president should use AI as an advisor, right? Like if you think about it, every president has a cabinet of individuals that have different expertise that they should listen to, right? That's kind of what we do. And you put smart people with smart expertise around certain issues and you listen. I don't see why AI can't function as one of those smart individuals giving input. So maybe there's an AI on healthcare, maybe there's an AI on education and right? Like all of these things that a human is processing, right? Because at the end of the day, there's people that are human that are going to be at the end of the decision. And I don't think as a world, as a culture, as a society, that we would totally believe, and this is us, like this is some fallacy about us, but we need to see that leader, that person as human. And most people don't realize that like leaders have a whole lot of advice, right? Like when they say something, it's not that they woke up, well, usually, they don't wake up in the morning and be like, I have a brilliant idea, right? It's usually a, okay, let me listen. I have a brilliant idea, but let me get a little bit of feedback on this. Like, okay. And then it's a, yeah, that was an awesome idea. Or it's like, yeah, let me go back. We already talked through a bunch of them, but are there some possible solutions to the biases present in our algorithms beyond what we just talked about? So I think there's two paths. One is to figure out how to systematically do the feedback and corrections. So right now it's ad hoc, right? It's a researcher identifies some outcomes that are not, don't seem to be fair, right? They publish it, they write about it, and either the developer or the companies that have adopted the algorithms may try to fix it, right? And so it's really ad hoc and it's not systematic. There's, it's just, it's kind of like, I'm a researcher, that seems like an interesting problem, which means that there's a whole lot out there that's not being looked at, right? Because it's kind of researcher driven. And I don't necessarily have a solution, but that process I think could be done a little bit better. One way is I'm going to poke a little bit at some of the corporations, right? Like maybe the corporations, when they think about a product, they should, instead of, in addition to hiring these, you know, bug, they give these- Oh yeah, yeah, yeah. Where you- Like awards when you find a bug. Yeah, yeah, security bug. You know, let's put it like, we will give the, whatever the award is that we give for the people who find these security holes, find an ethics hole, right? Like find an unfairness hole and we will pay you X for each one you find. I mean, why can't they do that? One is a win-win. They show that they're concerned about it, that this is important, and they don't have to necessarily dedicate their own internal resources. And it also means that everyone who has their own bias lens, like I'm interested in age, and so I'll find the ones based on age, and I'm interested in gender, right? Which means that you get all of these different perspectives. But you think of it in a data driven way. So like, sort of, if we look at a company like Twitter, it gets, it's under a lot of fire for discriminating against certain political beliefs. Correct. And sort of, there's a lot of people, this is the sad thing, because I know how hard the problem is, and I know the Twitter folks are working really hard at it. Even Facebook, that everyone seems to hate, are working really hard at this. You know, the kind of evidence that people bring is basically anecdotal evidence. Well, me or my friend, all we said is X, and for that we got banned. And that's kind of a discussion of saying, well, look, that's usually, first of all, the whole thing is taken out of context. So they present sort of anecdotal evidence. And how are you supposed to, as a company, in a healthy way, have a discourse about what is and isn't ethical? How do we make algorithms ethical when people are just blowing everything? Like, they're outraged about a particular anecdotal piece of evidence that's very difficult to sort of contextualize in a big data-driven way. Do you have a hope for companies like Twitter and Facebook? Yeah, so I think there's a couple of things going on. First off, remember this whole aspect of we are becoming reliant on technology. We're also becoming reliant on a lot of these, the apps and the resources that are provided. So some of it is kind of anger, like, I need you, right? And you're not working for me, right? Yeah, they're not working for me, they're right. But I think, and so some of it, and I wish that there was a little bit of change of rethinking. So some of it is like, oh, we'll fix it in-house. No, that's like, okay, I'm a fox, and I'm going to watch these hens because I think it's a problem that foxes eat hens. No, right? Like, be good citizens and say, look, we have a problem, and we are willing to open ourselves up for others to come in and look at it and not try to fix it in-house. Because if you fix it in-house, there's conflict of interest. If I find something, I'm probably going to want to fix it, and hopefully the media won't pick it up, right? And that then causes distrust because someone inside is going to be mad at you and go out and talk about how, yeah, they can the resume survey because, right? Like, be best people. Like, just say, look, we have this issue. Community, help us fix it, and we will give you the bug finder fee if you do. Did you ever hope that the community, us as a human civilization on the whole is good and can be trusted to guide the future of our civilization into a positive direction? I think so. So I'm an optimist, right? And there were some dark times in history, always. I think now we're in one of those dark times. I truly do. In which aspect? The polarization. And it's not just US, right? So if it was just US, I'd be like, yeah, it's a US thing, but we're seeing it worldwide, this polarization. And so I worry about that. But I do fundamentally believe that at the end of the day, people are good, right? And why do I say that? Because anytime there's a scenario where people are in danger, and I will use, so Atlanta, we had a snowmageddon, and people can laugh about that. People at the time, so the city closed for, you know, little snow, but it was ice, and the city closed down. But you had people opening up their homes and saying, hey, you have nowhere to go, come to my house, right? Hotels were just saying, like, sleep on the floor. Like places like, you know, the grocery stores were like, hey, here's food. There was no like, oh, how much are you gonna pay me? It was like this, such a community. And like people who didn't know each other, strangers were just like, can I give you a ride home? And that was a point I was like, you know what? That reveals that the deeper thing is, there's a compassionate love there. There's a love that we all have within us. It's just that when all of that is taken care of and get bored, we love drama. And that's, I think almost like the division is a sign of the times being good, is that it's just entertaining on some unpleasant mammalian level to watch, to disagree with others. And Twitter and Facebook are actually taking advantage of that in a sense, because it brings you back to the platform, and they're advertiser driven, so they make a lot of money. So you go back and you click. Love doesn't sell quite as well in terms of advertisement. It doesn't. So you've started your career at NASA Jet Propulsion Laboratory, but before I ask a few questions there, have you happened to have ever seen Space Odyssey, 2001 Space Odyssey? Yes. Okay, do you think Hal 9000, so we're talking about ethics, do you think Hal did the right thing by taking the priority of the mission over the lives of the astronauts? Do you think Hal is good or evil? Easy questions. Yeah. Hal was misguided. You're one of the people that would be in charge of an algorithm like Hal. Yeah. So how would you do better? If you think about what happened was there was no fail safe, right? So perfection, right? Like what is that? I'm gonna make something that I think is perfect, but if my assumptions are wrong, it'll be perfect based on the wrong assumptions, right? That's something that you don't know until you deploy, and then you're like, oh yeah, messed up. But what that means is that when we design software, such as in Space Odyssey, when we put things out, that there has to be a fail safe. There has to be the ability that once it's out there, we can grade it as an F and it fails, and it doesn't continue, right? There's some way that it can be brought in and removed and that's aspect. Because that's what happened with Hal. It was like assumptions were wrong. It was perfectly correct based on those assumptions, and there was no way to change it, change the assumptions at all. And the change, the fallback would be to a human. So you ultimately think like humans should be, it's not turtles or AI all the way down. It's at some point there's a human that actually makes it. I still think that, and again, because I do human robot interaction, I still think the human needs to be part of the equation at some point. So what, just looking back, what are some fascinating things in robotic space that NASA was working at the time, or just in general, what have you gotten to play with and what are your memories from working at NASA? Yeah, so one of my first memories was they were working on a surgical robot system that could do eye surgery, right? And this was back in, oh my gosh, it must've been, oh, maybe 92, 93, 94. So it's almost like a remote operation or- Yeah, it was remote operation. In fact, you can even find some old tech reports on it. So think of it, like now we have Da Vinci, right? Like think of it, but these were like the late 90s, right? And I remember going into the lab one day and I was like, what's that, right? And of course it wasn't pretty, right? Because the technology, but it was like functional and you had this individual that could use a version of haptics to actually do the surgery. And they had this mock-up of a human face and like the eyeballs, and you can see this little drill. And I was like, oh, that is so cool. That one I vividly remember because it was so outside of my possible thoughts of what could be done. Just the kind of precision and, I mean, what's the most amazing of a thing like that? I think it was the precision. It was the kind of first time that I had physically seen this robot machine human interface, right? Versus, because manufacturing had been, you saw those kind of big robots, right? But this was like, oh, this is in a person. There's a person and a robot like in the same space. Meeting them in person. Like for me, it was a magical moment that I can't, it was life transforming that I recently met Spot Mini from Boston Dynamics. I don't know why, but on the human-robot interaction, for some reason I realized how easy this to anthropomorphize. And it was, I don't know, it was almost like falling in love with this feeling of meeting. And I've obviously seen these robots a lot on video and so on, but meeting in person, just having that one-on-one time. It's different. It's different. So have you had a robot like that in your life that made you maybe fall in love with robotics? Sort of like meeting in person? I mean, I loved robotics. From the beginning. Yeah, so I was a 12-year-old, like I'm gonna be a roboticist. Actually, I called it cybernetics. But so my motivation was Bionic Woman. I don't know if you know that. And so, I mean, that was like a seminal moment, but I didn't meet, like that was TV, right? Like it wasn't like I was in the same space and I met, I was like, oh my gosh, you're like real. Just linking on Bionic Woman, which by the way, because I read that about you, I watched a bit of it and it's just so, no offense, terrible. It's cheesy. It's cheesy. Look at it now. It's cheesy. I've seen a couple of reruns lately. But it's, but of course at the time, it was probably, it captured the imagination. I mean, especially when you're younger, it just catches you. But which aspect, did you think of it, you mentioned cybernetics, did you think of it as robotics or did you think of it as almost constructing artificial beings? Like is it the intelligent part that captured your fascination or was it the whole thing, like even just the limbs and just the? So for me, it would have, in another world, I probably would have been more of a biomedical engineer because what fascinated me was the bionic, was the parts, like the bionic parts, the limbs, those aspects of it. Are you especially drawn to humanoid or human-like robots? I would say human-like, not humanoid, right? And when I say human-like, I think it's this aspect of that interaction, whether it's social and it's like a dog, right? Like that's human-like because it understand us, it interacts with us at that very social level. To, you know, humanoids are part of that, but only if they interact with us as if we are human. But just to linger on NASA for a little bit, what do you think, maybe if you have other memories, but also what do you think is the future of robots in space? We mentioned how, but there's incredible robots that NASA's working on in general, thinking about in our, as we venture out, human civilization ventures out into space. What do you think the future of robots is there? Yeah, so I mean, there's the near term. For example, they just announced the rover that's going to the moon, which, you know, that's kind of exciting, but that's like near term. You know, my favorite, favorite, favorite series is Star Trek, right? You know, I really hope, and even Star Trek, like if I calculate the years, I wouldn't be alive, but I would really, really love to be in that world. Like even if it's just at the beginning, like, you know, like Voyage, like Adventure One. So basically living in space. Yeah. With what robots, what do robots? With data. What role? The data would have to be, even though that wasn't, you know, that was like later, but. So data is a robot that has human-like qualities. Right, without the emotion ship, yeah. You don't like emotion in your robots. Well, so data with the emotion ship was kind of a mess, right? It took a while for that thing to adapt. But, and so why was that an issue? The issue is, is that emotions make us irrational agents. That's the problem. And yet he could think through things, even if it was based on an emotional scenario, right? Based on pros and cons. But as soon as you made him emotional, one of the metrics he used for evaluation was his own emotions, not people around him, right? Like, and so. We do that as children, right? So we're very egocentric when we're young. We are very egocentric. And so isn't that just an early version of the emotion ship then? I haven't watched much Star Trek. Except I have also met adults. Right, and so that is a developmental process. And I'm sure there's a bunch of psychologists that can go through, like you can have a 60-year-old adult who has the emotional maturity of a 10-year-old, right? And so there's various phases that people should go through in order to evolve, and sometimes you don't. So how much psychology do you think, a topic that's rarely mentioned in robotics, but how much does psychology come to play when you're talking about HRI, human-robot interaction, when you have to have robots that actually interact with humans? Tons. So we, like my group, as well as I read a lot in the cognitive science literature, as well as the psychology literature, because they understand a lot about human-human relations and developmental milestones and things like that. And so we tend to look to see what's been done out there. Sometimes what we'll do is we'll try to match that to see is that human-human relationship the same as human-robot? Sometimes it is, and sometimes it's different. And then when it's different, we try to figure out, okay, why is it different in this scenario, but it's the same in the other scenario, right? And so we try to do that quite a bit. Would you say that's, if we're looking at the future of human-robot interaction, would you say the psychology piece is the hardest? I mean, it's a funny notion for you. I don't know if you consider, yeah. I mean, one way to ask it, do you consider yourself a roboticist or a psychologist? Well, I consider myself a roboticist. That plays the act of a psychologist. But if you were to look at yourself sort of 20, 30 years from now, do you see yourself more and more wearing the psychology hat? Another way to put it is, are the hard problems in human-robot interactions fundamentally psychology, or is it still robotics, the perception, manipulation, planning, and all that kind of stuff? It's actually neither. The hardest part is the adaptation and the interaction. So it's the interface, it's the learning. And so if I think of, I've become much more of a roboticist slash AI person than when I, like originally, again, I was about the bionics. I was electrical engineer, I was control theory, right? And then I started realizing that my algorithms needed human data, right? And so then I was like, okay, what is this human thing? How do I incorporate human data? And then I realized that human perception had, like there was a lot in terms of how we perceive the world. And so trying to figure out how do I model human perception for my, and so I became a HRI person, human-robot interaction person, from being a control theory and realizing that humans actually offered quite a bit. And then when you do that, you become more of an artificial intelligence, AI. And so I see myself evolving more in this AI world under the lens of robotics, having hardware, interacting with people. So you're a world-class expert researcher in robotics, and yet others, there's a few, it's a small but fierce community of people, but most of them don't take the journey into the H of HRI, into the human. So why did you brave into the interaction with humans? It seems like a really hard problem. It's a hard problem and it's very risky as an academic. Yes. And I knew that when I started down that journey, that it was very risky as an academic in this world that was nuanced, it was just developing. And we didn't even have a conference, right, at the time. Because it was the interesting problems. That was what drove me. It was the fact that I looked at what interests me in terms of the application space and the problems, and that pushed me into trying to figure out what people were and what humans were and how to adapt to them. If those problems weren't so interesting, I'd probably still be sending rovers to glaciers, right? But the problems were interesting. And the other thing was that they were hard, right? So I like having to go into a room and being like, I don't know what to do. And then going back and saying, okay, I'm gonna figure this out. I'm not driven when I go in like, oh, there are no surprises. Like, I don't find that satisfying. If that was the case, I'd go someplace and make a lot more money, right? I think I stay in academic and choose to do this because I can go into a room and like, that's hard. Yeah, I think just from my perspective, maybe you can correct me on it, but if I just look at the field of AI broadly, it seems that human robot interaction has one of the most number of open problems. Like people, especially relative to how many people are willing to acknowledge that there are. Because most people are just afraid of the humans, so they don't even acknowledge how many open problems there are. But in terms of difficult problems to solve, exciting spaces, it seems to be incredible for that. It is, and it's exciting. You've mentioned trust before. What role does trust from, interacting with autopilot to in the medical context, what role does trust play in the human robot interactions? So some of the things I study in this domain is not just trust, but it really is overtrust. How do you think about overtrust? Like what is, first of all, what is trust and what is overtrust? Basically the way I look at it is, trust is not what you click on a survey. Trust is about your behavior. So if you interact with the technology based on the decision or the actions of the technology, as if you trust that decision, then you're trusting. And even in my group, we've done surveys that, on the thing, do you trust robots? Of course not. Would you follow this robot in a burning building? Of course not. And then you look at their actions and you're like, clearly your behavior does not match what you think, or what you think you would like to think, right? And so I'm really concerned about the behavior because that's really, at the end of the day, when you're in the world, that's what will impact others around you. It's not whether before you went onto the street, you clicked on, like, I don't trust self-driving cars. You know, that, from an outsider perspective, it's always frustrating to me. Well, I read a lot, so I'm insider in a certain philosophical sense. It's frustrating to me how often trust is used in surveys and how people say, make claims out of any kind of finding they make while somebody clicking on answer. Because trust is, yeah, behavior, just, you said it beautifully, I mean, the action, your own behavior is what trust is. I mean, everything else is not even close. It's almost like absurd comedic poetry that you weave around your actual behavior. So some people can say they trust, you know, I trust my wife, husband, or not, whatever, but the actions is what speaks volumes. You bug their car. Yeah. You probably don't trust them. I trust them, I'm just making sure. No, no, that's, yeah. Like, even if you think about cars, I think it's a beautiful case. I came here at some point, I'm sure, on either Uber or Lyft, right? I remember when it first came out. I bet if they had had a survey, would you get in the car with a stranger and pay them? Yes. How many people do you think would have said, like, really? You know, wait, even worse, would you get in the car with a stranger at 1 a.m. in the morning to have them drop you home as a single female? Yeah. Like, how many people would say, that's stupid? Yeah. And now look at where we are. I mean, people put kids, like, right? Like, oh yeah, my child has to go to school and I, yeah, I'm gonna put my kid in this car with a stranger. I mean, it's just fascinating how, like, what we think we think is not necessarily matching our behavior. Yeah, and certainly with robots, with autonomous vehicles, and all the kinds of robots you work with, that's, it's, yeah, it's, the way you answer it, especially if you've never interacted with that robot before, if you haven't had the experience, you being able to respond correctly on a survey is impossible. But what do you, what role does trust play in the interaction, do you think? Like, is it good to, is it good to trust a robot? What does overtrust mean? Or is it good to, kind of how you feel about autopilot currently, which is like, from a robotics perspective, is like, so very cautious? Yeah, so this is still an open area of research. But basically what I would like, in a perfect world, is that people trust the technology when it's working 100%, and people will be hypersensitive and identify when it's not. But of course, we're not there. That's the ideal world. And, but we find is that people swing, right? They tend to swing, which means that if my first, and like, we have some papers, but first impressions is everything, right? If my first instance with technology, with robotics is positive, it mitigates any risk, it correlates with like best outcomes, it means that I'm more likely to either not see it when it makes some mistakes or faults, or I'm more likely to forgive it. And so this is a problem because technology is not 100% accurate, right? It's not 100% accurate, although it may be perfect. How do you get that first moment right, do you think? There's also an education about the capabilities and limitations of the system. Do you have a sense of how you educate people correctly in that first interaction? Again, this is an open-ended problem. So one of the study that actually has given me some hope that I, we're trying to figure out how to put in robotics. So there was a research study that has showed for medical AI systems, giving information to radiologists about, here you need to look at these areas on the x-ray. What they found was that when the system provided one choice there was this aspect of either no trust or overtrust, right? Like I'm not going, I don't believe it at all, or a yes, yes, yes, yes. And they would miss things, right? Instead when the system gave them multiple choices, like here are the three, even if it knew, like it had estimated that the top area that you need to look at was heat, some place on the x-ray. If it gave like one plus others, the trust was maintained and the accuracy of the entire population increased. Right, so basically it was a, you're still trusting the system, but you're also putting in a little bit of like your human expertise, like your human decision processing into the equation. So it helps to mitigate that overtrust risk. Yeah, so there's a fascinating balance to have to strike. I haven't figured out again, in robotics it's still an open research. This is exciting open area research, exactly. So what are some exciting applications of human robot interaction? You started a company, maybe you can talk about the exciting efforts there, but in general also what other space can robots interact with humans and help? Yeah, so besides healthcare, because that's my bias lens. My other bias lens is education. I think that, well, one, we definitely, in the US we're doing okay with teachers, but there's a lot of school districts that don't have enough teachers. If you think about the teacher student ratio for at least public education in some districts, it's crazy. It's like, how can you have learning in that classroom? Right, because you just don't have the human capital. And so if you think about robotics, bringing that in to classrooms as well as the afterschool space, where they offset some of this lack of resources in certain communities, I think that's a good place. And then turning on the other end is using these systems then for workforce retraining and dealing with some of the things that are going to come out later on of job loss, like thinking about robots and in AI systems for retraining and workforce development. I think that's exciting areas that can be pushed even more, and it would have a huge, huge impact. What would you say are some of the open problems in education, sort of, it's exciting. So young kids and the older folks or just folks of all ages who need to be retrained, who need to sort of open themselves up to a whole nother area of work. What are the problems to be solved there? How do you think robots can help? We have the engagement aspect, right? So we can figure out the engagement. That's not a- What do you mean by engagement? So identifying whether a person is focused is, like that we can figure out. What we can figure out, and there's some positive results in this, is that personalized adaptation based on any concepts, right? So imagine I think about, I have an agent and I'm working with a kid learning, I don't know, algebra two. Can that same agent then switch and teach some type of new coding skill to a displaced mechanic? Like, what does that actually look like, right? Like hardware might be the same, content is different, two different target demographics of engagement. Like, how do you do that? How important do you think personalization is in human-robot interaction? And not just a mechanic or student, but like literally to the individual human being? I think personalization is really important, but a caveat is that I think we'd be okay if we can personalize to the group, right? And so if I can label you as along some certain dimensions, then even though it may not be you specifically, I can put you in this group. So the sample size, this is how they best learn, this is how they best engage. Even at that level, it's really important. And it's because, I mean, it's one of the reasons why educating in large classrooms is so hard, right? You teach to the median, but there's these individuals that are struggling and then you have highly intelligent individuals and those are the ones that are usually kind of left out. So highly intelligent individuals may be disruptive and those who are struggling might be disruptive because they're both bored. Yeah, and if you narrow the definition of the group or in the size of the group enough, you'll be able to address their individual, it's not individual needs, but really the most important group needs, right? And that's kind of what a lot of successful recommender systems do with Spotify and so on. So it's sad to believe, but I'm, as a music listener, probably in some sort of large group. It's very sadly predictable. You have been labeled. Yeah, I've been labeled and successfully so because they're able to recommend stuff that I like. Yeah, but applying that to education, right? There's no reason why it can't be done. Do you have a hope for our education system? I have more hope for workforce development. And that's because I'm seeing investments. Even if you look at VC investments in education, the majority of it has lately been going to workforce retraining, right? And so I think that government investments is increasing. There's like a claim and some of it's based on fear, right? Like AI is gonna come and take over all these jobs. What are we gonna do with all these non-paying taxes that aren't coming to us by our citizens? And so I think I'm more hopeful for that. Not so hopeful for early education because it's this, it's still a who's gonna pay for it. And you won't see the results for like 16 to 18 years. It's hard for people to wrap their heads around that. But on the retraining part, what are your thoughts? There's a candidate, Andrew Yang, running for president saying that sort of AI automation robots are gonna take our jobs. Universal basic income. Universal basic income in order to support us as we kind of, automation takes people's jobs and allows you to explore and find other means. Like do you have a concern of society transforming effects of automation and robots and so on? I do. I do know that AI robotics will displace workers. Like we do know that. But there'll be other workers that will be defined new jobs. What I worry about is, that's not what I worry about. Like will all the jobs go away? What I worry about is the type of jobs that will come out. Like people who graduate from Georgia Tech will be okay. We give them the skills, they will adapt even if their current job goes away. I do worry about those that don't have that quality of an education. Will they have the ability, the background to adapt to those new jobs? That I don't know. That I worry about, which will create even more polarization in our society, internationally and everywhere. I worry about that. I also worry about not having equal access to all these wonderful things that AI can do and robotics can do. I worry about that. People like me from Georgia Tech, from say MIT will be okay. But that's such a small part of the population that we need to think much more globally of having access to the beautiful things, whether it's AI in healthcare, AI in education, AI in politics, right? I worry about that. And that's part of the thing that you were talking about is people that build the technology have to be thinking about ethics, have to be thinking about access and all those things. And not just a small subset. Let me ask some philosophical, slightly romantic questions for people that listen to this. We'll be like, here he goes again. Okay. Do you think one day we'll build an AI system that a person can fall in love with and it would love them back? Like in the movie, Her, for example. Yeah. Although she kind of didn't fall in love with him. Or she fell in love with like a million other people, something like that. So- You're the jealous type, I see. Yes. We humans are the jealous type. Yes, so I do believe that we can design systems where people would fall in love with their robot, with their AI partner. That I do believe. Because it's actually, and I don't like to use the word manipulate, but as we see, there are certain individuals that can be manipulated if you understand the cognitive science about it, right? Right, so I mean, if you could think of all close relationship and love in general as a kind of mutual manipulation, that dance, the human dance. I mean, manipulation is a negative connotation. And that's why I don't like to use that word particularly. I guess another way to phrase it is, you're getting at it as it could be algorithmatized or something. It could be- The relationship building part can be. Yeah, yeah. I mean, just think about it. We have, and I don't use dating sites, but from what I heard, there are some individuals that have been dating that have never saw each other, right? In fact, there's a show I think that tries to weed out fake people. Like there's a show that comes out, right? Because like people start faking. Like what's the difference of that person on the other end being an AI agent, right? And having a communication, are you building a relationship remotely? Like there's no reason why that can't happen. In terms of human-robot interaction, so what role, you've kind of mentioned with data, emotion being, can be problematic if not implemented well, I suppose. What role does emotion and some other human-like things, the imperfect things come into play here for good human-robot interaction and something like love? Yeah, so in this case, and you had asked, can an AI agent love a human back? I think they can emulate love back, right? And so what does that actually mean? It just means that if you think about their programming, they might put the other person's needs in front of theirs in certain situations, right? You look at, think about it as return on investment. Like what's my return on investment? As part of that equation, that person's happiness, has some type of algorithm waiting to it. And the reason why is because I care about them, right? That's the only reason, right? But if I care about them and I show that, then my final objective function is length of time of the engagement, right? So you can think of how to do this actually quite easily. And so- But that's not love? Well, so that's the thing. I think it emulates love because we don't have a classical definition of love. Right, but, and we don't have the ability to look into each other's minds to see the algorithm. And I mean, I guess what I'm getting at is, is it possible that, especially if that's learned, especially if there's some mystery and black box nature to the system, how is that- How is it any different? How is it any different? And in terms of sort of if the system says, I'm conscious, I'm afraid of death, and it does indicate that it loves you, another way to sort of phrase it, I'd be curious to see what you think. Do you think there'll be a time when robots should have rights? You've kind of phrased the robot in a very roboticist way, and it's just a really good way, but saying, okay, well, there's an objective function, and I could see how you can create a compelling human-robot interaction experience that makes you believe that the robot cares for your needs and even something like loves you. But what if the robot says, please don't turn me off? What if the robot starts making you feel like there's an entity, a being, a soul there, right? Do you think there'll be a future, hopefully you won't laugh too much at this, but where they do ask for rights? So I can see a future if we don't address it in the near term where these agents, as they adapt and learn, could say, hey, this should be something that's fundamental. I hopefully think that we would address it before it gets to that point. You think that's a bad future? Is that a negative thing where they ask or being discriminated against? I guess it depends on what role have they attained at that point, right? And so if I think about now. Careful what you say because the robots 50 years from now will be listening to this, and you'll be on TV saying, this is what roboticists used to believe. Well, right, and so this is my, and as I said, I have a biased lens, and my robot friends will understand that. Yes. So if you think about it, and I actually put this in kind of the, as a roboticist, you don't necessarily think of robots as human with human rights, but you could think of them either in the category of property, or you could think of them in the category of animals. And so both of those have different types of rights. So animals have their own rights as a living being, but they can't vote, they can't write, they can be euthanized. But as humans, if we abuse them, we go to jail. So they do have some rights that protect them, but don't give them the rights of like citizenship. And then if you think about property, property, the rights are associated with the person. So if someone vandalizes your property or steals your property, like there are some rights, but it's associated with the person who owns that. If you think about it, back in the day, and if you remember, we talked about how society has changed, women were property, right? They were not thought of as having rights. They were thought of as property of like their- Yeah, assaulting a woman meant assaulting the property of somebody else's person. Exactly, and so what I envision is that we will establish some type of norm at some point, but that it might evolve, right? Like if you look at women's rights now, like there are still some countries that don't have, and the rest of the world is like, why that makes no sense, right? And so I do see a world where we do establish some type of grounding. It might be based on property rights, it might be based on animal rights. And if it evolves that way, I think we will have this conversation at that time, because that's the way our society traditionally has evolved. Beautifully put. Just out of curiosity, Anki, Jibo, Mayfield Robotics, with their robot Curie, Sci-Fi Works, Rethink Robotics, were all these amazing robotics companies led, created by incredible roboticists, and they've all went out of business recently. Why do you think they didn't last longer? Why is it so hard to run a robotics company, especially one like these, which are fundamentally HRI, Human Robot Interaction Robots? Yeah. Or personal robots. Each one has a story. Only one of them I don't understand, and that was Anki. That's actually the only one I don't understand. I don't understand it either. I mean, I look from the outside. I've looked at their sheets. I've looked at the data that's- Oh, you mean business-wise? Yeah. Gotcha. Yeah, and I look at that data, and I'm like, they seem to have product market fit. So that's the only one I don't understand. The rest of it was product market fit. What's product market fit? Just out of, how do you think about it? Yeah, so although we think robotics was getting there, but I think it's just the timing, their clock just timed out. I think if they'd been given a couple of more years, they would have been okay. But the other ones were still fairly early by the time they got into the market. And so product market fit is, I have a product that I wanna sell at a certain price. Are there enough people out there, the market, that are willing to buy the product at that market price for me to be a functional, viable, profit-bearing company, right? So product market fit. If it costs you $1,000 and everyone wants it and only is willing to pay a dollar, you have no product market fit, even if you could sell it for, you know, it's enough for a dollar, because you can't- So how hard is it for robots? So maybe if you look at iRobot, the company that makes Roombas, vacuum cleaners, can you comment on, did they find the right product, market product fit? Like, are people willing to pay for robots is also another kind of question underlying all this. So if you think about iRobot and their story, right? Like when they first, they had enough of a runway, right? When they first started, they weren't doing vacuum cleaners, right? They were a military, they were contracts, primarily government contracts, designing robots. Or military robots. Yeah, I mean, that's what they were. That's how they started, right? And then- They still do a lot of incredible work there, but yeah, that was the initial thing that gave them enough funding to- To then try to, the vacuum cleaner is what I've been told was not like their first rendezvous in terms of designing a product, right? And so they were able to survive until they got to the point that they found a product price market, right? And even with, if you look at the Roomba, the price point now is different than when it was first released, right? It was an early adopter price, but they found enough people who were willing to fund it. And I mean, I forgot what their loss profile was for the first couple of years, but they became profitable in sufficient time that they didn't have to close their doors. So they found the right, there's still people willing to pay a large amount of money, sort of over $1,000 for a vacuum cleaner. Unfortunately for them, now that they've proved everything out and figured it all out, now there's competitors. Yeah, and so that's the next thing, right? The competition, and they have quite a number, even internationally. Like there's some products out there, you can go to Europe and be like, oh, I didn't even know this one existed. So this is the thing though, like with any market, I would, this is not a bad time, although as a roboticist, it's kind of depressing, but I actually think about things like with, I would say that all of the companies that are now in the top five or six, they weren't the first to the stage, right? Like Google was not the first search engine, sorry AltaVista, right? Facebook was not the first, sorry, MySpace, right? Like think about it, they were not the first players. Those first players, like they're not in the top five, 10 of Fortune 500 companies, right? They proved, they started to prove out the market. They started to get people interested. They started the buzz, but they didn't make it to that next level. But the second batch, right? The second batch, I think might make it to the next level. When do you think the Facebook of, ugh. The Facebook of robotics. Sorry, I take that phrase back because people deeply, for some reason, well, I know why, but it's, I think, exaggerated distrust Facebook because of the privacy concerns and so on. And with robotics, one of the things you have to make sure is all the things we talked about is to be transparent and have people deeply trust you to let a robot into their lives, into their home. But when do you think the second batch of robots, is it five, 10 years, 20 years, that we'll have robots in our homes and robots in our hearts? So if I think about, because I try to follow the VC kind of space in terms of robotic investments. And right now, and I don't know if they're gonna be successful. I don't know if this is the second batch, but there's only one batch that's focused on the first batch. And then there's all these self-driving Xs. And so I don't know if they're a first batch of something or if, I don't know quite where they fit in, but there's a number of companies, the co-robot, I call them co-robots, that are still getting VC investments. Some of them have some of the flavor of Rethink Robotics. Some of them have some of the flavor of Curie. What's a co-robot? So basically a robot and human working in the same space. So some of the companies are focused on manufacturing. So having a robot and human working together in a factory, some of these co-robots are robots and humans working in the home, working in clinics. Like there's different versions of these companies in terms of their products, but they're all, so Rethink Robotics would be like one of the first, at least well-known companies focused on this space. So I don't know if this is a second batch or if this is still part of the first batch. That I don't know. And then you have all these other companies in this self-driving space. And I don't know if that's a first batch or again, a second batch. Yeah, so there's a lot of mystery about this now. Of course, it's hard to say that this is the second batch until it proves out, right? Correct. Yeah, exactly. Yeah, we need a unicorn. Yeah, exactly. Why do you think people are so afraid, at least in popular culture of legged robots, like those worked in Boston Dynamics or just robotics in general? If you were to psychoanalyze that fear, what do you make of it? And should they be afraid, sorry? So should people be afraid? I don't think people should be afraid. But with a caveat, I don't think people should be afraid given that most of us in this world understand that we need to change something, right? So given that. Now, if things don't change, be very afraid. Which is the dimension of change that's needed? So thinking about the ramifications, thinking about the ethics, thinking about the conversation is going on, right? It's no longer a, we're gonna deploy it and forget that, this is a car that can kill pedestrians that are walking across the street, right? We're not in that stage. We're putting these roads out. There are people out there. A car could be a weapon. People are now, solutions aren't there yet, but people are thinking about this as we need to be ethically responsible as we send these systems out, robotics, medical, self-driving. And military too. And military. Which is not as often talked about, but it's really where probably these robots will have a significant impact as well. Correct, correct. Right, making sure that they can think rationally, even having the conversations, who should pull the trigger, right? But overall, you're saying if we start to think more and more as a community about these ethical issues, people should not be afraid. Yeah, I don't think people should be afraid. I think that the return on investment, the positive impact will outweigh any of the potentially negative impacts. Do you have worries of existential threats of robots or AI that some people kind of talk about and romanticize about in the next decade, next few decades? No, I don't. Singularity would be an example. So my concept is that, so remember, robots, AI, is designed by people. It has our values. And I always correlate this with a parent and a child. So think about it, as a parent, what do we want? We want our kids to have a better life than us. We want them to expand. We want them to experience the world. And then as we grow older, our kids think and know they're smarter and better and more intelligent and have better opportunities. And they may even stop listening to us. They don't go out and then kill us, right? Like think about it. It's because it's instilled in them values. We instilled in them this whole aspect of community. And yes, even though you're maybe smarter and have more money and da, da, da, it's still about this love, caring relationship. And so that's what I believe. So even if like, you know, we've created the singularity in some archaic system back in like 1980 that suddenly evolves, the fact is it might say, I am smarter, I am sentient. These humans are really stupid, but I think it'll be like, yeah, but I just can't destroy them. Yeah, for sentimental value. Still just to come back for Thanksgiving dinner every once in a while. Exactly. That's so beautifully put. You've also said that The Matrix may be one of your more favorite AI-related movies. Can you elaborate why? Yeah, it is one of my favorite movies. And it's because it represents kind of all the things I think about. So there's a symbiotic relationship between robots and humans, right? That symbiotic relationship is that they don't destroy us, they enslave us, right? But think about it. Even though they enslaved us, they needed us to be happy, right? And in order to be happy, they had to create this crude world that they then had to live in, right? That's the whole premise. But then there were humans that had a choice, right? Like you had a choice to stay in this horrific, horrific world where it was your fantasy life with all of the anomalies, perfection, but not accurate. Or you can choose to be on your own and like have maybe no food for a couple of days, but you were totally autonomous. And so I think of that as, and that's why. So it's not necessarily us being enslaved, but I think about us having the symbiotic relationship. Robots and AI, even if they become sentient, they're still part of our society and they will suffer just as much as we. And there will be some kind of equilibrium that we'll have to find some symbiotic relationship. Right, and then you have the ethicists, the robotics folks that were like, no, this has got to stop. I will take the other pill in order to make a difference. So if you could hang out for a day with a robot, real or from science fiction, movies, books, safely, and get to pick his or her, their brain, who would you pick? Gotta say it's Data. Data. I was gonna say Rosie, but I don't, I'm not really interested in her brain. I'm interested in Data's brain. Data pre or post-emotionship? Pre. But don't you think it'd be a more interesting conversation post-emotionship? Yeah, it would be drama. And I, you know, I'm human. I deal with drama all the time. But the reason why I wanna pick Data's brain is because I could have a conversation with him and ask, for example, how can we fix this ethics problem? And he could go through like the rational thinking and through that, he could also help me think through it as well. And so that's, there's like these questions, fundamental questions I think I could ask him that he would help me also learn from. And that fascinates me. I don't think there's a better place to end it. Aiyana, thank you so much for talking to me. It was an honor. Thank you. This was fun. Thanks for listening to this conversation. And thank you to our presenting sponsor, Cash App. Download it, use code LexPodcast. You'll get $10 and $10 will go to FIRST, a STEM education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators. If you enjoy this podcast, subscribe on YouTube, get five stars on Apple Podcast, follow on Spotify, support on Patreon, or simply connect with me on Twitter. And now let me leave you with some words of wisdom from Arthur C. Clarke. Whether we are based on carbon or on silicon makes no fundamental difference. We should each be treated with appropriate respect. Thank you for listening and hope to see you next time.

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Higgs Particle (Harry Cliff) | AI Podcast Clips

I mean, wasn't the Higgs called the God particle at some point? It was by a guy trying to sell popular science books, yeah. Yeah, but I mean, I remember because when I was hearing it, I thought it would, I mean, that would solve a lot of, unify a lot of our ideas of physics, was my notion. But maybe you can speak to that. Is it as big of a leap? Is it a God particle or is it a Jesus particle? Which, you know, what's the big contribution of Higgs in terms of this unification power? Yeah, I mean, to understand that, it maybe helps to know the history a little bit. So when the, what we call electro weak theory was put together, which is where you unify electromagnetism with the weak force, and the Higgs is involved in all of that. So that theory, which was written in the mid seventies, predicted the existence of four new particles, the W plus boson, the W minus boson, the Z boson, and the Higgs boson. So there were these four particles that came with the theory that were predicted by the theory. In 1983, 84, the W's and the Z particles were discovered at an accelerator at CERN called the super proton synchrotron, which was a seven kilometer particle collider. So three of the bits of this theory had already been found. So people were pretty confident from the eighties that the Higgs must exist because it was a part of this family of particles that this theoretical structure only works if the Higgs is there. So what then happens, so this question about why is the LHC the size it is? Well, actually the tunnel that the LHC is in was not built for the LHC. It was built for a previous accelerator called the large electron positron collider. So that began operation in the late eighties, early nineties. They basically, that's when they dug the 27 kilometer tunnel. They put this accelerator into it, the collider that fires electrons and anti electrons at each other, electrons and positrons. So the purpose of that machine was, well, it was actually to look for the Higgs. That was one of the things it was trying to do, but it didn't have enough energy to do it in the end. But the main thing it achieved was it studied the W and the Z particles at very high precision. So it made loads of these things. Previously you can only make a few of them at the previous accelerator. So you could study these really, really precisely. And by studying their properties, you could really test this electroweak theory that had been invented in the seventies and really make sure that it worked. So actually by 1999, when this machine turned off, people knew, well, okay, you never know until you find the thing. But people were really confident this electroweak theory was right and that the Higgs or something very like the Higgs had to exist because otherwise the whole thing doesn't work. It'd be really weird if you could discover these particles. They all behave exactly as your theory tells you they should, but somehow this key piece of the picture is not there. So in a way, it depends how you look at it. The discovery of the Higgs on its own is obviously a huge achievement in many, both experimentally and theoretically. On the other hand, it's like having a jigsaw puzzle where every piece has been filled in. You've this beautiful image, there's one gap and you kind of know that that piece must be there somewhere. So the discovery in itself, although it's important, is not so interesting. It's like a confirmation of the obvious at that point. But what makes it interesting is not that it just completes the Standard Model, which is a theory that we've known had the basic layout of for 40 years or more now. It's that the Higgs actually is a unique particle. It's very different to any of the other particles in the Standard Model. And it's a theoretically very troublesome particle. There are a lot of nasty things to do with the Higgs, but also opportunities. So we don't really understand how such an object can exist in the form that it does. So there are lots of reasons for thinking that the Higgs must come with a bunch of other particles or that it's perhaps made of other things. So it's not a fundamental particle, that it's made of smaller things. I can talk about that if you like a bit. But that's still a notion, so the Higgs might not be a fundamental particle, there might be some, oh man. So that is an idea, it's not been demonstrated to be true. But I mean, all of these ideas basically come from the fact that this is a problem that motivated a lot of development in physics in the last 30 years or so. And it's this basic fact that the Higgs field, which is this field that's everywhere in the universe, this is the thing that gives mass to the particles. The Higgs field is different from all the other fields in that, let's say you take the electromagnetic field, which is, if we actually were to measure the electromagnetic field in this room, we would measure all kinds of stuff going on because there's light, there's going to be microwaves and radio waves and stuff. But let's say we could go to a really, really remote part of empty space and shield it and put a big box around it and then measure the electromagnetic field in that box, the field would be almost zero, apart from some little quantum fluctuations. But basically it goes to naught. The Higgs field has a value everywhere. So it's a bit like the whole, it's like the entire space has got this energy stored in the Higgs field, which is not zero, it's finite. It's a bit like having the temperature of space raised to some background temperature. And it's that energy that gives mass to the particles. So the reason that electrons and quarks have mass is through the interaction with this energy that's stored in the Higgs field. Now it turns out that the precise value this energy has, has to be very carefully tuned if you want a universe where interesting stuff can happen. So if you push the Higgs field down, it has a tendency to collapse to... If you do your sort of naive calculations, there are basically two possible likely configurations for the Higgs field, which is either it's zero everywhere, in which case you have a universe which is just particles with no mass that can't form atoms and just fly about at the speed of light. Or it explodes to an enormous value, what we call the Planck scale, which is the scale of quantum gravity. And at that point, if the Higgs field was that strong, even an electron would become so massive that it would collapse into a black hole. And then you have a universe made of black holes and nothing, like us. So it seems that the strength of the Higgs field is to achieve the value that we see requires what we call fine-tuning of the laws of physics. You have to fiddle around with the other fields in the Standard Model and their properties to just get it to this right sort of Goldilocks value that allows atoms to exist. This is deeply fishy. People really dislike this. LRW Well yeah, I guess, so what would be... So two explanations. One, there's a God that designed this perfectly, and two is there's an infinite number of alternate universes and we just happen to be in the one in which life is possible. Complexity. So when you say, I mean, life, any kind of complexity, that's not either complete chaos or black holes. I mean, how does that make you feel? What do you make of that? That's such a fascinating notion that this perfectly tuned field that's the same everywhere is there. What do you make of that? Yeah, what do you make of that? PYM Yeah, so you laid out two of the possible explanations. LRW Really? Is this a spoof? PYM Yeah, I mean, well, some cosmic creator went, yeah, let's fix that to be at the right level. That's one possibility, I guess. It's not a scientifically testable one, but theoretically, I guess, it's possible. LRW Sorry to interrupt, but there could also be, not a designer, but couldn't there be just, I guess, I'm not sure what that would be, but some kind of force that, some kind of mechanism by which this kind of field is enforced in order to create complexity. Basically forces that pull the universe towards an interesting complexity. PYM I mean, yeah, I mean, there are people who have those ideas. I don't really subscribe to them. LRW As I'm saying, it sounds really stupid. PYM No, I mean, there are definitely people that make those kind of arguments. There's ideas that, I think it's Lee Smolin's idea, I think, that universes are born inside black holes. And so universes, they basically have like Darwinian evolution of the universe, where universes give birth to other universes. And if universes where black holes can form are more likely to give birth to more universes, so you end up with universes which have similar laws. I mean, I don't know, whatever. LRW I talked to Lee recently on this podcast, and he's a reminder to me that the physics community has like so many interesting characters. It's fascinating. Anyway, sorry. PYM I mean, as an experimentalist, I tend to sort of think these are interesting ideas, but they're not really testable. So I tend not to think about it very much. So I mean, going back to the science of this, there is an explanation, there is a possible solution to this problem of the Higgs, which doesn't involve multiverses or creators fiddling about with the laws of physics. If the most popular solution was something called super symmetry, which is a theory which involves a new type of symmetry of the universe. In fact, it's one of the last types of symmetries that is possible to have that we haven't already seen in nature, which is a symmetry between force particles and matter particles. So what we call fermions, which are the matter particles and bosons, which are force particles. And if you have super symmetry, then there is a super partner for every particle in the standard model. And without going into the details, the effect of this basically is that you have a whole bunch of other fields. And these fields cancel out the effect of the standard model fields, and they stabilize the Higgs field at a nice sensible value. So in super symmetry, you naturally, without any tinkering about with the constants of nature or anything, you get a Higgs field with a nice value, which is the one we see. So this is one of the reasons, and super symmetry has also got lots of other things going for it. It predicts the existence of a dark matter particle, which would be great. It potentially suggests that the strong force and the electroweak force unify at high energy. So lots of reasons people thought this was a productive idea. And when the LHC was, just before it was turned on, there was a lot of hype, I guess, a lot of an expectation that we would discover these super partners. And particularly the main reason was that if super symmetry stabilizes the Higgs field at this nice Goldilocks value, these super particles should have a mass around the energy that we're probing at the LHC, around the energy of the Higgs. So it was kind of thought you discover the Higgs, you probably discover super partners as well. So once you start creating ripples in this Higgs field, you should be able to see these kinds of, you should be, yeah. So these super fields would be there. When I, at the very beginning I said we're probing the vacuum, what I mean is really that, you know, okay, let's say these super fields exist. The vacuum contains super fields. They're there, these super symmetric fields. If we hit them hard enough, we can make them vibrate. We see super particles come flying out. That's the sort of, that's the idea. That's the whole point. But we haven't. But we haven't. So, so far at least, I mean, we've had now a decade of data taking at the LHC. No signs of super partners have super symmetric particles have been found. In fact, no signs of any physics, any new particles beyond the standard model have been found. So super symmetry is not the only thing that can do this. There are other theories that involve additional dimensions of space or potentially involve the Higgs boson being made of smaller things, being made of other particles. That's an interesting, you know, I haven't heard that before. That's really, that's an interesting, but could you maybe linger on that? Like what, what could be, what could a Higgs particle be made of? So the oldest, I think the original ideas about this was these theories called technicolor, which were basically like an analogy with the strong force. So the idea was the Higgs boson was a bound state of two very strongly interacting particles that were a bit like quarks. So like quarks, but I guess higher energy things with a super strong force. So not the strong force, but a new force that was very strong. And the Higgs was a bound state of these, these objects. And the Higgs would in principle, if that was right, would be the first in a series of technicolor particles. Technicolor, I think not being a theorist, but it's not, it's basically not done very well particularly since the LHC found the Higgs that kind of, it rules out, you know, a lot of these technicolor theories, but there are other things that are a bit like technicolor. So there's a theory called partial compositeness, which is an idea that some of my colleagues at Cambridge have worked on, which is a similar sort of idea that the Higgs is a bound state of some strongly interacting particles and that the standard model particles themselves, the more exotic ones like the top quark are also sort of mixtures of these composite particles. So it's a kind of an extension to the standard model, which explains this problem with the Higgs bosons Goldilocks value, but also helps us understand we have, we're in a situation now again, a bit like the periodic table where we have six quarks, six leptons in this kind of you can arrange in this nice table and there you can see these columns where the patterns repeat and you go, okay, maybe there's something deeper going on here. And so this would potentially be something, this partial compositeness theory could explain a sort of enlarge this picture that allows us to see the whole symmetrical pattern and understand what the ingredients, why do we have, so one of the big questions in particle physics is why are there three copies of the matter particles? So in what we call the first generation, which is what we're made of, there's the electron, the electron neutrino, the up quark and the down quark. They're the most common matter particles in the universe. Then there are copies of these four particles in the second and the third generations. So things like muons and top quarks and other stuff. We don't know why we see these patterns. We have no idea where it comes from. So that's another big question. You know, can we find out the deeper order that explains this particular periodic table of particles that we see? Is it possible that the deeper order includes like almost a single entity? So like something that I guess like string theory dreams about, is this essentially the dream is to discover something simple, beautiful and unifying? Yeah, I mean, that is the dream. And I think for some people, for a lot of people, it still is the dream. So there's a great book by Steven Weinberg, who is one of the theoretical physicists who was instrumental in building the standard model. So he came up with some others with the electroweak theory, the theory that unified electromagnetism and the weak force. And he wrote this book, I think it was towards the end of the 80s, early 90s, called Dreams of a Final Theory, which is a very lovely, quite short book about this idea of a final unifying theory that brings everything together. And I think you get a sense reading his book written at the end of the 80s, early 90s, that there was this feeling that such a theory was coming. And that was the time when string theory was very exciting. So string theory, there's been this thing called the super string revolution and theoretical physicists getting very excited. They discovered these theoretical objects, these little vibrating loops of string that in principle not only was a quantum theory of gravity, but could explain all the particles in the standard model and bring it all together. And as you say, you have one object, the string, and you can pluck it. And the way it vibrates gives you these different notes, each of which is a different particle. So it's a very lovely idea. But the problem is that people discover that mathematics is very difficult. So people have spent three decades or more trying to understand string theory. And I think if you spoke to most string theorists, they would probably freely admit that no one really knows what string theory is yet. I mean, there's been a lot of work, but it's not really understood. And the other problem is that string theory mostly makes predictions about physics that occurs at energies far beyond what we will ever be able to probe in the laboratory. Yeah, probably ever. By the way, so sorry, that'd take a million tangents, but is there room for complete innovation of how to build a particle collider that could give us an order of magnitude increase in the kind of energies? Or do we need to keep just increasing the size of things? I mean, maybe. Yeah, I mean, there are ideas, but to give you a sense of the gulf that has to be bridged. So the LHC collides particles at an energy of what we call 14 tera electron volts. So that's basically the equivalent of you've accelerated a proton through 14 trillion volts. That gets us to the energies where the Higgs and these weak particles live. They're very massive. The scale where strings become manifest is something called the Planck scale, which I think is of the order 10 to the- hang on, get this right. It's 10 to the 18 giga electron volts. So about 10 to the 15 tera electron volts. So you're talking trillions of times more energy. Yeah, 10 to the 15, 10 to the 14th larger. I may be wrong, but it's a very big number. So we're not talking just an order of magnitude increase in energy. We're talking 14 orders of magnitude energy increase. So to give you a sense of what that would look like, were you to build a particle accelerator with today's technology- Bigger or smaller than our solar system? The size of the galaxy. The galaxy. So you'd need to put a particle accelerator that circled the Milky Way to get to the energies where you would see strings if they exist. So that is a fundamental problem, which is that most of the predictions of these unified theories, quantum theories of gravity, only make statements that are testable at energies that we will not be able to probe. And barring some unbelievable, completely unexpected technological or scientific breakthrough, which is almost impossible to imagine. Never say never, but it seems very unlikely. Yeah, I can just see the news story. Elon Musk decides to build a particle collider the size of our- It would have to be, we'd have to get together with all our galactic neighbors to pay for it I think. It'd be like CERN on megasteroids.

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How many alien civilizations are out there?

This video is about optimistic, pessimistic, and my own estimates of how many intelligent alien civilizations might be out there. I center this video around the Drake equation that combines a bunch of parameters, multiplies them together, and estimates, based on that, the number of alien civilizations in our galaxy, the Milky Way galaxy, and the observable universe. In general, this video is probably less about the estimates themselves and more about the mysteries behind the very question. Quick thanks to our two sponsors, Brave Browser, good for your privacy, and Neural Gum, good for your brain. Check them out in the description to support the podcast I host. Okay, the Drake equation combines seven parameters, I added an eighth one here. I'm not using the symbols in the equation because it's too easy for people to forget what each one stands for. The variables build on each other, hence the multiplication. Okay, they are the number of new stars born per year, the percent of those stars that have planets, the number of habitable planets per star, the chance of life developing on one of those planets, then the chance of intelligent life developing, and finally the chance of that intelligent civilization advancing far enough to develop the technology to be able to communicate, in our case, through electromagnetic signal. Seventh is the lifetime of that civilization while it's in the communicating stage of its development. And finally, the eighth parameter that wasn't in the original Drake equation is the average number of times that a civilization is born on a planet. That is, one time it's born and it becomes completely extinct and is reborn again. This parameter makes sense since the age of a planet can be billions of years. And then you multiply it all together to get the estimated answer to our question. I list today's estimates for the optimistic and the pessimistic based on the most recent publications that I'm aware of, and today's estimates for me based on how I'm actually feeling today. This estimate probably drastically changes from day to day or from hour to hour within the day, based on my optimism on several of the parameters I'll talk about. I should say that the optimistic and the pessimistic estimates don't reflect the best case and the worst case. They simply reflect a reasonable estimate for a high value for these parameters and a low value for these parameters. Okay, the number of new stars born per year. The pessimistic one is 1.5 and the optimistic is 3. I tend to side with the 3. The 1.5 to 3 stars per year is the latest estimate as of about five years ago from NASA. Most recent relevant paper that I'm aware of is in 2015. Either way, the variability on this parameter is not very large. Let's just wait until later. Okay, the percent of these stars with planets. This is a little bit tricky, but it seems to me as of 2012, just looking at some papers, almost everyone seems to believe that now pretty much all of these star systems have planets around them. Somebody's probably going to argue for the pessimistic one being decreased to like 90% or even the previous one of like 30 or even 20%. I don't think this affects it that much. The evidence seems to indicate that pretty much every star has a planet around it. I like big rocks and I like gravity, so I think this is pretty exciting. The number of habitable planets per star. This is where we start to get into some fun debate. Probably mainly centered around the word habitable. Like what does it mean for a planet to be habitable? The argument for the optimistic view is pretty simple. To be in the habitable zone of a star if it's all just about the range of distances from the star. The more interesting argument for me that I tend to hold is that in order for a planet to be habitable, meaning support life in the broad definition of what life is, the planet doesn't necessarily need to be Earth-like. There could be totally different kinds of planets that are able to support life that we're not even aware of. Those who argue for the low estimate like the general set of ideas behind the rare Earth hypothesis that you should check out, places a lot more constraints on habitability like suitably low radiation, high star metallicity, which by the way from an astronomer perspective a metal is anything that's not hydrogen or helium. So carbon is a metal. There you go. Fun facts with Lex. Okay, continuing the list of constraints, low enough density to avoid excessive asteroid bombardment, and there's much more. There's a long list. I don't know which one of these is most constraining to be honest, but it really centers around the question stated by the rare Earth hypothesis. Does a habitable planet really have to be Earth-like? And exactly how close to the precise conditions of Earth does it have to be? Next parameter is the probability of life developing on a habitable planet. This parameter to me is super exciting, especially because it is one of the biggest open questions within the reach of science. If we discover hard evidence of life on Mars for example, even if it's extinct, or on Europa, the icy moon of Jupiter, and maybe more concrete evidence about life on Venus that was recently discovered in gaseous form, and phosphine I think in the atmosphere. So if there's some good concrete evidence of life on another planet, that shows you that the probability of life developing is quite high. So the day-to-day variability in my estimate has to do with how optimistic I am about us discovering life on the planets or moons in our solar system. Going by recent papers, the optimistic is 13%, the pessimistic is 0.1%. We go somewhere between those all the time, sometimes much closer to 13%. Today it's 1%, we're the 1%ers folks. The argument I think for the high estimate is that life on Earth appears to have started quickly after conditions were right for it. So if it started super quick on Earth, maybe it's pretty easy to start when the conditions are right. And the conditions would be right if we passed the previous parameter of it being a habitable planet. Again, these parameters stack on top of each other, meaning they're conditioned on whatever the thing that the previous parameter represents being true. If we stick just on Earth for our evidence, then the argument for the pessimistic view is that there doesn't seem to be evidence of abiogenesis, or the origination of life occurring more than once on Earth. As far as I could tell, I did not see any good evidence that life sprung up on Earth more than once. Meaning evidence of very different kinds of ancestor organisms. Alright, now we're starting to have some fun. The probability of intelligent life developing. This is of course probably one I talk a lot about in the context of artificial intelligence. Optimistic estimate I've seen is 1%, and the pessimistic one is 0.1%. I tend to actually see this as pretty high probability. In fact, I think that once life starts, intelligence is basically 100%. It's almost inevitable if given enough time. The open question to me is how long do there have to be a range of stable conditions that support the evolution of life? And what precisely that range is once life gets going. In general, the argument for the higher value is that complexity of systems seems to increase effortlessly. And the argument for the lower value is that humans are allegedly the only intelligent species on Earth among a lot of the species that have lived here. So it may be quite difficult even for the evolutionary process to create something like the human brain. Which I do think is quite a special creation. Despite its, in my case, occasional manifestation as dad jokes on Twitter. Okay. Oh, and I don't understand the optimistic estimate 1% that I saw in a few places. So I doubled it to 2%. That's where I stand on the probability of intelligent life developing. There you go. Double it. Okay. Ability to communicate. I kind of think of this as the percent of civilizations that become technologically advanced in the more general context of building advanced technologies. And I tend to see communication as bigger here than maybe the original Drake estimate did. And that it's likely to go beyond electromagnetic communication. Something that we're not even aware of currently. So the argument for the high value here is that, again, systems seem to increase in complexity effortlessly. So it seems to me that tech advancement is inevitable once you have a sufficiently intelligent civilization. The arguments that I find somewhat interesting for the more pessimistic estimate is that civilizations, perhaps in time, tend to isolate themselves. They perhaps lose interest in colonization or just broadly in the whole task of exploration and communication. Another idea is that possibly there is a divergent methodology to the ways that intelligent civilizations might communicate. So there might not be intersection about them being able to communicate with each other. Like totally new ways of information transfer that we're just not even aware of currently. Which does not involve any kind of leakage of signal that would nevertheless still be detectable. So I tend to be on the optimistic side of communication ability developing with the 20% estimate. Next is the lifetime of the civilization once it's already in that communicating advanced technology stage. I think this is one of the more interesting, one of the more open parameters that basically changes the game in the final estimate. This is where the most variability comes from. The previous parameters I find inspiring as a scientist and engineer. This parameter I find inspiring as a human. Because the higher we can get it up as a human civilization, the more likely it is that we make extensive, deep, meaningful contact with other intelligent alien civilizations. So the optimistic values here are very high and they range all over the place. But it centers around the idea that there's one or multiple great filters. And once we get past them as a technological civilization, then we're basically immortal from a civilization perspective. That we will increasingly colonize space, I guess diversifying our use of resources such that it becomes increasingly more difficult to destroy ourselves through the various existential threats that we face. The pessimistic estimate, if we look at human civilization as an average case and assume we destroy ourselves within a couple of years, then for humans, the stage of advanced technology is only lasted about 100 years. When we were able to send out explicit electromagnetic signal. Of course, I don't think we chose to do so explicitly until maybe a few decades ago. I don't remember. I think it was the 70s. Stairway to Heaven, Led Zeppelin era. There you go. My estimate, to be honest, in terms of the survival of human civilization is almost always pretty optimistic. The actual estimate of the lifetime ranges all over the place. I think my current estimate, I just put it 10,000 years. I think even that's really far away. That's 100 centuries from now. We're just in the first 100, 150 years of our advanced technological development. And what's going to happen in the next 100 of those, especially given that the rate of innovation seems to be accelerating, the essentials of my optimism is grounded in the fact that the forces of good will be able to out-innovate the forces of evil. Now, what that looks like 10,000 years from now, it's impossible for me to even imagine. So I'm uncomfortable with an estimate of one billion years from now. So that's why I put my optimistic but not too optimistic estimate of a lifetime of advanced technological civilization at 10,000 years. We're 100 years in, 9,900 years to go to prove me wrong. And finally, this extra parameter of the number of times a civilization is born on a planet, given the age of a planet, and if it is habitable, then I think and some optimistic estimates think that it's possible for intelligent civilizations to be reborn on a planet and put that value at three. The original estimate, of course, it wasn't part of the Drake equation, so it was at one. And so that's the pessimistic estimate. Okay, so we multiply all these together. Of course, the percentages are treated as fractions, so 13% is 0.13, for example. And the result of that multiplication is the estimate of intelligent alien civilizations that are capable of communicating in our galaxy. And so for these three estimates, the result is 468,000 for the optimistic estimate, very, very close to zero for the pessimistic estimate, and 0.7 for my estimate. Now that's for our Milky Way galaxy. Interestingly enough, the estimates for the number of galaxies in the observable universe seems to be changing, and growing, actually, and the current estimate that I'm aware of is actually two trillion galaxies, which is a very high number. So if we look at the number of alien communicating civilizations in the universe, it's 940 quadrillion, which is 1,000 trillion for the optimistic estimate. It's 300,000 for the pessimistic estimate, and 1.4 trillion for my estimate as of this hour today. Obviously, there's quite a bit of variability, and I find it quite entertaining that my estimate landed on very close to one, which aligns well with the idea that if we're pretty average in the Milky Way, it's pretty average that we just may be the only ones in the Milky Way galaxy. But every galaxy's got one. There's a bunch of takeaways I have from this quick thought experiment, and the reason I made the video is I wanted to go through the thought experiment, provide my estimates, and also reason through the very question itself, and some of the open questions around the estimate. So my current view is that we're not alone in terms of communicating alien intelligent civilizations in the universe. But the sense I have in terms of the very concept of communication is that we don't yet have the tools of science to understand what it means to communicate with alien intelligence. I tend to believe that aliens are very unlikely to have the humanoid form, that much more likely the variety of life is greater than we imagine and greater than we can imagine. Some of the variability would perhaps invalidate entirely the very structure of the Drake equation itself, which makes a lot of cosmological assumptions. Life could exist in different dimensions, whatever the heck that would even mean for a physics perspective. As Carl Sagan talked about, it could exist on very different time scales and very different spatial scales, which would make communication to us appear, like I think Sagan said, like noise. Because of our tools, but also because of the human-centric perspective we have on intelligence, that we're just not accustomed to trying to detect signal that operates in a different time scale and even on a different spatial scale. And not just life itself, I think the variety and extent of intelligence and communication methodology is greater than we can imagine and greater than we can imagine. Intelligent beings could operate at different conceptual spaces or layers of abstraction. The nature of communication, I think for humans it's in the space of ideas. It could be in the space of experiences or it could be in the space of whatever lays behind consciousness, for example. Consciousness itself may be aliens communicating with us. I mean, from the current scientific perspective, all of this sounds pretty crazy, but if you step away and just think from first principles of how little we actually understand about the basic nature of the human mind, then you have to think that understanding our mind may unlock some totally new ways of communication and unlock our understanding of what it means to be an intelligent civilization that will totally transform the estimates provided by the Drake equation. And that's why I think it's really inspiring to scientists, engineers, just curious minds, that the pursuits, maybe in my field of AI, and perhaps eventually the field of AI starts to encompassing the concepts of artificial consciousness. I think that provides the opportunity for both the scientists and the engineers to understand the human mind and to build artificial versions of it, you know, artificial general intelligence. And that seems to hold the key. And that is an engineering problem, is a scientific problem, seems to hold the key for us to be able to better understand what kind of other intelligent civilizations might be out there. Again, that's super exciting because in a sense, understanding ourselves is one way to search for intelligent civilizations out there. And in general, as I mentioned, I think all, or at least most, of the parameters in the Drake equation can be illuminated through science and through our engineering pursuit. So if we discover life on Mars, for example, that shows that life is doable elsewhere. If we are able to build artificial general intelligence systems, at least to me, that shows that intelligence is doable elsewhere, other than the human brain. And, you know, as a society, if we're able to avoid existential risks that are before us today, I think that shows that survival is doable elsewhere. Okay, looking at point three, four, and five quickly, let me say that this whole idea of other intelligent alien civilizations out there is really exciting and inspiring to me. So I hope that governments, nation states, will be able to look at the search for intelligent life not as a threat, not as something that you keep as a secret, but as something that can inspire us. I think we're humans first and Americans second. We're curious descendants of apes. And I think the idea of threats and secrecy, I hope, will become an outdated concept. But of course, it's not just about hope. You have to work hard to make it happen. You have to have actual practical ideas how we get there. Because right now, the old systems are stuck in this place where it's nice to have two superpowers fighting against each other. There's the Soviet Union and the United States. Maybe the 21st century will be defined by China versus the United States and so on. I think it's possible, and I think we have to build systems that move us beyond that. I think for point number four, I think doing so is essential for the survival of the human species. Again, that's my current view, but I think about this a lot, and I go back and forth. It mostly has to do about at least my thinking on how much evil there is in the world. And right now, for a time at least, I'm quite optimistic about the fundamental good in human nature. And finally, of course, in terms of increasing the lifetime of human civilization, but in general, finding intelligent life out there, I think space exploration is really exciting. General, this whole topic, the reason I made this video, the reason I have sometimes these conversations about aliens is I do believe that science is the best tool we have, but we can still have an open mind to the mystery of the universe around us. And of course, to me, the most fascinating, the mystery of the human mind itself. So clearly, this particular human mind has to apologize for the probably too long, boring rambling about aliens, but I hope for the few of you still listening that it was at least somewhat interesting. Again, please do check out the Brave browser and NeuroGum sponsors in the description to show support for the podcast that I host. Thanks for tuning in. See you next time.

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Dmitri Dolgov: Waymo and the Future of Self-Driving Cars | Lex Fridman Podcast #147

The following is a conversation with Dmitry Dolgov, the CTO of Waymo, which is an autonomous driving company that started as Google's self-driving car project in 2009 and became Waymo in 2016. Dmitry was there all along. Waymo is currently leading in the fully autonomous vehicle space in that they actually have an at-scale deployment of publicly accessible autonomous vehicles driving passengers around with no safety driver, with nobody in the driver's seat. This to me is an incredible accomplishment of engineering on one of the most difficult and exciting artificial intelligence challenges of the 21st century. Quick mention of a sponsor followed by some thoughts related to the episode. Thank you to Trial Labs, a company that helps businesses apply machine learning to solve real world problems. Blinkist, an app I use for reading through summaries of books. BetterHelp, online therapy with a licensed professional. And CashApp, the app I use to send money to friends. Please check out the sponsors in the description to get a discount and to support this podcast. As a side note, let me say that autonomous and semi-autonomous driving was the focus of my work at MIT and is a problem space that I find fascinating and full of open questions from both a robotics and a human psychology perspective. There's quite a bit that I could say here about my experiences in academia on this topic that revealed to me, let's say, the less admirable sides of human beings. But I choose to focus on the positive, on solutions, on brilliant engineers like Dmitry and the team at Waymo who work tirelessly to innovate and to build amazing technology that will define our future. Because of Dmitry and others like him, I'm excited for this future. And who knows, perhaps I too will help contribute something of value to it. If you enjoy this thing, subscribe on YouTube, review it with Five Stars and Upper Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Dmitry Dolgov. When did you first fall in love with robotics or even computer science more in general? Computer science first at a fairly young age. The robotics happened much later. I think my first interesting introduction to computers was in the late 80s when we got our first computer. I think it was an IBM, I think IBM AT. Remember those things that had like a turbo button in the front? The radio would press it and make the thing go faster. Did that already have floppy disks? Yeah, yeah, yeah. Like the 5.4 inch ones. I think there was a bigger inch. So, one something, then five inches, then three inches. Yeah, I think that was the five. I don't know. Maybe that was before that was the giant plates and I didn't get that. But it was definitely not the three inch ones. Anyway, so we got that computer. I spent the first few months just playing video games, as you would expect. I got bored of that. So, I started messing around and trying to figure out how to make the thing do other stuff. Got into exploring programming. And a couple of years later, it got to a point where I actually wrote a game, a little game. And a game developer, a Japanese game developer actually offered to buy it for me for a few hundred bucks, but for a kid in Russia. That's a big deal. That's a big deal, yeah. I did not take the deal. Wow, integrity. Yeah, I instead... That's stupidity. Yes, that was not the most acute financial move that I made in my life, looking back at it now. I instead put it... Well, I had a reason. I put it online. It was... What did you call it back in the day? It was a freeware thing, right? It was not open source, but you could upload the binaries, you would put the game online. And the idea was that people like it and then they contribute and they send you little donations, right? So, I did my quick math of like, of course, thousands and millions of people are going to play my game, send me a couple of bucks a piece, should definitely do that. As I said, not the best financial decision of my life. You were already playing business models at that young age. Remember what language it was? What programming? It was a basic... Pascal. Which, what? Pascal. Pascal. And it had a graphical component, so it's not text-based. Yeah, yeah. It was like, I think 320 by 200, whatever it was. I think that was kind of the earlier version. That's the resolution. VGA resolution, right? And I actually think the reason why this company wanted to buy it is not like the fancy graphics or the implementation. It was maybe the idea of actual game. The idea of the game. Okay. Well, one of the things, it's so funny. I used to play this game called Golden Axe and the simplicity of the graphics and something about the simplicity of the music, like it still haunts me. I don't know if that's a childhood thing. I don't know if that's the same thing for Call of Duty these days for young kids, but I still think that the games are simple. That simple purity makes for, like allows your imagination to take over and thereby creating a more magical experience. Like now with better and better graphics, it feels like your imagination doesn't get to create worlds, which is kind of interesting. It could be just an old man on a porch, like waving at kids these days that have no respect. But I still think that graphics almost get in the way of the experience. I don't know. Flippy bird. Yeah. I don't know if the imagination... It's closed. Okay. It's closed. I don't, yeah. But that's more about games that, like, that's more like Tetris World where they optimally, masterfully, like, create a fun, short-term dopamine experience versus I'm more referring to like role-playing games where there's like a story. You can live in it for months or years. Like there's an Elder Scrolls series, which is probably my favorite set of games. That was a magical experience. And the graphics are terrible. The characters were all randomly generated, but they're, I don't know. It pulls you in. There's a story. It's like an interactive version of an Elder Scrolls Tolkien world and you get to live in it. I don't know. I miss it. It's one of the things that suck about being an adult is there's no, you have to live in the real world as opposed to the Elder Scrolls world. You know, whatever brings you joy, right? Minecraft, right? Minecraft's a great example. You create, like, it's not the fancy graphics, but it's the creation of your own worlds. Yeah. That one is crazy. You know, one of the pitches for being a parent that people tell me is that you can like use the excuse of parenting to go back into the video game world. And like, that's like, you know, father, son, father, daughter time, but really you just get to play video games with your kids. So anyway, at that time, did you have any ridiculous, ambitious dreams of where as a creator you might go as an engineer? What did you think of yourself as an engineer, as a tinkerer, or did you want to be like an astronaut or something like that? You know, I'm tempted to make something up about, you know, robots, engineering, or, you know, mysteries of the universe, but that's not the actual memory that pops into my mind when you ask me about childhood dreams. So I'll actually share the real thing. When I was maybe four or five years old, I, as we all do, I thought about what I wanted to do when I grow up. And I had this dream of being a traffic control cop. You know, they don't have those today, I think, but you know, back in the 80s, and you know, in Russia, you probably are familiar with that, Lex. They had these, you know, police officers that would stand in the middle of an intersection all day, and they would have their like striped, black and white batons that they would use to, you know, control the flow of traffic. And, you know, for whatever reasons, I was strangely infatuated with this whole process. And like that, that was my dream. That's what I wanted to do when I grew up. And, you know, my parents, both physics profs, by the way, I think were, you know, a little concerned with that level of ambition coming from their child at that age. Well, that it's an interesting, I don't know if you can relate, but I very much love that idea. I have a OCD nature that I think lends itself very close to the engineering mindset, which is you want to kind of optimize, you know, solve a problem by creating an automated solution, like a set of rules, that set of rules that you follow, and then thereby make it ultra efficient. I don't know if that's it was of that nature. I certainly have that. There's like fact like SimCity and factory building games, all those kinds of things, kind of speak to that engineering mindset. Or did you just like the uniform? I think it was more of the latter. I think it was the uniform and the, you know, the striped baton that made cars go in the right directions that did. But I guess, you know, I did end up, I guess, you know, working in the transportation industry one way or another. No uniform, no. That's right. Maybe it was my, you know, deep inner infatuation with the, you know, traffic control batons that led to this career. Okay, when did you, when was the leap from programming to robotics? That happened later. That was after grad school. After, and actually, self-driving cars was, I think, my first real hands-on introduction to robotics. But I never really had that much hands-on experience in school and training. I, you know, worked on applied math and physics. Then in college, I did more kind of abstract computer science. And it was after grad school that I really got involved in robotics, which was actually self-driving cars. And, you know, that was a big, big flip. What grad school? So I went to grad school in Michigan, and then I did a postdoc at Stanford, which is, that was the postdoc where I got to play with self-driving cars. Yeah, so we'll return there. Let's go back to Moscow. So, you know, for episode 100, I talked to my dad. And also I grew up with my dad, I guess. So I had to put up with him for many years. And he went to the FISTIECH, or MIPT. It's weird to say in English, because I've heard all of this in Russian. Moscow Institute of Physics and Technology. And to me, that was like, I met some super interesting, as a child, I met some super interesting characters. It felt to me like the greatest university in the world, the most elite university in the world. And just the people that I met that came out of there were like, like, not only brilliant, but also special humans. It seems like that place really tested the soul. Both like, in terms of technically and like, spiritually. So that could be just the romanticization of that place. I'm not sure. But so maybe you can speak to it. But did, is it correct to say that you spent some time at FISTIECH? Yeah, that's right. Six years. I got my bachelor's and master's in physics and math there. And it's actually interesting, because my dad, actually both my parents, went there. And I think all the stories that I heard, like, just like you, Alex, growing up about the place, and you know, how interesting and special and magical it was, I think that was a significant, maybe the main reason I wanted to go there for college. Enough so that I actually went back to Russia from the US. I graduated high school in the US. You went back there? I went back there. Yeah. Exactly the reaction most of my peers in college had. But, you know, perhaps a little bit stronger that, you know, point me out as this crazy kid. Were your parents supportive of that? Yeah. Yeah. Like, it was your previous question. They supported me and, you know, letting me kind of pursue my passions and the things that I was interested in. That's a bold move. Wow. What was it like there? It was interesting. You know, definitely fairly hardcore on the fundamentals of, you know, math and physics and, you know, lots of good memories from, you know, from those times. So, okay. So Stanford, how'd you get into autonomous vehicles? I had the great fortune and great honor to join Stanford's DARPA Urban Challenge Team in 2006. This was a third in the sequence of the DARPA challenges. There were two grand challenges prior to that. And then in 2007, they held the DARPA Urban Challenge. So, you know, I was doing my postdoc I had. I joined the team and worked on motion planning for, you know, that competition. So, okay. So for people who might not know, I know from a certain, autonomous vehicles is a funny world. In a certain circle of people, everybody knows everything. And then in a certain circle, nobody knows anything in terms of general public. So it's interesting. It's a good question what to talk about. But I do think that the Urban Challenge is worth revisiting. It's a fun little challenge. First, it like sparked so much, so many incredible minds to focus on one of the hardest problems of our time in artificial intelligence. So that's a success from a perspective of a single little challenge. But can you talk about like, what did the challenge involve? So were there pedestrians? Were there other cars? What was the goal? Who was on the team? How long did it take? Any fun sort of specs? Sure, sure, sure. So the way the challenge was constructed, and just a little bit of backgrounding, as I mentioned, this was the third competition in that series. The first two were the grand challenge, called the Grand Challenge. The goal there was to just drive in a completely static environment, you know, you had to drive in a desert. That was very successful. So then DARPA followed with what they call the Urban Challenge, where the goal was to have, you know, build vehicles that could operate in more dynamic environments and, you know, share them with other vehicles. There were no pedestrians there. But what DARPA did is they took over an abandoned Air Force Base. And it was kind of like a little fake city that they built out there. And they had a bunch of robots, you know, cars that were autonomous in there all at the same time, mixed in with other vehicles driven by professional drivers. And each car had a mission. And so there's a crude map that they received at the beginning, and they had a mission and go, you know, here and then there and over here. And they kind of all were sharing this environment at the same time they had to interact with each other, they had to interact with the human drivers. So it's this very first very rudimentary version of a self-driving car that could operate in an environment shared with other dynamic actors. That, as you said, really, in many ways, kickstarted this whole industry. Okay, so who was on the team? And how'd you do? I forget. I came in second. Perhaps that was my contribution to the team. I think the Stanford team came in first in the DARPA challenge. But then I joined the team and, you know, You were the one with the bug in the code. I mean, do you have sort of memories of some particularly challenging things? Or, you know, one of the cool things, it's not, you know, this isn't a product, this isn't the thing that, you know, you have a little bit more freedom to experiment, so you can take risks, and there's, so you can make mistakes. Is there interesting mistakes? Is there interesting challenges that stand out to you, or something that taught you a good technical lesson or a good philosophical lesson from that time? Yeah, definitely, definitely a very memorable time. Not really a challenge, but like one of the most vivid memories that I have from the time. And I think that was actually one of the days that really got me hooked on this whole field was the first time I got to run my software on the car. And I was working on a part of our planning algorithm that had to navigate in parking lots. So it was something that called free space motion planning. So the very first version of that, we tried on the car, it was on Stanford's campus in the middle of the night, and you had this little course constructed with cones in the middle of a parking lot. So we're there in like 3am. You know, by the time we got the code to, you know, compile and turn over, and, you know, it drove, I could actually did something quite reasonable. And, you know, it was, of course, very buggy at the time and had all kinds of problems. But it was pretty darn magical. I remember going back and, you know, you know, later at night, trying to fall asleep and just, you know, being unable to fall asleep for the rest of the night. Just my mind was blown. And that's what I've been doing ever since for more than a decade. In terms of challenges and, you know, interesting memories, like on the day of the competition, it was pretty nerve wracking. I remember standing there with Mike Montemarolo, who was the software lead and wrote most of the code. I think I did one little part of the planner, Mike, you know, incredibly did pretty much the rest of it with, you know, a bunch of other incredible people. But I remember standing on the day of the competition, you know, watching the car, you know, with Mike and cars are completely empty, right? They're all there lined up in the beginning of the race. And then, you know, DARPA sends them, you know, on their mission one by one. So then leave and like you just, they had these sirens, they all had their different silence, right? Each siren had its own personality, if you will. So, you know, off they go, and you don't see them, you just kind of, and then every once in a while, they, you know, come a little bit closer to where the audience is, and you can kind of hear, you know, the sound of your car, and you know, it seems to be moving along. So that, you know, gives you hope. And then, you know, it goes away, and you can't hear it for too long, you start getting anxious, right? It's a little bit like, you know, sending your kids to college, and like, you know, kind of you invested in them, you hope you, you build it properly, but like, it's still anxiety inducing. So that was an incredibly fun few days. In terms of, you know, bugs, as we mentioned, you know, one, that was my bug that caused us the loss of the first place, is still a debate that you occasionally have with people on the CMU team, CMU came first, I should mention that. CMU, haven't heard of them. But yeah, it's something, you know, it's a small school. It's, it's, it's, you know, really glitched that, you know, they happen to succeed at something robotics related. Very scenic, though. So most people go there for the scenery. Yeah, it's a beautiful campus. I'm like, unlike Stanford. So for people, yeah, that's true. Unlike Stanford, for people who don't know, CMU is one of the great robotics and sort of artificial intelligence universities in the world. CMU Carnegie Mellon University. Okay, sorry, go ahead. Good, good PSA. So in the part that I contributed to, which was navigating parking loss, and the way you know, that part of the mission work is, you in a parking lot, you would get from DARPA, an outline of the map, you basically get this, you know, giant polygon that define the perimeter of the parking lot. And there would be an entrance and maybe multiple entrances or access to it. And then you would get a goal within that open space, XY, you know, heading, where the car had to park, it had no information about the optical obstacles that the car might encounter there. So it had to navigate kind of completely free space from the entrance to the parking lot into that parking space. And then once you're parked there, it had to exit the parking lot. And while, of course, in counting and reasoning about all the obstacles that it encounters in real time. So our interpretation, or at least my interpretation of the rules was that you had to reverse out of the parking spot. And that's what our cars did, even if there's no obstacle in front. That's not what CMU's car did. And it just kind of drove right through. So there's still a debate. And of course, you know, as you stop and reverse out and go out the different way, that costs you some time. And so there's still a debate whether, you know, it was my poor implementation that cost us extra time or whether it was, you know, CMU violating an important rule of the competition. And, you know, I have my own opinion here. In terms of other bugs, and like, I have to apologize to Mike Montemariella for sharing this on air, but it is actually one of the more memorable ones. And it's something that's kind of become a bit of a metaphor and a label in the industry since then, I think, at least in some circles, it's called the Victory Circle or Victory Lap. And our cars did that. So in one of the missions in the urban challenge, in one of the courses, there was this big oval right by the start and finish of the race. So the ARPA had a lot of the missions would finish in that same location. And it was pretty cool because you could see the cars come by, you know, kind of finish that part, like over the trip, that like over the mission, and then go on and finish the rest of it. And other vehicles would, you know, come hit their waypoint and, you know, exit the oval and off they would go. Our car in the hand, which hit the checkpoint, and then it would do an extra lap around the oval and only then, you know, leave and go in its merry way. So over the course of, you know, the full day, it accumulated some extra time. And the problem was that we had a bug where it wouldn't, you know, start reasoning about the next waypoint and plan a route to get to that next point until it hit a previous one. And in that particular case, by the time you hit that one, it was too late for us to consider the next one and kind of make a lane change. So every time it would do like an extra lap. So, you know, that's the Stanford victory lap. Oh, that's, I feel like there's something philosophically profound in there somehow. But I mean, ultimately, everybody is a winner in that kind of competition. And it led to sort of famously to the creation of Google Self-Driving Car Project and now Waymo. So can we give an overview of how is Waymo born? How's the Google Self-Driving Car Project born? What is the mission? What is the hope? What is it is the engineering kind of set of milestones that it seeks to accomplish? There's a lot of questions in there. Yeah. I don't know. But you're right. Kind of the DARPA Urban Challenge and the previous DARPA Grand Challenges kind of led, I think, to a very large degree to that next step. And Larry and Sergey, Larry Page and Sergey Brin, Google founders, saw that competition and believed in the technology. So, you know, the Google Self-Driving Car Project was born, you know, at that time, and we started in 2009, it was a pretty small group of us, about a dozen people who came together to work on this project at Google. At that time, we saw, you know, that incredible early result in the DARPA Urban Challenge. I think we're all incredibly excited about where we got to and we believed in the future of the technology, but we still had a very rudimentary understanding of the problem space. So the first goal of this project in 2009 was to really better understand what we're up against. And, you know, with that goal in mind, when we started the project, we created a few milestones for ourselves that maximized learnings. Well, the two milestones were, you know, one was to drive a hundred thousand miles in autonomous mode, which was at that time, you know, orders of magnitude that more than anybody has ever done. And the second milestone was to drive 10 routes. Each one was a hundred miles long. They were specifically chosen to be kind of extra spicy, you know, extra complicated and sampled the full complexity of that domain. And you had to drive each one from beginning to end with no intervention, no human intervention. So you would get to the beginning of the course, you would press the button that would engage in autonomy, and you had to go for a hundred miles, you know, beginning to end with no interventions. And it sampled, again, the full complexity of driving conditions. Some were on freeways. We had one route that went all through all the freeways and all the bridges in the Bay Area. You know, we had some that went around Lake Tahoe and kind of mountains roads. We had some that drove through dense urban environments like in downtown Palo Alto and through San Francisco. So it was incredibly interesting to work on. And it took us just under two years, about a year and a half, a little bit more to finish both of these milestones. And in that process, A, it was an incredible amount of fun, probably the most fun I had in my professional career. And you're just learning so much. You are, you know, the goal here is to learn and prototype. You're not yet starting to build a production system, right? So you just, you were, you know, this is when you're kind of working 24 seven and hacking things together. And you also don't know how hard this is. I mean, that's the point. Like, so I mean, that's an ambitious, if I put myself in that mindset, even still, that's a really ambitious set of goals. Like just those two, just picking 10 different difficult, spicy challenges, and then having zero interventions. So like not saying gradually we're going to like, you know, over a period of 10 years, we're going to have a bunch of roots and gradually reduce the number of interventions. You know, that literally says like, by as soon as possible, we want to have zero and on hard roads. So like, to me, if I was facing that, it's unclear whether that takes two years or whether that takes 20 years. I mean, it took us under two. And I guess that that speaks to a really big difference between doing something once and having a prototype where you're going after, you know, learning about the problem versus how you go about engineering a product that, you know, where you look at, you know, do you do properly do evaluation, you look at metrics, you know, drive down, and you're confident that you can do that. And I guess that's the, you know, why it took a dozen people, you know, 16 months or a little bit more than that, back in 2009 and 2010, with the technology of, you know, the more than a decade ago, that amount of time to achieve that milestone of 10 routes, 100 miles each and no interventions. And, you know, it took us a little bit longer to get to, you know, a full driverless product that customers use. That's another really important moment. Is there some memories of technical lessons? Or just one, like, what did you learn about the problem of driving from that experience? I mean, we can now talk about like, what you learned from modern day Waymo. But I feel like you may have learned some profound things in those early days, even more so because it feels like what Waymo is now is to trying to, you know, how to do scale, how to make sure you create a product, how to make sure there's like safety and all those things, which is all fascinating challenges. But like, you were facing the more fundamental philosophical problem of driving in those early days, like, what the hell is driving as an autonomous vehicle? Maybe I'm again, romanticizing it. But is there some valuable lessons you picked up over there at those two years? A ton. The most important one is probably that we believe that it's doable. And we've gotten far enough into the problem that, you know, we had a, I think, only a glimpse of the true complexity of the domain. And it's a little bit like, you know, climbing a mountain where you kind of, you know, see the next peak, and you think that's kind of the summit, but then you get to that, and you kind of see that this is just the start of the journey. But we've tried, we've sampled enough of the problem space, and we've made enough rapid success, even, you know, with technology of 2009, 2010, that it gave us confidence to then pursue this as a real product. So, okay, so the next step, you mentioned the milestones that you had in those two years, what are the next milestones that then led to the creation of Waymo and beyond? Yeah, it was a really interesting journey. And, you know, Waymo came a little bit later. Then, you know, we completed those milestones in 2010. That was the pivot when we decided to focus on actually building a product, you know, using this technology. The initial couple years after that, we were focused on a freeway, you know, what you would call a driver assist, maybe, you know, an L3 driver assist program. Then around 2013, we've learned enough about the space and thought more deeply about, you know, the product that we wanted to build that we pivoted. We pivoted towards this vision of building a driver and deploying it fully driverless vehicles without a person. And that's the path that we've been on since then. And it was exactly the right decision for us. So there was a moment where you also considered like, what is the right trajectory here? What is the right role of automation in the task of driving? It wasn't from the early days, obviously, you want to go fully autonomous. From the early days, it was not. I think it was in 20, around 2013, maybe that we've, that became very clear. And we made that pivot and also became very clear. And that it's the way you go building a driver assist system is, you know, fundamentally different from how you go building a fully driverless vehicle. So, you know, we've pivoted towards the latter. And that's what we've been working on ever since. And so that was around 2013. Then there's a sequence of really meaningful for us really important, defining milestones since then. And 2015, we had our first, actually the world's first fully driverless ride on public roads. It was in a custom built vehicle that we had, I must have seen those, we call them the Firefly that, you know, funny looking marshmallow looking thing. And we put a passenger, his name was Steve Mann, a great friend of our project from the early days, the man happens to be blind. So we put him in that vehicle, the car had no steering wheel, no pedals, it was an uncontrolled environment, you know, no lead or chase cars, no police escorts. And, you know, we did that trip a few times in Austin, Texas. So that was a really big milestone. But that was in Austin. Yeah. Okay. And, you know, we only but at that time, we're only it took a tremendous amount of engineering, it took a tremendous amount of validation to get to that point. But now we only did it a few times, maybe only did that it was a fixed route. It was not kind of a controlled environment, but it was a fixed route. And we only did a few times. Then in 2016, end of 2016, beginning of 2017 is when we founded Waymo, the company, that's when we kind of that was the next phase of the project where I wanted, we believed in kind of the commercial vision of this technology. And it made sense to create an independent entity, you know, within that alphabet umbrella to pursue this product at scale. Beyond that, in 2017, later in 2017, was another really huge step for us really big milestone where we started, it was October of 2017. Where when we started regular driverless operations on public roads, that first day of operations we drove in one day, and that first day 100 miles and driverless fashion. And then we've the most the most important thing about that milestone was not that 100 miles in one day, but that it was the start of kind of regular ongoing driverless operations. And when you say driverless, it means no driver. That's exactly right. So on that first day, we actually had a mix. And in some, we didn't want to like, you know, be on YouTube and Twitter that same day. So in many of the rides, we had somebody in the driver's seat, but they could not disengage, like the car, not disengage. But actually, on that first day, some of the miles were driven and just completely empty driver's seat. And this is the key distinction that I think people don't realize, you know, that oftentimes when you talk about autonomous vehicles, you're, there's often a driver in the seat that's ready to take over what's called a safety driver. And then Waymo is really one of the only companies, at least that I'm aware of, or at least as like boldly and carefully and all that is actually has cases, and now we'll talk about more and more, where there's literally no driver. So that's another, the interesting case of where the driver is not supposed to disengage, that's like a nice middle ground, they're still there, but they're not supposed to disengage. But really there's the case when there's no, okay, there's something magical about there being nobody in the driver's seat. Like, just like to me, you mentioned the first time you wrote some code for free space navigation of the parking lot, that was like a magical moment. To me, just sort of as an observer of robots, the first magical moment is seeing an autonomous vehicle turn, like make a left turn, like apply sufficient torque to the steering wheel to where like there's a lot of rotation. And for some reason, and there's nobody in the driver's seat, for some reason that communicates that here's a being with power that makes a decision. There's something about like the steering wheel, because we perhaps romanticize the notion of the steering wheel, it's so essential to our conception, our 20th century conception of a car, and it turning the steering wheel with nobody in the driver's seat, that to me, I think maybe to others, it's really powerful. Like this thing is in control. And then there's this leap of trust that you give, like I'm going to put my life in the hands of this thing that's in control. So in that sense, when there's no driver in the driver's seat, that's a magical moment for robots. So I got a chance last year to take a ride in a William Will vehicle, and that was the magical moment. There's like nobody in the driver's seat. It's like the little details, you would think it doesn't matter whether there's a driver or not, but like if there's no driver and the steering wheel is turning on its own, I don't know, that's magical. It's absolutely magical. I've taken many of these rides in a completely empty car, no human in the car pulls up. You call it on your cell phone, it pulls up, you get in, it takes you on its way. There's nobody in the car but you, right? That's something called fully driverless, our rider only mode of operation. Yeah, it is magical. It is transformative. This is what we hear from our riders. It really changes your experience. And that really is what unlocks the real potential of this technology. But coming back to our journey, that was 2017 when we started truly driverless operations. Then in 2018, we've launched our public commercial service that we called Waymo One in Phoenix. In 2019, we started offering truly driverless rider only rides to our early rider population of users. And then 2020 has also been a pretty interesting year. One of the first ones, less about technology, but more about the maturing and the growth of Waymo as a company. We raised our first round of external financing this year. We were part of Alphabet, so obviously we have access to significant resources. But on the journey of Waymo maturing as a company, it made sense for us to partially go externally in this round. So we raised about $3.2 billion from that round. We've also started putting our fifth generation of our driver, our hardware, that is on the new vehicle. But it's also a qualitatively different set of self-driving hardware that is now on the JLR pace. So that was a very important step for us. Hardware specs, fifth generation, I think it'd be fun to maybe, I apologize if I'm interrupting, but maybe talk about maybe the generations with a focus on what we're talking about in the fifth generation in terms of hardware specs, like what's on this car? Sure. So we separated out the actual car that we are driving from the self-driving hardware we put on it. Right now we have, so this is, as I mentioned, the fifth generation. We've gone through, we started building our own hardware many, many years ago. And that Firefly vehicle also had the hardware suite that was mostly designed, engineered, and built in-house. Lighters are one of the more important components that we design and build from the ground up. So on the fifth generation of our drivers, of our self-driving hardware that we're switching to right now, we have, as with previous generations, in terms of sensing, we have lighters, cameras, and radars. And we have a pretty beefy computer that processes all that information and makes decisions in real time on board the car. So in all of the, and it's really a qualitative jump forward in terms of the capabilities and the various parameters and the specs of the hardware compared to what we had before, and compared to what you can kind of get off the shelf in the market today. Meaning from fifth to fourth or from fifth to first? Definitely from first to fifth, but also from the fourth. That was the world's dumbest question. Definitely from fourth to fifth, as well as that last step is a big step forward. So everything's in-house, so the lidar is built in-house, and cameras are built in-house? It's different. We work with partners and there's some components that we get from our manufacturing and supply chain partners. We have a lot of different components that we get from our manufacturing partners. What exactly is in-house is a bit different. We do a lot of custom design on all of our sensing models. There's lighters, radars, cameras. Exactly, there's lighters are almost exclusively in-house and some of the technologies that we have, some of the fundamental technologies there are completely unique to Waymo. That is also about radars and cameras. It's a little bit more of a mix in terms of what we do ourselves versus what we get from partners. Is there something super sexy about the computer that you can mention that's not top secret? Like for people who enjoy computers? I mean, there's a lot of machine learning involved, but there's a lot of just basic compute. You have to probably do a lot of signal processing on all the different sensors. You have to integrate everything has to be in real time. There's probably some kind of redundancy type of situation. Is there something interesting you could say about the computer for the people who love hardware? It does have all of the characteristics, all the properties that you just mentioned. Redundancy, very beefy compute for general processing, as well as inference and ML models. It is some of the more sensitive stuff that I don't want to get into for IP reasons, but we've shared a little bit in terms of the specs of the sensors that we have on the car. We actually shared some videos of what our lighters see in the world. We have 29 cameras, we have five lighters, we have six radars on these vehicles. You can kind of get a feel for the amount of data that they're producing. That all has to be processed in real time to do perception, to do complex reasoning. It kind of gives you some idea of how beefy those computers are, but I don't want to get into specifics of exactly how we build them. Okay, well, let me try some more questions that you can't get into the specifics of like GPU wise. Is that something you can get into? I know that Google works with GPUs and so on. I mean, for machine learning folks, it's kind of interesting. Or is there no... How do I ask it? I've been talking to people in the government about UFOs and they don't answer any questions. So this is how I feel right now asking about GPUs. But is there something interesting that you could reveal? Or is it just, you know, or leave it up to our imagination, some of the compute? Is there any, I guess, is there any fun trickery? Like I talked to Chris Latner for a second time and he is a key person about GPUs and there's a lot of fun stuff going on in Google in terms of hardware that optimizes for machine learning. Is there something you can reveal in terms of how much you mentioned customization, how much customization there is for hardware for machine learning purposes? I'm going to be like that government, you know, you've got a guy, a person that bought UFOs. But I guess I will say that it's really compute is really important. We have very data hungry and compute hungry ML models all over our stack. And this is where, both being part of Alphabet, as well as designing our own sensors and the entire hardware suite together, where on one hand, you get access to like really rich, raw sensor data that you can pipe from your sensors into your compute platform and build like build a whole pipe from sensor, raw sensor data to the big compute as then have the massive compute to process all that data. And this is where we're finding that having a lot of control of that hardware part of the stack is really advantageous. One of the fascinating magical places to me, again, might not be able to speak to the details, but it is the other compute, which is like, you know, this, we're just talking about a single car. But the, you know, the driving experience is a source of a lot of fascinating data. And you have a huge amount of data coming in on the car, on the car. And, you know, the infrastructure of storing some of that data to then train or to analyze or so on. That's a fascinating, like, piece of it that, that I understand a single car, I don't understand how you pull it all together in a nice way. Is that something that you could speak to in terms of the challenges of, of seeing the network of cars, and then bringing the data back and analyzing things and analyzing things that like, like edge cases of driving, be able to learn on them to improve the system to, to see where things went wrong, where, where things went right and analyze all that kind of stuff. Is there something interesting there in the, from an engineering perspective? Oh, there's an incredible amount of really interesting work that's happening there, both in the, you know, the real time operation of the fleet of cars and the information that they exchange with each other in real time to make better decisions, as well as the kind of the off board component where you have to deal with massive amounts of data for training your ML models, evaluating the ML models for simulating the entire system and for evaluating your entire system. And this is where being part of Alphabet has been, once again, been tremendously advantageous. I think we consume an incredible amount of, you know, compute for ML infrastructure, we build a lot of custom frameworks to, you know, get good at, you know, on data mining, finding the interesting edge cases for training and for evaluation of the system, for both training and evaluating sub components and your sub parts of the system and various ML models, as well as the evaluating the entire system and simulation. Okay, so that first piece that you mentioned that cars communicating to each other, essentially, I mean, through perhaps through a centralized point, but what, that's fascinating too. How much does that help you? Like, if you imagine, you know, right now, the number of way more vehicles is whatever x, I don't know if you can talk to what that number is, but it's not in the hundreds of millions yet. And imagine if the whole world is way more vehicles, like that changes potentially the power of connectivity, like the more cars you have, I guess, actually, if you look at Phoenix, because there's enough vehicles, there's enough, when there's like some level of density, you can start to probably do some really interesting stuff with the fact that cars can negotiate can be can communicate with each other and thereby make decisions. Is there something interesting there that you can talk to about like, how does that help with the driving problem from as compared to just a single car solving the driving problem by itself? Yeah, it's a spectrum. I first and say that, yeah, it's it helps. And it helps in various ways, but it's not required. Right now, the way we build our system, like each cars can operate independently, they can operate with no connectivity. So I think it is important that you have a fully autonomous, you know, fully capable driver, that computerized driver that each car has, then, you know, they do share information, and they share information in real time, it really, really helps. So the way we do this today is, you know, whenever one car encounters something interesting in the world, whether it might be an accident or a new construction zone, that information immediately gets, you know, uploaded over the air, and it's propagated to the rest of the fleet. So and that's kind of how we think about maps as priors, in terms of the knowledge of our drivers of our fleet of drivers that is distributed across the fleet, and it's updated in real time. So that's one use case. You know, you can imagine as the, you know, the density of these vehicles go up, that they can exchange more information in terms of what they're planning to do, and start influencing how they interact with each other, as well as, you know, potentially sharing some observations, right, to help with, you know, if you have enough density of these vehicles, where, you know, one car might be seeing something that another is relevant to another car, that is very dynamic, you know, it's not part of kind of you're updating your static prior of the map of the world, but it's more of a dynamic information that could be relevant to the decisions that another car is making real time. So you can see them exchanging that information, and you can build on that. But again, I see that as an advantage, but it's, you know, not a requirement. So what about the human in the loop? So when I got a chance to drive with a ride in a Waymo, you know, there's customer service. So like, there is somebody that's able to dynamically, like, tune in and help you out. What role does the human play in that picture? That's a fascinating, like, you know, the idea of teleoperation, be able to remotely control a vehicle. So here, what we're talking about is like, like frictionless, like a human being able to in a, in a frictionless way, sort of help you out. I don't know if they're able to actually control the vehicle. Is that something you could talk to? Yes. Okay. To be clear, we don't do teleoperation. I'm going to believe in teleoperation. For a reason, that's not what we have in our cars. We do, as you mentioned, have a version of customer support. We call it life health. In fact, we find that it's very important for our rider experience, especially if it's your first trip, you've never been in a fully driverless, right, or only Waymo vehicle, you get in, there's nobody there. So you can imagine having all kinds of questions in your head, like how this thing works. So we've put a lot of thought into kind of guiding our riders or customers through that experience, especially for the first time, they get some information on the phone. If the fully driverless vehicle is used to service their trip, when you get into the car, we have an in car, you know, screen and audio that kind of guides them and explains what to expect. They also have a button that they can push that will connect them to, you know, a real life human being that they can talk to, right about this whole process. So that's one aspect of it. There is, you know, I should mention that there is another function that humans provide to our cars, but it's not teleoperation. You can think of it a little bit more like, you know, fleet assistance, kind of like, you know, traffic control that you have, where our cars, again, they're responsible on their own for making all of the decisions, all of the driving decisions that don't require connectivity. They, you know, anything that is safety or latency critical is done, you know, purely autonomously by onboard, our onboard system. But there are situations where, you know, if connectivity is available, when a car encounters a particularly challenging situation, you can imagine like a super hairy scene of an accident, the cars will do their best, they will recognize that it's an off nominal situation. They will do their best to come up with the right interpretation, the best course of action in that scenario. But if connectivity is available, they can ask for confirmation from, you know, a human assistant to kind of confirm those actions and perhaps provide a little bit of kind of contextual information and guidance. So October 8th was when you're talking about the, was Waymo launched the, the, the fully self, the public version of its fully driverless, that's the right term, I think, service in Phoenix. Is that October 8th? That's right. It was the introduction of fully driverless rider-only vehicles into our public Waymo One service. Okay. So that's, that's amazing. So it's like anybody can get into Waymo in Phoenix? That's right. So we previously had early people in our early rider program, taking fully driverless rides in Phoenix. And just this, a little while ago, we opened on October 8th, we opened that mode of operation to the public. So I can download the app and go on a ride. There is a lot more demand right now for that service than we have capacity. So we're kind of managing that, but that's exactly the way you described it. Yeah, well, that's interesting. So there's more demand than you can, you can handle. Like what, what has been the reception so far? Like what, I mean, okay, so, you know, that's, this is a product, right? That's a whole nother discussion of like how compelling of a product it is. Great. But it's also like one of the most kind of transformational technologies of the 21st century. So there, it's also like a tourist attraction. Like it's fun to, you know, to be a part of it. So it'd be interesting to see like, what, what do people say? What do people, what have been the feedback so far? You know, still early days, but so far the feedback has been incredible, incredibly positive. They, you know, we asked them for feedback during the ride. We asked them for feedback after the ride as part of their trip. You know, we asked them some questions, we asked them to, you know, rate the performance of our driver. Most by far, you know, most of our drivers give us five stars in our app, which is absolutely great to see. And yeah, that's, and we're, they're also giving us feedback on, you know, things we can improve. And you know, that's, that's one of the main reasons we're doing this as Phoenix and, you know, over the last couple of years and every day today we are just learning a tremendous amount of new stuff from our users. There's, there's no substitute for actually doing the real thing, actually having a fully driverless product out there in the field with users that are actually paying us money to get from point A to point B. So this is a legitimate, like, this is a paid service. That's right. And the idea is you use the app to go from point A to point B, and then what, what are the A's? What are the, what's the freedom of the, of the starting and ending places? It's an area of geography where that service is enabled. It's a decent size of geography of territory. It's actually larger than, than size of San Francisco. And, you know, within that you have full freedom of, you know, selecting where you want to go. You know, of course, there are some, and you, on your app, you get a map, you tell the car where you want to be picked up, you know, where you want the car to pull over and pick you up. And then you tell it where you want to be dropped off. Right. And of course there are some exclusions, right. You don't want to be, you know, where in terms of where the car is allowed to pull over, right. So, you know, that you can't do, but besides that, it's amazing. It's not like a fixed, just would be very, I guess, I don't know, maybe that's, what's the question behind your question, but it's not a preset set of, yes, I guess. So within the geographic constraints with that, within that area, anywhere else, it can be, you can be picked up and dropped off anywhere. That's right. And, you know, people use them on like all kinds of trips. They, we have, and we have an incredible spectrum of riders. I think the youngest actually have car seats them. And we have, you know, people taking their kids and rides. I think the youngest riders we had on cars are one or two years old, you know, and the full spectrum of use cases, people can take them to, you know, schools, to, you know, go grocery shopping, to restaurants, to bars, you know, run errands, you know, go shopping, et cetera, et cetera. You can go to your office, right. Like the full spectrum of use cases and people are going to use them in their daily lives to get around. And we see all kinds of, you know, really interesting use cases and that, that, that there's providing us incredibly valuable experience that we then, you know, use to improve our product. So as somebody who's been on, done a few long rants with Joe Rogan and others about the toxicity of the internet and the comments and the negativity in the comments, I'm fascinated by feedback. I, I believe that most people are good and kind and intelligent and can provide like, even in disagreement, really fascinating ideas. So on the product side, it's fascinating to me, like, how do you get the richest possible user feedback, like to improve what's, what are the channels that you use to measure? Cause like you're, you're no longer, that's one of the magical things about autonomous vehicles is it's not like it's frictionless interaction with the human. So like you don't get to, you know, it's just giving a ride. So like, how do you get feedback from people to, in order to improve? Oh yeah. Great question. Various mechanisms. So as part of the normal flow, we ask people for feedback. They, as the car is driving around, you know, we have on the phone and in the car, and we have a touchscreen in the car, you can actually click some buttons and provide real-time feedback on how the car is doing and how the car is handling a particular situation, you know, both positive and negative. So that's one channel we have, as we discussed customer support or life help where, you know, if a customer wants to, has a question or he has some sort of concern, they can talk to a person in real time. So that, that is another mechanism that gives us feedback at the end of a trip. You know, we also ask them how things went. They give us comments and, you know, star rating. And, you know, if it's, we also, you know, ask them to explain what went well and, you know, what could be improved. And we have our writers providing, you know, very rich feedback there. A lot, a large fraction is very passionate, very excited about this technology. So we get really good feedback. We also run UXR studies, right? You know, specific that are kind of more, you know, go more in depth and we will run both kind of lateral and longitudinal studies where we have deeper engagement with our customers. You know, we have our user experience research team tracking over time and that's when you see the longitudinal is cool. That's exactly right. And, you know, that's another really valuable feedback, source of feedback. And we're just covering a tremendous amount, right? People go grocery shopping and they like want to load, you know, 20 bags of groceries in our cars. And like that's one workflow that you maybe don't, you know, think about, you know, getting just right when you're building the driverless product. I have people like, you know, who bike as part of their trip. So they, you know, bike somewhere, then they get on our cars, they take apart their bike, they load into our vehicle, then they go. And that's, you know, how they, you know, where we want to pull over and how that, you know, get in and get out process works, provides us very useful feedback. In terms of, you know, what makes a good pickup and drop off location, we get really valuable feedback. And in fact, we had to do some really interesting work with high definition maps and thinking about walking directions. And if you imagine you're in a store, right? And some giant space, and then, you know, you want to be picked up somewhere. If you just drop a pin at a current location, which is maybe in the middle of a shopping mall, like what's the best location for the car to come pick you up? And you can have simple heuristics where you just kind of take your, you know, you clean in distance and find the nearest spot where the car can pull over that's closest to you. But oftentimes, that's not the most convenient one. You know, I have many anecdotes where that heuristic breaks in horrible ways. One example that I often mentioned is somebody wanted to be, you know, dropped off in Phoenix, and, you know, we got car picked a location that was close, I think the closest to their, you know, where the pin was dropped on the map in terms of, you know, latitude and longitude. But it happened to be on the other side of a parking lot that had this row of cacti. And the poor person had to like walk all around the parking lot to get to where they wanted to be in 110 degree heat. So that, you know, that was a mock. So then, you know, we took all take all of these, all that feedback from our users and incorporated into our system and improve it. Yeah, I feel like that's like requires AGI to solve the problem of like, when you're which is a very common case when you're in a big space of some kind, like apartment building, it doesn't matter, it's some large space. And then you call the, like the Waymo from there, right? Like, whatever, it doesn't matter, ride share vehicle. And like, where's the pin supposed to drop? I feel like that's, I don't think, I think that requires AGI. I'm gonna, in order to solve, okay, the alternative, which I think the Google search engine is taught is like, there's something really valuable about the perhaps slightly dumb answer, but a really powerful one, which is like, what was done in the past by others? Like, what was the choice made by others? That seems to be like, in terms of Google search, when you have like billions of searches, you could see which, like when they recommend what you might possibly mean, they suggest based on not some machine learning thing, which they also do, but like, on what was successful for others in the past and finding a thing that they were happy with. Is that integrated at all to Waymo? Like what, what pickups work for others? It is. I think you're exactly right. So there's a real, it's an interesting problem. Naive solutions have interesting failure modes. So there's definitely lots of things that can be done to improve and both learning from what works, what doesn't work in actual hail from getting richer data and getting more information about the environment and richer maps. But you're absolutely right that there's something, I think there's some properties of solutions that in terms of the effect that they have on users so much, much, much, much better than others, right? And predictability and understandability is important. So you can have maybe something that is not quite as optimal, but is very natural and predictable to the user and kind of works the same way all the time. And that matters. That matters a lot for the user experience. And, but you know, to get to the basics, the pretty fundamental property is that the car actually arrives where you told it to ride. Like you can always, you know, change it, see it on the map and you can move it around if you don't like it. And, but like that property that the car actually shows up on the pin is critical, which, you know, where compared to some of the human driven analogs, I think, you know, you can have more predictability. It's actually the fact, if I have a little bit of a detour here, I think the fact that it's, you know, your phone and the car is two computers talking to each other can lead to some really interesting things we can do in terms of the user interfaces, you know, both in terms of function, like the car actually shows up exactly where you told it you want it to be, but also some, you know, really interesting things on the user interface, right? As the car is driving, as you call it, and it's on the way to come pick you up. And of course you get the position of the car and the route on the map, but, and they actually follow that route, of course, but it can also share some really interesting information about what it's doing. So, you know, our cars, as they are coming to pick you up, if it's come, if a car is coming up to a stop sign, it will actually show you that like it's there sitting because it's at a stop sign or a traffic light will show you that it's got, you know, sitting at a red light. So, you know, the little things, right. But it's, I find those little touches really interesting, really magical. And it's just, you know, little things like that, that you can do to kind of delight your users. You know, this makes me think of, there's some products that I just love. Like, there's a, there's a company called Rev, Rev.com, where I like for this podcast, for example, I can just drag and drop a video, and then they do all the captioning. It's humans doing the captioning, but they connect you, they automate everything of connecting you to the humans and they do the captioning and transcription. It's all effortless. And it like, I remember when I first started using them, it was like, life's good. Like, because it was so painful to figure that out earlier. The same thing with something called iZotope RX, this company I use for cleaning up audio, like the sound cleanup they do, it's like drag and drop and it just cleans everything up very nicely. The other thing is, another experience like that I had with Amazon OneClick Purchase, first time, I mean, other places do that now, but just the effortlessness of purchasing, making it frictionless. It kind of communicates to me, like, I'm a fan of design, I'm a fan of products, that you can just create a really pleasant experience that the simplicity of it, the elegance just makes you fall in love with it. So, do you think about this kind of stuff? I mean, it's exactly what we've been talking about, it's like the little details that somehow make you fall in love with the product. Is that, we went from like urban challenge days where love was not part of the conversation, probably, and to this point where there's human beings and you want them to fall in love with the experience. Is that something you're trying to optimize for, trying to think about, like, how do you create experience that people love? Absolutely. I think that's the vision is removing any friction or complexity from getting our users, our writers, to where they want to go. Making that as simple as possible. And then, you know, beyond that, just transportation, making things and goods, and goods get to their destination as seamlessly as possible. I talked about a drag and drop experience where I kind of express your intent and then it just magically happens. And for our writers, that's what we're trying to get to, is you download an app and you click and car shows up, it's the same car, it's very predictable, it's a safe and high quality experience, and then it gets you in a very reliable, very convenient, frictionless way to where you want to be. And along the journey, I think we also want to do little things to delight our users. Like the ride sharing companies, because they don't control the experience, I think, they can't make people fall in love necessarily with the experience. Or maybe they haven't put in the effort. But I think if I were to speak to the ride sharing experience I currently have, it's just very convenient. But there's a lot of room for falling in love with it. Like we can speak to sort of car companies, car companies do this well, you can fall in love with the car, right? And be like a loyal car person, like whatever. Like I like badass hot rods, I guess 69 Corvette. And at this point, you know, you can't really... Cars are so... owning a car is so 20th century, man. But is there something about the Waymo experience where you hope that people will fall in love with it? Because that is that part of it? Or is it part of... is it just about making a convenient ride? Not ride sharing, I don't know what the right term is, but just a convenient A to B autonomous transport? Or like, do you want them to fall in love with Waymo? Maybe elaborate a little bit. I mean, almost like from a business perspective, I'm curious, like, how... do you want to be in the background invisible? Or do you want to be like a source of joy that's in very much in the foreground? I want to provide the best, most enjoyable transportation solution. And that means building it, building our product and building our service in a way that people do. Use in a very seamless, frictionless way in their day-to-day lives. And I think that does mean in some way falling in love in that product. It just kind of becomes part of your routine. It comes down in my mind to safety, predictability of the experience, and privacy, I think, aspects of it. Cars, you get the same car, you get very predictable behavior. And that is important. And if you're going to use it in your daily life. Privacy, and when you're in a car, you can do other things. You're spending a bunch, just another space where you're spending a significant part of your life. And so not having to share it with other people who you don't want to share it with, I think is a very nice property. Maybe you want to take a phone call or do something else in the vehicle. And safety on the quality of the driving, as well as the physical safety of not having to share that ride is important to a lot of people. What about the idea that when there's somebody, like a human driving, and they do a rolling stop on a stop sign, sometimes you get an Uber or Lyft or whatever, like human driver, and they can be a little bit aggressive as drivers. It feels like there is not all aggression is bad. Now, that may be a wrong, again, 20th century conception of driving. Maybe it's possible to create a driving experience. If you're in the back, busy doing something, and you're in the back, and you're back, busy doing something, maybe aggression is not a good thing. It's a very different kind of experience, perhaps. But it feels like in order to navigate this world, you need to... how do I phrase this? You need to kind of bend the rules a little bit, or at least test the rules. I don't know what language politicians use to discuss this, but whatever language they use, you like flirt with the rules. I don't know. But you sort of have a bit of an aggressive way of driving that asserts your presence in this world, thereby making other vehicles and people respect your presence, and thereby allowing you to sort of navigate through intersections in a timely fashion. I don't know if any of that made sense, but how does that fit into the experience of driving autonomously? Is that... It's a lot of sense. This is... you're hitting on a very important point of a number of behavioral components and parameters that make your driving feel assertive and natural, comfortable, predictable. Our cars will follow rules, right? They will do the safest thing possible in all situations. Let me be clear on that. But if you think of really, really good drivers, just think about professional lemon drivers, right? They will follow the rules. They're very, very smooth, and yet they're very efficient. But they're assertive. They're comfortable for the people in the vehicle. They're predictable for the other people outside the vehicle that they share the environment with. And that's the kind of driver that we want to build. And you think if maybe there's a sport analogy there, right? You can do in very many sports, the true professionals are very efficient in their movements, right? They don't do like hectic flailing, right? They're smooth and precise, right? And they get the best results. So that's the kind of driver that we want to build. In terms of aggressiveness, yeah, you can roll through the stop signs. You can do crazy lane changes. Typically, it doesn't get you to your destination faster. Typically, not the safest or most predictable, very most comfortable thing to do. But there is a way to do both. And that's what we're trying to build, the driver that is safe, comfortable, smooth, and predictable. Yeah, that's a really interesting distinction. I think in the early days of autonomous vehicles, the vehicles felt cautious as opposed to efficient. And still probably. But when I rode in the Waymo, I mean, it was quite assertive. It moved pretty quickly. Like, yeah, then he's one of the surprising feelings was that it actually, it went fast. And it didn't feel like awkwardly cautious than autonomous vehicle. Like, so I've also programmed autonomous vehicles and everything I've ever built was felt awkwardly, either overly aggressive, okay, especially when it was my code, or like, awkwardly cautious is the way I would put it. And Waymo's vehicle felt like assertive, and I think efficient is like, the right terminology here. It wasn't. And I also like the professional limo driver, because we often think like, you know, an Uber driver, or a bus driver or taxi. This is the funny thing is, people think like, taxi drivers are professionals. I mean, it's like, that's like saying, I'm a professional walker, just because I've been walking all my life. I think there's an art to it, right? And if you take it seriously as an art form, then there's a certain way that mastery looks like. It's interesting to think about what is mastery look like in driving? And perhaps what we associate with like, aggressiveness is unnecessary. Like, it's not part of the experience of driving. It's like, unnecessary fluff. That efficiency, you can be, you can create a good driving experience within the rules. That's, I mean, you're the first person to tell me this. So it's kind of interesting. I need to think about this. But that's exactly what it felt like with Waymo. I kind of had this intuition, maybe it's the Russian thing. I don't know, that you have to break the rules in life to get anywhere. But maybe, maybe it's possible that that's not the case. In driving, I have to think about that. But it certainly felt that way on the streets of Phoenix when I was there in Waymo. That was a very pleasant experience. And it wasn't frustrating in that like, come on, move already kind of feeling. It wasn't, that wasn't there. Yeah, I mean, that's what we're going after. I don't think you have to pick one. I think truly good driving, it gives you both efficiency, assertiveness, but also comfort and predictability and safety. And that's what fundamental improvements in the core capabilities truly unlock. And you can kind of think of it as, you know, precision and recall trade off. You have certain capabilities of your model. And then it's very easy when you have some curve of precision recall, you can move things around and can choose your operating point and your training of precision versus recall false positives versus false negatives. Right. But then, and you know, you can tune things on that curve and be kind of more cautious or more aggressive, but then aggressive is bad or cautious is bad. But true capabilities come from actually moving the whole curve up. And then you are on kind of on a very different plane of those trade offs. And that's what we're trying to do here is to move the whole curve up. Before I forget, let's talk about trucks a little bit. So I also got a chance to check out some of the Waymo trucks. I'm not sure if we want to go too much into that space, but it's a fascinating one. So maybe we can mention at least briefly, you know, Waymo is also now doing autonomous trucking and how different, like philosophically and technically is that whole space of problems? It's one of our two big products and commercial applications of our driver, right? Right. Hailing and deliveries. We have Waymo One and Waymo Via, moving people and moving goods. Trucking is an example of moving goods. We've been working with a company called Waymo, working on trucking since 2017. It is a very interesting space. And your question, I mean, how different is it? It has this really nice property that the first order challenges, like the science, the hard engineering, whether it's hardware or onboard software or off board software, all of the systems that you build for training your ML models for evaluating your time system, like those fundamentals carry over the true challenges of driving perception, semantic understanding, prediction, decision making, planning, evaluation, the simulator, ML infrastructure, those carry over the data and the application and kind of the domains might be different, but the most difficult problems, all of that carries over between the domains. So that's very nice. So that's how we approach it. We're kind of built investing in the core, the technical core. And then there is specialization of that core technology to different product lines, to different commercial applications. So on just to tease it apart a little bit on trucks, so starting with the hardware, the configuration of the sensors is different. They're different physically, geometrically, different vehicles. So for example, we have two of our main laser on the trucks on both sides so that we have not have the blind spots. Whereas on the JLR I-PACE, we have one of it sitting at the very top, but the actual sensors are almost the same or largely the same. So all of the investment that over the years we've put into building our custom lighters, custom radars, pulling the whole system together, that carries over very nicely. Then on the perception side, the fundamental challenges of seeing, understanding the world, whether it's object detection, classification, tracking, semantic understanding, all that carries over. Yes, there's some specialization when you're driving on freeways, range becomes more important, the domain is a little bit different, but again, the fundamentals carry over very, very nicely. Same, and I guess you get into prediction or decision making. The fundamentals of what it takes to predict what other people are going to do, to find the long tail, to improve your system in that long tail of behavior prediction and response, that carries over, right? And so on and so on. So I mean, that's pretty exciting. By the way, does Waymo VA include using the smaller vehicles for transportation goods? That's an interesting distinction. So I would say there's three interesting modes of operation. So one is moving humans, one is moving goods, and one is like moving nothing, zero occupancy, meaning like you're going to the destination, your empty vehicle. I mean, it's the third is the less of it, if that's the entirety of it, it's less exciting from the commercial perspective. Well, I mean, in terms of if you think about what's inside a vehicle as it's moving, because some significant fraction of the vehicle's movement has to be empty. I mean, it's kind of fascinating, maybe just on that small point, is there different control and like policies that are applied for zero occupancy vehicle, so a vehicle with nothing in it? Or is it just move as if there is a person inside? Well, it was with some subtle differences. As a first order approximation, there are no differences. And if you think about safety and comfort and quality of driving, only part of it has to do with the people or the goods inside of the vehicle. But you want to drive smoothly, as we discussed, not purely for the benefit of whatever you have inside the car, it's also for the benefit of the people outside fitting naturally and predictably into the whole environment. So yes, there are some second order things you can do, you can change your route and optimize maybe your fleet, things at the fleet scale. And you would take into account whether some of your cars are actually serving a useful trip, whether with people or with goods, whereas other cars are driving completely empty to that next valuable trip that they're going to provide. But those are mostly second order effects. Okay, cool. So Phoenix is an incredible place. And what you've announced in Phoenix is kind of amazing. But you know, that's just like one city. How do you take over the world? I mean, I'm asking for a friend. One step at a time. Is that the cartoon pinky in the brain? Yeah. Okay. But gradually is a true answer. So I think the heart of your question is... Can you ask a better question than I asked? You're asking a great question. Answer that one. I'm just going to phrase it in the terms that I want to answer. Perfect. That's exactly right. Brilliant. Please. You know, where are we today? And what happens next? And what does it take to go beyond Phoenix? And what does it take to get this technology to more places and more people around the world? So our next big area of focus is exactly that. Larger scale commercialization and scaling up. If I think about the main... Phoenix gives us that platform and gives us that foundation upon which we can build. And there are a few really challenging aspects of this whole problem that you have to pull together in order to build the technology, in order to deploy it into the field, to go from a driverless car to a fleet of cars that are providing a service, and then all the way to commercialization. So, and this is what we have in Phoenix. We've taken the technology from a proof point to an actual deployment. And we've taken our driver from one car to a fleet that can provide a service. Beyond that, if I think about what it will take to scale up and deploy in more places with more customers, I tend to think about three main dimensions, three main axes of scale. One is the core technology, the hardware and software core capabilities of our driver. The second dimension is evaluation and deployment. And the third one is the product, commercial and operational excellence. So you can talk a bit about where we are along each one of those three dimensions, about where we are today and what will happen next. On the core technology, on the hardware and software, together, comprised of driver, we obviously have that foundation that is providing fully driverless trips to our customers as we speak, in fact. And we've learned a tremendous amount from that. So now what we're doing is we are incorporating all those lessons into some pretty fundamental improvements in our core technology, both on the hardware side and on the software side to build a more general, more robust solution that then will enable us to massively scale beyond Phoenix. So on the hardware side, all of those lessons are now incorporated into this fifth generation hardware platform that is being deployed right now. And we're also incorporating the software side of it right now. And that's the platform, the fourth generation, the thing that we have right now driving in Phoenix, it's good enough to operate fully driverless, night and day, various speeds and various conditions. But the fifth generation is the platform upon which we want to go to massive scale. We've really made qualitative improvements in terms of the capability of the system, the simplicity of the architecture, the reliability of the redundancy. It is designed to be manufacturable at very large scale and provides the right unit economics. So that's the next big step for us on the hardware side. That's already there for scale, the version five. That's right. And is that a coincidence or should we look into a conspiracy theory that it's the same version as the Pixel phone? Is that what's the hardware? I can neither confirm nor deny, Lux. All right, cool. So, sorry. So that's the, okay, that's that axis. What else? So similarly, you know, hardware is a very discreet jump, but similar to the, that to how we're making that change from the fourth generation hardware to the fifth, we're making similar improvements on the software side to make it more robust and more general and allow us to kind of quickly scale beyond Phoenix. So that's the first dimension of core technology. The second dimension is evaluation and deployment. Now, how do you measure your system? How do you evaluate it? How do you build the release and deployment process where, you know, with confidence, you can regularly release new versions of your driver into a fleet? How do you get good at it so that it is not a huge tax on your researchers and engineers that, you know, so you can, how do you build all of these processes, the frameworks, the simulation, the evaluation, the data science, the validation, so that people can focus on improving the system and kind of the releases just go out the door and get deployed across the fleet. So we've gotten really good at that in Phoenix. That's been a tremendously difficult problem, but that's what we have in Phoenix right now that gives us that foundation. And now we're working on kind of incorporating all the lessons that we've learned to make it more efficient, to go to new places, you know, and scale up and just kind of, you know, stamp things out. So that's that second dimension of evaluation and deployment. And the third dimension is product, commercial, and operational excellence. And again, Phoenix there is providing an incredibly valuable platform. You know, that's why we're doing things end to end in Phoenix. We're learning as, you know, we discussed a little earlier today, tremendous amount of really valuable lessons from our users getting really incredible feedback. And we'll continue to iterate on that and incorporate all those lessons into making our product, you know, even better and more convenient for our users. So you're converting this whole process of Phoenix in Phoenix into something that could be copy and pasted elsewhere. So like, perhaps you didn't think of it that way when you were doing the experimentation in Phoenix. But so how long did it basically, you can correct me, but you've, I mean, it's still early days, but you've taken the full journey in Phoenix, right? As you were saying, of like what it takes to basically automate. I mean, it's not the entirety of Phoenix, right? But I imagine it can encompass the entirety of Phoenix, that's some near term date, but that's not even perhaps important, as long as it's a large enough geographic area. So what, how copy pastable is that process currently? And how, like, you know, like when you copy and paste in Google Docs, I think, no, in Word, you can like apply source formatting or apply destination formatting. So when you copy and paste the Phoenix into like, say, Boston, how do you apply the destination formatting? Like how much of the core of the entire process of bringing an actual public transportation, autonomous transportation service to a city is there in Phoenix that you understand enough to copy and paste into Boston or wherever? So we're not quite there yet. We're not at a point where we're kind of massively copy and pasting all over the place. But Phoenix, what we did in Phoenix, and we very intentionally have chosen Phoenix as our first full deployment area, you know, exactly for that reason to kind of tease the problem apart, look at each dimension, focus on the fundamentals of complexity and de-risking those dimensions, and then bringing the entire thing together to get all the way and force ourselves to learn all those hard lessons on technology, hardware and software, on the evaluation deployment, on operating a service, operating a business, using, actually serving our customers all the way so that we're fully informed about the most difficult, most important challenges to get us to that next step of massive copy and pasting, as you said. And that's what we're doing right now. We're incorporating all those things that we learned into that next system that then will allow us to kind of copy and paste all over the place and to massively scale to more users and more locations. I mean, you know, I just talked a little bit about, you know, what does that mean along those different dimensions? So on the hardware side, for example, again, it's that switch from the fourth to the fifth generation. And the fifth generation is designed to kind of have that property. Can you say what other cities you're thinking about? Like, I'm thinking about, sorry, we're in San Francisco now. I thought I want to move to San Francisco, but I'm thinking about moving to Austin. I don't know why. People are not being very nice about San Francisco currently. Maybe it's a small, maybe it's in vogue right now. But Austin seems, I visited there and it was, I was in a Walmart. It's funny, these moments like turn your life. There's this very nice woman with kind eyes, just like stopped and said, you look so handsome in that tie, honey. To me, this has never happened to me in my life. But just the sweetness of this woman is something I've never experienced, certainly in the streets of Boston, but even in San Francisco where people wouldn't, that's just not how they speak or think. I don't know. There's a warmth to Austin that love. And since Waymo does have a little bit of a history there, is that a possibility? Is this your version of asking the question of like, you know, Dimitri, I know you can't share your commercial and deployment roadmap, but I'm thinking about moving to San Francisco, Austin, like in a blink twice, if you think I should move to it. That's true, that's true. You got me. We've been testing all over the place. I think we've been testing more than 25 cities. We drive in San Francisco, we drive in Michigan for snow. We are doing significant amount of testing in the Bay Area, including San Francisco. Which is not like, because we're talking about the very different thing, which is like a full-on large geographic area, public service. You can't share. Okay. What about Moscow? When is that happening? Take on Yandex. I'm not paying attention to those folks. They're doing, you know, there's a lot of fun. I mean, maybe as a way of a question, you didn't speak to sort of like policy or like, is there tricky things with government and so on? Like, is there other friction that you've encountered except sort of technological friction of solving this very difficult problem? Is there other stuff that you have to overcome when deploying a public service in a city? That's interesting. It's very important. So we put significant effort in creating those partnerships and those relationships with governments at all levels, local governments, municipalities, state level, federal level. We've been engaged in very deep conversations from the earliest days of our projects. Whenever at all of these levels, whenever we go to test or operate in a new area, we always lead with a conversation with the local officials. But the result of that investment is that, no, it's not challenges we have to overcome, but it is very important that we continue to have this conversation. Oh, yeah. I love politicians too. Okay. So Mr. Elon Musk said that LIDAR is a crutch. What are your thoughts? I wouldn't characterize it exactly that way. I know, I think LIDAR is very important. It is a key sensor that we use just like other modalities, right? As we discussed, our cars use cameras, LIDARs and radars. They are all very important. They are at the physical level, they are very different. They have very different physical characteristics. Cameras are passive, LIDARs and radars are active, use different wavelengths. So that means they complement each other very nicely. And together, combined, they can be used to build a much safer and much more capable system. So to me, it's more of a question, why the heck would you handicap yourself and not use one or more of those sensing modalities when they undoubtedly just make your system more capable and safer? Now, what might make sense for one product or one business might not make sense for another one. So if you're talking about driver assist technologies, you make certain design decisions and you make certain trade-offs and you make different ones if you're building a driver that you deploy in fully driverless vehicles. And LIDAR specifically, when this question comes up, typically the criticisms that I hear are the counterpoints that cost and aesthetics. And I don't find either of those, honestly, very compelling. So on the cost side, there's nothing fundamentally prohibitive about the cost of LIDARs. Radars used to be very expensive before people started, before people made certain advances in technology and started to manufacture them at massive scale and deploy them in vehicles, similar with LIDARs. And this is where the LIDARs that we have on our cars, especially the fifth generation, we've been able to make some pretty qualitative discontinuous jumps in terms of the fundamental technology that allow us to manufacture those things at very significant scale and at a fraction of the cost of both our previous generation, as well as a fraction of the cost of what might be available on the market off the shelf right now. And that improvement will continue. So I think cost is not a real issue. Second one is aesthetics. I don't think that's a real issue either. Beauty is in the eye of the beholder. You can make LIDAR sexy again. I think you're exactly right. I think it is sexy. Honestly, I think form holds its function. You know, actually, somebody brought this up to me. I mean, all forms of LIDAR, even like the ones that are big, you can make look beautiful. There's no sense in which you can't integrate it into design. There's all kinds of awesome designs. I don't think small and humble is beautiful. It could be like, you know, brutalism or like it could be like harsh corners. I mean, like I said, like hot rods. I don't necessarily like, oh man, I'm going to start so much controversy with this. I don't like Porsches. Okay. The Porsche 911, everyone says, oh, it's the most beautiful. No, it's like a baby car. It doesn't make any sense. But everyone, it's beauty is in the eye of the beholder. You're already looking at me like, what is this kid talking about? I'm happy to talk about. You're digging your own hole. The form and function and my take on the beauty of the hardware that we put on our vehicles. I will not comment on your Porsche monologue. Okay. All right. So, but aesthetics, fine. But there's an underlying like philosophical question behind the kind of lighter question is like how much of the problem can be solved with a computer vision, with machine learning. So I think without sort of disagreements and so on, it's nice to put it on the spectrum because Waymo is doing a lot of machine learning as well. It's interesting to think how much of driving, if we look at five years, 10 years, 50 years down the road, what can be learned in almost more and more and more end to end way. If we look at what Tesla is doing with as a machine learning problem, they're doing a multitask learning thing where it's just they break up driving into a bunch of learning tasks and they have one single neural network and they're just collecting huge amounts of data that's training that. I've recently hung out with George Hotz. I don't know if you know George. I love him so much. He's just an entertaining human being. We were off mic talking about Hunter S Thompson. He's the Hunter S Thompson of autonomous driving. Okay. So he, I didn't realize this with Kama AI, but they're like really trying to do end to end. They're the machine, like looking at the machine learning problem, they're really not doing multitask learning, but it's, it's, it's computing the drivable area as a machine learning task and hoping that like down the line, this level two system, this driver assistance will eventually lead to allowing you to have a fully autonomous vehicle. Okay. There's an underlying deep philosophical question there, technical question of how much of driving can be learned. So LIDAR is an effective tool today for actually deploying a successful service in Phoenix, right? That's safe, that's reliable, et cetera, et cetera. But the, the question, and I'm not saying you can't do machine learning on LIDAR, but the question is that like how much of driving can be learned eventually? Can we do fully autonomous that's learned? Yeah. You know, learning is all over the place and plays a key role in every part of our system. I, as you said, I would decouple the sensing modalities from the ML and the software parts of it. LIDAR, radar, cameras, it's all machine learning. All of the object detection classification, of course, like that's what these modern deep nets and con nets are very good at. You feed them raw data, massive amounts of raw data. And that's actually what our custom build LIDARs and radars are really good at. And radars, they don't just give you point estimates of objects in space. They give you raw, like physical observations. And then you take all of that raw information, whether it's colors of the pixels, whether it's LIDARs returns and some auxiliary information, it's not just distance, right? And angle and distance is much richer information that you get from those returns, plus really rich information from the radars. You fuse it all together and you feed it into those massive ML models that then lead to the best results in terms of object detection classification, state estimation. So there's a, sorry to interrupt, but there is a fusion. I mean, that's something that people didn't do for a very long time, which is like at the sensor fusion level, I guess, like early on fusing the information together, whether so that the sensory information that the vehicle receives from the different modalities or even from different cameras is combined before it is fed into the machine learning models. Yeah. So I think this is one of the trends you're seeing more of that. You mentioned end-to-end, there's different interpretation of end-to-end. There is kind of the purest interpretation of, I'm going to like have one model that goes from raw sensor data to like, you know, steering torque and, you know, gas brakes that, you know, that that's too much. I don't think that's the right way to do it. There's more, you know, smaller versions of end-to-end where you're kind of doing more end-to-end learning or core training or deep propagation of kind of signals back and forth across the different stages of your system. There's, you know, really good ways it gets into some fairly complex design choices where on one hand you want modularity and the composability the composability of your system. But on the other hand you don't want to create interfaces that are too narrow or too brittle, too engineered, where you're giving up on the generality of the solution or you're unable to properly propagate signal, you know, reach signal forward and losses and, you know, back so you can optimize the whole system jointly. So I would decouple and I guess what you're seeing in terms of the fusion of the sensing data from different modalities as well as kind of fusion at in the temporal level going more from, you know, frame by frame where, you know, you would have one net that would do frame by frame detection and camera and then, you know, something that does frame by frame and lighter and then radar and then you fuse it, you know, in a weaker engineered way later. The field over the last, you know, decade has been evolving in more kind of joint fusion, more end-to-end models that are, you know, solving some of these tasks, you know, jointly and there's tremendous power in that and, you know, that's the progression that you kind of our technology, our stack has been on as well. Now, to your, you know, that so I would decouple the kind of sensing and how that information is used from the role of ML and the entire stack and, you know, I guess it's, I, there's trade-offs and, you know, modularity and how do you inject inductive bias into your system, right? This is, there's tremendous power in being able to do that. So, you know, we have, there's no part of our system that is not heavily, that does not heavily, you know, leverage, you know, data-driven development or, you know, state-of-the-art ML. But there's mapping, there's a simulator, whether it's perception, you know, object level, you know, perception, whether it's semantic understanding, prediction, decision-making, you know, so forth and so on. It's, and of course, object detection and class specification, like you're finding pedestrians and cars and cyclists and, you know, cones and signs and vegetation and being very good at estimating kind of detection classification and state estimation, there's just stable stakes. Like, that's step zero of this whole stack. You can be incredibly good at that, whether you use cameras or light as a radar, but there's just, you know, that's stable stakes. That's just step zero. Beyond that, you get into the really interesting challenges of semantic understanding at the perception level. You get into scene level reasoning, you get into very deep problems that have to do with prediction and joint prediction and interaction, so on and interaction between all of the actors in the environment, pedestrians, cyclists, other cars, and you get into decision-making, right? So how do you build a lot of systems? So we leverage ML very heavily in all of these components. I do believe that the best results you achieve by kind of using a hybrid approach and having different types of ML, having different models with different degrees of inductive bias that you can have, and combining kind of model-free approaches with some model-based approaches and some rule-based, physics-based systems. So one example I can give you is traffic lights. There's a problem of the detection of traffic light state, and obviously that's a great problem for computer vision. ConfNets, that's their bread and butter, right? That's how you build that. But then the interpretation of a traffic light, you're going to need to learn that, right? You need to build some complex ML model that infers with some precision and recall that red means stop. It's a very clear engineered signal with very clear semantics, right? So you want to induce that bias. How you induce that bias and that, whether it's a constraint or a cost function in your stack, but it is important to be able to inject that clear semantic signal into your stack. You know, that's what we do. But then the question of like, and that's when you apply it to yourself, when you are making decisions whether you want to stop for a red light or not. But if you think about how other people treat traffic lights, we're back to the ML version of that. You know they're supposed to stop for a red light, but that doesn't mean they will. So then you're back in the very heavy ML domain where you're picking up on very subtle keys about, you know, they have to do with the behavior of objects and pedestrians, cyclists, cars, and the whole thing, you know, the entire configuration of the scene that allow you to make accurate predictions on whether they will in fact stop or run a red light. So it sounds like already for Waymo, like machine learning is a huge part of the stack. So it's a huge part of like, not just, so obviously the first level zero or whatever you said, which is like just the object detection of things that, you know, with know that machine learning can do, but also starting to do prediction behavior and so on to model the, what are the, what the other parties in the scene, entities in the scene are going to do. So machine learning is more and more playing a role in that as well. Of course. Oh, absolutely. I think we've been going back to the earliest days, like, you know, DARPA, the DARPA Grand Challenge, and team was leveraging, you know, machine learning. I was like pre, you know, ImageNet, and it was a very different type of ML, but, and I think actually it was before my time, but the Stanford team on, during the Grand Challenge had a very interesting machine learned system that would, you know, use lighter and camera when driving in desert. And it, we had built the model where it would kind of extend the range of free space reasoning. So we get a clear signal from lighter. And then it had a model. It's like, Hey, like this stuff on camera kind of sort of looks like this stuff and lighter. And I know this stuff and that I've seen in lighter, I'm very confident that it's free space. So let me extend that free space zone into the camera range that would allow the vehicle to drive faster. And then we've been building on top of that and kind of staying and pushing the state of the art in ML, in all kinds of different ML over the years. And in fact, from the earliest days, I think, you know, 2010, it's probably the year where Google, maybe 2011, probably got pretty heavily involved in machine learning, kind of deep nuts. And at that time, it was probably the only company that was being very heavily investing in kind of state of the art ML and self-driving cars. And they go hand in hand. And we've been on that journey ever since we're doing pushing a lot of these areas in terms of research at Waymo. And we collaborate very heavily with the researchers in Alphabet and like all kinds of ML, supervised ML, unsupervised ML, published some interesting research papers in the space, especially recently. It's just a super active learning as well. Yeah, so super, super active. And of course, there is kind of the more mature stuff like, you know, ConvNets for object detection. But there's some really interesting, really active work that's happening and bigger models and models that have more structure to them, not just large bitmaps and reason about temporal sequences. And some of the interesting breakthroughs that we've seen in language models, transformers, GPT-3 inference. There's some really interesting applications of some of the core breakthroughs to those problems of behavior prediction, as well as decision making and planning. You can think about it, kind of the behavior, how the path, the trajectories, how people drive, they have kind of a share a lot of the fundamental structure. This problem, there's sequential nature, there's a lot of structure in this representation. There is a strong locality, kind of like in sentences, words that follow each other, they're strongly connected, but there are also kind of larger context that doesn't have that locality. And you also see that in driving, right? What is happening in the scene as a whole has very strong implications on the kind of the next step in that sequence where, whether you're predicting what other people are going to do, whether you're making your own decisions, or whether in a simulator, you're building generative models of humans walking, cyclists riding, and other cars driving. Oh, that's all really fascinating. It's fascinating to think that transformer models and all the breakthroughs in language and NLP that might be applicable to driving at the higher level, at the behavioral level, that's kind of fascinating. Let me ask about pesky little creatures called pedestrians and cyclists. They seem, so humans are a problem, if we can get rid of them, I would. But unfortunately, they're also a source of joy and love and beauty, so let's keep them around. They're also our customers. For your perspective, yes, yes, for sure. They're a source of money, very good. But I don't even know where I was going. Oh yes, pedestrians and cyclists. They're a fascinating injection into the system of uncertainty, of like a game theoretic dance of what to do. And also, they have perceptions of their own, and they can tweet about your product, so you don't want to run them over, from that perspective. I mean, I don't know, I'm joking a lot, but I think in seriousness, pedestrians are a complicated computer vision problem, a complicated behavioral problem. Is there something interesting you could say about what you've learned from a machine learning perspective, from also an autonomous vehicle and a product perspective about just interacting with the humans in this world? Yeah, just to state on record, we care deeply about the safety of pedestrians, even the ones that don't have Twitter accounts. Thank you. All right, cool. Not me. But yes, I'm glad somebody does. But in all seriousness, safety of vulnerable road users, pedestrians or cyclists, is one of our highest priorities. We do a tremendous amount of testing and validation and put a very significant emphasis on the capabilities of our systems that have to do with safety around those unprotected vulnerable road users. Cars, as we discussed earlier, in Phoenix, we have completely empty cars, completely driverless cars driving in this very large area. And some people use them to go to school, so they will drive through school zones. Kids are the very special class of those vulnerable user road users, right? You want to be super, super safe and super, super cautious around those. We take it very, very, very seriously. And what does it take to be good at it? An incredible amount of performance across your whole stack. It starts with hardware. And again, you want to use all sensing of modalities available to you. Imagine driving on a residential road at night and kind of making a turn and you don't have headlights covering some part of the space and a kid might run out. And lighters are amazing at that. They see just as well in complete darkness as they do during the day. So just again, it gives you that extra margin in terms of capability and performance and safety and quality. And in fact, we oftentimes in these kinds of situations, we have our system detect something in some cases even earlier than our trained operators in the car might do, especially in conditions like very dark nights. So it starts with sensing, then perception has to be incredibly good. And you have to be very, very good at kind of detecting pedestrians in all kinds of situations and all kinds of environments, including people in weird poses, people kind of running around and being partially occluded. So that's step number one. Then you have to have very high accuracy and very low latency in terms of your reactions to what these actors might do. And we've put a tremendous amount of engineering and tremendous amount of validation into make sure our system performs properly. And oftentimes it does require a very strong reaction to do the safe thing. We actually see a lot of cases like that. That's the long tail of really rare, really crazy events that contribute to the safety around pedestrians. One example that comes to mind that we actually got happened in Phoenix, where we were driving along and I think it was a 45 mile per hour road. So you have pretty high speed traffic and there was a sidewalk next to it. And there was a cyclist on the sidewalk. And as we were in the right lane, right next to the side, it was a multi-lane road. So as we got close to the cyclist on the sidewalk, it was a woman, she tripped and fell, just fell right into the path of our vehicle. And our car, this was actually with a test driver, our test drivers did exactly the right thing. They kind of reacted and came to a stop. It requires both very strong steering and strong application of the brake. And then we simulated what our system would have done in that situation. And it did exactly the same thing. And that speaks to all of those components of really good state estimation and tracking. And imagine a person on a bike and they're falling over and they're doing that right in front of you. So you have to be really like, things are changing. The appearance of that whole thing is changing. And a person goes one way, they're falling on the road, they're being flat on the ground in front of you. The bike goes flying the other direction. The two objects that used to be one are now splitting apart and the car has to detect all of that. Milliseconds matter. And it's not good enough to just brake. You have to steer and brake and there's traffic around you. So it all has to come together. And it was really great to see in this case and other cases like that, that we're actually seeing in the wild, that our system is performing exactly the way that we would have liked and is able to avoid collisions like this. It's such an exciting space for robotics. In that split second to make decisions of life and death. I don't know. The stakes are high in a sense, but it's also beautiful that for somebody who loves artificial intelligence, the possibility that an AI system might be able to save a human life. That's kind of exciting as a problem. Like to wake up. It's terrifying probably for an engineer to wake up and to think about, but it's also exciting because it's in your hands. Let me try to ask a question that's often brought up about autonomous vehicles. And it might be fun to see if you have anything interesting to say, which is about the trolley problem. So a trolley problem is an interesting philosophical construct that highlights, and there's many others like it, of the difficult ethical decisions that we humans have before us in this complicated world. So specifically is the choice between if you were forced to choose to kill a group X of people versus a group Y of people, like one person. If you did nothing, you would kill one person, but if you would kill five people, and if you decide to swerve out of the way, you would only kill one person. Do you do nothing or you choose to do something? You can construct all kinds of sort of ethical experiments of this kind that I think at least on a positive note, inspire you to think about like introspect what are the physics of our morality. And there's usually not good answers there. I think people love it because it's just an exciting thing to think about. I think people who build autonomous vehicles usually roll their eyes because this is not, this one as constructed, this like literally never comes up in reality. You never have to choose between killing one or like one of two groups of people. But I wonder if you can speak to, is there something interesting to you as an engineer of autonomous vehicles that's within the trolley problem or maybe more generally, are there difficult ethical decisions that you find that the algorithm must make? On the specific version of the trolley problem, which one would you do if you're driving? The question itself is a profound question because we humans ourselves cannot answer. And that's the very point. I would kill both. Yeah, humans, I think you're exactly right in that humans are not particularly good. I think the kind of phrase is like, what would a computer do? But humans are not very good. And actually oftentimes I think that freezing and kind of not doing anything because like you've taken a few extra milliseconds to just process and then you end up like doing the worst of the possible outcomes. I do think that as you've pointed out, it can be a bit of a distraction and it can be a bit of a kind of a red herring. I think it's an interesting discussion in the realm of philosophy. But in terms of how that affects the actual engineering and deployment of self-driving vehicles, it's not how you go about building a system. We've talked about how you engineer a system, how you go about evaluating the different components and the safety of the entire thing. How do you kind of inject the various model-based, safety-based arguments? And yes, you reason at parts of the system, you reason about the probability of a collision, the severity of that collision. And that is incorporated and you have to properly reason about the uncertainty that flows through the system. So those factors definitely play a role in how the cars then behave, but they tend to be more of like the emergent behavior. And what do you see? You're absolutely right that these clear theoretical problems that you don't have covered that in system. And really kind of back to our previous discussion, which one do you choose? Well, oftentimes you made a mistake earlier. You shouldn't be in that situation in the first place. And in reality, the system comes up. If you build a very good, safe and capable driver, you have enough clues in the environment that you drive defensively. So you don't put yourself in that situation. And again, if you go back to that analogy of precision and recall, like, okay, you can make a very hard trade-off, but neither answer is really good. But what instead you focus on is kind of moving the whole curve up and then you focus on building the right capability and the right defensive driving so that you don't put yourself in a situation like this. I don't know if you have a good answer for this, but people love it when I ask this question about books. Are there books in your life that you've enjoyed, philosophical, fiction, technical, that had a big impact on you as an engineer or as a human being? Everything from science fiction to a favorite textbook. Is there three books that stand out that you can think of? CB. Three books that impacted me, I would say, and this one is, you probably know it well, but not generally well known, I think in the US or kind of internationally, The Master and Margarita. It's one of actually my favorite books. It is by Russian, it's a novel by Russian author Mikhail Bulgakov. It's a great book. It's one of those books that you can reread your entire life and it's very accessible. You can read it as a kid. The plot is interesting. It's the devil visiting the Soviet Union. You reread it at different stages of your life and you enjoy it for very different reasons and you keep finding deeper and deeper meaning. It definitely had an imprint on me, mostly from the cultural stylistic aspect. It makes you think of one of those books that is good and makes you think, but also has this really silly, quirky, dark sense of humor. LR. It captures the Russian soul more than perhaps many other books. On that slight note, just out of curiosity, one of the saddest things is I've read that book in English. Did you by chance read it in English or in Russian? AC. In Russian, only in Russian. Actually, that is a question I had posed to myself every once in a while. I wonder how well it translates, if it translates at all. There's the language aspect of it and then there's the cultural aspect. Actually, I'm not sure if either of those would work well in English. LR. Now, I forget their names, but when the COVID lifts a little bit, I'm traveling to Paris for several reasons. One is just I've never been to Paris. I want to go to Paris. There's the most famous translators of Dostoevsky, Tolstoy, of most of Russian literature live there. There's a couple. They're famous, a man and a woman. I'm going to have a series of conversations with them. In preparation for that, I'm starting to read Dostoevsky in Russian. I'm really embarrassed to say that I read everything I've read of Russian literature of serious depth has been in English. I can also read, obviously, in Russian, but for some reason, it seemed in the optimization of life, it seemed the improper decision to do it, to read in Russian. I need to think in English, not in Russian, but now I'm changing my mind on that. The question of how well it translates is a really fundamental one, even with Dostoevsky. From what I understand, Dostoevsky translates easier. Others don't as much. Obviously, the poetry doesn't translate as well. Also, the music, big fan of Vladimir Vysotsky. He doesn't obviously translate well. People have tried. But Mastermind, I don't know. I don't know about that one. I just know it in English. It's fun as hell in English. But it's a curious question, and I want to study it rigorously from both the machine learning aspect and also because I want to do a couple of interviews in Russia. I'm still unsure of how to properly conduct an interview across a language barrier. It's a fascinating question that ultimately communicates to an American audience. There's a few Russian people that I think are truly special human beings. I sometimes encounter this with some incredible scientists, and maybe you encounter this as well at some point in your life, that it feels like because of the language barrier, their ideas are lost to history. It's a sad thing. I think about Chinese scientists or even authors that we don't, in the English-speaking world, don't get to appreciate some of the depth of the culture because it's lost in translation. I feel like I would love to show that to the world. I'm just some idiot, but because I have at least some semblance of skill in speaking Russian, and I know how to record stuff on a video camera, I feel like I want to catch like Grigory Perlman, who's a mathematician. I'm not sure if you're familiar with him. I want to talk to him. He's a fascinating mind, and to bring him to a wider audience in English-speaking would be fascinating. But that requires to be rigorous about this question of how well Bulgakov translates. I mean, I know it's a silly concept, but it's a fundamental one because how do you translate? That's the thing that Google Translate is also facing as a more machine learning problem, but I wonder as a more bigger problem for AI, how do we capture the magic that's there in the language? I think that's a really interesting, really challenging problem. If you do read it, master Margarita in Russian, I'd be curious to get your opinion. I think part of it is language, but part of it is just centuries of culture. The cultures are different, so it's hard to connect that. Okay, so that was my first one. You had two more. The second one I would probably pick the science fiction by the Strogowski brothers. It's up there with Isaac Asimov and Ray Bradbury, and you know, company. The Strogowski brothers kind of appealed more to me. I think Morrie made more of an impression on me growing up. I apologize if I'm showing my complete ignorance. I'm so weak on sci-fi. What did they write? Oh, Roadside Picnic, Hard to Be a God, Beetle in an Ant Hill, Monday Starts on Saturday. It's not just science fiction. It also has very interesting interpersonal and societal questions, and some of the language is just completely hilarious. That's the one. Oh, interesting. Monday starts on Saturday. So, I need to read. Okay. Oh, boy. You put that in the category of science fiction? That one is, I mean, this was more of a silly, humorous work. I mean, there is kind of- But it's profound, too, right? Science fiction, right, is about this research institute, and it has deep parallels to serious research, but the setting, of course, is that they're working on magic, right? And there's a lot of silly- And that's their style, right? And other books are very different, right? Hard to be a god, right? It's about this higher society being injected into this primitive world and how they operate there, and some of the very deep ethical questions there, right? And they've got this full spectrum. Some is more about more adventure style. But I enjoy all of their books. There's probably a couple. Actually, one I think that they consider their most important work, I think, is The Snail on a Hill. I'm not exactly sure how it translates. I tried reading a couple of times. I still don't get it, but everything else I fully enjoyed. And for one of my birthdays as a kid, I got their entire collection occupied a giant shelf in my room. And then over the holidays, my parents couldn't drag me out of the room, and I read the whole thing cover to cover, and I really enjoyed it. And that's one more. For the third one, maybe a little bit darker, but it comes to mind is Orwell's 1984. And you asked what made an impression on me and the books that people should read. That one I think falls in the category of both. Definitely, it's one of those books that you read, and you just put it down, and you stare in space for a while. And that kind of work. I think there's lessons there people should not ignore. And nowadays, with everything that's happening in the world, I can't help it, but have my mind jump to some parallels with what Orwell described. And there's this whole concept of double think and ignoring logic and holding completely contradictory opinions in your mind and have that not bother you and stick into the party line at all costs. There's something there. If anything, 2020 has taught me, and I'm a huge fan of Animal Farm, which is a kind of friendly, is a friend of 1984 by Orwell. It's kind of another thought experiment of how our society may go in directions that we wouldn't like it to go. But if anything that's been kind of heartbreaking to an optimist about 2020 is that society's kind of fragile. This is a special little experiment we have going on. And it's not unbreakable. We should be careful to preserve whatever special thing we have going on. I think 1984 and these books, Brave New World, they're helpful in thinking stuff can go wrong in non-obvious ways. And it's up to us to preserve it. And it's a responsibility. It's been weighing heavy on me because for some reason, for some reason, more than my mom follows me on Twitter, I feel like I have now somehow a responsibility to this world. And it dawned on me that me and millions of others are like the little ants that maintain this little colony. So we have a responsibility not to be, I don't know what the right analogy is, but put a flamethrower to the place. We want to not do that. And there's interesting complicated ways of doing that as 1984 shows. It could be through bureaucracy, it could be through incompetence, it could be through misinformation, it could be through division and toxicity. I'm a huge believer in like that love will be somehow the solution. So love and robots. Love and robots, yeah. I think you're exactly right. Unfortunately, I think it's less of a flamethrower type of an answer. I think it's more of a, in many cases, can be more of a slow boil and that's the danger. Let me ask, it's a fun thing to make a world-class roboticist, engineer, and leader uncomfortable with a ridiculous question about life. What is the meaning of life, Dmitry, from a robotics and a human perspective? You only have a couple minutes, or one minute to answer, so. I don't know if that makes it more difficult or easier, actually. You know, I'm very tempted to quote one of the stories by Isaac Asimov, actually, actually titled, appropriately titled, The Last Question. It's a short story where the plot is that humans build this supercomputer, this AI intelligence, and once it gets powerful enough, they pose this question to it. How can the entropy in the universe be reduced? So the computer replies, hang on, as of yet, insufficient information to give a meaningful answer. And then thousands of years go by and they keep posing the same question. The computer gets more and more powerful and keeps giving the same answer, as of yet, insufficient information to give a meaningful answer, or something along those lines. And then it keeps happening and happening, you fast forward millions of years into the future, and billions of years, and at some point it's just the only entity in the universe. It's absorbed all humanity and all knowledge in the universe, and it keeps posing the same question to itself. And finally, it gets to the point where it is able to answer that question. But of course, at that point, the heat death of the universe has occurred, and that's the only entity, and there's nobody else to provide that answer to. So the only thing it can do is to answer it by demonstration. So it recreates the Big Bang and resets the clock. I can try to give kind of a different version of the answer, maybe not on the behalf of all humanity. I think that might be a little presumptuous for me to speak about the meaning of life on behalf of all humans, but at least personally, it changes. I think if you think about what gives you and your life meaning and purpose and what drives you, it seems to change over time, and the lifespan of your existence. When you just enter this world, it's all about new experiences. You get new smells, new sounds, new emotions, and that's what's driving you. You're experiencing new, amazing things, and that's magical. That's pretty awesome. That gives you meaning. Then you get a little bit older, you start more intentionally learning about things. I guess actually before you start intentionally learning, probably fun. Fun is a thing that gives you meaning and purpose and the thing you optimize for. Fun is good. Then you start learning. I guess that this joy of comprehension and discovery is another thing that gives you meaning and purpose and drives you. You learn enough stuff, and you want to give some of it back. So impact and contributions back to technology or society, people, local or more globally, becomes a new thing that drives a lot of your behavior and is something that gives you purpose and that you derive positive feedback from. Then you go and so on and so forth. You go through various stages of life. If you have kids, that definitely changes your perspective on things. I have three that definitely flips some bits in your head in terms of what you care about and what you optimize for and what matters, what doesn't matter. So on and so forth. It seems to me that it's all of those things. And as you go through life, you want these to be additive. New experiences, fun, learning, impact. You want to be accumulating. I don't want to stop having fun or experiencing new things. I think it's important that it just becomes additive as opposed to a replacement or subtraction. Those few as far as I got, but ask me in a few years, I might have one or two more to add to the list. Before you know it, time is up, just like it is for this conversation. But hopefully it was a fun ride. It was a huge honor to meet you. As you know, I've been a fan of yours and a fan of Google Self-Driving Car and Waymo for a long time. I can't wait. It's one of the most exciting, if we look back in the 21st century, I truly believe it'll be one of the most exciting things we, descendants of apes, have created on this earth. I'm a huge fan and I can't wait to see what you do next. Thanks so much for talking to me. Thanks for having me. I'm also a huge fan. I honestly really enjoy this. Thank you. Thanks for listening to this conversation with Dmitry Dolgov. Thank you to our sponsors, Trial Labs, a company that helps businesses apply machine learning to solve real-world problems. Blinkist, an app I use for reading through summaries of books. BetterHelp, online therapy with a licensed professional. And Cash App, the app I use to send money to friends. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now let me leave you with some words from Isaac Asimov. Science can amuse and fascinate us all, but it is engineering that changes the world. Thank you for listening and hope to see you next time.

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Oliver Cameron (CEO, Voyage) - MIT Self-Driving Cars

Alright, welcome back to 6.094, Deep Learning for Self-Driving Cars. Today we have Oliver Cameron. He's the co-founder and the CEO of Voyage. Before that, he was the lead of the Udacity Self-Driving Car Program that made ideas in autonomous vehicle research and development accessible to the entire world. He has a passion for the topic and a genuine open nature that makes him one of my favorite people in general and one of my favorite people working in this space and I think thousands of people agree with that. So please give Oliver a warm welcome. Thank you very much, Lex, and thank you all for having me here today. Super excited to speak all about Voyage. But in reality, the kind of thing I want to share today is kind of like this title says, how to start a self-driving car startup. Rarely do you kind of get an inside scoop of how a startup is formed. You kind of hear all the PR, all the kind of very lovey-dovey press releases out there. I want to share kind of the inside of how at least Voyage came to be, which was a little unconventional compared to your average self-driving car startup. They always tell you that the path to a startup, getting to the goal you want, is kind of a zigzag. Ours was kind of an insane zigzag. So we'll go through all of that stuff. Let's talk about my background. Also a little unconventional. I'm not very good at learning in a classroom. For me, I found learning by doing, by building, has always been the thing that's worked best for me. So going all the way back to when I was a teenager, software just in general was my passion. This idea that you can make something out of absolutely nothing, and then all of a sudden, millions, and in Facebook's case, billions of people can be using that thing. And after building lots of crazy stuff and perhaps not being too popular in high school because that's all I did, I started a company. I won't bore you with all the details, but learned a lot during the experience, and went through Y Combinator, which I believe started right here in Cambridge, which is very cool. And then this very pivotal moment happened to me. I heard about this online class which was generating a whole bunch of scandal and lots of controversy, and it was from this guy called Sebastian Thrun. He'd taken this Stanford class he taught in artificial intelligence and just said, screw it, we're going to put the whole thing online. And back then, and this was around 2011, this was a very controversial thing to do. Today, MIT and many others do this all the time, but back then there was a hell of a lot of controversy around doing something like this. But this learning format really just appealed to me. Being able to sit in front of my laptop, learn at my own pace, build, build, build, was something that really resonated with me. And I took this class in 2013, Artificial Intelligence for Robotics, and this again was just this pivotal moment. My head exploded, all the enthusiasm I'd had for software kind of transferred to artificial intelligence and robotics, and just became addicted to the format of what are now called MOOCs, Massively Open Online Courses. And I loved them so much that I decided, hey, I want to go do this and help others learn this stuff, so hey, let's go join Udacity and build more classes like this. So I did that for four years, led our machine learning, robotics, and eventually our self-driving car curriculum, which was a lot of fun. And I got to learn directly from two great company builders, like truly great company builders. One was Vishal Makkajani. He was the operator extraordinaire at Udacity, understood how to build a company, how to build a culture, how to incentivize, and how to do all those things that we don't often talk about. And Sebastian Thrun. He, of course, founded the Google Self-Driving Car Project in its early days, and right now I believe he's building flying cars. Just in general, I learned so much from him, but this idea that you are literally in control of your destiny, you can build absolutely anything if you put your mind to it, was always pretty inspirational. Today, of course, I build self-driving cars at Voyage, and we'll talk more about what makes us special compared to the other self-driving car companies you may have heard of in this class and beyond. Let's talk about Udacity. Can you raise your hand if you've heard of Udacity? Very curious. There you go. That's most of the room. Udacity, like I said, was founded by Sebastian Thrun. He took this class online and it all just exploded, and he built a company around it. Udacity's real focus is on increasing the world's GDP, this idea that talent is everywhere, that it isn't now just constrained to the best schools in the world, that because of this proliferation of content, there are talented students all over the world, and all they need is the content in which to be able to build crazy cool world-changing things. What I see as my job today is to go out into the world and find these ridiculously talented people and then put them to work on the hardest problems that exist. Udacity, to me, felt like the perfect place to do this. As a kind of prelude to this, about three years into Udacity, we had this real focus, like I said, on machine learning and robotics, but we really wanted to take it to the next step. We came up with this kind of concept internally that we called Only at Udacity. What if we taught the things that other places weren't teaching? What if people all around the world could come learn from what may appear to be niche topics but were just being taught at the right time because that industry is about to blow up? The first one we did of this, and we've done some after, including Flying Cars, a much more in-depth curriculum on artificial intelligence, was Self-Driving Cars. This is a quick video that introduces it, and this is, of course, Sebastian Thrun, robotics legend. Let's see if this plays. With a lean self-driving car has been the dream of my life. And I've dedicated more than 10 years to it. If we can build a safer car, we'll save a lot of lives. But on top of it, it's transformational. Just imagine, instead of owning a car, you have a little phone in your stomach compartment, and an empty car comes to you, you jump in, and it lets you go somewhere, and when you don't need it anymore, it disappears. There is an enormous market for self-driving car engineers. Lots and lots of companies that you wouldn't suspect have entered that field and are massively high-end. I challenge everybody to be a part of this. We're launching at the university another degree program called Self-Driving Cars so that everyone in the world can become a self-driving car engineer. And why did we want to do this? What was our goal? It was to accelerate the deployment of self-driving cars. Like Sebastian says in that video, there's a number of reasons why self-driving cars are transformational. At the time, this was around 2016, it felt like self-driving cars were just taking a little bit too long. We rewind to that particular spot in time. Google was really the only main effort going on, and what we believed is that it needed to happen faster, and that one of the reasons it wasn't happening fast enough is because there wasn't enough talent in the space. So what we decided to do is, like I said, build something quite special. We wanted to pair up a world-class curriculum, an actual self-driving car, which we'll talk about more, and what we called our open-source challenges. And all of that would come together to build this quite special curriculum. So let's start with the curriculum. One of our beliefs was that partnering with industry was the right way to go. That was because it felt, and I believe this, that the knowledge of how to build a self-driving car was not necessarily trapped in academia, it was trapped in industry. So we had to go straight to industry, work with engineers that were already challenging themselves with these problems, and get them on camera, have them teach the concepts that they know and build day in, day out, and have that be transplanted to thousands of minds around the world. So these are just some of those partners. There were many, many more, but we had a real focus on finding these engineers, wherever they may be, and getting those folks on camera. We also built an incredibly talented team. This is just a small snippet of the curriculum team, but of course, Sebastian Thrun was a big part of this curriculum. When I told folks that I'd gotten a chance to work with him on specifically self-driving cars, he likened it to getting basketball lessons from Michael Jordan, which I thought was pretty fun, and they were probably just as entertaining. But some really, truly great folks working on this curriculum and still doing that to this day, who deserve all of the credit, frankly. Here's a quick photo of our first lecture recordings with eventual Voyage co-founders, Eric and Mac. Eric, who's on the left, hates this picture, and here's why. There you go. He still isn't at Mac's height, but he still has that box on his desk. And we built a whole 12-month curriculum to take an intermediate software engineer, who may be in consumer software or just some other part of the software world, and take them into self-driving cars. We wanted to cover perception, prediction, planning, localization, controls even, just the whole breadth of the industry. And the reason we wanted to do that is because we saw the best fit for a Udacity student not necessarily being a specialist in a niche, for example, just perception, although there's been a whole bunch of folks doing that as well, but that the skills of a Udacity student tend to pair themselves well with being a generalist, someone that can contribute all across the stack. So we tried to give these folks that breadth of knowledge. So here's another quick video of just the curriculum that we built with some previews. In the first term, you'll build projects on deep learning and computer vision. For example, you'll build a behavioral cloning project where you drive a car yourself in a simulator, kind of like in a video game, and then you use data from your own driving in the simulator to train a neural network to drive that car for you. This is the type of project the cutting-edge Silicon Valley startups are working on right now, and it puts you at the forefront of the deep learning and autonomous vehicle industry. You'll also build a project to detect and track vehicles in a video stream, just like real autonomous vehicles have to do out on the highway. In term two, you'll learn about sensor fusion, localization, and control. This is hardcore robotics that every self-driving car engineer needs to know in order to actuate and move the vehicle through space. In the localization module, you'll build a kidnap vehicle project, which takes a vehicle that's lost and figures out where it is in the world with the help of sensor readings and a map. This is exactly what real self-driving cars have to do every time they turn on in order to figure out where they are in the world. In the control module, you'll build a model predictive controller, which is a really advanced type of controller that's actually how most self-driving cars move through the world and use the steering wheel, throttle, and brake to follow a set of waypoints or a trajectory to get from one point to the next. In term three, you'll learn about path planning, you'll have an elective month, and you'll learn about system integration. Path planning is really the brains of a self-driving car. It's how the car figures out how to get from one point to another, as well as how to react when you meet obstacles in terms of seating. I'm going to give you a sneak preview of how path planning works, and this is something that nobody's ever seen before, so get ready. Path planning involves three parts. There's prediction, which is figuring out what the other vehicles are going to do around us. There's behavior, which is figuring out what we want to do. This goes on for a while, so we'll pause it there. The impact of this curriculum was bigger than we thought it would be. When we pitched as a small team this idea to Sebastian and to Vish at Udacity, there was a lot of skepticism that something like this was going to be successful. And the reason that there was that skepticism is that one of the kind of formulas that Udacity looked at to determine the impact of building a certain type of content was the number of open jobs available. If there was, for example, in web development, mobile development, all that good stuff, there was millions of jobs open, so it felt like there was a massive opportunity to impact the area. But if you were to, in 2016, search for self-driving car engineers or the different disciplines that exist within, it was kind of just Google. So it was very interesting just to see the instantaneous reaction that we had to launching this curriculum. Today, over 14,000 successful students from all around the world, as you can see. Probably the most exciting thing is to see what students have done with this sort of curriculum. For example, I learned recently that a set of our students here are building a self-driving truck startup in India. Another set of students in South Korea are building a perception engine for self-driving cars. Just a whole bunch of folks building truly amazing things. And not only that, they've gotten jobs at Cruise, Zoox, Waymo, Argo, all the big names, and are actively impacting those companies today. Now, for the fun stuff. We also decided to make that curriculum extra special. And we decided to do that by building an actual self-driving car. And whenever I talked about this internally at Udacity, people asked me why. Why do we need to do this? Isn't the curriculum just enough? Why go to the length of building an actual self-driving car? And selfishly, some of it was just a personal want to build a self-driving car. But the reasoning that I use is that what better way to prove to these students that are putting their faith in us that we know what we're doing than to build our own self-driving car. And also, what better way to collaborate with these students on an area that is really infantile than, again, by having this platform that students could actually run code on a car. So, we decided to buy a car, and we'll talk more about that in a second, but we set ourselves a milestone for our self-driving car. It was to drive from Mountain View to San Francisco, 32 miles of driving with zero disengagements. It should be repeatable. It won't be zero disengagements every single time, because otherwise we've got an actual self-driving car. But in a short period of time, how much progress can we make towards this stated goal? Raise your hand if you've been on El Camino Real in that sort of region. So, you probably understand it's got a lot of traffic lights. In fact, in our route, about 130 traffic lights. It's multi-lane, three lanes, speed limit of about 40, 45, something like that. So, it's fairly complex, but it's also got some constraining factors, which is what we're looking for, too. So, it focused our tech efforts. This is the car we bought. You're probably very familiar, if you follow self-driving cars, with the Lincoln MKZs of the world. They're everywhere, and there's a reason for that in terms of the drive-by-wire nature of the vehicle and other stuff. And we outfitted a whole bunch of sensors, some cameras, some LIDARs, all that good stuff. We also tried to build our own mount. We affectionately called this the Periscope. I don't know why it's in slow motion, but this was not our final design. We built all this from parts at Home Depot. Truly an MVP. And then we got to work. The goal was to accomplish that milestone within six months. So, we of course had to work fast, assembled a dream team of folks that I'd worked with on different projects at Udacity, that also wanted to come dabble in this, folks that worked on the machine learning curriculum, robotics curriculum, etc. So, this was one of our first days testing. And we did this at the Shoreline Amphitheater parking lot, which actually now is a very popular place to test self-driving cars in the Bay Area, because Google used to do it in the past. We saw a lot of weird stuff. For example, you'll see here. We saw what I believe to be a motorcycle gang. And we made progress. We kept iterating, kept building, and it started to come together. In fact, some stuff that we thought wouldn't work, surprisingly, just started to work. This is on El Camino Real. I'm in the back seat here. So, Mac discovered that we shouldn't have stopped at that traffic light. But we did. We resolved the mystery later. Let's go to the next video. And of course, we learned a lot by going in this route, the different behaviors of drivers. One of the things that we were worried about is vehicles cutting us off. And when we say cutting us off, it means a vehicle pulling out in front of us, even a few hundred feet in front. You'll see here. We drove a little slow. 25. It turned out it was fine. And pretty soon it got quite boring. The car was doing very well driving itself. We built some cool algorithms to change lanes when necessary. Similar to what you see with Tesla Autopilot these days. We collaborated with some students on a traffic light classifier, which was integrated into ROS there. And yeah, pretty boring stuff. So you can tell Eric was surprised that it was just fine. And we also had a penchant for building, for recording themed videos, like you saw maybe from Elon Musk and the Tesla team with Paint It Black. We've got our own version of that. Eventually, we became pretty confident, but we always wanted to test most of the day just to get the most learnings out of everything. This video was made at 2.30am, driving from Mountain View to San Francisco, all 32 miles. This is a backing track. This is a backing track. Maybe I want to turn it down. So it's easier because there's less traffic, right? This is kind of cheating and didn't count as the milestone, just to be clear. You'll see that we eventually hit the 32 miles. And Matt, who's in the driver's seat, is pretty excited about that. Still pretty good. And they hit it. But of course, that didn't count because it's in the middle of the night and that's not going to be a very useful route. But it was an awesome accomplishment just to even make it 32 miles with no disengagements when this traffic lights lane changes, all that good stuff. But after four months, this is in the daytime, this began I believe at like 6, sorry 7am, we accomplished it. That small team had come together and built something pretty cool that could handle again multi-lane roadways, varying speed limits, traffic lights, objects, all that good stuff. And the thing that really brought this home to me is that the industry was now ready, right? And I think this feeling I had in software where someone in their bedroom can go and build something and launch it almost feeling overnight could now, not quite the same, but close to the same, happen in self-driving cars. But we'll talk more about what this led to in a little bit. Let's talk about open source challenges. We also got the same question, why do this? And it was clear to me that for something like self-driving cars, which was so formative, we had to collaborate with students to figure out the best stuff. Because even the folks that were at Udacity were not necessarily the world's leading experts in these topics. So we wanted to use this hive mind of activity from around the world to teach the best stuff. So just through a period of a year, these are all the different challenges we launched. There was prizes and leaderboards and all this sort of fun stuff. The one that I'll focus most on today is using deep learning to predict steering angles. And the challenge was clear. It was that given a single camera frame, you have to predict the appropriate steering angle of the vehicle. If anyone had read NVIDIA's end-to-end papers in 2016, this stuff was all the rage. And it felt like one of those areas that was just begging for more exploration. And again, let's use all these students from around the world to do it. And we did have students from all around the world. There was over 100 teams, people self-organized into these little groups to go and build this. And over the course of about four months, we had a whole bunch of submissions all taking incredibly different approaches to the problem. We released data sets, validation sets, all that good stuff. Here you'll see our V-winning model. And I later found out that the author of this model actually went on to lead the self-driving car team at Yandex, which if you've been following CES is doing some pretty cool stuff in self-driving cars today. But you'll see this is on a route from the Bay Area to Half Moon Bay, a very windy road. And you'll see that the prediction matches pretty closely to the actual, which is nice. And if you read his description of his solution, it's a pretty cool solution. And I think the most exciting thing was just the number of different approaches to the problem all resulting in some awesome stuff. And again, in true Voyage fashion, we recorded a video of what this model performed like on our car. It wasn't perfect as any first model, and just the general approach of camera-only driving had its faults. One of the main ones that we realized after trying all this stuff out is that, of course, a car, when steered by such an input, performs differently in a car than it does on your desk in a simulator or through pre-recorded camera frames. So adjusting for those corrections that might need to be made is something that students after the fact added, which was pretty cool. So after all of these things, building that curriculum, building a self-driving car, launching these challenges, it felt like it was time for something new. It was awesome to go and collaborate with all these students, and it felt like I had to go build something. So gathered that same team that had built this curriculum, and we said, we're going to go build a self-driving car. This is from my pitch at Coastal Ventures. You can kind of see the pitch deck there a little bit. Voyage is a new kind of taxi service. Our pitch has changed somewhat through time, but that's still pretty accurate. We started what is now called Voyage. Our goal really was that we wanted to, again, build a self-driving car, but we wanted to do it differently. We didn't want to follow the same formula that we felt we'd seen from some of the other folks in the field. The reason is that those folks have real advantages. When you think about Google's project, of which I'm a big fan, they have this massive engineering pipeline of folks that want to go build a self-driving car at today Waymo, but they also have a cash-bank balance of billions of dollars that is hard to match. They also have the brand recognition of getting to work with Google and all that good stuff. So we just knew we had to think about this problem quite differently. What motivated me is that today, as we all know, we have this incredibly broken transportation system. You step outside onto the roads today, and I don't know about you guys, but I don't feel particularly safe when I jump into my car. We all know the stats. Over one million people suffer fatalities on the roads today. It doesn't include folks that break necks, that injure, break bones, all that horrific stuff. It's also incredibly inefficient. We've, again, all observed this as we go about our day. Perhaps the number of lanes that exist on a road today to account for peak traffic, the number of vehicles which have enough room for eight people, have usually one person in that front seat. I read a stat recently that only 7% of the average vehicle's energy usage is going towards moving the things that are actually in the car. The rest is waste. So an incredibly inefficient system. It's also expensive. The reason we see a lot of old cars on the road today is because that's, at least today, the most optimal and affordable way for lots of folks to get around, and inaccessible. And you'll see why this matters to us in particular. Our goal is to introduce a new way to explore our communities. This is a video of one of our cars at a particularly cool place, which we'll talk more about. And this is kind of our mission. And why now? Why is it possible to build a self-driving car now? A number of factors that we learned during that Udacity experience, but some new as well. It feels, from everything we see, that sensors are now in this position, which these sensors are now capable of level four self-driving cars. The resolution, the range, the reliability, all those things that were necessary for an L4 self-driving car are today ready. That didn't used to be the case. If you rewind to 2007 and look at the cars that were participating in the DARPA challenges, you'll see a lot of single channel lasers. You'll see the relic of the Velodyne HTL64, the spinning bucket, as it's called today. And no one would have claimed those sensors already. But today, you've got this enormous breadth of sensors that can take you that way. Deep is there, when we think about the recent rise in GPUs and whatnot. Finally, being able to have enough performance in the back of a car with the power constraints that you have, it's there. And talent. Again, this is not just Google today. You've got all of these great minds from all around the world building this technology. So you're able to recruit those folks, put them to work on the problems they've solved in many cases beforehand. The reason I have yellow for computer vision, which is not a knock against computer vision, is because it's not quite there yet for a fully driverless self-driving car. If you, again, rewound three, four, five years, this would have been a red. But today, with all the community and whatnot around computer vision, this is steadily getting to a green state. So pretty soon, that will be green. And of course, then you'll have that perfect formula for level four driving. What we run after is ride sharing. We believe that the optimal way for people to move around is to be able to summon a car. But the thing that's suboptimal today is that you have to have a human driving you whenever you want to move around. Prevents the cost from being lower, prevents some safety issues, prevents some quality issues. And we think solving that will mean these next generation way of moving around will come to fruition. But what we also see is that if you, let's say we never remove the driver from the car, that a ride-hailing network always had a human driver, you are inherently limited by the number of miles you can drive, which means that it'll never replace personal car ownership, will never fix that fatality number I talked about, all of those things we must solve. So we think by having a self-driving car that these next generation transportation networks will come to fruition. Our lead VC is a guy called Vinod Khosla, the founder of Khosla Ventures, an awesome guy who's done some truly world-changing things. He has this quote, which I'm a big fan of. Your market entry strategy is often different from your market disruption. Start where you find a gap in the market and push your way through. And this better communicated what I mentioned at the very beginning, which is that we should build a self-driving car, but do it in a different way. Because if we don't do that, we're going to fall into the same traps as many of the others that have died along the way. We have to find a way to do something different that we own and that we are really, really good at. And for us, that was retirement communities. Hands up if you've ever visited a retirement community. Way less. There you go. Surprise, Lex. You're the one. But these are just amazing places. And the reasons we choose retirement communities first to deploy our self-driving technology in is for these four reasons. They are slower. The speed limits in these communities tend to be far slower than you'd see on public road. Much calmer roadway. When you visit these locations, I liken it to listening to a podcast at 0.75x. It's very constrained, very slow, and a little boring from time to time. But you've also got these heartfelt transportation challenges. We hear from these residents all the time about how transportation is a pain point and that their only option is a personally owned vehicle. These folks know in many cases they shouldn't be driving, but because they don't have an alternative, they still drive. We hear from folks that put off much needed surgeries, hip replacements, things like that, because they don't have a friend in town who's going to be able to move them around. We hear from folks with vision degeneration that they just don't see a way that they'll be able to move around and keep that quality of life that they've been able to have. Folks gripping steering wheels for extended period of times. All these challenges that felt like the best first place for a self-driving car to begin. And a clear path to customers. We see that on the roads today, ride sharing on public cities and whatnot is a particularly brutal battle. A race to the bottom in terms of cost. If we owned every retirement community in the country, meaning the transportation networks there, that would in and of itself be a very valuable business. One of my favorite passengers is Anahid. She came to visit us recently and gave this quick speech about why self-driving cars matter to her and her community. Let's talk about our first community. This is The Villages. Whenever I show this slide, people are astounded by the number of residents in a community like this. Over 125,000 and growing. Over 750 miles of road. And what we have in this location is an exclusive license to operate an autonomous vehicle service. This is one of our other beliefs, which is that by partnering very deeply with the community, it means that we're able to deliver a better service and that we're able to grow a more reliable business. We won't have entrants and competitors from all of the other self-driving car companies in our communities. What we actually do in exchange for that exclusive license is grant these communities equity. Because if we win, it's probably, in fact, highly likely as a result of those communities. And the addressable market of transportation in these regions is massive. These residents tend to be, as a lot of seniors tend to be, quite affluent, which means that they have some disposable income when it comes to being able to pay for ride-sharing services and other things like that. So we find that that recipe is absolutely perfect here. And we're launching and have launched passenger services to these residents. I've gotten a lot of awesome feedback, learned a lot about the needs of providing ride-sharing for senior citizens. Just some quick stats. This is from my Series X fundraising deck. Just about the size of the senior market. Again, this is the first place we go, but you can get a feel for just how large this transportation market is. Today there are 47 million seniors. That's growing by 2060 to over 100 million seniors in the US. The total addressable market for just seniors is incredibly large. 2,500 plus communities, all that good stuff. And this is how we see the world, the landscape of potential deployments. You've kind of got a lot of the big guys focusing on that bottom left quadrant. They're focusing on large cities. And it makes sense because it's playing to their unique strengths. It's playing to their ability to deploy thousands of cars, tens of thousands of cars. It plays to the strength that they have at least some patience or ability to have more extended timelines when it comes to building this technology. But for a startup like us that fights for survival every single day, it means that we have to do things differently. So we focus on that top right quadrant there. What we've kind of coined as self-contained communities. These places are simpler, slower, but they also have this ability for us to have that exclusivity that I talked about. And there's some others, of course, that we play in, whether it's the senior market or maybe even small cities and things like that. Let's talk about autonomous technology. So just to reiterate, why do we deploy in retirement communities? Slower speed, simpler roadway. There is a central authority. These places tend to be run by private companies, which makes for a quite unique relationship in a very positive way. It means we can deploy faster. It means we have the potential to have more impact in these regions. It also turns out that retirement communities tend to be located where there's ideal weather for self-driving cars. Think about Arizona, Florida, et cetera. We have a world-class team building this at Voyage from all the major programs out there, and that makes our lives infinitely easier. One thing that also makes our lives easier is the sensor configuration of our car. We've intentionally made this decision that we're not going to focus on optimizing for cost today, but to optimize for performance. We want to get to truly driverless sooner than most, and one of the easiest ways you can again make your life easier is by optimizing for high-resolution sensors. At the very top of the vehicle, we have the VLS-128, which is a 128-channel LiDAR that's capable of seeing 300 meters in 360 degrees. Many of the different LiDARs on the vehicle to cover different certain blind spots, all together we process 12.6 million points per second, and that just looks incredibly high-resolution. You'll see our car at the bottom there, and that's the raw point cloud output that we see in the world. We run towards level four, and for us what that means is that if you're building a demo self-driving car, kind of like we did at the Udacity project, you may focus on just the top four items, that top row. You may focus on perception, prediction, planning, and controls. It turns out you can build a very impressive demo quite quickly by just focusing on those things. But, of course, those things fall apart whenever edge cases are introduced, which happen all the time. So we've spent a ton of time on all the items here, because again, our goal is to build not a demo, but a truly driverless vehicle. We also have an emphasis on partnerships, because what we've noticed in the self-driving ecosystem is that there's not just more self-driving car companies building the full stack. There's now folks getting into simulation, to mapping, to middlewares, to teleoperations, to routing, to sensors, of course, and a ton more. So we make our lives, again, easier by partnering with companies like this, so that we don't have to spin up a simulation team, or we don't have to spin up an operations team to go map the world. We can just work with these very cool companies. Let's talk about one unsolved problem, which fascinates me. It's to do with perception. And you probably won't be able to notice this unsolved problem from just this picture, but maybe if I add some annotations, you might. Foliage, trees, bushes, whatever you want to call them. You may have seen some quotes in the media about some popular AV programs struggling with such foliage. For example, cruise cars sometimes slow down or stop if they see a bush on the side of a street or a lane dividing pole, that was in the information. This one, Uber's self-driving car software has routinely been fooled by the shadows of tree branches, which it would sometimes mistake for real objects, insiders say, that's Business Insider, and even Voyage. There's only one hard stop on the way, the culprit is a bush two feet high that protrudes into a lane from a street median, which Voyage considers a possible threat, Voyage may trim it. That's a joke. But we don't think that's scalable, and maybe it is, I don't know. But we, at the beginning of 2018, decided to solve this problem. So of course, all of this resides in the world of perception, an area of particular fascination for me. We're sharing these slides, but these are just some of the papers and research that we see going on that intends to solve those sorts of issues. One of the reasons you've seen those programs, including ours, be particularly sensitive to foliage is because, from a perception perspective, one of the most well-known ways to detect objects is to utilize the map. If you have this map, and you effectively, it's simplifying to a certain extent, but subtract objects that aren't in the map, and then use that as a way to understand what's in and around you that's dynamic, then of course you'll end up with decent representations of cars and pedestrians and whatnot. But if foliage grows, which it does, trees, then that's going to extend out from the map and mean that that particular bush is now an object in your path. These networks here, of which these are all neural networks, don't use that same technique. They don't use the map as a prior. Instead, what they do is take, of course, this 3D scan of the world, and then take a more learned approach to the problem. You'll have tens of thousands, hundreds of thousands of labels of cars, humans, et cetera, and then these next networks will be able to pick these ones out. We're particularly fascinated by Picsor, which came from some great research at Uber ATG. VoxelNet came from Apple SPG. I've heard our engineers talking a lot about Fast and Furious recently, which merges together perception, prediction, and tracking into a single network, which is pretty cool. And PointPillars, which I think came from the Neutronomy team recently. I think Carl is speaking soon, right? So just in general, we see a whole bunch of work going out there to solve these issues. The other one that these sorts of networks solve, which I also find particularly fascinating, is that if you use traditional clustering algorithms, what you might see is that if two people are stood next to each other, a traditional algorithm will cluster as one object, which when you're trying to move away from those edge cases and build a truly self-driving car, that's a non-starter, right? Because pedestrians are the most important thing you can probably detect, and detecting two things as one thing is not going to cut it. And of course, it does that because it's a dumb algorithm. It's not trained on any sort of information. But these networks, again, are very, very good at understanding the features and perspectives of humans, even if they are in crowds and whatnot. And that then helps all your stack downstream, because if you have accurate perception information about objects in and around you, your predictions are much better, your tracking is much better, and ultimately how you navigate the world is much safer. I'm also particularly fascinated by reinforcement learning, which I know Lex is as well. If you've read Waymo's recent work on imitation learning, I think that's particularly cool. Another company we track quite closely, just because they do amazing stuff, is Wave, trying to build an entirely self-driving car powered by reinforcement learning. Think about disengagements as rewards and things like that, to be able to tune that to better performance. Also just areas of learned behavior planning, ultimately fusing rules of the road with more learned behaviors. The ecosystem, I think it's this area that is thriving today, seeing just how many folks are diving into not just the full stack, but building tools and building other really important parts of the stack. The maturation of sensors, not just higher resolution LiDAR, but things like 3D radar. We get pitched all the time from these companies, and it's clear to see there's been a rise in volume from all these great efforts. Lessons learned. Now that I've been building Voyage for two years, and prior to that, four years at Udacity, what things have I personally learned that are not technical in nature? So many things. These all may look like cliches, but I promise you they all came from lessons which were really, really painful in the moment. Don't be intimidated. The thing that I feel happens a lot in self-driving cars is that because it started in this very academic sense, meaning Stanford, Carnegie Mellon, and whatnot, that it felt like to break into the industry, you had to also go through that same path. You had to get a PhD in something and really go the path that was well-trodden. I think that only takes the industry so far. I think it's really important that we get folks from all different backgrounds, all different industries to come contribute to this field, because if we don't, there is no driverless. It can't happen in that isolated bubble. It needs to be extended out. So don't be intimidated by those things. Understand your limitations. This is perhaps more of a CEO lesson for myself, but I think when you're building out a company from one person or five people to today we're 44 folks, you cannot do everything. It's really important that you build a team around you that is able to do what you used to do, but do it 10 times better. I probably didn't spend enough time building out that team until we had some challenges our way when it comes to that stuff. Be proactive versus reactive. I think it's really crucial, again, when you're building a company to try and predict what's going to happen next, because if you're reactive you're constantly two steps behind what other folks are doing. Get out of the way. I think a lot of folks, again, perhaps overstay their welcome in certain areas of the company. When they should just say, okay, I've got experts now, I can just step aside and let those folks do what they do best. And speaking of which, hire the best. It's really easy when all this pressure's on when you're building a company to sacrifice when it comes to your culture, when it comes to hiring. It's really crucial that you find folks that are not just the best in their field, but are the best match for your company. And always be curious. I think it's always one of the things we believe in at Voyage is that it's important that knowledge is not isolated to just one person, that that knowledge should be spread throughout the company. Because even though it may feel like oversharing or overcommunicating, what that knowledge may mean for someone that has a particularly unique background is they may do something incredibly cool with it. They may build something that totally transforms our company. So that's about it. Jump to questions if that's helpful. That was great. Please give a big hand. How did you identify retired communities as the target market to prioritize? Yes. So retirement communities for us was actually, there's a really long story, but I'll trim it down a little bit. So when we were starting Voyage, Sebastian Thrum was very helpful in helping us start this company. And of course, as kind of naive founders of a company, we were like, let's just take this El Camino thing and put it on everywhere else that looks like El Camino and just do that over and over again. But he cautioned against that. And very wisely so, because again, you're nothing special compared to the other self-driving car companies out there by doing so. And in 2009, he had really advocated to Google leadership, et cetera, Larry Page, that retirement communities for self-driving cars might just be the best way for Google to go about deploying their self-driving cars. But and I can understand why, I think the Google folks were Google, right? We're not just about retirement communities, we're about the world, like level five or nothing, right? So he got some pushback, but he did some research in that process, met some folks. So when we were starting, he was like, you got to check out these retirement communities. So we did, we went to visit and eventually we got there. So we wouldn't have got to that point without Sebastian pushing for that. Just to follow up on the question of retirement communities, the question is, do you ever think about the other collateral issues, especially the retirement community would have to get into a car? And how exactly would they interface, like somebody wants to make a call to have a car come to their, wherever they are, and they have to move from A, point A to point B. So how did you ever think about all these issues that are very germane? It's not just a vehicle moving on its own, but these are all collateral issues. How do you plan to address this? It's a good question. So the way we think about this is that today we've intentionally focused it on a segment of the market, which is called the active adult communities. These folks tend to be able to go into their own cars or into a taxi, open the door, sit down without the need for any assistance when it comes to that. But they may have vision issues, they may have other issues that prevent them from driving perhaps. For example, we hear a lot that folks feel really uncomfortable driving in the evenings. They feel comfortable driving in the daytime because their vision supports it, but when it comes to the evening time, they have this mad rush to get home. But there is that other market which you're talking about, right, which is folks that just need that helping hand towards getting to the car. And one of our beliefs as a company is that the senior market like I had in that slide is surprisingly large. And what that means to us is that we think we can own it. We think we can be that company that any senior citizen in that situation thinks, oh, I should call Voyage because I need to get from point A to point B, instead of thinking I should call Waymo or Cruise or any of the folks that are going to go after the general big market, they'll think about Voyage. And the reason they'll think about it is because we'll deliver a product to them that is meant for those folks, that is designed for their use cases. It may be that actually if they're going on a long trip, let's say they're traveling 50 miles, the first mile of that trip and the last mile of that trip may involve a human, like helping them into the car and then dropping that human off somewhere else to go do that all over again. It may involve crazy robots that help people from their cars. We've heard from folks at Toyota that are building these bag-carrying robots and other things that may assist seniors from getting to the cars and whatnot. So I think that's why that market for us is particularly exciting, because it feels like you can deliver these tailored products that would enable us to be the market leader. But today we focus on active adult, but who knows where you go next. Can you talk a little bit about how you determined your final sensor suite? Yeah. So the truth is it's never final. So we think about generations of vehicles. So we have our first generation vehicle, which was a Ford Fusion, had a single Validyne HDL-64 in it, a bunch of cameras, radar, and we set some milestones based on that vehicle and we accomplished those milestones. And then once we reached the max in which we're able to take that vehicle, we then say, oh, we need to bring on our G2 vehicle, our second generation vehicle. So we did that and we said, okay, we have these certain goals in mind, which are pretty lofty and pretty ambitious. We need incredible range, incredible resolution for these things. And actually what we've discovered is that in our particular communities going at the speeds that we're going at, radar isn't particularly useful. So we don't have radar on our second generation vehicle, for example. But I'm sure that when we go to that third generation vehicle, there'll be other driving factors that we work backwards from the milestone to say, what do we need on this vehicle? It may be cost in the third generation vehicle, right? We may say that, hey, we need a more affordable sensor suite than what exists in our second generation vehicle. But they're driven by technical requirements and that means that we are able to really marry the two with the vehicle. I was curious, when you showed the student-led content, or when you showed one of the students in your first practice car had developed a traffic light sensor, and then you showed later on that you were getting student input for deep learning models for steering wheel turns. I was wondering what your system architecture looks like in terms of the kinds of perception that you take in, how modular it is, and to what extent deep learning algorithms have played a part in those different parts of that ecosystem? Yeah, that's a good question. So I really encourage folks to get familiar with ROS. So ROS has always been this kind of playground for roboticists of all different types of robots, to be able to try things out on robots. And ROS 1 is particularly notorious for kind of hacky and hobbyist types of projects, but it's not meant for production. ROS 2, though, which is in kind of an alpha release state, is definitely meant for more production-oriented things. And the reason I mention ROS is because it has this awesome architecture which lets you plug and play what they call nodes and be able to experiment with different approaches to the problem. So for example, what was running that deep learning model, predicting steering angles, effectively replaced our more rules-based planner and perception engine. And we just plugged the output of that, of the steering angle, straight to our controller to just actuate the vehicle. And ROS is particularly good at those sorts of architectures. And it's all open source, so you can do some cool stuff with it. Can you tell how you handle the liability insurance for passengers for your vehicles also? How we handle insurance? Is that a question? So we have a pretty cool deal with a company called Intact Insurance. And the idea is that insurance in the autonomous age is going to be very different than insurance today for human drivers because there's different risk assessments and whatnot. And one of the ways that we're able to prove to these insurers that we're good at what we do is actually sending them data. We send them data from our cars as we drive, showing that as we move through the world, we accurately detected things and planned around things and all that good stuff. And then they use that data to inform our rates of insurance. I think that the future actually of insurance will be on a similar lines, but perhaps more extreme where, for example, the rates will change depending on the complexity of the environment. If we're just driving down a straight road, completely straight, and there's zero vehicles around us, our insurance rate should be super low. But if we enter a city center and there's thousands of people and cars and all that crazy stuff, our insurance rate should just rise almost instantaneously. So we're partnering with someone today that insures the passenger, the car, sensors, all that stuff. But I think there's a lot of room for innovation there too. Did you have any problems onboarding the retired people initially? When they're skeptical, scared? And then the other question is, what are the major missing pieces in terms of computer vision to achieve L4? What was that last? Missing pieces between computer vision? In computer vision to achieve L4 self-driving. Gotcha. So one of the more interesting insights I think we had about retirees is that, again, in my kind of naive state back in 2016, my general feeling was retirement communities might not be the first to adopt this technology, right? Because they may be slower to adopt new technology, might be scared of the technology, all those sorts of things. And to kind of validate that, I went to talk to some senior citizens because I talked to my own grandma. She hates self-driving cars. I was like, that's not a good sign. But went to talk to these folks in these sorts of locations. And the really interesting thing we learned is that traditional consumer software or devices, yes, there is definitely a lag in adoption with senior citizens. And that's proven in many studies, many stats, that senior citizens are slower to adopt the Facebooks of the world or the Instagrams or the WhatsApps, all those sorts of things. Cryptocurrency, I don't know. But that's because they have these very well-defined processes that they've had for most of their lives, right? Instead of using Facebook, they call someone up and they have a conversation with someone about their day or stuff that's going on. Or they don't share a picture on Instagram, they physically mail a picture or something like that. So to change that behavior is tough, right? Because that's a behavior that is fundamentally different than what they're used to. They have to log onto a computer, go to this weird Facebook thing and share pictures with thousands of people, that's weird. But the difference between that and a self-driving car is that our experience is no different than the car they're used to. It just turns out it's being driven differently, right? Like they see a car, it's the same, similar form factor to what they're used to. They open the door, they sit in the back seat. Okay, there is a button I have to press to say go, but it's pretty similar to what I'm used to in my past. I don't have to learn a new behavior, I don't have to change something that I'm used to. So that was our first learning. And then also, they actually really don't care too much that it's autonomous. They are very, when I'm in the car, I'm quite curious and enthusiastic about the technology and want to tell them about, I don't know, LiDAR and deep learning and perception and they just don't want to hear any of that stuff. And it kind of dawned on me that the reason that is is because what they, senior citizens, have witnessed over their lifetimes is far more dramatic than I have, right? Our oldest passenger was 93 and she told me a story about how when she was very young, she remembers literally moving on an almost daily basis in a horse and cart. So when you talk about self-driving cars to those folks, they couldn't care less because between that period and today, they've seen the birth of flight planes everywhere, they've seen car proliferation, they've seen scooters now, they've seen all of this crazy subway systems. So a self-driving car to them is like, oh, that's cool. I just want it to move me. That's our biggest learning there. The question was computer vision, what needs to happen between now and level four? So I think the holy grail, right? So if you had perfect perception, self-driving cars are solved. If we knew every object that was on the road, in and around us, within a reasonable distance, self-driving cars are solved. False positives are accepted today, which I think is good, but you really want to minimize false negatives, right? You want zero false negatives in the world. And I think that's why we still have a tiny bit of work to do. Because when you think about the reason for a test driver being in the vehicle, well, perception feeds everything downstream, right? So if you miss an object, misidentify an object, any of that sort of stuff, then that effect causes the whole stack downstream to become quite chaotic. That's why I'm excited about all those networks that I talked about. One of the other things we believe that helps us minimize false negatives to non-existent kind of status for us is that we band together multiple networks. So we don't just rely on a single layer of perception. We say different networks have different strengths. For example, VoxelNet is particularly good at pedestrians, but Pixar is not so great at pedestrians because it's from a bird's eye view, where pedestrians are quite thin and whatnot. So let's band those two networks together, and let's also band together some more traditional computer vision algorithms that may not be processed on the entire 360 scan, but may be processed on a small sample, maybe at the front of the vehicle, for example. So there's just lots of little bits and pieces like that to go through to minimize the worst-case scenario, which is a false negative. But it's clear when you see Waymo and whatnot that they feel very, very, very close to that sort of state. You mentioned that weather was one of the main reasons this was a great place to start. Can you talk about hurricanes? Yes. It was funny. I got a question recently from Alex Roy, me and Lex were just talking about, okay, in the event of a hurricane, right, let's not talk about the technology second, but in the event of a hurricane, we've all seen those pictures of people getting on the freeways and trying to get out of the path of the hurricane, right? How is that going to work in a world where self-driving cars are everywhere and personally driven vehicles are maybe more of the smaller size? I don't quite have an answer to that yet, but I think it's an interesting kind of thought problem. From a technology perspective, the really important part of weather for us is remote operation. So inside every one of our, sorry, all of our vehicles have a cellular connection, right? And each of those vehicles is connected to a remote operator that's sat in somewhat close proximity to that vehicle. And that remote operator has a few jobs. One is to just ensure the safe operation of the vehicle, make sure that vehicle is doing as it's intended to do, all those good things. But another is to make sure that the operational domain that we are currently operating in is the one that it's designed for. So all these different camera feeds are being live streamed to this remote operator. And if there is sudden downpour of rain, that remote operator has the ability to bring that vehicle to a safe stop until that rain shower disappears or whatever, or hurricane, whatever it may be. But there are companies, I was pitched recently by a company that's building weather forecasting on a scale that is not really used today, but really microclimate. So thinking about just like this small subsection of the villages, predicting and understanding exact weather within those regions and then having web hooks to tell you as Voyage that that's about to happen. So there's a lot of cool stuff happening there. But remote operators currently are kind of the eyes and ears of our cars to prevent that sort of issue. So please give Oliver a big hand. Thank you very much. Thank you guys.

https://youtu.be/-j0tc0Y1CIE

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Andrew Ng: Advice on Getting Started in Deep Learning | AI Podcast Clips

So let's perhaps talk about each of these areas first. Deep learning.AI. How the basic question, how does a person interested in deep learning get started in the field? Deep learning.AI is working to create causes to help people break into AI. So my machine learning course that I taught through Stanford remains one of the most popular causes on Coursera. To this day, it's probably one of the courses, sort of, if I ask somebody, how did you get into machine learning or how did you fall in love with machine learning or what gets you interested, it always goes back to Andrew Yang at some point. The amount of people you influence is ridiculous. So for that, I'm sure I speak for a lot of people, say big thank you. No, yeah, thank you. You know, I was once reading a news article, I think it was tech review and I'm going to mess up the statistic, but I remember reading an article that said something like one third of our programmers are self-taught. I may have the number one third wrong, it was two thirds. But when I read that article, I thought, this doesn't make sense. Everyone is self-taught. So because you teach yourself, I don't teach people. That's well put. So, yeah, so how does one get started in deep learning and where does deeplearning.ai fit into that? So the deep learning specialization offered by deeplearning.ai is, I think, was Coursera's top specialization. It might still be. So it's a very popular way for people to take that specialization, to learn about everything from neural networks to how to tune a neural network, to what does a conf net do, what is a RNN or a sequence model, or what is an attention model. And so the deep learning specialization steps everyone through those algorithms so you deeply understand it and can implement it and use it for whatever applications. From the very beginning? So what would you say are the prerequisites for somebody to take the deep learning specialization in terms of maybe math or programming background? Yeah, you need to understand basic programming since there are programming exercises in Python. And the math prereq is quite basic. So no calculus is needed. If you know calculus, it's great. You get better intuitions. But deliberately try to teach that specialization without requiring calculus. So I think high school math would be sufficient. If you know how to multiply two matrices, I think that's great. So a little basic linear algebra is great. Basic linear algebra, even very, very basic linear algebra in some programming. I think that people that have done the machine learning course will find the deep learning specialization a bit easier. But it's also possible to jump into the deep learning specialization directly, but it will be a little bit harder since we tend to go over faster concepts like how does gradient descent work and what is the objective function, which is covered more slowly in the machine learning course. Could you briefly mention some of the key concepts in deep learning that students should learn that you envision them learning in the first few months, in the first year or so? So if you take the deep learning specialization, you learn the foundations of what is a neural network, how do you build up a neural network from a single logistic unit to a stack of layers to different activation functions. You learn how to train the neural networks. One thing I'm very proud of in that specialization is we go through a lot of practical know-how of how to actually make these things work. So what are the differences between different optimization algorithms? What do you do if the algorithm overfits? So how do you tell if the algorithm is overfitting, when do you collect more data, when should you not bother to collect more data? I find that even today, unfortunately, there are engineers that will spend six months trying to pursue a particular direction, such as collect more data because we heard more data is valuable. But sometimes you could run some tests and could have figured out six months earlier that for this particular problem, collecting more data isn't going to cut it. So just don't spend six months collecting more data, spend your time modifying the architecture or trying something else. So it goes through a lot of the practical know-how so that when someone, when you take the deep learning specialization, you have those skills to be very efficient in how you build these networks. So dive right in to play with the network, to train it, to do the inference on a particular data set, to build the intuition about it without building it up too big to where you spend like you said, six months learning, building up your big project without building any intuition of a small aspect of the data that could already tell you everything you need to know about that data. Yes. And also the systematic frameworks of thinking for how to go about building practical machine learning. Maybe to make an analogy, when we learn to code, we have to learn the syntax of some programming language, right, be it Python or C++ or Octave or whatever, but that equally important, or maybe even more important part of coding is to understand how to string together these lines of code into coherent things. So when should you put something in a function column? When should you not? How do you think about abstraction? So those frameworks are what makes a programmer efficient, even more than understanding the syntax. I remember when I was an undergrad at Carnegie Mellon, one of my friends would debug their code by first trying to compile it, and then it was C++ code. And then every line that has syntax error, they want to get rid of the syntax errors as quickly as possible. So how do you do that? Well, they would delete every single line of code with a syntax error. So really efficient for getting rid of syntax errors, but horrible debugging service. So we learn how to debug. And I think in machine learning, the way you debug, a machine learning program is very different than the way you do binary search or whatever, or use a debugger, trace through the code in traditional software engineering. So it's an evolving discipline, but I find that the people that are really good at debugging machine learning algorithms are easily 10x, maybe 100x faster at getting something to work. And the basic process of debugging is, so the bug in this case, why isn't this thing learning improving, sort of going into the questions of overfitting and all those kinds of things. So that's the logical space that the debugging is happening in with neural network. Yeah. Often the question is, why doesn't it work yet? Can I expect this to eventually work? And what are the things I could try? Change the architecture, more data, more regularization, different optimization algorithm, different types of data. So to answer those questions systematically, so you don't spend six months heading down the blind alley before someone comes and says, why should you spend six months doing this? What concepts in deep learning do you think students struggle the most with? Or sort of is the biggest challenge for them was to get over that hill. It hooks them and it inspires them and they really get it. Similar to learning mathematics, I think one of the challenges of deep learning is that there are a lot of concepts that build on top of each other. If you ask me what's hard about mathematics, I have a hard time pinpointing one thing. Is it addition, subtraction? Is it a carry? Is it multiplication? There's just a lot of stuff. I think one of the challenges of learning math and of learning certain technical fields is that there are a lot of concepts and if you miss a concept, then you're kind of missing the prerequisite for something that comes later. So in the deep learning specialization, try to break down the concepts to maximize the odds of each component being understandable. So when you move on to the more advanced thing, we learn confinates. Hopefully you have enough intuitions from the earlier sections to then understand why we structure confinates in a certain way and then eventually why we build RNNs and LSTMs or attention models in a certain way, building on top of the earlier concepts. Actually, I'm curious, you do a lot of teaching as well. Do you have a favorite, this is the hard concept moment in your teaching? Well, I don't think anyone's ever turned the interview on me. I'm glad to be first. I think that's a really good question. Yeah, it's really hard to capture the moment when they struggle. I think you put it really eloquently. I do think there's moments that are like aha moments that really inspire people. I think for some reason reinforcement learning, especially deep reinforcement learning, is a really great way to really inspire people and get what the use of neural networks can do. Even though neural networks really are just a part of the deep RL framework, but it's a really nice way to paint the entirety of the picture of a neural network being able to learn from scratch, knowing nothing and explore the world and pick up lessons. I find that a lot of the aha moments happen when you use deep RL to teach people about neural networks, which is counterintuitive. I find a lot of the inspired fire in people's passion, people's eyes, comes from the RL world. Do you find reinforcement learning to be a useful part of the teaching process or no? I still teach reinforcement learning in one of my Stanford classes, and my PhD thesis was on reinforcement learning, so I clearly love the field. I find that if I'm trying to teach students the most useful techniques for them to use today, I end up shrinking the amount of time I talk about reinforcement learning. It's not what's working today. Now our world changes so fast, maybe it'll be totally different in a couple of years. I think we need a couple more things for reinforcement learning to get there. One of my teams is looking to reinforcement learning for some robotic control tasks, so I see the applications. If you look at it as a percentage of all of the impact of the types of things we do, at least today, outside of playing video games and a few other games, the scope... Actually, at NeurIPS, a bunch of us were standing around saying, hey, what's your best example of an actual deploy reinforcement learning application among senior machine learning researchers? Again, there are some emerging ones, but there are not that many great examples. I think you're absolutely right. The sad thing is there hasn't been a big application, impactful real-world application of reinforcement learning. I think its biggest impact to me has been in the toy domain, in the game domain, in the small example. That's what I mean for educational purpose. It seems to be a fun thing to explore neural networks with. But I think from your perspective, and I think that might be the best perspective, is if you're trying to educate with a simple example in order to illustrate how this can actually be grown to scale and have a real-world impact, then perhaps focusing on the fundamentals of supervised learning in the context of a simple dataset, even like an MNIST dataset is the right way, is the right path to take. The amount of fun I've seen people have with reinforcement learning has been great, but not in the applied impact on the real-world setting. It's a trade-off, how much impact you want to have versus how much fun you want to have. That's really cool. I feel like the world actually needs all sorts. Even within machine learning, I feel like deep learning is so exciting, but the AI team shouldn't just use deep learning. I find that my teams use a portfolio of tools. Maybe that's not the exciting thing to say, but some days we use a neural net, some days we use a PCA. Actually, the other day I was sitting down with my team looking at PCA residuals, trying to figure out what's going on with PCA applied to a manufacturing problem. Some days we use a probabilistic graphical model, some days we use a knowledge draft, which is one of the things that has tremendous industry impact, but the amount of chatter about knowledge drafts in academia is really thin compared to the actual real-world impact. I think reinforcement learning should be in that portfolio, and it's about balancing how much we teach all of these things. The world should have diverse skills. It'd be sad if everyone just learned one narrow thing. Yeah, the diverse skills help you discover the right tool for the job. If we could return to maybe talk quickly about the specifics of deeplearning.ai, the deep learning specialization, perhaps. How long does it take to complete the course, would you say? The official length of the deep learning specialization is, I think, 16 weeks, so about four months, but it's go at your own pace. So if you subscribe to the deep learning specialization, there are people that finish it in less than a month by working more intensely and studying more intensely. So it really depends on the individual. When we created the deep learning specialization, we wanted to make it very accessible and very affordable. And with Coursera and deeplearning.ai's education mission, one of the things that's really important to me is that if there's someone for whom paying anything is a financial hardship, then just apply for financial aid and get it for free. If you were to recommend a daily schedule for people in learning, whether it's through the deeplearning.ai specialization or just learning in the world of deep learning, what would you recommend? How do they go about day to day, sort of specific advice about learning, about their journey in the world of deep learning, machine learning? I think getting the habit of learning is key and that means regularity. So for example, we send out our weekly newsletter, The Batch, every Wednesday. So people know it's coming Wednesday, you can spend a little bit of time on Wednesday catching up on the latest news through The Batch on Wednesday. And for myself, I've picked up a habit of spending some time every Saturday and every Sunday reading or studying. So I don't wake up on a Saturday and have to make a decision, do I feel like reading or studying today or not? It's just what I do. The fact it's a habit makes it easier. So I think if someone can get into that habit, it's like we brush our teeth every morning. I don't think about it. If I thought about it, it's a little bit annoying to have to spend two minutes doing that. But it's a habit that it takes no cognitive load, but this would be so much harder if we have to make a decision every morning. So and actually that's the reason why I wear the same thing every day as well. It's just one less decision. I just get up and wear my blue shirt. So I think if you can get that habit, that consistency of studying, then it actually feels easier. So yeah, it's kind of amazing. In my own life, I play guitar every day for, I force myself to at least for five minutes play guitar. It's a ridiculously short period of time. But because I've gotten into that habit, it's incredible what you can accomplish in a period of a year or two years. You can become exceptionally good at certain aspects of a thing by just doing it every day for a very short period of time. It's kind of a miracle that that's how it works. It adds up over time. Yeah. And I think it's often not about the burst of sustained effort and the all-nighters, because you could only do that a limited number of times. It's the sustained effort over a long time. I think reading two research papers is a nice thing to do, but the power is not reading two research papers. It's reading two research papers a week for a year. Then you've read a hundred papers and you actually learn a lot when you read a hundred papers. So regularity and making learning a habit. Do you have general other study tips for particularly deep learning that people should, in their process of learning, is there some kind of recommendations or tips you have as they learn? One thing I still do when I'm trying to study something really deeply is take handwritten notes. It varies. I know there are a lot of people that take the deep learning courses during commutes or something where it may be more awkward to take notes. So I know it may not work for everyone, but when I'm taking courses on Coursera, and I still take some every now and then, the most recent one I took was a course on clinical trials, because I was interested in that. I got out my little Moleskine notebook and I was sitting at my desk just taking down notes of what the instructor was saying. We know that that act of taking notes, preferably handwritten notes, increases retention. So as you're watching the video, just kind of pausing maybe and then taking the basic insights down on paper? So there have been a few studies, if you search online, you find some of these studies that taking handwritten notes, because handwriting is slower, as we were saying just now, it causes you to recode the knowledge in your own words more, and that process of recoding promotes long-term retention. This is as opposed to typing, which is fine. Again, typing is better than nothing, and taking a class and not taking notes is better than not taking any class at all. But comparing handwritten notes and typing, you can usually type faster. For a lot of people, you can handwrite notes, and so when people type, they're more likely to just transcribe verbatim what they heard, and that reduces the amount of recoding, and that actually results in less long-term retention. I don't know what the psychological effect there is, but it's so true. There's something fundamentally different about writing, handwriting. I wonder what that is. I wonder if it is as simple as just the time it takes to write is slower. Yeah, and because you can't write as many words, you have to take what they said and summarize it into fewer words, and that summarization process requires deeper processing of the meaning, which then results in better retention. That's fascinating. Oh, and I've spent, I think, because of Coursera, I've spent so much time studying pedagogy. It's actually one of my passions. I really love learning how to more efficiently help others learn. One of the things I do both when creating videos or when we write the batch is I try to think, is one minute spent with us going to be a more efficient learning experience than one minute spent anywhere else? And we really try to make it time efficient for the learners because everyone's busy. So when we're editing, I often tell my teams, every word needs to fight for its life, and if you can delete a word, let's just delete it and let's not waste the learner's time. So it's so amazing that you think that way because there is millions of people that are impacted by your teaching, and sort of that one minute spent has a ripple effect, right, through years of time, which is fascinating to think about. How does one make a career out of an interest in deep learning? Do you have advice for people? We just talked about sort of the beginning, early steps, but if you want to make it an entire life's journey, or at least a journey of a decade or two, how do you do it? So most important thing is to get started. And I think in the early parts of a career, coursework, like the deep learning specialization, is a very efficient way to master this material. So because instructors, be it me or someone else, or Lawrence Moroney, who teaches our TensorFlow specialization, and other things we're working on, spend effort to try to make it time efficient for you to learn a new concept. So coursework is actually a very efficient way for people to learn concepts in the beginning parts of breaking into a new field. In fact, one thing I see at Stanford, some of my PhD students want to jump into research right away, and I actually tend to say, look, in your first couple of years as a PhD student, spend time taking courses because it lays the foundation. It's fine if you're less productive in your first couple of years. You'll be better off in the long term. Beyond a certain point, there's materials that doesn't exist in courses because it's too cutting edge, the course hasn't been created yet, there's some practical experience that we're not yet that good at teaching in a course. And I think after exhausting the efficient coursework, then most people need to go on to either ideally work on projects, and then maybe also continue their learning by reading blog posts and research papers and things like that. Learning process is really important. And again, I think it's important to start small and just do something. Today you read about deep learning, it feels like, oh, all these people are doing such exciting things. What if I'm not building a neural network that changes the world? Then what's the point? Well, the point is sometimes building that tiny neural network, be it MNIST or upgrade to a fashion MNIST, to whatever, doing your own fun hobby project. That's how you gain the skills to let you do bigger and bigger projects. I find this to be true at the individual level and also at the organizational level. For a company to become good at machine learning, sometimes the right thing to do is not to tackle the giant project, is instead to do the small project that lets the organization learn and then build up from there. But this is true both for individuals and for companies. Taking the first step and then taking small steps is the key. Should students pursue a PhD, do you think? You can do so much. That's one of the fascinating things in machine learning. You can have so much impact without ever getting a PhD. So what are your thoughts? Should people go to grad school? Should people get a PhD? I think that there are multiple good options of which doing a PhD could be one of them. I think that if someone's admitted to a top PhD program at MIT, Stanford, top schools, I think that's a very good experience. Or if someone gets a job at a top organization, at a top AI team, I think that's also a very good experience. There are some things you still need a PhD to do. If someone's aspiration is to be a professor at the top academic university, you just need a PhD to do that. But if it goes to start a company, build a company, do great technical work, I think a PhD is a good experience. But I would look at the different options available to someone. Where are the places where you can get a job? Where are the places where you can get a PhD program and weigh the pros and cons of those? So just to linger on that for a little bit longer, what final dreams and goals do you think people should have? What options should they explore? So you can work in industry, so for a large company, like Google, Facebook, Baidu, all these large companies that already have huge teams of machine learning engineers. You can also do within industry, more research groups, like Google Research, Google Brain. You can also do, like we said, a professor in academia. And what else? Oh, you can build your own company. You can do a startup. Is there anything that stands out between those options? Are they all beautiful, different journeys that people should consider? I think the thing that affects your experience more is less, are you in this company versus that company or academia versus industry? I think the thing that affects your experience most is who are the people you're interacting with in a daily basis. So even if you look at some of the large companies, the experience of individuals in different teams is very different. And what matters most is not the logo above the door when you walk into the giant building every day. What matters the most is who are the 10 people, who are the 30 people you interact with every day? So I actually tend to advise people, if you get a job from a company, ask who is your manager, who are your peers, who are you actually going to talk to? We're all social creatures. We tend to become more like the people around us. And if you're working with great people, you will learn faster. Or if you get admitted, if you get a job at a great company or a great university, maybe the logo you walk in is great, but you're actually stuck in some team doing really work that doesn't excite you, and then that's actually a really bad experience. So this is true both for universities and for large companies. For small companies, you can kind of figure out who you'll be working with quite quickly. And I tend to advise people, if a company refuses to tell you who you will work with, someone will say, oh, join us. There's a rotation system. We'll figure it out. I think that that's a worrying answer because it means you may not get sent to, you may not actually get to a team with great peers and great people to work with. It's actually a really profound advice that we kind of sometimes sweep. We don't consider too rigorously or carefully. The people around you are really often, especially when you accomplish great things, it seems the great things are accomplished because of the people around you. So it's not about whether you learn this thing or that thing, or like you said, the logo that hangs up top. It's the people. It's fascinating. And it's such a hard search process of finding, just like finding the right friends and somebody to get married with and that kind of thing. It's a very hard search. It's a people search problem. Yeah. But I think when someone interviews at a university or the research lab or the large corporation, it's good to insist on just asking who are the people, who is my manager? And if you refuse to tell me, I'm going to think, well, maybe that's because you don't have a good answer. It may not be someone I like. And if you don't particularly connect or something feels off with the people, then don't stick to it. That's a really important signal to consider. And actually, in my Stanford class, CS230, as well as an ACM talk, I think I gave like an hour-long talk on career advice, including on the job search process and some of these. So you can find those videos online. Awesome. I'll point people to them. Beautiful.

https://youtu.be/1k37OcjH7BM

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Carl Hart: Heroin, Cocaine, MDMA, Alcohol & the Role of Drugs in Society | Lex Fridman Podcast #233

The following is a conversation with Carl Hart, Department Chair and Professor of Psychology at Columbia University. He's the author of several books on the topic of drugs, including his most recent called Drug Use for Grown-Ups that challenges us to, quote, use empirical evidence to guide public policy even if it makes us uncomfortable. His research on drugs, including hard drugs like heroin and cocaine, challenges much of what we think we know about drugs and their role in society. His main thesis is that drug addiction has less to do with the drugs themselves and more to do with co-occurring psychiatric disorders, such as depression and schizophrenia, and socioeconomic factors, such as unemployment, underemployment, and resource deprivation within the community. In addition, he believes that we should legalize all drugs so that if people choose to use them, they could do so responsibly and openly and get help if needed in a controlled, safe environment. His ideas are controversial, but are fundamentally grounded in empirical data and rigorous scientific studies. I don't know if his conclusions are right, but they are at least worth thinking about. So I ask that you consider these ideas with an open mind and as always, make sure you exercise your critical thinking skills in making decisions about substances you put in your body. You are a free thinking being, the main character, if you will, the hero in a story that's being written by you. So at the end of the day, you are responsible for the choices you make. So choose wisely. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Carl Hart. I think it is bold and powerful to admit to using in your private life the drugs that you study in your research, including heroin and cocaine. So let me ask, what is the experience of taking heroin like? What happens to the body? What happens to the mind when you take it? Well, you know, I take MDMA, cannabis, and all the rest of these drugs too. I've tried those drugs. The experience in the body and the mind, I don't really know what people want to know in that regard. It's like saying, what is the experience of having an orgasm in the body and the mind? Or some other sort of event that you really enjoy. So I don't really know what people- Is that what poetry is for, for describing these kinds of experiences? I mean, I guess given MDMA, given psilocybin, in the full context of that, maybe it's more useful to say, what are the differences in experiences that your mind goes through? Like chemically, biologically, keeping it strictly to the biology of it versus the full environmental human experience. Yeah, see, this is a mistake that people make all the time. They try to act as if biology is the only determinant of drug effects, and that's just not how it works. You need the environment. You need the cage, as they say. If you don't have the cage, you don't get the full extent of the effects. And so you can take MDMA and have an awful time. You can have a time in which you get paranoid and so forth, and then you can take that drug under the right conditions, and it just be like one of the best moments you've ever had. It certainly enhanced a number of my relationships. But I've also had some times with MDMA that haven't been so lovely, when the people who you are hanging out with, you don't know them, you're distrustful, and all of those kinds of things. So it's important to put context in it. Now, we can talk about drugs at a biochemical level, at a biological level, and we kind of do that in this country with this fascination with neuroscience. And that's an inappropriate kind of fascination in the way we talk about it. So we can talk about opioids, and then we can talk about endogenous opioid system in the brain. We can talk about dopamine and other sort of monoamine transmitters and what opioids are doing to them. And we can do the same thing with MDMA. And we won't be any closer to understanding the sort of experience that is induced by these drugs. Certainly the experience that we all seek, you know what I'm saying? So getting a positive experience or getting a negative experience is strongly defined by the environment. Strongly dependent upon the environment. But the environment is a very, it's a short word that can describe a lot of things. So would you say the environment is important, or the people, where you are currently in your life, or is it also dependent on the full trajectory of your psychology, of your life experiences, of your parents, of the people you came up with, of the trauma you've experienced, of the hopes and dreams that were crushed or not, or the opposite, or the success levels, or all those things? Like what are the interesting sort of landscape of experiences that contribute to how you actually feel when you take a drug? Right on. So all of those things are important. But you know, like if someone had trauma in childhood and they did the work and they dealt with it, that's not so important in this case. But if they didn't deal with it and that trauma is being triggered in that event, in that moment, then it's important. But let's just take somebody like me. I'm 54 years old. I'll be 55 this month, actually. And you know, I've done a lot of work in terms of figuring out who I am. And I'm comfortable with myself. And I know how to set limits for whatever it is I'm doing. And so I know I need to work out. I know I need to eat well. I know I need to sleep well. I know I need to be in an environment with people within my trust. And then if all of those things are met, oh, it's likely to be a good time. You know what I'm saying? But if I haven't slept, if I haven't worked out, if I don't feel good, it won't be a good time. But I try and be responsible and take care of my eating habits, sleeping habits, make sure my responsibilities are taken care of. And so when I'm in that moment, I just enjoy that moment. I'm there. I'm not thinking about a bill that I didn't pay. I'm not thinking about, oh, I forgot to do this for my kid. I'm not thinking about that because all of those things are taken care of. If they're not taken care of, it will impact the experience. And it may negatively impact the experience. Well, that is the counterintuitive, even controversial finding from your recent book. So we should kind of, I know it seems obvious to you, but I think a lot of people hearing this would think it's quite non-obvious. So in your new book, Drug Use for Grownups, you write for the finding section, I discovered that the predominant effects produced by the drugs discussed in this book are positive. It didn't matter whether the drug in question was cannabis, cocaine, heroin, methamphetamine, or psilocybin. Overwhelmingly, consumers express feeling more altruistic, empathetic, euphoric, focused, grateful, and tranquil. They also experienced enhanced social interactions that create a sense of purpose and meaning and increased sexual intimacy and performance. This constellation of findings challenged my original beliefs about drugs and their effects. I had been indoctrinated to be biased toward the negative effects of drug use, but over the past two plus decades, I had gained a deeper, more nuanced understanding. These words are very counterintuitive to a lot of people. I think like you also mentioned in the book and elsewhere, people have come around to maybe psilocybin being one such drug, maybe cannabis being one such drug, but you also mentioned other drugs like cocaine, heroin, methamphetamine. Can you just linger on this point? How do we get the positive effects of those drugs and why in the media and the general conception we have of these drugs is that they were going to make a bad life worse or ruin a good life? Well, so your first question was how do we harness the positive effects? How do we increase the likelihood of getting the positive effects? Again, like I said, we want to make sure that people are responsible and they've handled their responsibilities, make sure they eat well, sleep well, exercise, all of those sorts of things play an important role. And also if they know exactly what they're getting and then they're not paranoid about, oh, it's something contaminated in some adulterant in my drug. So you want to make sure you know exactly what you have. Once you satisfy those kinds of things, you understand the dose and potency, you understand all of those things, to decrease any sort of anxiety you might have about the substance itself, it increases the likelihood that you will have a better time. So anxiety is the big one. You need to remove the anxiety. Anxiety is critical. It's huge. Many of the negative effects that we see with drugs have to do with anxiety and not necessarily anxiety because the drug induced it. It's the anxiety that the situation induced a lot of times. And then you ask like, well, why does this sound counterintuitive? Why does the media report differently? Well, because there's money in reporting the negative effects almost exclusively. Think about writing a newspaper article. It's really easy to get the population all ginned up about something like an opioid crisis, overdoses, you don't even have to tell people how to keep people safe if you're talking about overdose. You don't even have to say why people are dying from overdoses. Like overdoses in our country happen largely because people get contaminated drug, because people are combining sedatives and they don't know that this enhances the respiratory depressing effects of drugs. They don't know. But when you read these newspaper articles, they don't say this. They don't say how to keep people safe. All they do is frighten the population. There's money in that. And then we think about people who write TV shows, the people who write movies. Most of the stuff written about drugs is just bullshit. I think about, I love going to watch comedians and the comedians, when they talk about drugs, again, most of the things that they say about drugs is bullshit. I mean, you can say the stupidest things about drugs and be believed. You can write a movie and you don't even have to develop your characters if you throw drugs into the mix. You say, oh, he's a drug dealer. You don't have to say anything about that person's background or about that person being developed as a character, because the population thinks they know. And the writer is lazy and does not do any sort of development. Just think about any... Let's think about The Sopranos, for example. They have a new program coming out. So let's think about them for a second. The Sopranos is a show in which the lead character, Tony, kills people for a living. That's what he does, right? This character actually made us sympathetic for him when he is besmirching and denigrating his nephew, Christopher, for using a drug. And we feel sympathy for Tony, the character, who just killed somebody, who is a horrible person, but being a drug user is a worse person. That's what the show wants us to believe. Tony's a racist, a murderer, all of these things, but we feel sympathy for him. But we don't feel sympathy for anyone who uses drugs. That's some crazy shit. I mean, and the American public buys into it. That's wild to me, that we all bought into this crap. And that's what we do in damn near everything that's in film, on television. And it's like, what's wrong with you people? So why are there not more stories of grownups using drugs? The full spectrum of drugs that we're talking about? Why isn't there? So we talked offline about Joe Rogan. He's somebody who started smoking weed later in life, which is an interesting story. Like when he's already very successful and he has a very interesting way of describing his experience with weed, that it was like enhancing his productivity. Actually, I think he says like it increases anxiety a little bit in a way that was productive, like paranoia, not anxiety. And so that's an interesting story of an adult talking about the use of weed for productivity purposes. But you don't get those stories very often. Why? I think fear. People are afraid that they will be belittled, dismissed, all of these things as a drug addict or some negative thing. But cannabis is lightweight. Come on. You can emit cannabis these days. And the fact that I don't know when Joe started, but if he did start later in life, that's cool. I mean, you are mature, developed. You have developed some responsibility skills, responsibility skills, all of these kinds of things. This is a good thing. You don't want people to engage in any kind of behaviors when they're young and immature that might put them in harm's way. And so we want people to be developed at least. I mean, whether it's being in a relationship with a partner or whether it's driving an automobile, all of these things that can be potentially harmful, but extremely beneficial if you are responsible enough to handle them. You want people to be mature. So that's a good thing. So how are you supposed to, like somebody like me, somebody like Joe, how are you supposed to understand what the dangers are, what the negative effects are? So you said automobile, relationships. I think I have a reasonably, it's crappy, but reasonable understanding of all the troubles I can get with in relationships and what things to avoid. Same thing with driving a car. I have no idea. I'm in the dark in terms of what are the things to be careful about, what to avoid with drug use when we're talking about the heavy drugs. Have you ever drank alcohol? Yes. I'm Russian. I know. I drank a lot, but I understand that because culture came up. I was taught a lot of like, this is what you don't do and this is what you do. This is when you drink a lot. I mean, you see the effects, you see the, there's a lot of negative examples, there's positive examples of social stimulant. There's examples of great artists using alcohol to sort of, I don't know, to help be the catalyst for that magic moment for all of that. I have some examples now, especially in America, the same with weed. More and more, you're starting to get a lot of stories on psychedelics of different kinds. There's psilocybin where you have mushrooms or even MDMA used sort of positively. There's kind of like negative stories from the past about acid, about LSD being used ultimately for productive ends, but it destroyed the person. That's kind of how the story goes. It was like a trade-off. You take, it's like, what is it? Robert Johnson sold his soul to the devil to learn guitar. Like it's a trade-off. You could take the drug, you're going to create some good stuff, but you have to pay for it. Those are the stories. That's some bullshit we tell children. Come on. That's exactly right. You're exactly right. These fairy tales, these cautionary tales that we tell people, we have to grow up. That's what the book is about, drug use for grownups. We tell people, Pinocchio, if you lie, your nose grow. Who believes that? Who believes that there are fairy tales? But that's exactly what these stories are. They're in the same vein as those kind of stories, as Pinocchio. Like you said, when you were learning about alcohol, you were told what to do, what not to do, so forth. The same can be true with MDMA, with cocaine, with heroin. The same is true because there are some times when there are some potential dangers that you should avoid. I wrote about some of them, certainly in my work, just throughout all of my writings. I talk about those kinds of things, and other people talk about these things. The problem is that we're getting our education from bullshit sources, from people who believe in this kind of Pinocchio thing, and it just does not fit with the evidence. The evidence we all publish in the scientific literature, all these things that I'm saying, it's there in the literature. I mean, at a place like Columbia, we give these drugs thousands of doses every year. Do you think we would be doing this, and we do this with research grants that's funded by the public, taxpayers' dollars. Do you think we would be allowed to do this if these drugs were so dangerous? It's just nonsense. I mean, and the drugs we're talking about, they are all approved for medical use somewhere in the world. And the studies you conduct are basically asking what kinds of questions. So you take the full range of drugs you're talking about, from marijuana to psilocybin to MDMA to cocaine and heroin. What is the study looking at? Like, what the actual experience, what the positive and negative effects of the experience on the drug are in controlled conditions? Yeah, so we did these kind of experiments with alcohol, nicotine, all these drugs, in order to have an empirical database to tell people exactly what these drugs do and what they don't do. The conditions under which the drugs will produce positive effects, the conditions under which the drugs were more likely to produce negative effects, all of this information is important for a society to know. And we do know, and that's why we're collecting the data. We're collecting the data to help us with treatment if someone is having problems with these data. Hopefully we'll understand more about how to help them deal with their problems based on some of the research that we're doing. So what kind of negative effects are we looking out for? What are the properties of drugs we should be careful about? Is it addictive properties? How addictive it is? How destructive or painful, whatever, the withdrawal processes? What kind of things are we looking out for? Yeah, those are certain kind of questions we certainly have asked because something like crack cocaine versus alcohol or heroin when it comes to withdrawal or physical dependence. Cocaine has a very limited sort of withdrawal symptoms. I mean, it's hard to see. Same is true with methamphetamine. But with heroin, you certainly can see a withdrawal syndrome that's unpleasant. But with alcohol, that withdrawal can actually kill you. So heroin is unpleasant and not lovely. But with alcohol withdrawal, that's the one that's the most dangerous. I mean, all of these kind of questions we want to know answers to. And so when we think about heroin or some other drugs and you say like, what kind of negative effects? Negative effects, we don't talk about much in the society. The main thing that really concerns me about like heroin use really is constipation. So if people are using heroin on a regular basis and then they have a sort of slowing of their gut motility, they're likely to increase constipation. And that's not good. I mean, for your general health. But we never talk about that in this society. And that's probably the most important thing aside from the fact that people get contaminated street drugs and that sort of stuff and increase the likelihood of maybe dying from some contaminant or people who are inexperienced and they're mixing heroin with other sedatives. That's not good. But the constipation is a huge one. And then other sort of drugs, negative effects, like the amphetamines, all of the amphetamines, they disrupt sleep, food intake. All of these things are so critical for sustaining human life. But we never talk about that because it's not as sexy as this nonsense that people write about like addiction. Addiction has almost nothing to do with the drugs themselves. And I make that comment because the vast majority of users for any drug never become addicted. And so if the vast majority of users don't become addicted, then you have to move beyond the drug when you're talking about the phenomena interest, in this case, addiction. And so when we think about addiction, it has much more to do with our psychosocial environment than the drug itself. But that's not sexy. So addiction is even a property of the environment, not a property, a result of the environment. It certainly can be. There are people who are suffering from a co-occurring mental illness like depression, anxiety. I mean, that's within the person, of course, and that increases the likelihood for addiction. So that's not so much the environment, but there are people who, for example, they have chronic, unrealistic expectations heaped on them. And those people are more likely to have some problems with drugs. There are people who are just immature, not developed, haven't developed responsibility skills. They are likely to have some problems if they engage in some of these behaviors. There are people who lost their jobs, COVID, factories went away, a wide range of things. And those people used to have standing in their community. Now they have none. Those people might be susceptible to having a drug-related problem if they indulge. All of these kind of issues are far more important than the drug itself. And so they could seek escape in a particular drug. I mean, there is a biochemical thing to each of these drugs and some pull you in harder than others when you need the escape, right, when you're not doing well in life. What evidence you have for that? I don't. Yeah, because there is none. There is absolutely none. I mean, people say stuff like that, and that's the problem. That's precisely the problem. See, I'm operating from limited personal evidence. Well, this is a problem though, but we have a scientific database. We don't need personal evidence for this. In my book, I try to go through some of the science so people could understand. It's like when you have a math problem, you don't want people saying, well, you know, I feel like this. Fuck what you feel. What does the data say? So one of the problems with the data, so one data is there's the studies that you're doing. This is excellent research work, but there's some of the drugs are illegal. Yes. And some are legal. So you have just, it's unfortunate that some of the drugs are illegal or whatever you believe, but there's not enough of a data set of public and the open use. That's like you had in the wild data set. It'd be nice to do thousands of people and see from all the different kinds of environments and all that kind of stuff to get an understanding. I think we have a substantial database, but people just ignore it. Got it. That said, let me ask you the question of legalization. So should, in your view, all drugs be legalized? The drugs that people seek certainly should be legally regulated and available to adults. So when I say the drugs people seek like cannabis, MDMA, cocaine, heroin, those drugs certainly should be available. And some of the psychedelics that people seek. Now, the thing about it is that some people think that, oh, it will be a free fall. These drugs are available to everyone. That's not true. I mean, it will be, there'll be age requirements and maybe other requirements, but they should be available. And we should also do like what we do with alcohol. We can put enough alcohol in a bottle to kill you, but we don't. So we regulate it such that the amount that's in the bottle enhances the safety and minimizes the potential harms. We can do the same thing with these other drugs. And we can also say, okay, we won't be selling intravenous preparations of any of these drugs. The drugs that the routes of administration will be oral and I don't know, let's say intranasal. Again, routes of administration, the dose that you have in each unit, all can minimize harm based on how you do these things. And we can do that. We have the technology, we have the know-how. You're actually making me think about alcohol a little bit. So if I were, say the drugs become legalized in the way you're describing and me, Lex, wanted to, as an adult, explore some of these drugs, what are some procedures do you think for sort of safe, positive exploration of those drugs? The reason I say I'm thinking about alcohol, because I don't think besides not putting enough alcohol in a bottle to kill you, I don't think anyone ever gave me specific instructions. I think it's kind of word of mouth and examples of people doing the wrong thing. You kind of get it through osmosis that way. Is that basically what we would do? This kind of free exploration of use? No, we have to change our education about these things. I mean, let's just take a drug like cocaine. Cocaine is a stimulant. You want to make sure people understand that they shouldn't be taking cocaine near bedtime. They need to get a certain amount of hours of sleep and they need to get up in the morning. Cocaine probably isn't a drug for you at night. Certainly not. Certainly not amphetamines at night for most people. And also if you want to make sure that you, they need to understand that cocaine can also disrupt your food intake. Not as much as the amphetamines, but all of these kinds of things people need to know so they can have proper nutrition and they can time their drug use around these other important functions that sustain human life. So we have to make sure that we educate people. We can't just throw people in a while. That's stupid. I gotta tell you, I mean, for me, even given your book and for people listening to this, it's still tough to hear that the thing we should be concerned about with cocaine is the same as with caffeine. Don't take it before bed. And the thing we should be concerned with heroin is constipation. Okay. But the questions I keep wanting to ask you, I should be asking the same things of alcohol. But when you're not doing well psychologically, in the ways you described, when the environment is not right, there's some aspect in which saying that drugs can be used responsibly and effectively and mostly positive can give those folks a pass to use it instead of working on themselves and fixing their environment first. I don't know. What do you want me to say to that? I mean, they have access to alcohol. They have access to the, you know, we live in a world where we have a lot of people that have access to the, you know, we live in this country called the United States where our Declaration of Independence says that we are free to live like we want to live so long as we don't disrupt other people from doing the same. But it's remarkable to me how we try to control the behaviors of other people. That's just remarkable. Yeah. And that's partially what your book is about. I mean, it's not just about drugs, it's about freedom. That's the bigger issue that we can't get to. It's like this issue of freedom. And freedom comes with a tremendous amount of responsibility. I am responsible for my neighbors, my brothers. I mean, I can't impede their freedoms. Like some people think that their freedom supersedes everybody else's freedoms. No. And that's what I'm trying to remind people in this book. I am responsible to you as a citizen. And we're in this together. And I tried to make that point in the book. And people have conveniently ignored things like that. Do you think the war on drugs has done more positive or negative for the world? Depends on which world you live in. The war on drugs has been hugely beneficial to law enforcement, to the media, to people who make bullshit TV shows, The Sopranos, The Wire, all of those shows, they benefit from this kind of nonsense. Who else have benefited? People who provide treatment, many of them benefit from the war on drugs. The folks who do urine testing for drugs, they've all benefited. They're making mad money. People who run prisons, the phone companies who charge the prisoners, the people who run the hotels that are around the prisons where people's family have to come and stay, the restaurants, they are making out like bandits. But many of us are getting screwed as a society in general. We're getting screwed. But there are people who are just benefiting handsomely. That's why it continues. Politicians benefit. I mean, whether you're Democrat or Republican, you have the same stance on drugs anyway. So they all benefit from this. So many questions I want to ask you, because you're challenging a lot of beliefs that people have about drugs, about society in general. So it's difficult for me to ask the right questions here. But if you were with a sort of a snap of a finger, change the world, what, from a policy perspective, would you, and from just a, I don't know, a human to human perspective, what would you like to see in the United States of America in terms of that fixes some of the problems we're discussing here? First of all, I would not, we wouldn't be arresting anybody for drugs anymore. That would go away. Yeah. The folks who are in prison for drugs, that would go away. Their records would be a sponge. That would just go away. And then we work on a system to make sure that responsible adults can legally obtain these substances. And we'll have a corresponding educational system to teach people how to do this. That's where I would start initially. Yeah, the arresting for drug use or anything drug-related is absurd, especially in the context of how destructive alcohol is and tobacco. Alcohol can be destructive to some people, but alcohol also is a hugely beneficial drug, to be honest, which I couldn't have gotten through many of the sort of receptions and functions I had to go through as the chair of the department without alcohol. Yeah, you have a line I really liked. The vast amount of predictably favorable drug effects intrigued me so much so that I expanded my own drug use to take advantage of the wide array of beneficial outcomes specific drugs can offer. The part that entertained me was this, to put this in personal terms, my position as department chairman from 2016 to 2019 was far more detrimental to my health than my drug use ever was. I mean, there is a standard we're treating drugs, certain kinds of drugs that's completely different than the standard we're treating everything else in our lives. Yeah, I mean, it's almost difficult to snap out of it as I'm listening to you and reading your work. It's difficult because it's like, why is everybody living this idea that certain drugs are so horribly destructive and others are not? And we just kind of fix that idea. And then there's this narrative. I hate to be so cynical to think that there is just a system that just propagates narratives. I always kind of think that truth wins out. Truth is the best narrative. I believe that too. Obviously, that's why I'm out here and subjecting myself to this sort of criticism and so forth, because I believe that truth ultimately wins out. But I might be wrong. But I have to live my life like it's true. Otherwise, then I have no hope. Then why be here? Well, if you can steel man or at least show respect to criticisms, you've, I'm sure, received quite a bit of criticism for your work. I've heard quite a bit of BS criticism, sort of ignorant stuff that don't actually pay attention to your work. But is there some serious, like, is there some pushback that makes you think twice? People say, like, I'm presenting a too rosy picture of drugs. You know, like, I don't want to do that. I don't want people to think that I'm not aware of the potential negative effects of any activity, including drug use. And so I do acknowledge that there are potential harms associated with drugs. I acknowledge that in the book. But the fact remains, the beneficial effects far outweigh the potential harmful effects. And we have technology, information to help people to minimize the likelihood of those negative effects. But this sort of approach that we have, where we say we're only exclusively presenting the harmful effects, and that should make people, make people, keep people safe, I just have a problem with that. But I certainly, I take the point that people say there are negative effects. Absolutely. I absolutely agree. What do you, if I can just talk about specific drugs, what's the difference between opioids and benzos, for example? Specifically, I mean, these are drugs that you often read about being misused at scale. I mean, the misuse is the problem, right? No matter what the drug is. And that's actually what you're pushing for is education, and it should be legal, and should be so people should know what's the difference between proper use, positive use, and misuse. I mean, one public figure who has been going through this is Jordan Peterson. He's been public about his struggle of getting off benzos, the withdrawal he's going through. I mean, what are your thoughts about the misuse of benzos or opioids and so on, the epidemic that people talk about? Yeah, I don't know Jordan's specific case, but certainly with benzodiazepines in general, we talked about withdrawal earlier. When I said that with alcohol withdrawal, you can die. So benzos and alcohol, they're closely related. So benzo withdrawal too can kill you, just like alcohol. So when we think about the effects that benzodiazepines produce, think about the effects that alcohol produce. They're comparable or similar. And so I know that it's a difficult one to wean yourself off if you develop the dependence, but we have protocols for that, and I hope he's okay. It's interesting you say we have protocols for that, but from my understanding was that the protocols aren't standardized. It feels like a lot of doctors aren't as helpful as they could be in this process. It's a bit of a mess. Certainly with withdrawal, they're more standardized than anything. So if someone is going through alcohol withdrawal, there is a standard protocol that most physicians in this business, they follow. The same is true with benzo withdrawal. But the thing where it gets murky is when they're treating addiction itself. So when you're thinking about the substance use disorder in the DSM, not just withdrawal, but the entire addiction, that's where you have this sort of divergence or diversity in terms of approaches, and many of those approaches are rubbish. Can you just elaborate technically what the term addiction means that you're referring to? When I use the term addiction, I'm referring to the Diagnostic Statistical Manual of the American Psychiatric Association, number five now, the DSM-5. That's never been wrong, right? I'm just kidding. No, you're absolutely right. That point is well taken. And your point is that their definition of substance use disorder, that's addiction, that's what I'm talking about. But that definition continues to evolve. And so you're right, they still are working it out. We're getting new information from scientific studies and so forth. And so it's supposed to be incorporated into the DSM. But there are some problems with the DSM, like for example, they also have this sort of once an addict, always an addict thing, and there's no evidence to support that. But it's evolving. And it's the definition that people in science and medicine use. And so we all know we're talking about the same language when we call someone a substance use disorder patient or someone who meets criteria for addiction. We all are speaking the same language. We're not saying that simply because this person use heroin, they are an addict. That's not what we're saying. You have to meet these criteria where you have disruptions in your psychosocial functioning, that's one. And two, you, the person, are distressed by these disruptions. So people have to meet those two basic criteria before we say they are addicted. So once an addict, always an addict, this idea. So I've, I mean, some of it is always mapped to the person, right? But just the people I've interacted with who have struggled with alcohol addiction, I don't know what the proper term is. It seems like with Alcohol Anonymous, the process of putting that addiction behind you is a very, very long process. It's surprisingly long to me. That almost seems like a whole life. Like, it's not always an addict, but it takes decades. It seems like. What is that? What can you maybe just, from your understanding as a scientist, from your understanding as a human who studies human nature, why does it take so long to treat, to deal with that addiction? Well, you cited Alcohol Anonymous, right? And so I don't think of Alcohol Anonymous as like a treatment that I would send any relative to, like for a drug-related problem. I think Alcohol Anonymous AA is really good for social interactions, making sure people have a social group and they have peers. I mean, that's a good thing. We all need that social interaction, but I don't think they know much about drugs. That's not, it's like saying, well, my uncle broke his knee and he has this support group and they said this, said this, and then we follow that. That doesn't make any sense. But in our society, judges even sentence people to go to AA. Are you kidding me? But that's the kind of thing that has been allowed to happen in this society because we think of drugs as this moral failing, or drug addiction as this moral failing. And any idiot can provide treatment. And no disrespect to AA because I think what they do is a lot more than what some people do because at least they have this social, these social interactions, you have a social group. That's better than what a lot of these other idiots out here do. Well, and that social support group, unrelated to the drug, it helps cure some of the environment issues you might be in. Absolutely. That's the whole point. Absolutely. So we kind of coupled the drug to the environment, but the reality is, as you argue, most of the problems come from the environment. Certainly with people who are experiencing drug-related problem with most of the people, not all, but most. There are differences like that psychedelics and like psilocybin has versus alcohol. I personally think, I've enjoyed both experiences in different ways. Is it possible, or are we getting into the realm of poetry to describe the benefits, how the different drugs alter the mind and the places it can take you that produce a positive experience? Yeah. No, it's very real. Some drugs take people in places that other drugs can't, and that's very real. I have friends, some of them you know, they, for example, say that they've never had an experience like the one they had with ayahuasca, and they've done a number of sort of things. But they did the ayahuasca in a setting with a shaman and this group, and they felt like they actually began to heal or solve some problems that they were trying to solve for some years. And that's great. That's great for them. And nothing else does it for them like that. And that's absolutely fantastic. All I argue is that if that kind of thing happens for you with ayahuasca, with psilocybin, with some other psychedelic, why isn't it possible that heroin does that for someone or cocaine does that for someone else, or MDMA does it for someone? That's it. That's interesting to imagine like a shaman for heroin. Like why not? And or cocaine, you said creating an environment for yourself for use of these different substances. And that environment has a very strong impact on the actual experience that you have. But I mean, so cocaine is an upper and then heroin? Yeah, the way we define drugs like uppers and downers, that's a really kind of inappropriate way, but it's a quick way. So we certainly say cocaine is an upper or stimulant. But it depends on the activity of the person before they take the drug. Say like if you're like really active before taking a drug like cocaine, it might actually calm you. So it all depends on the activity of the person before they take the drug. I remember, I don't know if you know Matthew Johnson is, of course, he did all these studies on or I remember just reading a paper. I didn't get a chance to talk with him much about it, but it was about condom use and cocaine and then, you know, what like the doses and whether people are more or less likely, like the unsafe thing there is the using or not using or not using, I guess, condoms during sexual intercourse. I don't know. I just I love that these drugs that have connotation probably because of Hollywood, negative connotations are actually being studied by science and then the actual impact they have and what are the negative effects. Again, in those studies often the positive effects are difficult to quantify, I think. Maybe, I guess, you can from self-report and so on. Positive effects are not difficult to quantify. You ask people about their euphoria, you can see how well people are getting along. Like in our studies, we have people sometimes in groups and you see how well they get along on the various drug conditions or placebo conditions. It's really, it's not that difficult. And then you can see these amazing studies with like Rick Doblin, like looking at MDMA and combined with therapy, like how you can overcome certain PTSD things or depression and so on. Yeah, it's really interesting. It's really interesting. I gotta ask you because you mentioned The Wire. Do you think The Wire, you think movies like Trainspotting, do you think they're ultimately destructive? Because, okay, yes, they celebrate murder, right? The Godfather a little bit. Yeah. But another one, I mean, it's like these racist ass motherfuckers and they also are killing people but yet they say, we don't do drugs. What kind of shit is that? I mean, people who are doing drugs, psilocybin or whatever, the thing is we're trying to be better people and trying to make our society better and you're killing people and you are denigrating people for using drugs. Are you fucking kidding me? And we let them get away with that as a society. Do you see those movies, I apologize if I'm not sufficiently informed, you see them as denigrating drugs? Of course. I mean, The Godfather. Yes, that's right. That's a good example. The Godfather, Sopranos is all about that. I mean, Christopher is using heroin in the Sopranos and they have an intervention in one season and they are denigrating him. Are you kidding me? You just cut somebody's head off. Yeah. But to be fair, they were denigrating, I think, all drugs. And then they're drinking alcohol in the Butterbean. Yeah. Come on. First of all, they're killing people. They don't have any space, none, to denigrate somebody who's just trying to alter their consciousness. Are you kidding me? And not bothering anyone else. But there's a lot of other mob movies that Scarface celebrates the murder and the drugs equally. So, I mean, it celebrates all of the, not just drugs or so on. It's street. All of those movies. I loved all those movies. I'm from Miami. I loved Scarface. I even liked the Sopranos that I started looking at that shit with a critical eye and see what it's doing. But Scarface is dependent upon the American viewer having a certain view of people who deal in drugs. And that view is that these people are animals, basically. And in the end, the animal kills himself with too much cocaine and he was high, and that's what they show. And so it's like, what the fuck? So it's leveraging, it's playing into not the better angels of our nature. The question- Don't take away these great movies from me. But it's true. You have to think about them critically in this context. Wait, wait, wait, wait, wait. I like these movies. It's not a matter of taking away. It's a matter of making the writers be more honest to the reality. That's it. That's true. That's really true. And the writers, the people, the culture, all of it. I mean, they write these things. I just think about some hip hop artists, they say, this is real. This is my experience and so forth. And that's how these movie writers, they write this bullshit and then say, well, this is real. Anyway, I get so upset talking about it because I know the harm it's doing. And I know those kind of movies are the reason that we have this war on drugs. And all of these people are going to jail because of those kind of movies. In the epilogue of your book, you quote James Baldwin, you cannot know what you will discover on the journey, what you will do with what you find, or what you find will do to you. So let me ask, how has drug use or the study of drugs change you as a human being? It has helped me think about other people's experience, right? So how we're all connected, like going to Northern Ireland. I don't know if you know much about the situation with the troubles and what those people went through. And so I see people there, Northern Ireland, by the way, is all white. And you see those people there suffering for the same reasons that people in Appalachia are suffering for. Neglected by politicians who told them lies about drugs and not dealing with the real problems, like West Virginia, for example. Their water's polluted, the factories have gone away, people are desperate, and they're blaming drugs. Are you kidding me? So the politicians don't have to bring back the jobs, so we don't have to really make sure they have clean drinking water, things of that nature. And so those people are connected to the people in Northern Ireland. They're connected to the people in Brownsville. They're connected to the people in other places in the United States for the same reason. They're connected to the people in Sao Paulo, Brazil. Same thing. People are catching hell for the same reason in the Philippines for the same reason. And that's why I feel so strongly about this thing, because I know there are people getting paid and their paycheck is predicated on subjugating and the suffering of those other people. So when we hear about the destructive effects of drugs, it's essentially a scapegoat for the failures of leaders and politicians to help alleviate the suffering of people in those communities. Absolutely. It's so easy to say, I'm going to rid your community of drugs. I'm going to put more cops on the street. If you want a problem not to be solved, just give it to the military or the cops. You had a tough childhood growing up in Miami, like you said. What memories, memory stands out in particular that was formative in helping make you the man you are? Make you the man you are. That's so hard to say. My grandmother was really important. So maybe just her trying to make sure that I think critically, I guess that's the biggest one. So you moved in with her, your parents split. Six, seven, yeah. What have you learned about life from her? Be self-sufficient, be critical and keep your eyes open and watch out for the okey-doke. And that's what this whole drug thing is about. It's the okey-doke. It really boils down to just simple thing. We're all similar in that we're all just trying to live our life, trying to take care of our kids. We want the best for our kids, all of us. But yet somehow we've been made to believe that we're different in that way. But fundamentally, we're all the same. So when people are seeking to feel pleasure, to feel better, why don't we celebrate that? Instead, we denigrate people for that. I mean, if I feel better, I'm more likely to treat you well. I gotta say still though, you're going against the grain and you're a Columbia. It takes a lot of guts to sort of speak out about these ideas so boldly. I don't know how to ask this question. Where do you find the guts? Because it's also perhaps inspirational to others in different disciplines that are sort of taken on the conventional wisdom of the day and challenging it. What does it take to do that? What advice would you give to others like you, kind of a little bit afraid to do so? Once you know, you cannot not know, as they say. And so I have to look in the mirror. And then looking in the mirror, I have to face myself. Have I lived honestly? And if I can't face myself, then what am I doing here? That's how I see it. One of the things that people don't really talk about with drugs and people who die from some drug-related death. And I've been thinking about this a whole lot over the past couple of years. It's like some of these drugs can take you to a place where you feel so optimistic and positive about humans, our fellow humans. And you want to do your best to contribute because you know the possibilities of what we can be as a society. And then you come up with resistance. And like you say, there's a lot of resistance and people just have a hard time. And so if you know humans can be better and they refuse to be better, why be here as someone who knows that we can do this better? I certainly don't want to do it the way we're doing it. So you kind of see drugs as mechanisms for potentially elevating the human spirit, sort of making people feel better. So you want to communicate that message. So it's that plus the fact that drugs are used as a scapegoat to not alleviate the suffering of certain communities. So those two things come together. One of the sort of main points of the book too was to try and get people to understand the possibilities that we could have if we imagine we could have if we embraced certain drug use. If we allowed adults to do this sort of thing. Relationships can be better. A wide range of beneficial effects. People would be or can learn to be more magnanimous. All of these pro-social things that we say we value. In your previous book, High Price, you talk about rap and DJing, chapter five. There's a nice picture of you DJing from 1983. So let me ask, who in your view, this is the toughest question of this interview, is the greatest hip hop artist of all time? Maybe give some candidates. Oh wow, who is the greatest hip hop artist? I don't know if I'm qualified to make that bet, because you know, I have to go back to like Gil Scott Heron. People think of him as one of the fathers of hip hop. That's my all time favorite. People like Chuck D from Public Enemy. Some of the things that they were doing, I was really digging. But even though I was digging Public Enemy, but even they got it wrong on drugs. Even Gil Scott Heron got it wrong on drugs. But they were doing so much other good stuff. It helped me to develop as a person. And so I think like my son is a hip hop artist now. I think those folks who are in the game now, they might be, they are a lot more qualified to talk about who's the greatest hip hop artist. I'm not qualified. The evolution, I mean, have you tracked the evolution from sort of the 90s with Wu-Tang and Tupac and Biggie and then to what we have today? So there's just been a crazy amount of progress. It's like almost difficult to track. Yeah. I mean, I really love what they're doing. I like what they, except the part where they get over 40 and they become fucking cops on TV. I mean, other than that, I dig what- Yeah, what's that about? Yeah, I don't understand that, but that's what they do. Again, this sort of glorification of cops, that's dangerous for a society. And those cats who do that kind of thing, I have a problem with that. Is it all sort of to push back a little bit, because I come from the Soviet Union where there's a huge amount of corruption. And when I see what's going on with cops in this country, there's a lot of proper criticism you can apply, but like relative to other places, this is, well, in so many ways, this country is incredible. Is your criticism towards cops or towards what cops are asked to do? Yeah, towards what cops are asked to do. Cops provide the shield for politicians and those in power. Absolutely, because I was in the military. I spent four years in the military and I did what I was told to do. And I was ignorant and thought I was doing the right thing. And I did what I was told to do. And so just like these guys are doing what they're told to do. But no, my real beef is with the power structure, the folks who are telling them what to do. And also the folks who go play cops on television. That imagery, that sort of glorifying cops, that's a problem in a democracy. Yeah, all sides of the glorification of the drug war is a problem. Yeah. If I can just linger on a little longer in terms of the effects of drugs on the positive, like mind expanding components of it. What have mind altering drugs teach you about the human mind? Sort of from a neuroscience, not even like a biochemical, but just like the human mind is amazing, right? The places it can go. Are there some insights you've learned from studying drugs about the mind? Yeah. Can I start from a neurochemical perspective first and then we'll go larger? Just from a neurochemical perspective. I mean, everything I know about the brain, I learned through drugs, because of my interest in drugs. So I learned a lot about dopamine neurons in certain regions of the brain, about neuro endorphin neurons and a wide range of other sort of how our neural transmission happened because of drugs. And so that's a really valuable tool lessons for me. But then when we think that we move out a bit and we think more globally, what have I learned in terms of the mind from drugs? I have really learned how to be more forgiving of people and myself and tolerant, more tolerant of people and certainly learned a lot more about empathy as a result of drug use. And like I said earlier, I'm learning what we can be as a species and it's quite incredible, but because of drugs. But because of drugs. Yeah, there's a certain property of drugs in different ways. They take you out of your body, like they help you evaluate yourself from like a third person perspective. It's almost like you have a consciousness in here and you get to step outside of it a little bit. I mean, that's kind of what meditation does to all of these processes. That's a hell of a good workout does to it makes you evaluate yourself and that somehow that allows you to be forgiving to yourself and forgiving to others. So empathize, it trains that part of your brain. So stepping outside of yourself, not taking yourself too seriously, that process and different drugs do that in different ways. Obviously, I don't know from personal experience on some of them, but I'm now curious, it's unfortunate that the Hollywood and different stories we have demonize certain drugs and sort of basically, I don't know, make it difficult for people like me to explore those ideas. But then I'm really thankful for people like you who are pushing the science forward and are unafraid to talk about this kind of stuff. Because I'm really fascinated with consciousness on the engineering side. I really want to build robots that have elements of intelligence, emotion, even consciousness. And for that, we need to understand it in ourselves and drugs is all the different kinds of drugs. If used safely, seems like an incredible tool to understand ourselves. And if we're limiting ourselves from certain drugs, because of certain political games that being played, it's sad. And people know this, a lot of middle to upper class people know this, they elicit drug trade business. It's a multi-million dollar industry, multi-billion dollar industry that could not be supported by people who are poor. And that has to be supported by a lot of customers. And a lot of people around the world know this, they're in the closet. And in the book, I call for them to get out of the closet. So we can start being more honest, and we can take the pressure off of those people who are not as privileged. Like I said, you're brave, you're bold. I gotta ask you for some advice. What advice would you give to a young person today, high school, maybe undergrad, college, thinking about their career, thinking about how to live a life they can be proud of? Yeah, whatever career they choose, just make sure that they dedicate themselves to it and be the best at what they do first. That's what you have to do first. Like people see me advocating for this position. 30 years of science is in these opinions, this view. And trust me, I would be dismissed if I didn't know my shit, if I was not. Yeah, you did the work, you proved yourself, you're legit by the people, in the eyes of the people who know. Absolutely. So that's the main thing that I would encourage people to do, really know your craft. If you know your craft, and then maybe you will be a service to your fellow citizens. There are so many people out here faking the funk, and they don't know their craft, and they're not a service to the people that they claim to serve. And that's a problem. And when you have a fair number of people like that in positions of power, your society is going to crumble. What about the scientific path? You recommend people get a PhD? Not necessarily. Like my own children, I don't recommend that. So science can, certainly my science can be a very petty sort of space to be in. But it was the only sort of path that I had. And so I had to do it. But no, I would really encourage people to just do something that they enjoy, and something that makes them happy. Because the greater number of happy people in our society, the better off we all are. All right, since you mentioned happiness, got to ask you about the pursuit of happiness and the ridiculous question about meaning. Do you think this life has meaning? What do you think is the meaning of life? I'm sorry. I certainly hope it has meaning. I mean, I'm certainly trying to live my life like it has meaning. You know, I really love my life now. I just got back from Geneva. I spent the summer abroad in Europe and trying to be in a more civilized place where you can enjoy yourself as a responsible adult. And then it allowed me to decompress and then come back here. The thing about coming back here is that you have to be ready to fight. And I don't want to fight anymore. You know, I just want to be able to help a society and people. And so I'll have to keep a place in Europe to go and decompress and then come back to be able to tolerate the situation. So life for me has a lot of meaning. I'm enjoying life. This is like the greatest, the best part of my life ever right now at this moment. So it's the joy, but you also enjoy the fight a little bit or? No, I don't really. I'm tired of that. You know, it's like, why? I'm trying to help people to see how they can be happy. And then people are fighting me on that. I don't want to be happy. I want to be ignorant. Leave me alone. That's what people are saying. Well, so what is the source of joy for you when you decompress? MDMA is a source, you know, and a place where you don't have to worry about laws. That's like Europe. You can feel really free. Yeah. Heroin can even be a nice space if I'm in my own head, but with others MDMA is great. So good friends, good food. The usual. Yeah. Family, love. Yeah, that's right. Carl, you're an incredible human being. You really make me think, everyone listens to this. I mean, I'm really glad you exist. I know you say you don't like the fight, but I'm really glad you're fighting the fight because it's going to help a lot of people. It's going to help at the very least, help a lot of people think and challenge the conventions of the day and maybe challenge them to find joy. I really appreciate you spending your valuable time with me. This was an awesome conversation. Thank you so much for talking to me. Thank you for having me, man. Thanks for listening to this conversation with Carl. Thanks for listening to this conversation with Carl Hart. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Frank Zappa. A drug is not bad. A drug is a chemical compound. The problem comes in when people who take drugs treat them like a license to behave like an asshole. Thank you for listening and hope to see you next time.

https://youtu.be/3LWNY70Oj4A

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Lisa Feldman Barrett: Love, Evolution, and the Human Brain | Lex Fridman Podcast #140

The following is a conversation with Lisa Feldman Barrett, her second time on the podcast. She's a neuroscientist at Northeastern University and one of my favorite people. Her new book called Seven and a Half Lessons About the Brain is out now as of a couple of days ago, so you should definitely support Lisa by buying it and sharing with friends if you like it. It's a great short intro to the human brain. Quick mention of each sponsor, followed by some thoughts related to the episode. Athleta Greens, the all-in-one drink that I start every day with to cover all my nutritional bases. Eight Sleep, a mattress that cools itself and gives me yet another reason to enjoy sleep. Masterclass, online courses that I enjoy from some of the most amazing people in history. And BetterHelp, online therapy with a licensed professional. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that Lisa, just like Manolis Kellis, is a local brilliant mind and friend and someone I can see talking to many more times. Sometimes it's fun to talk to a scientist not just about their field of expertise, but also about random topics, even silly ones, from love to music to philosophy. Ultimately, it's about having fun, something I know nothing about. This conversation is certainly that. It may not always work, but it's worth a shot. I think it's valuable to alternate along all kinds of dimensions, like between deeper technical discussions and more fun random discussion, from liberal thinker to conservative thinker, from musician to athlete, from CEO to junior engineer, from friend to stranger. Variety makes life and conversation more interesting. Let's see where this little podcast journey goes. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcasts, follow on Spotify, support it on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Lisa Feldman Barrett. Based on the comments in our previous conversation, I think a lot of people will be very disappointed, I should say, to learn that you are in fact married. As they say, all the good ones are taken. Okay, so I'm a fan of your husband as well, Dan. He's a programmer, a musician, so a man after my own heart. Can I ask a ridiculously over-romanticized question of when did you first fall in love with Dan? It's actually, it's a really romantic story, I think. So I was divorced by the time I was 26, 27, 26, I guess. And I was in my first academic job, which was Penn State University, which is in the middle of Pennsylvania, surrounded by mountains. So you have, it's four hours to get anywhere, to get to Philadelphia, New York, Washington. I mean, you're basically stuck, you know? And I was very fortunate to have a lot of other assistant professors who were hired at the same time as I was. So there were a lot of us, we were all friends, which was really fun. But I was single, and I didn't wanna date a student. And there were no, and I wasn't gonna date somebody in my department, that's just a recipe for disaster. Yeah. So. So even at 20, whatever you were, you were already wise enough to know that. Yeah, a little bit, maybe, yeah. I wouldn't call me wise at that age. But anyways, not sure that I would say that I'm wise now, but, and so, after, you know, I was spending probably 16 hours a day in the lab, because it was my first year, as an assistant professor, and there's a lot to do. And I was also bitching and moaning to my friends that I hadn't had sex in I don't know how many months, and I was starting to become unhappy with my life. And I think at a certain point, they just got tired of listening to me bitch and moan, and said, just do something about it then, like do, you know, if you're unhappy. And so the first thing I did was I made friends with a sushi chef in town, and this is like a, State College Pennsylvania, in the early 90s, was there was like a pizza shop, and a sub shop, and actually a very good bagel shop, and one good coffee shop, and maybe one nice restaurant. I mean, there was really, but there was a, the second son of a Japanese sushi chef, who was not going to inherit the restaurant, and so he moved to Pennsylvania, and was giving sushi lessons. So I met this guy, the sushi chef, and we decided to throw a sushi party at the coffee shop. So we basically, it was, the goal was to invite every eligible bachelor, really, within like a 20 mile radius. We had a totally fun time. I wore an awesome, crushed, velvet, burgundy dress. It was a beautiful dress. And I didn't meet any, I met a lot of new friends, but I did not meet anybody. So then I thought, okay, well, maybe I'll try the personals ads, which I had never used before in my life. And I first tried the paper personals ads. Like in the newspaper? Like in the newspaper. That didn't work. And then a friend of mine said, oh, you know, there's this thing called Net News. This is like 1992, maybe. So there was this anonymous, you could do it anonymously. So you would read, you could post, or you could read ads, and then respond to an address, which was anonymous, and that was yoked to somebody's real address. And there was always a lag, because it was this like a bulletin board sort of thing. So at first I read them over, and I decided to respond to one or two. And you know, it was interesting. Sorry, this is not on the internet. Yeah, this is totally on the internet. But it takes, there's a delay of a couple days, or whatever. Yeah, right, right. It's 1992. There's no web. Web. No pictures. There's no pictures. The web doesn't exist. It's all done in ASCII format, sort of. And you know, but the ratio. Lovely NASCII, yeah. But the ratio of men to women was like 10 to one. I mean, there were many more men, because it was basically academics and the government. That was it. That was no, I mean, I think AOL maybe was just starting to become popular. And so the first person I met told me that he was a scientist who worked for NASA. And yeah. Anyways, it turned out that he didn't, actually. Yeah, that's just how they brag, is like you elevate your, as opposed to saying you're taller than you are, you say like your position is. Yeah, and I actually, I would have been fine dating somebody who wasn't a scientist. It's just that they have, it's just that whoever I date has to just accept that I am, and that I was pretty ambitious and was trying to make my career. And you know, that's not, I think it's maybe more common now for men to maybe accept that in their female partners, but at that time, not so common. It could be intimidating, I guess. Yes, that has been said. And so then the next one I actually corresponded with, and we actually got to the point of talking on the phone, and we had this really kind of funny conversation where we're chatting, and he said, he introduces the idea that he's really looking for a dominant woman, and I'm thinking, I'm a psychologist by training, so I'm thinking, oh, he means sex roles. Like, I'm like, no, I'm very assertive, and I'm glad you think that. Anyways, long story short, that's not really what he meant. Oh. Okay, got it. Yeah, so, and I just, you know, that will just show you my level of naivete. Like, I was like, I didn't completely understand, but I was like, well, yeah, you know, no. At one point, he asked me how I felt about him wearing my lingerie, and I was like, I don't even share my lingerie with my sister. Like, I don't share my lingerie with anybody, you know? No. The third one I interacted with was a banker who lived in Singapore, and that conversation didn't last very long because he made an, I guess he made an analogy between me and a character in The Fountainhead, the woman who's raped in The Fountainhead, and I was like, okay, that's not. That's not a good. That's not a good, no, that's not a good one. Not that part, not that scene. Not that scene. So then I was like, okay, you know what? I'm gonna post my own ad, and so I did. I posted, well, first I wrote my ad, and then, of course, I checked it with my friends who were all also assistant professors, they were like my little Greek chorus, and then I posted it, and I got something like, I don't know, 80-something responses in 24 hours. I mean, it was very. Do you remember the pitch? Like how you, I guess, condensed yourself? I don't remember it exactly, although Dan has it, but actually for our 20th wedding anniversary, he took our exchanges and he printed them off and put them in a leather-bound book for us to read, which was really sweet. Yeah, I think I was just really direct. Like, I'm almost 30, I'm a scientist, I'm not looking, I'm looking for something serious. But the thing is, I forgot to say where my location was, and my age, which I forgot. So I got lots of, I mean, I will say, so I printed off all of the responses, and I had all my friends over, and we had a big, I made a big pot of gumbo, and we drank through several bottles of wine reading these responses. And I would say for the most part, they were really sweet, like earnest and genuine, as much as you could tell that somebody's being genuine. I mean, it seemed, you know, there were a couple of really funky ones, like this one couple who told me that I was their soulmate, the two of them, then they were looking for a third person, and I was like, okay. But mostly super, seemed like super genuine people. And so I chose five men to start corresponding with, and I was corresponding with them. And then about a week later, I get this other email. And okay, and then I post something the next day that said, okay, you know, thank you so much, and I'm gonna, I answered every person back. But then after that, I said, okay, and I'm not gonna answer anymore. You know, because it was, they were still coming in, and I couldn't, you know, I have a job, and you know, a house to take care of and stuff. So, and then about a week later, I get this other email. And he says, you know, he just describes himself, like I'm this, I'm this, I'm this, I'm a chef, I'm a scientist, I'm a this, I'm a this. And so I emailed him back, and I said, you know, you seem interesting, you can write me at my actual address if you want, here's my address. I'm not really responding, I'm not really responding to other people anymore, but you seem interesting, you know, you can write to me if you want. And then he wrote to me, and I, then I wrote him back, and it was a nondescript kind of email, and I wrote him back, and I said, thanks for responding. You know, I'm really busy right now, I was in the middle of writing my first slate of grant applications, so I was really consumed, and I said, I'll get back to you in a couple of days. And so I did, I waited a couple of days, I told my grants were, you know, safe, grant applications safely out the door. And then I emailed him back, and then he emailed me, and then really across two days, we sent 100 emails. And text only, was there pictures, any of that stuff? Text only, text only. Wow. And then, so this was like a Thursday and a Friday, and then Friday, he said, let's talk on the weekend on the phone, and I said okay. And he wanted to talk Sunday night, and I had a date Sunday night. So I said, okay, sure, we can talk Sunday night. And then I was like, well, you know, I don't really wanna cancel my date, so I'm just gonna call him on Saturday. So I just called, I cold called him on Saturday, and a woman answered. Oh wow. That's not cool. Not cool. And so she says, you know, hello, and I say, oh, you know, I stand there, and she said, sure, can I ask who's calling? And I said, tell him it's Lisa. And she went, oh my God, oh my God, I'm just a friend. I'm just a friend, I just have to tell you, I'm just a friend. And I was like, this is adorable, right? And then he gets on the phone, not hi, nice to meet you. The first thing he says to me, she's just a friend. So I was just so charmed, really, by the whole thing. So it was Yom Kippur, it was the Jewish Day of Atonement that was ending, and they were baking cookies and going to a break fast. So people, as you know, fast all day, and then they go to a party and they break fast. So I thought, okay, I'll just cancel my date. So I did, and I stayed home, and we talked for eight hours, and then the next night for six hours, and basically it just went on like that, and then by the end of the week, he flew to State College. And we'd gone through this whole thing where I'd said, we're gonna take it slow, we're gonna get to know each other. And then really by, I think we talked two or three times, these really long conversations, and then he said, I'm just gonna fly there. And then, so of course, there's, I don't even know that there were fax machines at that point, maybe there were, but I don't think so. Anyway, so we decide we'll exchange pictures. So I take my photograph, and I give it to my secretary, and I say to my secretary. Fax this. I say, send this priority mail. Priority mail. And he goes, okay, I'll send a priority mail. Let me, it's a priority mail. He's like, I know, priority mail, okay. And then, so I get Dan's photograph in the mail, and it's him in shorts, and you can see that he's probably somewhere like the Bahamas or something like that, and it's like cropped. So clearly what he's done is he's taken a photograph where he's in it with someone else who turned out to be his ex-wife. So I'm thinking, well, this is awesome. I've hit the jackpot. He's very appealing to me, very attractive. And then my photograph doesn't show up, and it doesn't show up. And so one day, and then two days, and then he's like, I said, well, I asked my secretary to send a priority. I mean, I don't know what he did. And he's like, I said, I'm like, well, you don't have to come. And he's like, no, no, no, I'm gonna, we've had like five dates, the equivalent of five dates practically. And then, so he's supposed to fly on a Thursday or Friday, I can't remember, and I get a call like maybe an hour before his flight's supposed to leave, and he says, hi, and I say, and it's just something in his voice, right? And I say, because at this point, I think I've talked to him like for 25 hours, I don't know. And he says, hi, and I'm like, you got the picture? And he's like, yeah, and I'm like, you don't like it? And he's like, well, I'm sure it's not, I'm sure it's your, I'm sure it's just not a good, you know, it's probably not your best. Oh, no. You know, you don't have to come. And he's like, no, no, no, I'm coming. And I'm like, no, you don't have to come. And he's like, no, no, I really wanna, I'm getting on the plane. I'm like, you don't have to get on the plane. He's like, no, I'm getting on the plane. And so I go down to my, I go, I'm in my office, this is happening, right? So I go downstairs to my, one of my closest friends, who's still actually one of my closest friends, who is one of my colleagues, and Kevin, and I say, Kevin, and I go to Kevin, I go, Kevin, Kevin, Kevin, he doesn't like the photograph. And Kevin's like, well, which photograph should you send? And I'm like, well, you know the one where we're shooting pool? And he's like, you sent that photograph? That's a horrible photograph. I'm like, yeah, but it's the only one that I had that was like, where my hair was kind of similar to what it is now. And he's like, Lisa, do I have to check everything for you? You should not have sent that. But still, he flew over. So he flew. Where from, by the way? He was in graduate school at Amherst, yeah, at UMass Amherst. So he flew, and I picked him up at the airport, and he was happy. So whatever the concern was, was gone. And I was dressed, you know, I carefully, carefully dressed. Were you nervous? I was really, really nervous. Because I don't really believe in fate, and I don't really think there's only one person that you can be with. But I think, you know, some people are curvy, they're kind of complicated, and so the number of people who fit them is maybe less than. I like it, mathematically speaking, yeah. And so when I was going to pick him up at the airport, I was thinking, well, I could be going to pick up the person I'm gonna marry, or not. I mean, like I really, but I really, you know, like our conversations were just very authentic and very moving, and we really connected. And I really felt like he understood me, actually, in a way that a lot of people don't. And what was really nice was, at the time, you know, the airport was this tiny little airport out in a cornfield, basically. And so driving back to the town, we were in the car for 15 minutes, completely in the dark as I was driving. And so it was very similar to, we had just spent, you know, 20-something hours on the telephone, sitting in the dark, talking to each other. So it was very familiar. And we basically spent the whole weekend together, and he met all my friends, and we had a big party. And at the end of the weekend, I said, okay, you know, if we're gonna give this a shot, we probably, we shouldn't see other people. So it's a risk, you know? It's a commitment. But I just didn't see how it would work if we were dating people locally, and then also seeing each other at a distance. Because I've had long-distance relationships before, and they're hard, and they take a lot of effort. And so we decided we'd give it three months and see what happened, and that was it. This is an interesting thing. Like, we're all, what is it, there's several billion of us, and we're kind of roaming this world, and then you kind of stick together. You find somebody that just, like, gets you. And it's interesting to think about, there's probably thousands, if not millions, of people that would be sticky to you, depending on the curvature of your space. But what is the, could you speak to the stickiness, like, to the, just the falling in love? Like, seeing that somebody really gets you? Maybe by way of telling, do you think, do you remember there was a moment when you just realized, damn it, I think I'm, like, I think that's, this is the guy. I think I'm in love. We were having these conversations, actually, from the, really from the second weekend we were together. So he flew back the next weekend to State College, because it was my birthday, it was my 30th birthday, and my friends were throwing me a party. And we went hiking, and we hiked up some mountain, and we were sitting on a cliff over this overlook and talking to each other, and I was thinking, and I actually said to him, like, I haven't really known you very long, but I feel like I'm falling in love with you, which can't possibly be happening. I must be projecting. But it, but it, but it certainly feels that way, right? Like, I don't believe in love at first sight, so this can't really be happening, but it sort of feels like it is. And he was like, I know what you mean. And so, for the first three months or four months, we would say things to each other, like, I feel like I'm in love with you, but, you know, but that can't, but things don't really work like that. So, but, you know, so, and then it became a joke, like, I feel like I'm in love with you, and then eventually, you know, I think, but I think that was one moment where we were, we were talking about, I don't know, just, you know, not just all the great aspirations you have or all the things, but also things you don't like about yourself, things that you're worried about, things that you're scared of. And then I think the, that was sort of solidified the relationship, and then there was one weekend where we went to Maine in the winter, which I, I mean, I really love the beach always, but in the winter, particularly. Because it's just beautiful and calm and whatever. Yeah, and I also, I do find beauty in starkness sometimes, like, so there's this grand majestic scene of, you know, this very powerful ocean, and it's all these, like, beautiful blue grays, and it's just, it's just stunning. And so we were sitting on this huge rock in Maine, and where we'd gone for the weekend, it was freezing cold. And I honestly can't remember what he said or what I said or what, but I definitely remember having this feeling of, I absolutely wanna stay with this person. Like, I, and I don't know what my life will be like if I'm not with this person. Like, I need to be with this person. Can we, from a scientific and a human perspective, dig into your belief that first love at first sight is not possible, you don't believe in it? Because there is, you don't think there's, like, a magic where you see somebody in the Jack Kerouac way, and you're like, wow, that's something. That's a special little glimmer or something. Oh, I definitely think you can connect with someone in an instance. And I definitely think you can say, oh, there's something there, and I'm really clicking with that person. Romantically, but also just as friends, it's possible to do that. You recognize a mind that's like yours or that's compatible with yours. There are ways that you feel like you're being understood or that you understand something about this person, or maybe you see something in this person that you find really compelling or intriguing. But I think your brain is predictive organ, right? You're using your past. You're projecting. You're using your past to make predictions. And I mean, not deliberately, that's how your brain is wired, that's what it does. And so it's filling in all of the gaps that you, there are lots of gaps of information that you don't, information you don't have. And so your brain is filling those in, and... But isn't that what love is? No, I don't think so, actually. I mean, to some extent, sure, you always, there's research to show that people who are in love always see the best in each other, and they, when there's a negative interpretation or a positive interpretation, they choose the positive ones. There's a little bit of positive illusion there going on. That's what the research shows. But I think, I think that when you find somebody who not just appreciates your faults, but loves you for them, actually, like maybe even doesn't see them as a fault, that's, so you have to be honest enough about what your faults are. So it's easy to love someone for all the things that they, for all the wonderful characteristics they have. It's harder, I think, to love someone despite their faults, or maybe even the faults that they see aren't really faults at all to you. They're actually something really special. But isn't that, can't you explain that by saying the brain kind of, like you're projecting, it's, you have a conception of a human being, or just a spirit that really connects with you, and you're projecting that onto that person, and within that framework, all their faults then become beautiful, like little. Maybe, but you just have to pay attention to the prediction error. No, but maybe that's what love, like maybe you start ignoring the prediction error. Maybe love is just your ability, like. To ignore the prediction error? Well, I think that there's some research that might say that, but that's not my experience, I guess. But there is some research that says, I mean, there's some research that says you have to have an optimal margin of illusion, which means that you put a positive spin on smaller things, but you don't ignore the bigger things, right? And I think, without being judgmental at all, when someone says to me, you're not who I thought you were, I mean, nobody has said that to me in a really long time, but certainly when I was younger, that was, you're not who I thought you were, my reaction to that was, well, whose fault is that? You know? I'm a pretty upfront person. I mean, I will, though, say that in my experience, people don't lie to you about who they are. They lie to themselves in your presence. Yeah. And so, you know, you don't wanna get tied up in that, tangled up in that. And I think from the get-go, Dan and I were just, for whatever reason, maybe it's because we both have been divorced already, and, you know, he told me who he thought he was, and he was pretty accurate as far as I could. He was accurate? Pretty much, actually. I mean, there's very, I can't say that I've ever come across a characteristic in him that really surprised me in a bad way. It's hard to know yourself. It is hard to know yourself. And to communicate that. For sure. I mean, I'll say, you know, I had the advantage of training as a therapist, which meant for five years, I was under a fucking microscope. Yeah. You know, when I was training as a therapist, it was hour for hour supervision, which meant if you were in a room with a client for an hour, you had an hour with a supervisor. So that supervisor was behind the mirror for your session, and then you went and had an hour of discussion about what you said, what you didn't say, learning to use your own feelings and thoughts as a tool to probe the mind of the client and so on. And so you can't help but learn a lot of, you can't help but learn a lot about yourself in that process. Do you think knowing or learning how the sausage is made ruins the magic of the actual experience? Like, you as a neuroscientist who studies the brain, do you think it ruins the magic of love at first sight? Are you, do you consciously are still able to lose yourself in the moment? I'm definitely able to lose myself in the moment. Is wine involved? Not always. Chocolate? I mean, some kind of wine, all drugs, substance, right? But yeah, for sure. I mean, I guess what I would say, though, is that for me, part of the magic is the process. Like, so I remember a day, there was, while I was working on this book of essays, I was in New York. I can't remember why I was in New York, but I was in New York for something, and I was in Central Park, and I was looking at all the people with their babies, and I was thinking, every, each one of these, there's a tiny little brain that's wiring itself right now. And I just, I felt, in that moment, I was like, I am never gonna look at an infant in the same way ever again. And so to me, I mean, honestly, before I started learning about brain development, I thought babies were cute, but not that interesting until they could interact with you and do things. Of course, my own infant, I thought, was extraordinarily interesting, but they're kinda like lumps. That's until they can interact with you, but they are anything but lumps. I mean, like, you know, so, and part of the, I mean, all I can say is I have deep affection now for tiny little babies in a way that I didn't really before, because of the, I'm just so curious. But the actual process, the mechanisms of the wiring of the brain, the learning, all the magic of the neurobiology. Yeah, and or something like, when you make eye contact with someone directly, sometimes you feel something, right? Yeah. And- Yeah, that's weird. What is it? And what is that? And so to me, that's not backing away from the moment. That's like expanding the moment. It's like, that's incredibly cool. You know, when I was, I'll just say that, when I was in graduate school, I also was in therapy, because it's almost a given that you're gonna be in therapy yourself if you're gonna become a therapist. And I had a deal, you know, with my therapist, which was that I could call time out at any moment that I wanted to, as long as I was being responsible about it. And I wasn't using it as a way to get out of something. And he could tell me, no, you know, he could decline and say, no, you're using this to get out of something. But I could call time out whenever I want and say, what are you doing right now? Like, what are you, here's what I'm experiencing. What are you trying to do? Like, I wanted to use my own experience to interrogate what the process was. And that made it more helpful in a way. Do you know what I mean? So yeah, I don't think learning how something works makes it less magical, actually, but that's just me, I guess. I don't know, would you? Yes. I tend to have two modes. One is an engineer and one is a romantic. And I'm conscious of like, there's two rooms. You can go into the one, the engineer room, and I think that ruins the romance. So I tend to, there's two rooms. One is the engineering room. Think from first principles, how do we build the thing that creates this kind of behavior? And then you go into the romantic room where you're like emotional, it's a roller coaster, and then you're, the thing is, let's take it slow, and then you get married the next night. You're just this giant mess, and you write a song, and then you cry, and then you send a bunch of texts, and anger, and whatever, and somehow you're in Vegas, and there's random people, and you're drunk, and whatever, all that, like in poetry, and just mess of it, fighting. Yeah, that's not, those are two rooms, and you go back between them. But I think the way you put it is quite poetic. I think you're much better at adulting with love than perhaps I am, because there's a magic to children. I also think of adults as children. It's kind of cool to see, it's a cool thought experiment to look at adults and think like that used to be a baby, and then that's like a fully wired baby, and it's just walking around pretending to be all serious and important, wearing a suit or something, but that used to be a baby. And then you think of the parenting and all the experiences they had. It's cool to think of it that way, but then I start thinking of it from a machine learning perspective. But once you're, the romantic moments, all that kind of stuff, all that falls away. I forget about all that, I don't know. That's the Russian thing. Maybe, maybe. But I also think it might be an age thing or maybe an experience thing. So I think we all, I mean, if you're exposed to Western culture at all, you are exposed to the sort of idealized, stereotypic, romantic exchange. And what does it mean to be romantic? And so here's a test. I'm gonna see how to phrase it. Okay, so not really a test, but this tells you something about your own ideas about romance. For Valentine's Day one year, my husband bought me a six-way plug. Is that romantic or not romantic? Like, sorry, six-way plug, that's like an outlet. Yeah, like to put it in an outlet. Is that romantic or not romantic? I mean, it depends the look in his eyes when he does it. I mean, it depends on the conversation that led up to that point. Depends how much, it's like the music, because you have a very, you're both from my experiences with you as a fan, you have both a romantic nature, but you have a very pragmatic, like you cut through the bullshit of the fuzziness. And there's something about a six-way plug that cuts through the bullshit, that connects to the human, like he understands who you are. Exactly. Yeah. Exactly. That was the most romantic gift he could have given me because he knows me so well. He has a deep understanding of me, which is that I will sit and suffer and complain about the fact that I have to plug and unplug things. And I will bitch and moan until the cows come home, but it would never occur to me to go buy a bloody six-way plug. Whereas for him, he bought it, he plugged it in, he arranged, he taped up all my wires, he made it like really usable. And for me, that was the best present. The most romantic thing. It was the most romantic thing because he understood who I was and he did something very, or just the casual, like we moved into a house that we went from having a two-car garage to a one-car garage. And I said, okay, I'm from Canada, I'm not bothered by snow. Well, I mean, I'm a little bothered by snow, but he's very bothered by snow. So I'm like, okay, you can park your car in the garage, it's fine. Every day when it snows, he goes out and cleans my car. Every day. Like I never asked him to do it, he just does it. Because he knows that I'm cutting it really close in the morning, when we all used to go to work. I have it timed to the second so that I can get up as late as possible, work out as long as possible, just to make it into my office like a minute before my first meeting. And so if it snows unexpectedly or something, I'm screwed because now that's an added 10 or 15 minutes I'm gonna be late. Anyways, it's just these little tiny things. He's a really easygoing guy. And he doesn't look like somebody who pays attention to detail. He doesn't fuss about detail, but he definitely pays attention to detail. And it is very, very romantic in the sense that he loves me despite my little details. And he understands you. Yeah, he understands me. But it is kind of hilarious that that is, the six-way plug is the most fulfilling, richest display of romance in your life. I love it. I love it. That's what I mean about romance. Romance is really, it's not all about chocolates and flowers and whatever. I mean, those are all nice too, but. Sometimes it's about the six-way plug. Sometimes it's about the six-way plug. So maybe one way I could ask before we talk about the details, you also have the author of another book as we talked about how emotions are made. So it's interesting to talk about the process of writing. You mentioned you were in New York. What have you learned from writing these two books about the actual process of writing? And maybe, I don't know what's the most interesting thing to talk about there. Maybe the biggest challenges or the boring, mundane, systematic, like day-to-day of what worked for you, like hacks or even just about the neuroscience that you've learned through the process of trying to write them. Here's the thing I learned. If you think that it's gonna take you a year to write your book, it's going to take you three years to write your book. That's the first thing I learned is that no matter how organized you are, it's always gonna take way longer than what you think in part because very few people make an outline and then just stick to it. Some of the topics really take on a life of their own and to some extent, you wanna let them have their voice. You wanna follow leads until you feel satisfied that you've dealt with the topic appropriately. But I, and that part is actually fun. It's not fun to feel like you're constantly behind the eight ball in terms of time, but it is the exploration and the foraging for information is incredibly fun for me anyways. I found it really enjoyable. And if I wasn't also running a lab at the same time and trying to keep my family going, the whole thing would have just been fun. But I would say the hardest thing about, the most important thing I think I learned is also the hardest thing for me, which is knowing what to leave out. A really good storyteller knows what to leave out. In academic writing, you shouldn't leave anything out. All the details should be there. And I've written or participated in writing over 200 papers, peer reviewed papers, so I'm pretty good with detail. Knowing what to leave out, knowing what to leave out and not harming the validity of the story. That is a tricky, tricky thing. It was tricky when I wrote how emotions are made, but that's a standard popular science book. So it's 300 something pages and then it has like a thousand end notes and then each of the end notes is attached to a web note, which is also long. So I mean, it's, and it start, and I mean the final draft, I mean, I wrote three drafts of that book actually and the final draft, and then I had to cut by a third. I mean, or, I mean, I, you know, it was like 150,000 words or something and I had to cut it down to like 110. So obviously I struggle with what to leave out. You know, brevity is not my strong suit. I'm always telling people that, it's a warning. So that's why this book was, I, you know, I'd always been really fascinated with essays. I love reading essays and after reading a small set of essays by Anne Fadiman called At Large and at Small, which I just loved these little essays. What's the topic of those essays? They are, they're called familiar essays. So the topics are like everyday topics, like mail, coffee, chocolate. I mean, just like, and what she does is she weaves her own experience. It's a little bit like these conversations that you're so good at curating actually. You're weaving together history and philosophy and science and also personal reflections. And a little bit you feel like you're like eavesdropping on someone's train of thought in a way. It's really, they're really compelling to me. Even if it's just like a mundane topic. Yeah, but it's so interesting to learn about like all of these little stories in the wrapping of the history of like mail. Like that's really interesting. And so I read these essays and then I wrote to her a little fangirl email. This was many years ago. And I said, I just love this book and how did you learn to write essays like this? And she gave me a reading list of essays that I should read, like writers. And so I read them all. And anyway, so I decided it would be a really good challenge for me to try to write something really brief where I could focus on one or two really fascinating tidbits of neuroscience. Connect it to, connect each one to something philosophical or like just a question about human nature. Do it in a really brief format without violating the validity of the science. That was a, I just set myself this, what I thought of as a really, really big challenge in part because it was an incredibly hard thing for me to do in the first book. Yeah, we should say that this is, The Seven and a Half Lessons is a very short book. I mean, it's like it embodies brevity, right? The whole point throughout is just, I mean, you could tell that there's editing, like there's pain in trying to bring it as brief as possible, as clean as possible, yeah. Yeah, so it's, the way I think of it is, it's a little book of big science and big ideas. Yeah, really big ideas in brief little packages. And I wrote it so that people could read it. I love reading on the beach. I love reading essays on the beach. I read it, I wrote it so people could read it on the beach or in the bathtub or a subway stop. Even if the beach is frozen over in the snow. Yeah, so my husband, Dan, calls it the first neuroscience beach read. That's his phrasing, yeah. And like you said, you learn a lot about writing from your husband, like you were saying offline. Well, he is, of the two of us, he is the better writer. He's a masterful writer. He's also, I mean, he's a PhD in computer science. He's a software engineer, but he's also really good at organization of knowledge. So he built, for a company he used to work for, he built one of the first knowledge management systems. And he now works at Google where he does engineering education. Like he understands how to tell a good story just about anything really. He's got impeccable timing, he's really funny. And luckily for me, he knows very little about psychology or neuroscience. Well, now he knows more obviously. But so he was really, when how emotions were made, he was really, really helpful to me because the first draft of every chapter was me talking to him about what, I would talk out loud about what I wanted to say and the order in which I wanted to say it. And then I would write it, and then he would read it and tell me all the bits that could be excised. And sometimes we would, I should say, I mean, we don't, he and I don't really argue about much except directions in the car. Like that's, if we're gonna have an argument, that's gonna be where it's gonna happen. What's the nature of the argument about directions exactly? I don't really know. It's just that we're very, I think it's that spatially, I use egocentric space. So I wanna say, turn left. I'm reasoning in relation to my own physical corporeal body. So you walk to the church and you turn left and you, then whatever. I'm always like, and his, he gives directions allocentrically, which means organized around North, South, East, West. So to you, the Earth is at the center of the solar system and to him, reasonably, you're at the center of the solar system. Okay, so. Anyway, so we, but here we, we had some really rip roaring arguments, like really rip roaring arguments where he would say, like, who is this for? Is this for the 1%? And I'd be like, 1% meaning not wealth, but like civilians versus academics. Are these for the scientists or is this for the civilians? So he speaks for the people, for the civilians. He speaks for the people and I'd be like, no, you have to. And so he made, after one terrible argument that we had, where it was really starting to affect our relationship because we were so mad at each other all the time, he made these little signs, writing and science. And we only use them, this was like, when you pulled out a sign, that's it. Like the other person just wins and you have to stop fighting about it and that's it. And so we just did that. And we didn't really have to use it too much for this book because this book was in some ways, I didn't have to learn a lot of new things for this book. I had to learn some, but a lot of what I learned for How Emotions Are Made really stood me in good stead for this book. So there was a little bit, each essay was a little bit of learning. A couple were, was a little more than the small amount, but I didn't have so much trouble here. I had a lot of trouble with the first book, but still even here, he would tell me that I could take something out and I really wanted to keep it. And I think we only use the signs once. Well, if we could dive in some aspects of the book, I would love that. Can we talk about, so one of the essays looks at evolution. Let me ask the big question, did the human brain evolve to think? That's essentially the question that you address in the essay can you speak to it? Sure, the big caveat here is that we don't really know why brains evolved. The big why questions are called teleological questions and in general, scientists should avoid those questions because we don't know really why, we don't know the why. However, for a very long time, the assumption was that evolution worked in a progressive upward scale, that you start off with simple organisms and those organisms get more complex and more complex and more complex. Now, obviously that's true in some really general way, that life started off as single cell organisms and things got more complex. But the idea that brains evolved in some upward trajectory from simple brains in simple animals to complex brains in complex animals is called a phylogenetic scale. And that phylogenetic scale is embedded in a lot of evolutionary thinking, including Darwin's actually. And it's been seriously challenged, I would say, by modern evolutionary biology. And so, thinking is something that, rationality is something that humans, at least in the West, really prize as a great human achievement. And so, the idea that the most common evolutionary story is that brains evolved in sedimentary rock with a layer for instincts, that's your lizard brain, and a layer on top of that for emotions, that's your limbic system, limbic meaning border. So, it borders the parts that are for instincts. And then the neocortex or new cortex where rationality is supposed to live, that's the sort of traditional story. It just keeps getting layered on top by evolution. Right, and so, you can think about, I mean, sedimentary rock is the way typically people describe it. The way I sometimes like to think about it is thinking about the cerebral cortex like icing on an already baked cake, where the cake is your inner beast, these boiling, roiling instincts and emotions that have to be contained. And by the cortex, and it's just, it's a fiction. It's a myth. It's a myth that you can trace all the way back to stories about morality in ancient Greece. But what you can do is look at the scientific record and say, well, there are other stories that you could tell about brain evolution and the context in which brains evolved. So when you look at creatures who don't have brains and you look at creatures who do, what's the difference? And you can look at some animals. So we call, scientists call an environment that an animal lives in a niche, their environmental niche. What are the things, what are the parts of the environment that matter to that animal? And so there's some animals whose niche hasn't changed in 400 million years. So they're not, these creatures are modern creatures, but they're living in a niche that hasn't changed much. And so their biology hasn't changed much. And you can kind of verify that by looking at the genes that lurk deep in the molecular structure of cells. And so you can, by looking at various animals in their developmental state, meaning not, you don't look at adult animals, you look at embryos of animals and developing animals, you can see, you can piece together a different story. And that story is that brains evolved under the selection pressure of hunting. That in the Cambrian period, hunting emerged on the scene where animals deliberately ate one another. And what, so before the Cambrian period, the animals didn't really have, well, they didn't have brains, but they also didn't have senses really, the very, very rudimentary senses. So the animal that I wrote about in seven and a half lessons is called an amphioxus or a lancelet. And little amphioxus has no eyes, it has no ears, it has no nose, it has no eyes. It has a couple of cells for detecting light and dark for circadian rhythm purposes. And it can't hear, it has a vestibular cell to keep its body upright. It has a very rudimentary sense of touch, and it doesn't really have any internal organs other than this like basically stomach. It's like a, just like a, it doesn't have an enteric nervous system, it doesn't have like a gut that moves like we do, it just has basically a tube. So it's like- A little container. Like a little container, yeah. And so, and really it doesn't move very much, it can move, it just sort of wriggles, it doesn't have very sophisticated movement. And it's this really sweet little animal, it sort of wriggles its way to a spot and then plants itself in the sand and just filters food as the food goes by. And then when the food concentration decreases, it just ejects itself, wriggles to some spot randomly where probabilistically there will be more food and plants itself again. So it's not really aware, very aware that it has an environment. It has a niche, but that niche is very small and it's not really experiencing that niche very much. So it's basically like a little stomach on a stick. That's really what it is. But when animals start to literally hunt each other, all of a sudden it becomes important to be able to sense your environment. Because you need to know, is that blob up ahead gonna eat me or should I eat it? And so all of a sudden you want, distance senses are very useful. And so in the water, distance senses are vision and a little bit hearing, olfaction, smelling, and touch. Because in the water, touch is a distance sense because you can feel the vibration. On land, vision is a distance sense. Touch, not so much, but for elephants maybe. The vibrations. Vibrations. Olfaction, definitely, because of the concentration of, the more concentrated something is, the more likely it is to be close to you. So animals developed senses. They developed a head, like a literal head. So amphioxus doesn't even have a head, really. It's just a long- What's the purpose of a head? That's a great question. Is it to have a jaw? That's a great question. So jaw, so yes, jaws are a major- Useful feature. Yeah, obviously they're a major adaptation after there's a split between vertebrates and invertebrates. So amphioxus is thought to be very, very similar to the animal that's before that split. But then after the development, very quickly after the development of a head is the development of a jaw, which is a big thing. And what goes along with that is the development of a brain. Is that just a coincidence that the thing, the part of our body, of the mammal, I think, body, that we eat with and attack others with is also the thing that contains all the majority of the brain type of stuff? Well, actually, the brain goes with the development of a head and the development of a visual system and an auditory system and an olfactory system and so on. So your senses are developing. And the other thing that's happening, right, is that animals are getting bigger. Because they're, and also their niche is getting bigger. Well, this is the, just sorry to take a tiny tangent on the niche thing, is it seems like the niche is getting bigger, but not just bigger, like more complicated, like shaped in weird ways. So like predation seems to create, like the whole world becomes your oyster, whatever. But like you also start to carve out the places in which you can operate the best. Yeah, and in fact, that's absolutely right. And in fact, some scientists think that theory of mind, your ability to make inferences about the inner life of other creatures, actually developed under the selection pressure of predation. Because it makes you a better predator. Do you ever look at, you just said you looked at babies as these wiring creatures. Do you ever think of humans as just clever predators? Like that there is under, underneath it all is this, the Nietzschean will to power in all of its forms? Or are we now friendlier? Yeah, so it's interesting. I mean, there are zeitgeists in how humans think about themselves, right? And so if you look in the 20th century, you can see that the idea of an inner beast, that we're just predators, we're just basically animals, baseless animals, violent animals that have to be contained by culture and by our prodigious neocortex, really took hold, particularly after World War I, and really held sway for much of that century. And then around, at least in Western writing, I would say, you know, we're talking mainly about Western scientific writing, Western philosophical writing. And then, you know, late 90s maybe, you start to see books and articles about our social nature, that we're social animals. And we are social animals, but what does that mean exactly? And about- It's us carving out different niches in the space of ideas, it looks like. I think so, I think so. So, you know, do humans, can humans be violent? Yes. Can humans be really helpful? Yes, actually. And humans are interesting creatures because, you know, other animals can also be helpful to one another. In fact, there's a whole literature, booming literature on how other animals are, you know, support one another. They regulate each other's nervous systems in interesting ways, and they will be helpful to one another, right? So for example, there's a whole literature on rodents and how they signal one another, what is safe to eat, and they will perform acts of generosity to their conspecifics that are related to them or who they were raised with. So if an animal was raised in a litter that they were raised in, although not even at the same time, they'll be more likely to help that animal. So there's always some kind of physical relationship between animals that predicts whether or not they'll help one another. For humans, you know, we have ways of categorizing who's in our group and who isn't by non-physical ways, right, even by just something abstract like an idea. And we are much more likely to extend help to people in our own group, whatever that group may be, at that moment, whatever feature you're using to define who's in your group and who isn't, we're more likely to help those people than even members of our own family at times. So humans are much more flexible in their, in the way that they help one another, but also in the way that they harm one another. So I don't, I don't think I subscribe to, I don't think I subscribe to, you know, we are primarily this or we are primarily that. I don't think humans have essences in that way, really. I apologize to take us in this direction for a brief moment, but I've been really deep on Stalin and Hitler recently in terms of reading. And is there something that you think about in terms of the nature of evil from a neuroscience perspective? Is there some lessons that are sort of hopeful about human civilization that we can find in our brain with regard to the Hitlers of the world? Do you think about the nature of evil? Yeah, I do. I don't know that what I have to say is so useful from a, I don't know that I can say as a neuroscientist, well, here's a study that, you know, so I sort of have to take off my lab coat, right? And now I'm gonna now conjecture as a human who just also, who has opinions, but who also maybe has some knowledge about neuroscience. But I'm not speaking as a neuroscientist when I say this, because I don't think neuroscientists know enough, really, to be able to say. But I guess the kinds of things I think about are what, so I have always thought, even before I knew anything about neuroscience, I've always thought that, I don't think anybody could become Hitler, but I think the majority of people can be, can do, are capable of doing very bad things. It's just, the question is really how much encouragement does it take from the environment to get them to do something bad? That's what I, kind of when I look at the life of Hitler, it seems like there's so many places where- Something could have intervened. Intervened, no, it could change completely the person. I mean, there's like the caricature, like the obvious places where he was an artist, and if he wasn't rejected as an artist, he was a reasonably good artist, so that could have changed. But just his entire, like where he went in Vienna and all these kinds of things, little interactions could have changed. And there's probably millions of other people who are capable, who the environment may be able to mold in the same way did this particular person to create this particular kind of charismatic leader in this particular moment of time. Absolutely, and I guess the way that I would say it, I would agree 100%, and I guess the way that I would say it is like this. In the West, we have a way of reasoning about causation, which focuses on single, simple causes for things. There's an essence to Hitler, there's an essence to his character. He was born with that essence, or it was forged very, very early in his life, and that explains the landscape of his, the horrible landscape of his behavior. But there's another way to think about it, a way that actually is much more consistent with what we know about biology, how biology works in the physical world, and that is that most things are complex, not as in, wow, this is really complex and hard, but complex as in complexity, that is more than the sum of their parts, and that most phenomena have many, many weak, non-linear interacting causes. And so little things that we might not even be aware of can shift someone's developmental trajectory from this to that, and that's enough to take it on a whole set of other paths, and that these things are happening all the time. So it's not random, and it's not really, it's not deterministic in the sense that everything you do determines your outcome, but it's a little more like, you're nudging someone from one set of possibilities to another set of possibilities, but I think the thing that I find optimistic is that the other side of that coin is also true, right? So look at all the people who risk their lives to help people they didn't even know. I mean, I just watched Borat, the new Borat movie, and the thing that I came away with, but you know, the thing I came away with was, look at how generous people were in that, oh, because he's making, there are a lot of people he makes fun of, and that's fine, but think about those two guys, those- The Trump supporter guys. The Trump supporter guys. Those guys- That was cool. There's kindness in them, right? They took a complete stranger in a pandemic into their house. Who does that? That's a really nice thing, or there's one scene, I mean, I don't wanna spoil it for people who haven't seen it, but- Spoiler alert. But there's one scene where he goes in, he dresses up as a Jew. I laugh myself sick at that scene, seriously, but he goes in and there are these two old Jewish ladies. What a bunch of sweethearts, oh my gosh, like really? I mean, that was what I was struck by, actually. I mean, there are other ones, or like the babysitter, right? I mean, she was really kind, and yeah, so that's really what I was more struck by. Sure, there are other people who do very bad things or say bad things or whatever, but there's one guy who's completely stoic, like the guy who's doing the, sending the messages, I don't know if it's fax or whatever. He's just completely stoic, but he's doing his job, actually. You don't know what he was thinking inside his head. You don't know what he was feeling, but he was totally professional doing his job. So I guess I just, I had a bit of a different view, I guess. So I also think that about people. I think everybody is capable of kindness, but the question is how much does it take and what are the circumstances? So for some people, it's gonna take a lot, and for some people, it only takes a little bit. But are we actually cultivating an environment for the next generation that provides opportunities for people to go in the direction of caring and kindness? And I'm not saying that as like a Pollyanna-ish person. I think there's a lot of room for competition and debate and so on, but I don't see Hitler as an anomaly. And I never have. That was even before I learned anything about neuroscience. And now I would say knowing what we know about developmental trajectories and life histories and how important that is, knowing what we know about that the whole question of nature versus nurture is a completely wrong question. We have the kind of nature that requires nurture. We have the kind of genes that allow infants to be born with unfinished brains where their brains are wired across a 25-year period with wiring instructions from the world that is created for them. And so I don't think Hitler is an anomaly. Even if it's less probable that that would happen, it's possible that it could happen again. And it's not like he's a bad seed. I mean, that doesn't, I just wanna say, of course he's completely 100% responsible for his actions and all the bad things that happen. So I'm not in any way, this is not me saying. But the environment is also responsible in part for creating the evil in this world. So like Hitler's in different versions of even more subtle, more smaller scale versions of evil. But I tend to believe that there's a much stronger, I don't like to talk about evolutionary advantages, but it seems like it makes sense for love to be a more powerful emergent phenomena of our collective intelligence versus hate and evil and destruction. Because from a survival, from a niche perspective, it seems to be, like in my own life, in my thinking about the intuition about the way humans work together to solve problems, it seems that love is a very useful tool. I definitely agree with you. But I think the caveat here is that humans, the research suggests that humans are capable of great acts of kindness and great acts of generosity to people in their in-group. Right. And- So we're also tribal. Yeah, I mean, that's the kitschy way to say it. We're tribes, we're tribal, yeah. So that's the kitschy way to say it. What I would say is that there are a lot of features that you can use to describe yourself. You don't have one identity, you don't have one self, you have many selves, you have many identities. Sometimes you're a man, sometimes you're a scientist, sometimes you're a, do you have a brother or a sister? Yeah, brother. So sometimes you're a brother. Sometimes you're a friend. Sometimes you're a human, so you can keep zooming out. Yes, exactly. Living organism on Earth. Yes, exactly, that's exactly right. And so there are some people who, there is research which suggests that there are some people who will tell you, I think it's appropriate and better to help, I should help my family more than I should help my neighbors and I should help my neighbors more than I should help the average stranger and I should help the average stranger in my country more than I should help somebody outside my country and I should help humans more than I should help other animals. And I should, so there's a clear hierarchy of helping. And there are other people who, their niche is much more inclusive, right? And that they're humans first, right? Or creatures of the Earth first, let's say. And I don't think we know how flexible those attitudes are because I don't think the research really tells us that. But in any case, there are, and there are beliefs, people also have beliefs about, there's this really interesting research in really in anthropology that looks at what are cultures particularly afraid of? Like what, the people in a particular culture are organizing their social systems to prevent certain types of problems. So what are the problems that they're worried about? And so there are some cultures that are much more hierarchical and some cultures that are much more egalitarian. There are some cultures that in the debate of getting along versus getting ahead, there are some cultures that really prioritize the individual over the group. And there are other cultures that really prioritize the group over the individual. It's not like one of these is right and one of these is wrong. It's that different combinations of these features are different solutions that humans have come up with for living in groups, which is a major adaptive advantage of our species. And it's not the case that one of these is better and one of these is worse. Although as a person, of course, I have opinions about that. And as a person, I can say, I would very much prefer certain, I have certain beliefs and I really want everyone in the world to live by those beliefs. But as a scientist, I know that it's not really the case that for the species, any one of these is better than any other. There are different solutions that work differentially well in particular, you know, ecological parts of the world. But for individual humans, there are definitely some systems that are better and some systems that are worse, right? But when anthropologists or when neuroscientists or biologists are talking, they're not usually talking about the lives of individual people. They're talking about, you know, the species, what's better for the species, the survivability of the species. And what's better for the survivability of the species is variation, that we have lots of cultures with lots of different solutions because if the environment were to change drastically, some of those solutions will work better than others. And you can see that happening with COVID. Right, so some people might be more susceptible to this virus than others. And so variation is very useful. Say COVID was much, much more destructive than it is. And like, I don't know, 20% of the population died. So, you know, it's good to have variability because then at least some percent will survive. Yeah, I mean, the way that I used to describe it was using, you know, those movies like the War of the Worlds or Pacific Rim, you know, where like aliens come down from outer space and they, you know, wanna kill humans. And so all the humans band together as a species and they all, like all the, you know, little squabbling from countries and whatever, all, you know, goes away and everyone is just one big, you know, well, that, you know, that doesn't happen. I mean, because COVID, you know, a virus like COVID-19 is like a creature from outer space. And that's not what you see happening. What you do see happening, it is true that some people, I mean, we could use this as an example of essentialism also. So just to say like exposure to the virus does not mean that you will become infected with a disease. So, I mean, in controlled studies, one of which was actually a coronavirus, not COVID, but this was, these are studies from 10 or so years ago, you know, only somewhere between 20 and 40% of people were developed respiratory illness when a virus was placed in their nose. And so- And there's a dose question, all those- Well, not in these studies, actually. So in these studies, the dose was consistent across all people and everything, you know, they were sequestered in hotel rooms and what they ate was, you know, measured out by scientists and so on. And so when you hold dose, I mean, the dose issue is a real issue in the real world, but in these studies, that was controlled. And only somewhere between 20, depending on the study, between 20 and 40% of people became infected with a disease. So exposure to a virus doesn't mean de facto that you will develop an illness. You will be a carrier and you will spread the virus to other people, but you yourself may not, your immune system may be in a state that you can make enough antibodies to not show symptoms, not develop symptoms. And so, of course, what this means is, again, is that, you know, like if I asked you, do you think a virus is the cause of a common cold, or, you know, most people, if I asked this question, I can tell you, I asked this question. So do you think a virus is the cause of a cold? Most people would say, yes, I think it is. And then I say, yeah, well, only 20 to 40% of people develop respiratory illness in exposure to a virus. So clearly, it is a necessary cause, but it's not a sufficient cause. And there are other causes, again, so not simple single causes for things, right? Multiple interacting influences. So it is true that individuals vary in their susceptibility to illness upon exposure, but different cultures have different sets of norms and practices that allow, that will slow or speed the spread. And that's the point that I was actually trying to make here that, you know, when the environment changes, that is, there's a mutation of a virus that is incredibly infectious, some cultures will succumb, people in some cultures will succumb faster because of the particular norms and practices that they've developed in their culture versus other cultures. Now, there could be some other, you know, thing that changes that, where those other cultures, you know, would do better. So very individualistic cultures like ours may do much better under other types of selection pressures, but for COVID, for things like COVID, you know, my colleague, Michelle Gelfand, her research shows that she looks at like loose cultures and tight cultures, so cultures that have very, very strict rules versus cultures that are much more individualistic and where personal freedoms are more valued. And she, you know, her research suggests that for a pandemic circumstances, tight cultures actually, the people survive better. Just to linger a little bit longer, we started this part of the conversation talking about, you know, did humans evolve to think, did the human brain evolve to think, implying is there like a progress to the thing that's always improving? That's right, we never, yeah. And so the answer is no. But let me sort of push back, so your intuition is very strong here, not your intuition, the way you described this, but is it possible there's a direction to this evolution? Like, do you think of this evolution as having a direction? Like it's like walking along a certain path towards something? Is it, you know, what is it? Is it Elon Musk said like the earth got bombarded with photons and then all of a sudden, like a Tesla was launched into space or whatever, a rocket started coming. Like, is there a sense in which, even though in the, like within the system, the evolution seems to be this massive variation, we're kind of trying to find our niches and so on, but do you think there ultimately when you zoom out, there is a direction that's strong, that does tend towards greater complexity and intelligence? No. So, I mean, and again, what I would say is I'm really just echoing people who are much smarter than I am about this. But see, you're saying smarter. I thought it doesn't, there's no, I thought there's no smarter. No, I didn't say there's no smarter, I said there's no direction. So I think the thing to say or what I understand to be the case is that there's variation. It's not unbounded variation. And there are selectors. There are pressures that will select. And so not anything is possible because we live on a planet that has certain physical realities to it, right? But those physical realities are what constrain the possibilities, the physical realities of our genes and the physical realities of our corporeal bodies and the physical realities of life on this planet. So what I would say is that there's no direction, but there is, it's not infinite possibility because we live on a particular planet that has particular statistical regularities in it and some things will never happen. And so all of those things are interacting with our genes and so on and our, you know, the physical nature of our bodies to make some things more possible and some things less possible. Look, I mean, humans have very complex brains, but birds have complex brains. And so do, you know, so do octopuses have very complex brains. And all three sets of, all three of those brains are somewhat different from one another. You know, birds, some birds have very complex brains. Some even have rudimentary language. They have no cerebral cortex. I mean, they, admittedly, they have, this is now lesson two, right? They have, is it lesson two or lesson one? Let me think. No, this is lesson one. They have, they have the same neurons, the same neurons that in a human become the cerebral cortex. Birds have those neurons. They just don't form themselves into a cerebral cortex. But I mean, crows, for example, are very sophisticated animals. They can do a lot of the things that humans can do. In fact, all of the things that humans do that are very special, that seem very special, there's at least one other animal on the planet that can do those things too. What's special about the human brain is that we put them all together. So we learn from one another. We don't have to experience everything ourselves. We can watch another animal or another human experience something and we can learn from that. Well, there are many other animals who can learn by copying. That we communicate with each other very, very efficiently. We have language. But we're not the only animals who are efficiently, efficient communicators. There are lots of other animals who can efficiently communicate, like bees, for example. We cooperate really well with one another to do grand things. But there are other animals that cooperate too. And so every innovation that we have, other animals have too. What we have is we have all of those together, interwoven in this very complex dance, in a brain that is not unique, exactly, but that is, it does have some features that make it particularly useful for us to do all of these things, to have all of these things intertwined. So our brains are, actually the last time we talked, I made a mistake. Because I said, in my enthusiasm, I said, our brains are not larger, relative to our bodies, our brains are not larger than other primates. And that's actually not true, actually. Our brains, relative to our body size, is somewhat larger. So an ape, who's not a human, that's not a human, their brains are larger than their body sizes than, say, relative to a smaller monkey. And a human's brain is larger, relative to its body size, than a gorilla or a. So that's a good approximation of your, of whatever, of the bunch of stuff that you can shove in there. But, well, what I was gonna say is, but our cerebral cortex is not larger than what you would expect for a brain of its size. So relative to, say, an ape, like a gorilla or a chimp, or even a mammal, like a dolphin or an elephant, you know, our brains, our cerebral cortex is as large as you would expect it to be for a brain of our size. So there's nothing special about our cerebral cortex. And this is something I explain in the book, where I say, okay, you know, like by analogy, if you walk into somebody's house and you see that they have a huge kitchen, you know, you might think, well, maybe, you know, maybe this is a place I really definitely wanna eat dinner at because, you know, these people must be gourmet cooks. But you don't know anything about what the size of their kitchen means unless you consider it in relation to the size of the rest of the house. If it's a big kitchen in a really big house, it's not telling you anything special, right? If it's a big kitchen in a small house, then that might be a place that you wanna eat for, you wanna stay for dinner, because it's more likely that that kitchen is large for a special reason. And so the cerebral cortex of a human brain isn't in and of itself special because of its size. However, there are some genetic changes that have happened in the human brain as it's grown with to whatever size is, you know, typical for the whole brain size, right? There are some changes that do give the human brain slightly more of some capacities. They're not special, but there's just, they just, you know, we can do some things much better than other animals. And, you know, correspondingly, other animals can do some things much better than we can. We can't grow back limbs, we can't lift 50 times our own body weight. Well, I mean, maybe you can, but I can't lift 50 times my own body weight. Ants with that regard are very impressive. And then you're saying with the frontal cortex, like that's, the size is not always the right measure of capability, I guess. So size isn't everything. Size isn't everything. That's a quote about, you know, people like it when I disagree, so let me disagree with you on something, or just like play devil's advocate a little bit. So you've painted a really nice picture that evolution doesn't have a direction, but is it possible if we just ran Earth over and over again, like this video game, that the final result will be the same? So in the sense that we're, eventually there'll be an AGI type HAL 9000 type system that just like flies and colonizes nearby Earth-like planets, and it's always will be the same. And the different organisms and the different evolution of the brain, like it doesn't feel like it has like a direction, but given the constraints of Earth, and whatever this imperative, whatever the hell is running this universe, like it seems like it's running towards something, is it possible that it will always be the same? Thereby, it will be a direction. Yeah, I think, you know, as you know better than anyone else, that the answer to that question is, of course, there's some probability that that could happen, right? It's not a yes or no answer, it's what's the probability that that would happen? And there's a whole distribution of possibilities. So maybe we end up, what's the probability we end up with exactly the same complement of creatures, including us? What's the likelihood that we end up with, you know, creatures that are similar to humans, that are, but you know, similar in certain ways, let's say, but not exactly humans, or you know, all the way to a completely different distribution of creatures? What's your intuition? Like if you were to bet money, what does that distribution look like if we ran Earth over and over and over again? I would say given the, you're now asking me questions that- This is not science. This is not science. But I would say, okay, well, what's the probability that it's gonna be a carbon life form? Probably high, but that's because I don't know anything about really- Alternatives? Yeah, you know, I don't, I'm not really well versed that. What's the probability that, you know, so what's the probability that the animals will begin in the ocean and crawl out onto land? Versus the other way. Versus the, I would say probably high. I don't know, but you know, but do I think, what's the likelihood that we would end up with exactly the same or very similar? I think it's low, actually. I wouldn't say it's low, but I would say it's not, it's not 100% and I'm not even sure it's 50%. You know, I would say, I don't think that we're here by accident because I think, like I said, there are constraints. Like there are some physical constraints about Earth. Now, of course, if you were a cosmologist, you could say, well, the fact that the Earth is, if you were to do the Big Bang over again and keep doing it over and over and over again, would you still get the same solar systems? Would you still get the same planets? Would, you know, would you still get the same galaxies, the same solar systems, the same planets? You know, I don't know, but my guess is probably not because there are random things that happen that can, again, send things in one direct, you know, make one set of trajectories possible and another set impossible. So, but I guess my, if I were gonna bet something, money or something valuable, I would probably say it's not zero and it's not 100% and it's probably not even 50%. So, there's some probability, but I don't know. That it will be similar. That it will be similar, but I don't think, I just think there are too many degrees of freedom. There are too many degrees of freedom. I mean, one of the real tensions in writing this book is to, on the one hand, there's some truth in saying that humans are not special. We are just, you know, we're not special in the animal kingdom. All animals are well-adapted. If they're survived, they're well-adapted to their niche. It does happen to be the case that our niche is large. For any individual human, your niche is whatever it is, but for the species, right, we live almost everywhere, not everywhere, but almost everywhere on the planet, but not in the ocean, and actually other animals like bacteria, for example, have us beat miles, you know, hands down, right? So, by any definition, we're not special. We're just, you know, adapted to our environment. But bacteria don't have a podcast. Exactly, exactly. They're not able to introspect. So, that's the tension, right? So, on the one hand, you know, we're not special animals. We're just, you know, particularly well-adapted to our niche. On the other hand, our niche is huge, and we don't just adapt to our environment. We add to our environment. We make stuff up, give it a name, and then it becomes real. And so, no other animal can do that. And so, I think the way to think about it from my perspective, or the way I made sense of it, is to say, you can look at any individual single characteristic that a human has that seems remarkable, and you can find that in some other animal. What you can't find in any other animal is all of those characteristics together in a brain that is souped up in particular ways, like ours is. And if you combine these things, multiple interacting causes, right? Not one essence, like your big neocortex, but, which isn't really that big. I mean, it's just big for your big brain, for the size of your big brain. It's the size it should be. If you add all those things together, and they interact with each other, that produces some pretty remarkable results. And if you're aware of that, then you can start asking different kinds of questions about what it means to be human, and what kind of a human you wanna be, and what kind of a world do you wanna curate for the next generation of humans? So, I think that's the goal anyways, right? It's just to have a glimpse of, instead of thinking about things in a simple, linear way, just to have a glimpse of some of the things that matter, that evidence suggests matters, to the kind of brain in the kind of bodies that we have. Once you know that, you can work with it a little bit. You write, words have power over your biology. Right now, I can text the words, I love you, from the United States to my close friend in Belgium. And even though she cannot hear my voice or see my face, I will change her heart rate, her breathing, and her metabolism. By the way, beautifully written. Or someone could text something ambiguous to you, like, is your door locked? And odds are that it would affect your nervous system in an unpleasant way. So, I mean, there's a lot of stuff to talk about here, but just one way to ask is, why do you think words have so much power over our brain? Well, I think we just have to look at the anatomy of the brain to answer that question. So, if you look at the parts of the brain, the systems that are important for processing language, you can see that some of these regions are also important for controlling your major organ systems and your autonomic nervous system that controls your cardiovascular system, your respiratory system, and so on, that these regions control your endocrine system, your immune system, and so on. So, and you can actually see this in other animals, too. So, in birds, for example, the neurons that are responsible for bird song also control the systems of a bird's body. And the reason why I bring that up is that some scientists think that the anatomy of a bird's brain that control bird song are homologous or structurally have a similar origin to the human system for language. So, the parts of the brain that are important for processing language are not unique and specialized for language. They do many things. And one of the things they do is control your major organ systems. Do you think we can fall in love, I have arguments about this all the time, do you think we can fall in love based on words alone? Well, I think people have been doing it for centuries. I mean, it used to be the case that people wrote letters to each other. And then that was how they communicated. I guess that's how you and Dan got. Exactly, exactly, exactly, yeah, exactly. So, is the answer a clear yes there? Because I get a lot of pushback from people often that you need the touch and the smell and the bodily stuff. I think the touch and the smell and the bodily stuff helps. Okay. But I don't think it's necessary. Do you think you can have a lifelong monogamous relationship with an AI system that only communicates with you in a romantic context, romantic relationship? Well, I suppose that's an empirical question that hasn't been answered yet. But I guess what I would say is, I don't think I could. Could any human, could the average human? So, if I, even I wanna even modify that and say, I'm thinking now of Tom Hanks and the movie. Castaway? Yeah, with Wilson. Yeah. I think if you had to make that work, if you had to make that work. With the volleyball, yeah. If you had to make it work, could you, prediction and simulation, right? So, if you had to make it work, could you make it work? Using simulation and your past experience, could you make it work? Could you make it work, you as a human, could you? Could you have a relationship literally with an inanimate object and have it sustain you in the way that another human could? Your life would probably be shorter because you wouldn't actually derive the body budgeting benefits from, right? So, we've talked about how your brain, its most important job is to control your body and you can describe that as your brain running a budget for your body. And there are metaphorical deposits and withdrawals into your body budget. And you also make deposits and withdrawals in other people's body budgets, figuratively speaking. So, you wouldn't have that particular benefit. So, your life would probably be shorter. But I think it would be harder for some people than for other people. Yeah, I tend to, my intuition is that you can have a deep, fulfilling relationship with a volleyball. I think a lot of the environments that set up, I think that's a really good example. Like the constraints of your particular environment define the, like, I believe like scarcity is a good catalyst for deep, meaningful connection with other humans and with inanimate objects. So, the less you have, the more fulfilling those relationships are. And I would say a relationship with a volleyball, the sex is not great, but everything else, I feel like it could be a very fulfilling relationship, which I don't know, from an engineering perspective, what to do with that. And just like you said, it is an empirical question. But there are places to learn about that, right? So, for example, think about children and their blankets. Right, so there, there's something tactile and there's something olfactory. And it's very comforting. I mean, even for non-human little animals, right? Like puppies and, so I don't know about cats, but. But. Cats are cold-hearted. There's no, there's nothing going on there. I don't know. There are some cats that are very dog-like. I mean, really, so. Some cats identify as dogs, yes. I think that's true. Yeah, they're species fluid. So, you also write, when it comes to human minds, variation is the norm. And what we call, quote, human nature is really many human natures. Again, many questions I can ask here. But maybe an interesting one to ask is, I often hear, you know, we often hear this idea of be yourself. Is this possible to be yourself? Is it a good idea to strive to be yourself? Is it, does that even have any meaning? It's a very Western question, first of all. Because which self are you talking about? You don't have one self. There is no self that's an essence of you. You have multiple selves. Actually, there is research on this. You know, to quote the great social psychologist, Hazel Marcus, you're never, you cannot be a self by yourself. You, you know, you. And so, different contexts pull for, or draw on different features of your, of who you are or what you believe, what you feel, what your actions are. Different contexts, you know, will put certain things, or make more, some features be more in the foreground and some in the background. It takes us back right to our discussion earlier about Stalin and Hitler and so on. The thing that I would caution, in addition to the fact that there is no single self, you know, that you have multiple selves, who you can be, and you can certainly choose the situations that you put yourself in to some extent. Not everybody has complete choice, but everybody has a little bit of choice. And I think I said this to you before, that one of the pieces of advice that we gave Sophia, you know, when she went, our daughter, when she was going off to college, was try to spend time around people, choose relationships that allow you to be your best self. We should have said your best selves, but. The pool of selves, given the environment. Yeah, but the one thing I do wanna say is that the risk of saying be yourself, just be yourself, is that that can be used as an excuse. Well, this is just the way that I am. I'm just like this. And that, I think, should be tremendously resisted. So that's one, that's for the excuse side, but I'm really self-critical often, I'm full of doubt, and people often tell me, just don't worry about it, just be yourself, man. And the thing is, it's not, from an engineering perspective, does not seem like actionable advice. Because I guess constantly worrying about who, what are the right words to say to express how I'm feeling is, I guess, myself. There's a kind of line, I guess, that this might be a Western idea, but something that feels genuine and something that feels non-genuine. And I'm not sure what that means, because I would like to be fully genuine and fully open, but I'm also aware, like this morning, I was very silly and giddy. I was just being funny and relaxed and light. There's nothing that could bother me in the world. I was just smiling and happy. And then I remember last night, was just feeling very grumpy, like stuff was bothering me. Like certain things were bothering me. And like, what are those? Are those the different selves? Like what, who am I in that? And what do I do? Because if you take Twitter as an example, if I actually send a tweet last night and a tweet this morning, it's gonna be very two different people tweeting that. And I don't know what to do with that, because one does seem to be more me than the other. But that's maybe because there's a narrative, the story that I'm trying, there's something I'm striving to be, like the ultimate human that I might become. I have maybe a vision of that, and I'm trying to become that. But it does seem like there's a lot of different minds in there. And they're all like having a discussion and a battle for who's gonna win. I suppose you could think of it that way, but there's another way to think of it, I think. And that is that maybe the more Buddhist way to think of it, right? Or a more contemplative way to think about it, which is not that you have multiple personalities inside your head, but you have, your brain has this amazing capacity. It has a population of experiences that you've had that it can regenerate, reconstitute. And it can even take bits and pieces of those experiences and combine them into something new. And it's often doing this to predict what's going to happen next and to plan your actions. But it's also happening, this also happens just, that's what mind-wandering is, or just internal thought and so on. That's, it's the same mechanism, really. And so a lot of times we hear the saying, just think, if you think differently, you'll feel differently. But your brain is having a conversation continually with your body. And your body, your brain's trying to control your body, well, trying, your brain is controlling your body, your body is sending information back to the brain. And in part, the information that your body sends back to your brain, just like the information coming from the world, initiates the next volley of predictions or simulations. So in some ways, you could also say, the way that you feel, I think we talked before about affective feeling or mood coming from the sensations of body budgeting, you know, influences what you think. And as much as, so feelings influence thought as much as thought influence feeling, and maybe more. But just, the whole thing doesn't seem stable. Well, it's a dynamic system, Mr. Engineer. Yeah. Right, it's a dynamic, it's a dynamical system, right? Nonlinear dynamical system. And I think that's, I'm actually writing a paper with a bunch of engineers about this, actually. But I mean, other people have talked about the brain as a dynamical system before, but you know, the real tricky bit is trying to figure out how do you get mental features out of that system? I guess one thing to figure out how you get a motor movement out of that system, it's another thing to figure out how you get a mental feature, like a feeling of being loved or a feeling of being worthwhile, or a feeling of, you know, just basically feeling like shit. How do you get a feeling, a mental features out of that system? So what I would say is that you aren't, the Buddhist thing to say is that you're not one person and you're not many people. You are the sum of your experiences and who you are in any given moment, meaning what your actions will be, is influenced by the state of your body and the state of the world that you've put yourself in. And you can change either of those things. One is a little easier to change than the other, right? You can change your environment by literally getting up and moving, or you can change it by paying attention to some things differently and letting some features come to the fore and other features be backgrounded. Like I'm looking around your place. Oh no, this is not something you should do. No, but I'm gonna say one thing. No green plants. No green plants. Because green plants mean a home and I want this to be temporary. Fair, fair, but. What goes through your mind when you see no green plants? No, I'm just making the point that what if you, again, not everybody has control over their environment. Some people don't have control over the noise or the temperature or any of those things. But everybody has a little bit of control and you can place things in your environment, photographs, plants, anything that's meaningful to you and use it as a shift of environment when you need it. You can also do things to change the conditions of your body. When you exercise every day, you're making an investment in your body. Actually, you're making an investment in your brain too. It makes you, even though it's unpleasant and there's a cost to it, if you replenish, if you invest and you make up that, you make a deposit and you make up that, what you've spent, you're basically making an investment in making it easier for your brain to control your body in the future. So you can make sure you're hydrated, drink water. You don't have to drink bottled water. You can drink water from the tap. This is in most places, maybe not everywhere, but most places in the developed world. You can try to get enough sleep. Not everybody has that luxury, but everybody can do something to make their body budgets a little more solvent. And that will also make it more likely that certain thoughts will emerge from that prediction machine, basically. That's the control you do have, is being able to control the environment. That's really well put. I don't think we've talked about this, so let's go to the biggest unanswerable questions of consciousness. What is, you just rolled your eyes. I did, that was my, yeah. So what is consciousness from a neuroscience perspective? I know you, I mean. I made notes, you know, because you gave me some questions in advance, and I made notes for every single. Oh, except that one? Yeah, well, that one I had, what the fuck? And then I took it out. So is there something interesting, because you're so pragmatic, is there something interesting to say about intuition building about consciousness? Or is this something that we're just totally clueless about, that this is, let's focus on the body, the brain listens to the body, the body speaks to the brain, and let's just figure this piece out, and then consciousness will probably emerge somehow after that. No, I think, you know, well, first of all, I'll just say up front, I am not a philosopher of consciousness, and I'm not a neuroscientist who focuses on consciousness. I mean, in some sense, I do study it, because I study affect and mood, and that is the, you know, to use the phrase, that is the hard question of consciousness. How is it that your brain is modeling your body? Brain is modeling the sensory conditions of your body, and it's being updated, that model is being updated by the sense data that's coming from your body, and it's happening continuously your whole life, and you don't feel those sensations directly. What you feel is a general sense of pleasantness or unpleasantness, comfort, discomfort, feeling worked up, feeling calm, so we call that affect, you know, most people call it mood. So how is it that your brain gives you this very low-dimensional feeling of mood or affect when it's presumably receiving a very high-dimensional array of sense data, and the model that the brain is running of the body has to be high-dimensional, because there's a lot going on in there, right? You're not aware, but as you're sitting there quietly, as your listeners, as our viewers are sitting. They might be working out, running now, or as many of them write to me, they're laying in bed, smoking weed with their eyes closed in the street. That's fair, so maybe we should say that bit again then. So if, so some people may be working out, some people may be, you know, relaxing. But even if you're sitting very still while you're watching this or listening to this, there's a whole drama going on inside your body that you're largely unaware of. Yet, your brain makes you aware, or gives you a status report in a sense, by virtue of these mental features of feeling pleasant, feeling unpleasant, feeling comfortable, feeling uncomfortable, feeling energetic, feeling tired, and so on. And so how the hell is it doing that? That is the basic question of consciousness. And like the status reports seem to be, in the way we experience them, seem to be quite simple. Like, it doesn't feel like there's a lot of data. Yeah, no, there isn't. So when you feel discomfort, when you're feeling basically like shit, you feel like shit, what does that tell you? Like, what are you supposed to do next? What caused it? I mean, the thing is, not one thing caused it, right? It's multiple factors probably influencing your physical state. Your body budget. It's very high dimensional, yeah. It's very high dimensional. And there are different temporal scales of influence, right? So the state of your gut is not just influenced by what you ate five minutes ago. It's also what you ate a day ago and two days ago, and so on. So I think, I think, you know, when I'm, I'm not trying to weasel out of the question. I just think it's the hardest question, actually. Do you think we'll ever understand it? As scientists. I think that we will understand it as well as we understand other things, like the birth of the universe, or the, you know, the nature of the universe, I guess I would say. So do I think we can get to that level of an explanation? I do, actually, but I think that we have to start asking somewhat different questions and approaching the science somewhat differently than we have in the past. I mean, it's also possible that consciousness is much more difficult to understand than the nature of the universe. It is, but I wasn't necessarily saying that it was a question that was of equivalent complexity. I was saying that I do think that we could get to some, I am optimistic that, I would not, I would be very willing to invest my, the time, my time on this earth as a scientist in trying to answer that question if I could do it the way that I wanna do it, not the way that it's currently being done. So like rigorously? I don't wanna say unrigorously. I just wanna say that there are a certain set of assumptions that, you know, scientists have what I would call ontological commitments. They're commitments about the way the world is or the way that nature is, and these commitments lead scientists sometimes blindly without, they don't, scientists sometimes, sometimes scientists are aware of these commitments, but sometimes they're not. And these commitments, nonetheless, influence how scientists ask questions, what they measure, how they measure, and I just have very different views than a lot of my colleagues about the ways to approach this. Not everybody, but the way that I would approach it would be different and it would cost more and it would take longer. It doesn't fit very well into the current incentive structure of science. And so do I think that doing science the way science is currently done with the budget that it currently has and the incentive structure that it currently has, will we have an answer? No, I think absolutely not. Good luck is what I would say. People love book recommendations. Let me ask what three books? Oh, you can't just give me three. I mean, like, really, three? What seven and a half books you can recommend? So you're also the author of seven and a half lessons about the brain. You're author of How Emotions Are Made. Okay, so definitely those are the top two recommendations of all, the two greatest books of all time. Other than that, are there books that, technical, fiction, philosophical, that you've enjoyed or you might recommend to others? Yes. Actually, you know, every PhD student, when they graduate with their PhD, I give them a set, like a little library, like a set of books, you know, some of which they've already read, some of which I want them to read. But I think nonfiction books, I would read, the things I would recommend are The Triple Helix by Richard Luontan. It's a little book published in 2000, which is, I think, a really good introduction to complexity and population thinking, as opposed to essentialism. So this idea, essentialism is this idea that, you know, there's an essence to each person, whether it's a soul or your genes or what have you, as opposed to this idea that you, we have the kind of nature that requires a nurturer. We are, we are, you are the product of a complex dance between an environment, between a set of genes and an environment that turns those genes on and off to produce your brain and your body and really who you are at any given moment. It's a good title for that, Triple Helix. So playing on the double helix, where it's just the biology, it's bigger than the biology. Exactly. It's a wonderful book. I've read it probably six or seven times throughout the year. He has another book, too, which is, it's more, I think, scientists would find it, I don't know, I loved it. It's called Biology as Ideology. And it really is all about, I wouldn't call it one of the best books of all time, but I love the book because it really does point out, you know, that science as it's currently practiced, I mean, the book was written in 1991, but it actually, I think, still holds, that science as it's currently practiced has a set of ontological commitments which are somewhat problematic. So the assumptions are limiting. Yeah, in ways that you, it's like you're a fish in water and you don't, like, okay, so here's the- David Foster Wallace and stuff. Well, but here's a really cool thing I just learned recently. Is it okay to go off on this tangent for a minute? Yeah, yeah, let's go tangents, great. I was just gonna say that I just learned recently that we don't have water receptors on our skin. So how do you know when you're sweating? How do you know when a raindrop, when it's gonna rain and, you know, like a raindrop hits your skin and you can feel that little drop of wetness? How is it that you feel that drop of wetness when we don't have water receptors in our skin? And I was, when I- My mind's blown already. Yeah, that was my reaction too, right? I was like, of course we don't because we evolved in the water. Like, why would we need, you know, it was just this, like, you know, you have these moments where you're like, oh, of course, there's like a, yeah, so- You'll never see rain the same way again. So the answer is it's a combination of temperature and touch. But it's a complex sense that's only computed in your brain. There's no receptor for it. Anyways. Yeah, that's why, like, snow versus cold rain versus warm rain all feel different because you're trying to infer stuff from the temperature and the size of the droplets is fascinating. Yeah, your brain is a prediction machine. It's using lots and lots of information combining it. Anyways, so. But, so, Biology is Ideology is, I wouldn't say it's one of the greatest books of all time, but it is a really useful book. There's a book by, if you're interested in psychology or the mind at all, there's a wonderful book, a little, it's a fairly small book called Naming the Mind by Kurt Danziger, who's a historian of psychology. Everybody in my lab reads both of these books. So what's the book? It's about the origin of the, where did we get the theory of mind that we have, that the human mind is populated by thoughts and feelings and perceptions, and where did those categories come from? Because they don't exist in all cultures. Oh, so this isn't, that's a cultural construct? The idea that you have thoughts and feelings and they're very distinct is definitely a cultural construct. That's another mind-blowing thing, just like the rain. So Kurt Danziger is a, the opening chapter in that book is absolutely mind-blowing. I love it, I love it. I just think it's fantastic. And I would say that there are many, many popular science books that I could recommend that I think are extremely well-written in their own way. You know, before I, maybe I said this to you, but before I undertook writing How Emotions Are Made, I read, I don't know, somewhere on the order of 50 or 60 popular science books to try to figure out how to write a popular science book, because while there are many books about writing, Stephen King has a great book about writing, on writing, and you know, where he gives tips interlaced with his own personal history. That was where I learned you write for a specific person. You have a specific person in mind, and that's, for me, that person is Dan. That's fascinating, I mean, that's a whole other conversation to have, like, which popular science books, like what you learn from that search, because there's, I have, for me, some popular science books are like, I just roll my eyes, like this is too, it's the same with TED Talks. Like, some of them go too much into the flowery, and I would say don't give enough respect to the intelligence of the reader. But this is my own bias, very specifically. I completely agree with you, and in fact, I have a colleague, his name is Van Yang, who, you know, he produced a cinematic lecture of how emotions are made that we wrote together with Joseph Fridman, no relation. Yes. Well, we're all related. Well, I mean, you and I are probably, you know, have some, yeah. Yeah, I remember. It's, the memories are in there somewhere. Yeah, it's from many, many, many generations ago. Well, half my family is Russian, so from. The good half. The good half, right. But, you know, he, his goal, actually, is to produce, you know, videos and lectures that are beautiful and educational and that don't dumb the material down. And he's really remarkable at it, actually. I mean, just, but again, you know, that requires a bit of a paradigm shift. We could have a whole conversation about the split between entertainment and education in this country and why it is the way it is, but that's another conversation. To be continued. But I would say, if I were to pick one book that I think is a really good example of good science writing, it would be The Beak of the Finch, which won a Pulitzer Prize a number of years ago. And I'm not, I'm not remembering the author's name. I'm blanking. But the, I'm guessing, is it focusing on birds and the evolution of birds? Actually, there's also The Evolution of Beauty, which is, yeah, which is also a great book. But no, The Beak of the Finch is, it's a, it has two storylines that are interwoven. One is about Darwin and Darwin's explorations in the Galapagos Island. And then modern day researchers from Princeton who have a research program in the Galapagos looking at Darwin's finches. And it's just a really, first of all, there's top-notch science in there. And really science, like, you know, evolutionary biology that a lot of people don't know. And it's told really, really well. It sounds like there also, there's a narrative in there. There's, it's like storytelling, too. Yeah, I think all good popular science books are storytelling, you know, but storytelling grounded, constrained by, you know, the evidence. And then I just wanna say that there are, for fiction, I'm a really big fan of love stories, just to return us to the topic that we began with. And so my, some of my favorite love stories are Major Pettigrew's Last Stand by Helen Simonson. It's a love story about people who you wouldn't expect to fall in love and all the people around them who have to overcome their prejudices. And I love this book. What do you like, like what makes a good love story? There isn't one thing, you know, there are many different things that make a good love story. But I think in this case, you can feel, you can feel the journey. You can feel the journey that these characters are on and all the people around them are on this journey, too, basically to come to grips with this really unexpected love, really profound love that develops between these two characters who are very unlikely to have fallen in love, but they do. And it's just, it's very gentle. Another book like that is the storied life of A.J. Feerke, which is also a love story, but in this case, it's a love story between a little girl and her adopted dad. And the dad is this like real curmudgeon-y, you know, guy, but of course there's a story there. And it's just a beautiful love story. But it also, it's like everybody in this community falls in love with him because he falls in love with her. And he, you know, she just gets left at his store, his bookstore, he has this failing bookstore. And he discovers that, you know, he feels like inexplicably this need to take care of this little baby. And this whole life emerges out of that one decision, which is really beautiful, actually. Very poignant. Do you think the greatest stories have a happy ending or a heartbreak at the end? That's such a Russian question. It's like Russian tragedies, you know? So I would say the answer to that for me, there has to be heartbreak. Yeah, I really don't like heartbreak. I don't like heartbreak. I want there to be a happy ending, or at least a hopeful ending. But, you know, like Dr. Zhivago, like, or the English patient. Oh my goodness, like why? Oh, it's just, yeah, no, mm-mm. Well, I don't think there's a better way to end it on a happy note like this. Lisa, like I said, I'm a huge fan of yours. Thank you for wasting yet more time with me talking again. People should definitely get your book. And maybe one day I can't wait to talk to your husband as well. Well, right back at you, Lexi. Thanks for listening to this conversation with Lisa Feldman Barrett, and thank you to our sponsors. Athletic Greens, the all-in-one drink that I start every day with to cover all my nutritional bases. 8 Sleep, a mattress that cools itself and gives me yet another reason to enjoy sleep. Masterclass, online courses that I enjoy from some of the most amazing humans in history. And BetterHelp, online therapy with a licensed professional. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars and Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from Sun Tzu and the Art of War. There are not more than five musical notes, yet the combination of these five give rise to more melodies that can ever be heard. There are not more than five primary colors, yet in combination they produce more hues than can ever be seen. There are not more than five cardinal tastes, and yet combinations of them yield more flavors than can ever be tasted. Thank you for listening and hope to see you next time.

https://youtu.be/S_AFc_BXht4

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Ray Dalio: Is Credit Good for Society? | AI Podcast Clips

When you're doing that kind of back and forth on a topic like the economy, which you have, to me, perhaps I'm naive, but it seems both incredible and incredibly complex, the economy, the trading, the transactions, that these transactions between two individuals somehow add up to this giant mechanism. You've put out a 30 minute video, you have a lot of incredible videos online that people should definitely watch on YouTube, but you've put out this 30 minute video titled How the Economic Machine Works. That is probably one of the best, if not the best, video I've seen on the internet in terms of educational videos. So people should definitely watch it, especially because it's not that the individual components of the video are somehow revolutionary, but the simplicity and the clarity of the different components just makes you... There's a few light bulb moments there about how the economy works as a machine. So as you described, there's three main forces that drive the economy, productivity growth, short term debt cycle, long term debt cycle. The former, productivity growth, is how much value people create, valuable things people create. The latter is people borrowing from their future selves to hopefully create those valuable things faster. So this is an incredible system to me. Maybe we can linger on it a little bit, but you've also said what most people think about as money is actually credit. Total amount of credit in the US is $50 trillion. Total amount of money is $3 trillion. That's just crazy to me. Maybe I'm silly, maybe you can educate me, but that seems crazy. It gives me just pause that human civilization has been able to create a system that has so much credit. So that's a long way to ask, do you think credit is good or bad for society? That system that's so fundamentally based on credit. I think credit is great, even though people often overdo it. Credit is that somebody has earned money, and what happens is they lend it to somebody else who's got better ideas, and they cut a deal, and then that person with the better ideas is going to pay it back. And if it works well, it helps resource allocations go well, providing people like the entrepreneurs and all of those, they need capital. They don't have capital themselves, and so somebody's going to give them capital, and they'll give them credit, and along those lines. Then what happens is it's not managed well in a variety of ways. So I did another book on principles, principles of big debt crises that go into that. And it's free, by the way. I put it free online as a PDF. So if you go online and you look principles for big debt crisis under my name, you can download it in a PDF, or you can buy a print book of it. And it goes through that particular process. And so you always have it overdone in always the same way. Everything by the way, almost everything happens over and over again for the same reasons. So these debt crises all happen over and over again for the same reasons. They get it overdone. In the book it explains how you identify whether it's overdone or not. They get it overdone, and then you go through the process of making the adjustments according to that, and it explains how they can use the levers and so on. If you didn't have credit, then you would be sort of, everybody would sort of be stuck. So credit is a good thing, but it can easily be overdone. So now we get into the question, what is money? What is credit? Okay, you get into money and credit. So if you're holding credit and you think that's worthwhile, keep in mind that the central bank, let's say, it can print the money. What is that prompt? You have an IOU, and the IOU says you're going to get a certain number of dollars, let's say, or yen or euros. And that is what the IOU is. And so the question is, will you get that money and what will it be worth? And then also you have a government, which is a participant in that process, because they are on the hook, they owe money. And then will they print the money to make it easy for everybody to pay? So you have to pay attention to those two. I would suggest, like you recommend to other people, just take that 30 minutes and it comes across pretty clearly. But my conclusion is that, of course, you want it. And even if you understand it and the cycles well, you can benefit from those cycles rather than to be hurt by those cycles, because I don't know the way the cycle works. If somebody gets overindebted, they have to sell an asset, okay, then I don't know. That's when assets become cheaper. How do you acquire the asset? It's a whole process.

https://youtu.be/asAveTK0piw

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Geometric Unity - A Theory of Everything (Eric Weinstein) | AI Podcast Clips

You recently published the video of a lecture you gave at Oxford presenting some aspects of a theory, a theory of everything called geometric unity. So this was a work of 30, 30 plus years. This is life's work. Let me ask sort of the silly old question, how do you feel as a human? Excited, scared, the experience of posting it. You know it's funny, one of the things that you learn to feel as an academic is the great sins you can commit in academics is to show yourself to be a non-serious person, to show yourself to have delusions, to avoid the standard practices which everyone is signed up for. And you know it's weird because like you know that those people are going to be angry. He did what? You know, why would he do that? And what we're referring to for example, there's traditions of sort of publishing incrementally, certainly not trying to have a theory of everything, perhaps working within the academic departments, all those things. That's true. And so you're going outside of all of that. Well I mean I was going inside of all of that and we did not come to terms when I was inside. And what they did was so outside to me, was so weird, so freakish. Like the most senior respectable people at the most senior respectable places were functionally insane as far as I could tell. And again it's like being functionally stupid if you're the head of the CDC or something where you know you're giving recommendations out that aren't based on what you actually believe, they're based on what you think you have to be doing. Well in some sense I think that that's a lot of how I saw the math and physics world as the physics world was really crazy and the math world was considerably less crazy, just very strict and kind of dogmatic. We'll psychoanalyze those folks, but I really want to maybe linger on it a little bit longer of how you feel because this is such a special moment in your life. Well I really appreciate it. It's a great question. So if we can pair off some of those other issues. It's new being able to say what the Observer's is, which is my attempt to replace space time with something that is both closely related to space time and not space time. So I used to carry the number 14 as a closely guarded secret in my life. And where 14 is really four dimensions of space and time plus 10 extra dimensions of rulers and protractors or for the cool kids out there, symmetric two tensors. So you had a geometric, complicated, beautiful geometric view of the world that you carried with you for a long time. Did you have friends that you, colleagues that you- Essentially no. Talked? No. In fact, part of some of these stories are me coming out to my friends, and I use the phrase coming out because I think that gays have monopolized the concept of a closet. Many of us are in closets having nothing to do with our sexual orientation. Yeah I didn't really feel comfortable talking to almost anyone. So this was a closely guarded secret. And I think that I let on in some ways that I was up to something and probably, but it was a very weird life. So I had to have a series of things that I pretended to care about so that I could use that as the stalking horse for what I really cared about. And to your point, I never understood this whole thing about theories of everything. If you were going to go into something like theoretical physics, isn't that what you would normally pursue? Wouldn't it be crazy to do something that difficult and that poorly paid if you were going to try to do something other than figure out what this is all about? Now I have to reveal my cards, my weaknesses and lack and understanding of the music of physics and math departments. But there's an analogy here to artificial intelligence. And often folks come in and say, okay, so there's a giant department working on quote unquote artificial intelligence. But why is nobody actually working on intelligence? You're all just building little toys. You're not actually trying to understand. And that breaks a lot of people. It confuses them. Because like, okay, so I'm at MIT, I'm at Stanford, I'm at Harvard, I'm here, I dreamed of being working on artificial intelligence. Why is everybody not actually working on intelligence? I have the same kind of sense that that's what working on the theory of everything is. That strangely you somehow become an outcast for even- But we know why this is, right? Why? Well, it's because, let's play with AGI for example. I think that the idea starts off with nobody really knows how to work on that. And so if we don't know how to work on it, we choose instead to work on a program that is tangentially related to it. So we do a component of a program that is related to that big question because it's felt like at least I can make progress there. And that wasn't where I was. It's funny, there was this book called Frieden-Uhlenbeck and it had this weird mysterious line in the beginning of it. And I tried to get clarification of this weird mysterious line and everyone said wrong things. And then I said, okay, well, so I can tell that nobody's thinking properly because I just asked the entire department and nobody has a correct interpretation of this. And so it's a little bit like you see a crime scene photo and you have a different idea. There's a smoking gun and you figure, that's actually a cigarette lighter. I don't really believe that. And then there's a pack of cards and you think, oh, that looks like the blunt instrument that the person was beaten with. So you have a very different idea about how things go. And very quickly you realize that there's no one thinking about that. There's a few human sides to this and technical sides, both of which I'd love to try to get down to. So the human side, I can tell from my perspective, I think it was before April 1st, April fools, maybe the day before, I forget. But I was laying in bed in the middle of the night and somehow it popped up on my feed somewhere that your beautiful face is speaking live and I clicked. And it's kind of weird how the universe just brings things together in this kind of way. And all of a sudden I realized that there's something big happening at this particular moment. It's strange. On a day like any day. And all of a sudden you were thinking of, you had this somber tone, like you were serious, like you were going through some difficult decision. And it seems strange. I almost thought you were maybe joking, but there was a serious decision being made. And it was a wonderful experience to go through with you. I really appreciate it. I mean, it was April 1st. Yeah, it's kind of fascinating. I mean, it's just the whole experience. And so I want to ask, I mean, thank you for letting me be part of that kind of journey of decision-making that took 30 years, but why now? Why did you think, why did you struggle so long not to release it and decide to release it now? While the whole world is on lockdown, on April fools, is it just because you like the comedy of absurd ways that the universe comes together? I don't think so. I think that the COVID epidemic is the end of the big nap. And I think that I actually tried this seven years earlier in Oxford. So I, and it was too early. Which part was too, is it the platform? Because your platform is quite different now, actually. The internet, I remember you, I read several of your brilliant answers that people should read for the Edge questions. One of them was related to the internet. It was the first one. Was it the first one? An essay called Go Virtual, Young Man. Yeah. Yeah, that's like forever ago now. Well, that was 10 years ago. And that's exactly what I did is I decamped to the internet, which is where the portal lives. The portal, the portal, the portal. Yeah. We'll insert the whole, the theme, the ominous theme music, which you just listen to forever. I actually started recording tiny guitar licks for the audio portion, not for the video portion. Beautiful. You kind of inspire me with bringing your guitar into the story, but keep going. So you thought, so the Oxford was like step one. You kind of, you put your foot into the, in the water to sample it, but it was too cold at the time. So you didn't want to step in all the- I was just really disappointed. What, what was disappointing about that experience? It's very, it's a hard thing to talk about. It has to do with the fact that, and I can see this, you know, this mirrors a disappointment within myself. There are two separate issues. One is the issue of making sure that the idea is actually heard and explored. And the other is the, is the question about, will I become disconnected from my work because it will be ridiculed, it will, it will be immediately improved. It will be found to be derivative of something that occurred in some paper in 1957. When the community does not want you to gain a voice, it's a little bit like a policeman deciding to weirdly enforce all of these little known regulations against you and, you know, sometimes nobody else. And I think that's kind of, you know, this weird thing where I just don't believe that we can reach the final theory necessarily within the political economy of academics. So if you think about how academics are tortured by each other and how they're paid and where they have freedom and where they don't, I actually weirdly think that that system of selective pressures is going to eliminate anybody who's going to make real progress. So that's interesting. So if you look at the story of Andrew Wiles, for example, with the Fermat's last theorem, he, as far as I understand, he pretty much isolated himself from the world of academics in terms of the bulk of the work he did. And from my perspective, it's dramatic and fun to read about, but it seemed exceptionally stressful the first steps he took when actually making the work public. That seemed to me it would be hell. Yeah, but it's like so artificially dramatic. You know, he leads up to it at a series of lectures. He doesn't want to say it. And then he finally says it at the end, because obviously this comes out of a body of work. Where, I mean, the funny part about Fermat's last theorem is that wasn't originally thought to be a deep and meaningful problem. It was just an easy to state one that had gone unsolved. But if you think about it, it became attached to the body of regular theory. So he built up this body of regular theory, gets all the way up to the end, announces. And then like, there's this whole drama about, okay, somebody is checking the proof. I don't understand what's going on in line 37. You know, and like, oh, is this serious? Seems a little bit more serious than we knew. I mean, do you see parallels? Do you share the concern that your experience might be something similar? Well, in his case, I think that if I recall correctly, his original proof was unsalvageable. He actually came up with a second proof with a colleague, Richard Taylor. And it was that second proof which carried the day. So it was a little bit that he got put under incredible pressure and then had to succeed in a new way, having failed the first time, which is like even a weirder and stranger story. That's an incredible story in some sense. But I mean, I'm trying to get a sense of the kind of stress you're under. I think that this is, okay, but I'm rejecting. What I don't think people understand with me is the scale of the critique. People say, well, you must implicitly agree with this and implicitly agree. It's like, no, try me. Ask before you decide that I am mostly in agreement with the community about how these things should be handled or what these things mean. Can you elaborate? And also just why does criticism matter so much here? So you seem to dislike the burden of criticism that it will choke away all. There's different kinds of criticism. There's constructive criticism and there's destructive criticism. And what I don't like is I don't like a community that can't, first of all, like if you take the physics community, just the way we screwed up on masks and PPE, just the way we screwed up in the financial crisis and mortgage backed securities, we screwed up on string theory. Can we just forget the string theory happened or? Sure. But then somebody should say that, right? Somebody should say, you know, it didn't work out. Yeah. Okay, but you're asking this, like, why do you guys get to keep the prestige after failing for 35 years? That's an interesting question. Who is these you guys? Because to me- Whoever the profession, look, these things, if there is a theory of everything to be had, right? It's going to be a relatively small group of people where this will be sorted out. Absolutely. It's not tens of thousands. It's probably hundreds at the top. But within that community, there's the assholes. There's the, I mean, you always in this world have people who are kind, open-minded. It's not a question about kind. It's a question about, okay, let's imagine, for example, that you have a story where you believe that ulcers are definitely caused by stress and you've never questioned it. Or maybe you felt like the Japanese came out of the blue and attacked us at Pearl Harbor. And now somebody introduces a new idea to you, which is like, what if it isn't stress at all? Or what if we actually tried to make resource-starved Japan attack us somewhere in the Pacific so we could have Cassius Belli to enter the Asian theater? Person's original idea is like, what? What are you even saying? It's like too crazy. Well when Dirac in 1963 talked about the importance of beauty as a guiding principle in physics, and he wasn't talking about the scientific method, that was crazy talk. But he was actually making a great point. He was using Schrodinger, and I think Schrodinger was standing in for him. And he said that if your equations don't agree with experiment, that's kind of a minor detail. If they have true beauty in them, you should explore them because very often the agreement with experiment is an issue of fine-tuning of your model, of the instantiation. And so it doesn't really tell you that your model is wrong. Of course, Heisenberg told Dirac that his model was wrong because the proton and the electron should be the same mass if they are each other's antiparticles. And that was an irrelevant kind of silliness rather than a real threat to the Dirac theory. But okay, so amidst all this silliness, I'm hoping that we could talk about the journey that Geometric Unity has taken and will take as an idea and an idea that will see the light. So first of all, I'm thinking of writing a book called Geometric Unity for Idiots. And I need you as a consultant. So can we... First of all, I hope I have the trademark on Geometric Unity. You do. Good. Can you give a basic introduction of the goals of Geometric Unity, the basic tools of mathematics, use the viewpoints in general for idiots like me? Sure. Okay, great, fun. So what's the goal of Geometric Unity? The goal of Geometric Unity is to start with something so completely bland that you can simply say, well, that's the something that begins the game is as close to a mathematical nothing as possible. In other words, I can't answer the question, why is there something rather than nothing? But if there has to be a something that we begin from, let it begin from something that's like a blank canvas. Let's even more basic. So what is something? What are we trying to describe here? Right now, we have a model of our world, and it's got two sectors. One of the sectors is called general relativity. The other is called the standard model. So we'll call it GR for general relativity and SM for standard model. What's the difference between the two? What are the two described? So general relativity gives pride of place to gravity, and everything else is acting as a sort of a backup singer. Gravity is the star of the show. Gravity is the star of general relativity. And in the standard model, the other three non-gravitational forces, so if there are four forces that we know about, three of the four are non-gravitational, that's where they get to shine. Great. So tiny little particles and how they interact with each other. So photons, gluons, and so-called intermediate vector bosons. Those are the things that the standard model showcases, and general relativity showcases gravity. And then you have matter, which is accommodated in both theories, but much more beautifully inside of the standard model. So what does a theory of everything do? So first of all, I think that that's the first place where we haven't talked enough. We assume that we know what it means, but we don't actually have any idea what it means. And what I claim it is, is that it's a theory where the questions beyond that theory are no longer of a mathematical nature. In other words, if I say, let us take X to be a four-dimensional manifold, to a mathematician or a physicist, I've said very little. I've simply said there's some place for calculus and linear algebra to dance together and to play. And that's what manifolds are. They're the most natural place where our two greatest math theories can really intertwine. Which are the two? Oh, you mean calculus and linear algebra. Calculus and linear algebra, right. Okay, now the question is beyond that. So it's sort of like saying, I'm an artist and I want to order a canvas. Now the question is, does the canvas paint itself? Does the canvas come up with an artist and paint an ink, which then paint the canvas? That's the hard part about theories of everything, which I don't think people talk enough about. Can we just, you bring up Escher and the hand that draws itself. The fire that lights itself or drawing hands. The drawing hands. Yeah. And every time I start to think about that, my mind shuts down. Don't do that. There's a spark. No, but this is the most beautiful part. We should do this together. No, it's beautiful, but this robot's brain sparks fly. So can we try to say the same thing over and over in different ways about what you mean by that having to be a thing we have to contend with? Sure. Like why do you think that creating a theory of everything, as you call the source code, understanding our source code, require a view like the hand that draws itself? Okay, well, here's what goes on in the regular physics picture. We've got these two main theories, general relativity and the standard model, right? Think of general relativity as more or less the theory of the canvas. Okay. And maybe you have the canvas in a particularly rigid shape. Maybe you've measured it, so it's got length and it's got an angle, but more or less it's just canvas and length and angle. And that's all that really general relativity is, but it allows the canvas to warp a bit. Then we have the second thing, which is this import of foreign libraries, which aren't tied to space and time. So we've got this crazy set of symmetries called SU3 cross SU2 cross U1. We've got this collection of 16 particles in a generation, which are these sort of twisted spinners and we've got three copies of them. Then we've got this weird Higgs field that comes in and like Deus Ex Machina solves all the problems that have been created in the play that can't be resolved otherwise. So that's the standard model of quantum field theory just plopped on top of this canvas. Yes, it's a problem of the double origin story. One origin story is about space and time. The other origin story is about what we would call internal quantum numbers and internal symmetries. And then there was an attempt to get one to follow from the other called Calusa-Klein theory, which didn't work out. And this is sort of in that vein. So you said origin story. So in the hand that draws itself, what is it? So it's as if you had the canvas and then you ordered up also give me paint brushes, paints, pigments, pencils, and artists. But you're saying that's like if you want to create a universe from scratch, the canvas should be generating the paintbrushes and the paintbrushes should be generating the canvas. Yeah, yeah, yeah. Right. Like you should. Who's the artist in this analogy? Well, this is, sorry, then we're going to get into a religious thing and I don't want to do that. Okay. Well, you know my shtick, which is that we are the AI. We have two great stories about the simulation and artificial general intelligence. In one story, man fears that some program we've given birth to will become self-aware, smarter than us and will take over. In another story, there are genius simulators and we live in their simulation and we haven't realized that those two stories are the same story. In one case, we are the simulator. In another case, we are the simulated. And if you buy those and you put them together, we are the AGI and whether or not we have simulators, we may be trying to wake up by learning our own source code. So this could be our Skynet moment, which is one of the reasons I have some issues around it. I think we'll talk about that because I. Well, that's the issue of the emergent artist within the story. Just to get back to the point. Okay. So now the key point is the standard way we tell the story is that Einstein sets the canvas and then we order all the stuff that we want and then that paints the picture that is our universe. So you order the paint, you order the artist, you order the brushes and that then when you collide the two, gives you two separate origin stories. The canvas came from one place and everything else came from somewhere else. So what are the mathematical tools required to construct consistent geometric theory? You know, make this concrete. Well somehow you need to get three copies, for example, of generations with 16 particles each. Right. And so the question would be like, well, there's a lot, there's a lot of special personality in those symmetries. Where would they come from? So for example, you've got what would be called grand unified theories that sound like SU5, the George I. Glashow theory. There's something that should be called spin 10, but physicists insist on calling it SO10. There's something called the Petit-Salam theory that tends to be called SU4 cross SU2 cross SU2, which should be called spin six cross spin four. I can get into all of these. What are they all accomplishing? They're all taking the known forces that we see and packaging them up to say, we can't get rid of the second origin story, but we can at least make that origin story more unified. So they're trying grand unification as the attempt to- And that's a mistake in your- It's not a mistake. The problem is, is it was born lifeless. When George I. Glashow first came out with the SU5 theory, it was very exciting because it could be tested in a South Dakota mine filled up with like, I don't know, cleaning fluid or something like that. And they looked for proton decay and didn't see it. And then they gave up because in that day when your experiment didn't work, you gave up on the theory. It didn't come to us born of a fusion between Einstein and Bohr. And that was kind of the problem is that it had this weird parenting where it was just on the Bohr side. There was no Einsteinian contribution. Lex, how can I help you most? I'm trying to figure out what questions you want to ask so that you get the most satisfying answers. There's a bunch. There's a bunch of questions I want to ask. I mean, and I'm trying to sneak up on you somehow to reveal in an accessible way the nature of our universe. So I can just give you a guess, right? We have to be very careful that we're not claiming that this has been accepted. This is a speculation. But I will make the speculation that I think what you would want to ask me is how can the canvas generate all the stuff that usually has to be ordered separately? Should we do that? Let's go there. Okay. So the first thing is, is that you have a concept in computers called technical debt. You're coding and you cut corners and you know you're going to have to do it right before the thing is safe for the world. But you're piling up some series of IOUs to yourself and your project as you're going along. So the first thing is we can't figure out if you have only four degrees of freedom and that's what your canvas is. How do you get at least Einstein's world? Einstein says, look, it's not just four degrees of freedom, but there need to be rulers and protractors to measure length and angle in the world. You can't just have a flabby four degrees of freedom. So the first thing you do is you create 10 extra variables, which is like if we can't choose any particular set of rulers and protractors to measure length and angle, let's take the set of all possible rulers and protractors. And that would be called symmetric non-degenerate two tensors on the tangent space of the four manifold X four. Now because there are four degrees of freedom, you start off with four dimensions. Then you need four rulers for each of those different directions. So that's four, that gets us up to eight variables and then between four original variables, there are six possible angles. So four plus four plus six is equal to 14. So now you've replaced X four with another space, which in the lecture I think I called U 14, but I'm now calling Y 14. This is one of the big problems of working on something in private is every time you pull it out, you sort of can't remember it and you name something new. Okay, so you've got a 14 dimensional world, which is the original four dimensional world plus a lot of extra gadgetry for measurement. And because you're not in the four dimensional world, you don't have the technical debt. No, now you've got a lot of technical debt because now you have to explain away a 14 dimensional world, which is a big, you're taking a huge advance on your payday check. But aren't more dimensions allow you more freedom? Maybe but you have to get rid of them somehow because we don't perceive them. So eventually you have to collapse it down to the thing that we perceive. Or you have to sample a four dimensional filament within that 14 dimensional world known as a section of a bundle. Okay, so how do we get from the 14 dimensional world where I imagine a lot of... Oh, wait, wait, wait. You're cheating. The first question was, how do we get something from almost nothing? Like how do we get the... If I've said that the who and the what in the newspaper story that is a theory of everything are bosons and fermions. So let's make the who the fermions and the what the bosons. Think of it as the players and the equipment for a game. Are we supposed to be thinking of actual physical things with mass or energy? Sure. Okay. So think about everything you see in this room. So from chemistry, you know, it's all protons, neutrons and electrons, but from a little bit of late 1960s physics, we know that the protons and neutrons are all made of up quarks and down quarks. So everything in this room is basically up quarks, down quarks and electrons stuck together with the what, the equipment. Okay. Now the way we see it currently is we see that there are space time indices, which we would call spinners that correspond to the who that is the fermions, the matter, the stuff, the up quarks, the down quarks, the electrons. And there are also 16 degrees of freedom that come from this in this space of internal quantum numbers. So in my theory in 14 dimensions, there's no internal quantum number space that figures in it's all just spinorial. So spinners in 14 dimensions without any festooning with extra linear algebraic information, there's a concept of a, of, of, of spinners, which is natural if you have a manifold with length and angle. And why 14 is almost a manifold with length and angle it's, it's so close. It's in other words, because you're looking at the space of all rulers and protractors, maybe it's not that surprising that a space of rulers and protractors might come very close to having rulers and protractors on it itself. Like can you measure the space of measurements and you almost can't in a space that has length and angle if it doesn't have a topological obstruction comes with these objects called spinners. Now, spinners are the stuff of, uh, of our world. We are made of spinners. They're the most important, really deep object that I can tell you about. They were very surprising. What is a spinner? So famously there are these weird things that require 720 degrees of rotation in order to come back to normal. And that doesn't make sense. And the reason for this is that there's a knottedness in our three-dimensional world that people don't observe. And you know, you can famously see it by this Dirac string trick. So if you take a glass of water, imagine that this was a tumbler and I didn't want to spill any of it. And the question is, if I rotate, um, the cup without losing my grip on the base 360 degrees and I can't go backwards, is there any way I can take a sip? And the answer is this weird motion, which is go over first and under second. And that that's 720 degrees of rotation to come back to normal so that I can take a sip. Well that weird principle, which sometimes is known as the Philippine wine glass dance, because waitresses in the Philippines apparently learned how to do this. That move defines, if you will, this hidden space that nobody knew was there of spinners, which Dirac figured out when he took the square root of something called the Klein-Gordon equation, which I think had earlier work incorporated from Cartan and Killing and Company in mathematics. So spinners are one of the most profound aspects of human existence. I mean, forgive me for the perhaps dumb questions, but would a spinner be the mathematical objects that's the basic unit of our universe? When you, when you start with a manifold, um, which is just like something like a donut or a sphere, a circle or a Mobius band, a spinner is usually the first wildly surprising thing that you found was hidden in your original purchase. So you order a manifold and you didn't even realize, it's like buying a house and finding a panic room inside that you hadn't counted on. It's very surprising when you understand that spinners are running around in your spaces. Again perhaps a dumb question, but we're talking about 14 dimensions and four dimensions. What is the manifold we're operating under? So in my case, it's proto-spacetime. It's before, it's before Einstein can slap rulers and protractors on spacetime. And what you mean by that, sorry to interrupt, is spacetime is the 4D manifold. Spacetime is a four dimensional manifold with extra structure. What's the extra structure? It's called a semi-Romanian or pseudo-Romanian metric. In essence, there is something akin to a four by four symmetric matrix, which is equivalent to length and angle. So when I talk about rulers and protractors or I talk about length and angle, or I talk about Romanian or pseudo-Romanian or semi-Romanian manifolds, I'm usually talking about the same thing. Can you measure how long something is and what the angle is between two different rays or vectors? So that's what Einstein gave us as his arena, his place to play, his canvas. There's a bunch of questions I can ask here, but like I said, I'm working on this book, Geometric Unity for Idiots. And I think what would be really nice as your editor, to have beautiful, maybe even visualizations that people could try to play with, try to reveal small little beauties about the way you're thinking about the score. Well, I usually use the Joe Rogan program for that. Sometimes I have him doing this Philippine wine glass dance, I had the hop vibration. The part of the problem is that most people don't know this language about spinners, bundles, metrics, gauge fields. And they're very curious about the theory of everything, but they have no understanding of even what we know about our own world. Is it a hopeless pursuit? No. So like even gauge theory. Right. Just this, I mean, it seems to be very inaccessible. Is there some aspect of it that could be made accessible? I mean, I could go to the board right there and give you a five minute lecture on gauge theory that would be better than the official lecture on gauge theory. You would know what gauge theory was. So it's possible to make it accessible. Yeah. But nobody does, like in other words, you're gonna watch over the next year, lots of different discussions about quantum entanglement or the multiverse, where are we now? Or many worlds, are they all equally real? Right? I mean, yeah, that's like- Okay, but you're not gonna hear anything about the hop vibration except if it's from me, and I hate that. Why can't you be the one? Well, because I'm going a different path. I think that we've made a huge mistake, which is we have things we can show people about the actual models. We can push out visualizations where they're not listening by analogy, they're watching the same thing that we're seeing. And as I've said to you before, this is like choosing to perform sheet music that hasn't been performed in a long time, or the experts can't afford orchestras, so they just trade Beethoven symphonies as sheet music. And they're like, oh, wow, that was beautiful. But it's like nobody heard anything. They just looked at the score. Well, that's how mathematicians and physicists trade papers and ideas, is that they write down the things that represent stuff. I want to at least close out this thought line that you started, which is how does the canvas order all of this other stuff into being? So I at least want to say some incomprehensible things about that, and then we'll have that much done. All right? On that just point, does it have to be incomprehensible? Do you know what the Schrodinger equation is? Yes. Do you know what the Dirac equation is? No. What does no mean? Well, my point is, you're going to have some feeling that you know what the Schrodinger equation is. Yes. As soon as we get to the Dirac equation, your eyes are going to get a little bit glazed. Right? So now why is that? Well, the answer to me is that you want to ask me about the theory of everything, but you haven't even digested the theory of everything as we've had it since 1928 when Dirac came out with his equation. So for whatever reason, and this isn't a hit on you, you haven't been motivated enough in all the time that you've been on earth to at least get as far as the Dirac equation. And this was very interesting to me after I gave the talk in Oxford, new scientist who had done kind of a hatchet job on me to begin with, sent a reporter to come to the third version of the talk that I gave. And that person had never heard of the Dirac equation. So you have a person who's completely professionally not qualified to ask these questions wanting to know, well, how does your theory solve new problems? And like, well, in the case of the Dirac equation, well, tell me about that. I don't know what that is. So then the point is, okay, I got it. You're not even caught up minimally to where we are now. And that's not a knock on you. Almost nobody is. But then how does it become my job to digest what has been available for like over 90 years? Well, to me, the open question is whether what's been available for over 90 years, there could be a blueprint of a journey that one takes to understand it. Oh, I want to do that with you. And one of the things I think I've been relatively successful at, for example, when you ask other people what gauge theory is, you get these very confusing responses. And my response is much simpler. It's, oh, it's a theory of differentiation, where when you calculate the instantaneous rise over run, you measure the rise not from a flat horizontal, but from a custom endogenous reference level. What do you mean by that? It's like, okay. And then I do this thing with Mount Everest, which is Mount Everest is how high? Then they give the height. I say above what? Then they say sea level. And I say, which sea is that in Nepal? They're like, oh, I guess there isn't a sea because it's landlocked. It's like, okay, well, what do you mean by sea level? Oh, there's this thing called the geoid I'd never heard of. Oh, that's the reference level. It's a custom reference level that we imported. So all sorts of people have remembered the exact height of Mount Everest without ever knowing what it's a height from. Well, in this case, in gauge theory, there's a hidden reference level where you measure the rise in rise over run to give the slope of a line. What if you have different concepts of what, of where that rise should be measured from that vary within the theory that are endogenous to the theory? That's what gauge theory is. Okay. We have a video here, right? Yeah. Okay. I'm going to use my phone. If I want to measure my hand and its slope, this is my attempt to measure it using standard calculus. In other words, the reference level is apparently flat and I measure the rise above that phone using my hand. Okay. If I want to use gauge theory, it means I can do this or I can do that or I can do this or I can do this or I could do what I did from the beginning. Okay. At some level, that's what gauge theory is. Now that is an act. Now I've never heard anyone describe it that way. So while the community may say, well, who is this guy and why does he have the right to talk in public, I'm waiting for somebody to jump out of the woodwork and say, you know, Eric's whole shtick about rulers and protractors, uh, leading to a derivative derivatives are measured as rise of a run above reference level of reference levels. Don't fit to get like, I go through this whole shtick in order to make it accessible. I've never heard anyone say it. I'm trying to make it. Prometheus would like to discuss fire with everybody else. All right. I'm going to just say one thing to close out the earlier line, which is what I think we should have continued with. When you take the naturally occurring spinners, the unadorned spinners, the naked spinners, not on, on this 14 dimensional manifold, but on something very closely tied to it, which I've called the chimeric tangent bundle. That is the, the object which stands in for the thing that should have had length and angle on it, but just missed. Okay. When you take that object and you form spinners on that and you don't adorn them, so you're still in the single origin story, you get very large spin oriole objects upstairs on this 14 dimensional world. Why 14, which is part of the observers. When you pull that information back from Y 14 down to X four, it miraculously looks like the adorned spinners, the festoon spinners, the spinners that we play with in ordinary reality. In other words, the 14 dimensional world looks like a four dimensional world plus a 10 dimensional compliment. So 10 plus four equals 14 that 10 dimensional compliment, which is called a normal bundle generates spin properties, internal quantum numbers that look like the things that give our PR our particles personality that make, um, let's say up quarks and down quarks charged by negative one third or plus two thirds, you know, that kind of stuff or whether or not, um, you know, some quarks feel the weak force and other quarks do not. So the X four generates Y 14, Y 14 generates something called the chimeric tangent bundle. Chimeric tangent bundle generates unadorned spinners. The unadorned spinners get pulled back from 14 down to four where they look like adorned spinners and we have the right number of them. You thought you needed three, you only got two, but then something else that you'd never seen before broke apart on this journey and it broke into another copy of the thing that you already have two copies of. One piece of that thing broke off. So now you have two generations plus an imposter third generation, which is, I don't know why we never talk about this possibility in regular physics. And then you've got a bunch of stuff that we haven't seen, which has descriptions. So people always say, does it make any falsifiable predictions? Yes, it does. It says that the matter that you should be seeing, um, next has particular properties that can be read off like, like a weak ISIS spin, weak hypercharge, like the responsiveness to the strong force. The one I can't tell you is what energy scale it would happen at. So you, if you can't say if those characteristics can be detected with the current, it may be that somebody else can. I'm not a physicist. I'm not a quantum field theorist. I can't, I don't know how you would do that. The hope for me is that there's some simple explanations for all of it. Like, should we have a drink? You're having fun. No, I'm trying to have fun with you. You know, there's a bunch of fun things to talk about here. Anyway, that was how I got what I thought you wanted, which is if you think about the fermions as the artists and the bosons as the brushes and the paint, what I told you is that's how we get the artists. What are the open questions for you in this? What are the challenges? So you're not done. Well, there's things that I would like to have in better order. So a lot of people will say, see, the reason I hesitate on this is I just have a totally different view than the community. So for example, I believe that general relativity began in 1913 with Einstein and Grossman. Now that was the first of like four major papers in this line of thinking to most physicists. General relativity happened when Einstein produced a divergence free gradient, which turned out to be the gradient of the, of the so-called Hilbert or Einstein Hilbert action. And from my perspective, that wasn't true. This is that it began when Einstein said, look, this is about differential geometry. And it's the final answer is going to look like a curvature tensor on one side and matter and energy on the other side. And that was enough. And then he published a wrong version of it where it was the Ricci tensor, not the Einstein tensor. Then he corrected the Ricci tensor to make it into the Einstein tensor. Then he corrected that to add a cosmological constant. I can't stand that the community thinks in those terms. There's some things about which, like there's a question about which contraction do I use? There's an Einstein contraction. There's a Ricci contraction. They both go between the same spaces. I'm not sure what I should do. I'm not sure which contraction I should choose. This is called a Shiab operator for ship in a bottle in my stuff. You have this big platform in many ways that inspires people's curiosity about physics and mathematics. And I'm one of those people. Well, great. But then you start using a lot of words that I don't understand. I might know them, but I don't understand. And what's unclear to me, if I'm supposed to be listening to those words, or if it's just if this is one of those technical things that's intended for a very small community, or if I'm supposed to actually take those words and start a multi-year study, not a serious study, but the kind of study when you're interested in learning about machine learning, for example, or any kind of discipline. That's where I'm a little bit confused. So you speak beautifully about ideas. You often reveal the beauty in mathematics, in geometry. And I'm unclear in what are the steps I should be taking. I'm curious. How can I explore? How can I play with something? How can I play with these ideas and enjoy the beauty of not necessarily understanding the depth of a theory that you're presenting, but start to share in the beauty. As opposed to sharing and enjoying the beauty of just the way, the passion with which you speak, which is in itself fun to listen to, but also starting to be able to understand some aspects of this theory that I can enjoy it. And start to build an intuition, what the heck we're even talking about. Because you're basically saying we need to throw a lot of our ideas of views of the universe out. And I'm trying to find accessible ways in. Not in this conversation. No, I appreciate that. So one of the things that I've done is I've picked on one paragraph from Edward Witten. And I said, this is the paragraph. If I could only take one paragraph with me, this is the one I'd take. And it's almost all in prose, not in equations. And he says, look, this is our knowledge of the universe at its deepest level. And he was writing this during the 1980s. And he has three separate points that constitute our deepest knowledge. And those three points refer to equations. One to the Einstein field equation, one to the Dirac equation, and one to the Yang-Mills-Maxwell equation. Now one thing I would do is take a look at that paragraph and say, okay, what do these three lines mean? Like it's a finite amount of verbiage. You can write down every word that you don't know. You can say, what do I think? Done. Now, young man, there's a beautiful wall in Stony Brook, New York, built by someone who I know you will interview named Jim Simons. And Jim Simons, he's not the artist, but he's the guy who funded it. World's greatest hedge fund manager. And on that wall contain the three equations that Whitten refers to in that paragraph. And so that is the transmission from the paragraph or graph to the wall. Now that wall needs an owner's manual, which Roger Penrose has written called the road to reality. Let's call that the tome. So this is the subject of the so-called graph wall tome project that is going on in our discord server and our general group around the portal community, which is how do you take something that purports in one paragraph to say what the deepest understanding man has of the universe in which he lives. It's memorialized on a wall, which nobody knows about, which is an incredibly gorgeous piece of art. And that was written up in a book which has been written for no man. Maybe it's for a woman, I don't know. But no one should be able to read this book because either you're a professional and you know a lot of this book, in which case it's kind of a refresher to see how Roger thinks about these things. Or you don't even know that this book is a self-contained invitation to understanding our deepest nature. So I would say find yourself in the graph wall tome transmission sequence and join the graph wall tome project if that's of interest. Okay, beautiful. Now, just to linger on a little longer, what kind of journey do you see Geometric Unity taking? I don't know. I mean, that's the thing is that first of all, the professional community has to get very angry and outraged and they have to work through their feelings. This is nonsense, this is bullshit, or like, no, wait a minute, this is really cool. Actually, I need some clarification over here. So there's going to be some sort of weird coming back together process. Are you already hearing murmurings of that? It's very funny. Officially, I've seen very little. So it's perhaps happening quietly. And we're getting closer to getting exists like that.

https://youtu.be/vdW9XDBuxjU

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Anthony Pompliano: Bitcoin | Lex Fridman Podcast #171

The following is a conversation with Anthony Pompliano, entrepreneur, technology investor, prolific writer, podcaster, and Twitter user on topics of finance, cryptocurrency, technology, and economics. I highly recommend his popular podcast and daily letter called The Pomp Podcast and The Pomp Letter. Quick thank you to our sponsors, Theragun Muscle Recovery Device, Sun Basket Meal Delivery Service, ExpressVPN, and Indeed Hiring website. Click their links to support this podcast. As a side note, let me say that I'll be having many conversations in the coming months about cryptocurrency with people of all kinds of backgrounds and worldviews. Those who are proponents of Bitcoin, like Anthony, Nick Carter, Robert Breedlove, Alex Glassstein, and many others. And those who are proponents of other cryptocurrency technologies, like Vitalik Buterin, Charles Hoskinson, Richard Hart, Sergey Nazarov, Silvia McCauley, and many others as well. I'm not framing this as a debate. I'm simply looking to explore exciting ideas in the space of technologies that could very well change human civilization and AGI civilization as well. I appreciate that some communities are a bit more intense in their style of communication than others, but I personally am only interested in open-minded, respectful collaboration in exploring ideas. I personally try to, like to approach conversations by considering that I may be wrong about everything and I'm looking to learn. I won't engage in groupthink, social signaling, outrage mobs, mocking, and derision. If you do, I understand. It's just not my thing. I send you my love either way and hope to meet you in person over some drinks, some good laughs, and a good conversation one day. No matter the difference in style or substance, we're all just human after all. This is an amazing ride we're all on together. Buy the ticket, take the ride, as Hunter S. Thompson said. Whether you pay for that ticket with Bitcoin, Ethereum, the dollar, gold, seashells, a beer, or just a good old smile. This is the Lex Friedman Podcast and here is my conversation with Anthony Pompliano. You served in the US Army for six years and spent 13 months in Iraq in 2008 and nine. Can you tell the story of why you joined the Army and what were some of the moving difficult and maybe lasting experiences from the time you served? Sure, I joined when I was 17 years old. I needed my parents to basically sign in order to join. And I graduated a semester early from high school and I thought I was gonna go play football in college and kind of enroll in the spring semester. And when that didn't happen, basically was working at Chick-fil-A in Quiznos and had in my mind, look, this is probably not the path in life that I want. And so I knew I was gonna go to college. I knew I was gonna go play football in the fall, but I had this window of time. And so I walked into a recruiting office and just basically was like, I'm assuming you guys need some help. And they gave me the whole pitch and give you a signing bonus. You can go jump out of planes and go do all this crazy stuff. I just said, okay, let's do it. This was close to 9-11. This was in 2006, about five years after. So what impact, I mean, do you remember 9-11? What impact did that have on your thinking about this? So I was in eighth grade. If I remember correctly. And I remember being in school when it happened and I walked into a classroom and the entire class, it was somebody else's class, they were all talking to the teacher about something. The second that me and a couple other kids walked in, everyone got real quiet. And the teacher was like, hey, go back to your like homeroom. And so it was just kind of a weird, like what's going on. And then next thing I know, they called all of the students into the cafeteria. And this is back before, every classroom really had a television in it and cable and all that kind of stuff. And so when we were there, they basically just said, listen, there's been this event that's occurred. All of your parents are gonna come pick you guys up and they'll explain it to you. And so to a kid in eighth grade, you're basically like, what happened? And so I got home and I remember talking to my dad about it. And my dad basically gave me the core American kind of talking points, right? Look, somebody from another country came here and tried to kill Americans and was successful in doing that. And to some extent, he just said, and I'm willing to bet, we're gonna go back after them. Did that wake you up a little bit to the idea that there's evil out there, that even just the idea of terrorism, for many people that was, when it hits you on your own land, it really shakes up your mind. In some sense, World War II, that's why World War II was fundamentally different for Americans than it is for the people like in Russia, in England, in France, in Europe in general, there's something about when there's families, women, children dying on your own land, that's different. And that was one of the first times in America where like on your, of course, it's Pearl Harbor, but like this is like in recent history, it's like they hit us here. That was like a profound idea. I think America was very, very good at exporting the violence elsewhere for a long time. And there was this element of complacency, but also this element of really just American superiority, that doesn't happen here. And I think that that woke people up, not only to kind of the idea that other places around the world may not like the American ideals, may not like democracy and capitalism and that, but also maybe we aren't as big, tough, and secure as we thought we were. And so obviously I think you see the kind of the over-rotation with a lot of the kind of security theater that came after that of almost psychologically, let's make our citizens feel like they're safe, even if the things that we're doing don't necessarily kind of change that apparatus. But on top of that, I think that it really woke people up to extremism around the world. And I don't know if necessarily there was a change in the extremism as much as it just was an awareness thing. How many people kind of drew a line from, was it 92 or 93 with the World Trade Center bombing to deep levels of extremism and hatred of kind of the American industrial complex? Probably not that many. 2001, a lot of people. And so I think that was, again, as a young kid, you don't understand a lot of this stuff. You basically just, hey, somebody came here and tried to kill Americans. And so we should go fight back, right? Was kind of the response I think that I had. What role did that have psychologically for you when you then in 2006 joined the Army? I mean, this is a very different joining the Army than in a time when it's more peaceful. Here you're essentially facing, I mean, I don't know if you see it that way, but there is a war on terror. And I know that people kind of criticize that whole formulation framework of thinking, but nevertheless, you are going to Iraq, you are going to Afghanistan, you're going to these places and are fighting these complicated, I mean, it's not even clear what you're fighting. Yeah, well, I think that there's a couple of key pieces. So one, like one of the actual most impactful data points, if you were, or kind of stories for me was the Pat Tillman story. So I played football in high school and I was gonna go play in college and seeing this NFL player who basically just one day said, hey, I'm gonna go and do this instead and walk away. I don't know necessarily if it was a, I wanna pursue the same story, right? And obviously he ended up dying and so not exactly the end result that you want, but I think it was almost like he made it okay if you were on a certain trajectory in life to go take this detour and to go do it. But the second thing is I was 17. You're pretty stupid when you're 17, you're pretty naive when you're 17, right? And so I almost kind of backed into the deployment because I signed up as a reserve member. And so basically the plan was to sign up for the reserves, I was gonna go to basic training, get all the kind of education and qualification. I was gonna go to college and then after college, maybe there's a chance that you will go and serve or do whatever. For me, I ended up getting deployed when I was a junior in college, literally got pulled out of school. And so at 20 years old, it's not exactly what you thought you were signing up for, right, especially to kind of leave school to go do it. And then on top of that, I probably had an advantage over most people, both on the entry to combat and the exit to kind of a combat situation, which was football. So I always explain that in hindsight, you're in a male-dominated, testosterone-driven kind of combative sport where it's us versus them and there's training and injuries and just kind of all of the things that go into playing a combat sport like football, to now they give you guns, but you still have a uniform on, still male-dominated. It's just a little bit more serious in terms of the injuries and potential death and things like that. But also on the exit from that deployment, most guys I was there with, they're going back to being prison guards, police officers, working at the lumberyard, just kind of everyday Americans. And so I had the fortunate ability to go back into kind of that combative environment, go back to play football. And so it was almost this de-escalation on the way out where they take your guns away, but you still got a uniform, still male-dominated, still combative, and then eventually you're just a normal citizen. And so I think that in some weird way, I was very fortunate to kind of on the entry and exit have that experience where other guys didn't. So what, you were deployed to Iraq, were there any memories, experiences that changed you? Or in general, like you're probably a different man on the other side of it. How did that time change you? I think there was two main takeaways that I took, right? So one was not a specific moment, but on multiple occasions, I remember we were driving down the road and I would look and there would be a 10, 12, 14-year-old kid. And if you've never seen somebody who literally has hate and disdain in their eyes. So it was you? Not necessarily to you personally, just to the uniform, to what you stand for, to all this stuff. When you see it, you see it, right? And I always think of, if you've ever watched the movie, 12 Strong, and in it, they've got this Afghanistan warlord and he's talking to a bunch of soldiers. And he says, you don't have killer eyes, you do, you do. And he's just like, he can just tell, right? He's seen so many soldiers. And so I think that that was a memory on a number of occasions where I just saw young kids and I just said, they hate us, right? And it's not you personally, it's what you stand for. But the really big event was when you first get to these combat zones, a lot of times what will happen is you basically, your unit teams up with a unit that's leaving and there's a handoff. And it happens over a couple of weeks. And so you can imagine almost 1% of our team goes out with 99% of their team, then 5, 95, 10, 90, all the way until it's 50, 50. And then eventually it rotates and then it's majority of our team and a small number of their team. And so what a lot of people will explain is the two most dangerous times in war are actually the first two or three weeks and the last two or three weeks. When you first get there, you don't know who the people are. You don't know the terrain. You don't know kind of the local cultures and who to look out for, what signs, all that kind of stuff. And the last two or three weeks is you basically think you've survived the deployment. You're looking forward to going home. So you become complacent, things like that. And so we made it through that transition period with no issues, but the literally the very first mission that we went out as a team ourselves, 100%, there was two separate incidents. One was we were driving in the middle of the night and what we think was a sniper shot at a truck that I was in. I was standing up outside of it along with another guy. And that was kind of just a wake up call again of never been shot at before, right? And so I'll never forget, you kind of heard this whiz go by and the guy next to me was from a rural Pennsylvania and he just said, you know, look, I've never been shot at before either, but I've done a lot of hunting, get the fuck down. Right? So, okay. And so we kept driving that night and later on in the night, an IED went off. A guy ran over an IED who was at the front of the convoy. And when that IED went off again, I had never been in a convoy that had been blown up before, but the training kicks in. And so immediately every single person starts screaming out, IED, IED, and they start looking and trying to figure it out. And you realize the United States military did a fantastic job training us before we went, because in that moment, nobody thought about anything. You just did what you had been programmed to do. And so ultimately kind of through the end of that event, there was a US soldier that ended up dying. He was shot in the head. And when we got back to the base kind of after that entire event, I think it just hit us. We are at war and if we make mistakes here, that is the cost of kind of those mistakes. And this was somebody who I didn't know. It was somebody who literally showed up kind of as secondary support for our unit and basically was there to help us. And so it was one of those weird situations where you have this emotional connection because it's somebody who shared an event with you, but you didn't know them. And you learn their name later and you understand that they have a family and they have young kids and all this stuff. And so again, as a 20 year old kid, you're kind of processing all this and you just realize like, the gun I have in my hands, it's real for a reason. And we better take this seriously. This is not, let's joking around in kind of the barracks and all the things that you would expect guys who do in the army. So I think that was like the moment where I said, hey, I'm gonna learn a lot here and I gotta make sure I get home. And you snap it into the training, but nevertheless, I mean, you're somebody who thinks philosophically about this world now. You're very intelligent and thinks deeply about the world. So looking back, you mentioned hatred in the 14 year old kid's eyes, there's death. So the way you kind of describe this whole story is like training kicks in, this shit is serious. Like this is, there's a reason there's a gun in your hand. So there's a strategic element. There's like, you have to get the job done. There's a task at hand. But at the same time, if you zoom out, there's a kid who has hate for you. Some of those kids would probably, if they could, would kill you for the thing you stand for in the uniform. And then there's bullets flying at you. And then there's people that some of them you might already care for deeply are dying. What the hell do you make of that? Do you think about that? Does any of that haunt you? How do you think about the world having witnessed that? Yeah, a lot of times when we would talk about it, we were there. If I was that kid, I would wanna kill that person too. I would have hatred as well. Imagine if in the United States tomorrow, you and I woke up and there was tanks rolling down the street from another country and they were basically imposing their rules on us, whether they thought it was the right thing to do or not, the soldiers were there and they were doing this, we would probably feel not so great about it, right? At kind of a minimum and at a maximum, we'd be really, really pissed off, we would fight back. And so what you don't understand when you're in the heat of the moment is, why does this person feel this way? And so what's very weird is, well, what happens if a year ago, US soldiers came through, they got shot at, they returned fire and they killed that kid's uncle? You'd be pissed off, right? And so you just start to understand we look at war very black and white. We look at it very much from a clinical perspective. We're gonna go, we're gonna go kind of invade somewhere. We are the most dominant military in the world. We're very good at invading and we will crush wherever we invade. But when you're actually on the ground, what you understand is the humanity of it all, right? And so what becomes very interesting is, pretty much every veteran I know that comes back, they're some of the largest pacifists in the world. And I always revert back to Marcus Luttrell, who's a famous Navy SEAL and there's a movie made about him and his story. He gave a speech one time that I saw and he basically said, listen, if you're a politician, your job is to be the diplomat, do everything you possibly can not to send me and my friends anywhere. Because when you send us, we're gonna bring hell with us, right? And understand that is the business that we are in. But every single other person up until we get sent has a job to do to prevent having to send us. And I think that ultimately that's where you see a lot of kind of this generation that has fought in Iraq and Afghanistan that says, listen, maybe we shouldn't be running around the world being the police. Maybe we shouldn't be going and invading all these different countries because when you actually get to see firsthand what happens, it's just something that we should avoid at all costs. But if we have to go or we have to actually send soldiers somewhere, understand what happens when that occurs. And the United States is the best in the world at doing it. Do you think, I'm thinking about that kid with the hatred. Do you think there will always be hatred in the world? Do you think from another perspective, do you think there'll be war always? Is that a fundamental aspect of human nature or is that something we can escape? Yeah, so war I think has like very negative connotations in terms of bullets and bombs and death and kind of just very morbid type understanding. Conflict on the other hand, I think people look at and say, of course there will always be conflict. You just can't have billions of people all on the same planet without some level of disagreement, whether that's a disagreement of ideas, disagreement over physical geography or something else. And so I think conflict will always exist. The question is what form does war take moving forward? And so in my mind, it's starting to look a lot more clinical, a lot more drones, a lot less soldiers on the ground, a lot more use of special forces and kind of these small, highly specialized teams rather than kind of big mechanical armies. And then you get into like the information warfare and kind of cyber warfare. And you start to understand that we're at war with a lot of people right now, right? Doesn't mean we're necessarily dropping bombs on their countries. Doesn't necessarily mean we're sending soldiers there, but on a daily basis, we are engaged in these kind of cyber battlefields. And so if that's where war starts to play out, one changes the tools and tactics and techniques that we need to arm our country and other countries will arm themselves with. But it also changes the way that we think about war, right? It sounds a lot less worrisome if I say, hey, we're gonna go to war with a country, by the way, there's gonna be no death, right? Okay, like that doesn't sound nearly as bad as, hey, we're gonna go send 10,000 soldiers and some percentage of them are gonna die on the battlefield and then we're gonna basically pipe back videos and articles saying that American soldiers are dying. Yeah, there does seem to be a fundamental difference between the Genghis Khan style. Like if I would feel differently if somebody like hand to hand with a knife murdered my family versus cybersecurity where I stole all their data, stole all their money, stole everything they own, falsified their identity, all that kind of stuff. That those are both traumatic events, but they do seem to be fundamentally different, but maybe that's actually very narrow style thinking because ultimately you have to think about what is life and what's happiness. And it's like the samurai thinking, I'm not sure what's more painful. If I take it to myself, like I'm not sure what I would rather live through, being stabbed like to death or having my identity stolen, all my money stolen, or maybe reputation destroyed like with lies or something like that. That's very interesting to think about if you think about quality of life and all those kinds of things. Well, one's finite, right? One's the pain ends and the other is kind of a long, prolonged almost torture. So it's physical pain versus psychological pain. That's really interesting to think about. And I think another key piece to this, which I don't have answers to, but there is an element of emotion and rage in the physical violence versus, again, more of that clinical information warfare. And so it's really easy to show a battlefield where there's death on both sides and bombs being dropped and buildings destroyed. It fits very well into propaganda for everyone involved, right, regardless of what side they're on. When you start talking about cyber warfare, how many times have we seen a big company get data hacked or information hacked and we all read the headlines, maybe throw a tweet out and then move on with our day and don't remember it anymore. And so it's just very, very different, I think, in the emotion and response that it invokes in people when they hear about it as well. Given the conflict, do you think people are fundamentally good? Or are we all sort of like blank slates that could be evil, given the environment, or good, given the environment? Or can we kind of, is there some base that we can rely on that people, if left to their own devices, will be good and trustworthy and honest? I think you have to separate out intention from action. So if you talk to some of the most heinous criminals in the world, they've rationalized their actions. And so you've got to ask yourself, what is the level of which they understood what they were doing, that they intended to be malicious, nefarious, and kind of do bad things, versus the actual actions themselves. And so even as a society, if let's say, for example, you were to walk down the street and you were to murder somebody on the sidewalk, completely unprovoked, we would look at you and say, you are a sociopath, you have everything wrong with you, and that is somebody that we do not want in our society, and therefore we will levy the extent of rule of law against you in order to protect society from you, right? And you become that monster, that beast. If in the same situation, somebody walks in your house with a knife and you murder them or you kill them, now we put you up on a pedestal as a hero. And those are two very, very different responses. They may be just as morbid, they may be just as violent in terms of the actual actions, the intentions, the way it's perceived is very, very different. And so I think that as a world, we like a very black and white, clean cut, good, bad, I think the world's a lot more messy than that. And I think that a lot of times when you look at intention, it's hard for us to tell what somebody's intention is. But I've looked at a lot of people who are both considered very good, and also a lot of people are considered very bad. And they sound very similar in terms of the motivations for their actions. And so I think that it's just a really hard problem that probably doesn't have a perfect solution or an answer. Do you give much value to the intention? Or do you think it's better to look at the results of the behavior as opposed to the underlying ideology, the underlying intention of the behavior? I think that intention gets at the question of like, are people inherently good or bad, right? Is I think that they're generally inherently good. And the intention is driving towards the thing that they believe is the best outcome or the best thing for them to pursue. The action I think is where we spend most of our time focused on. And frankly, we actually may be a better society or kind of kinder as a humanity to each other if we spent more time looking at intention rather than action. But again, if somebody walks down the street and murders somebody, it's really hard to have a conversation and it may be inappropriate for us to have a conversation about intention versus any level of action, right? So you're one of the prominent, I would say even the faces of the world of cryptocurrency, Bitcoin, that whole entire world. Let's dive straight in and ask, do you consider yourself a Bitcoin maximalist? I think that the way I really look at it is I work backwards off of what is the maximalism that I believe in. And the world that I believe in is kind of an automated world that is run on these open decentralized protocols. And what we ultimately do is we return sovereignty and individualism and kind of personal responsibility and liberty to people over institutions. And what we end up doing is we end up kind of taking what has historically been a very analog or physical world economy and geographic rule. And we then kind of put it in the cloud and this digital economy becomes the prevalent way that we all conduct commerce, communicate, et cetera. And so it's less about any one single technology to me. I think that it's pretty stupid for people to almost in a way put an inanimate object up for some sort of obsession. To me, it's much more about the ideals, the ethos and the most rational and likely path to that kind of end result or that world that I think is at this point just a foregone conclusion. So the distinction there, and maybe people don't know the terminology, maximalism is basically saying, I really think this is a good idea. Like, if you prefer a certain kind of diet, you could be a keto maximalist saying like, this is probably, maybe it's not 100%, but probably the diet that's healthiest for humans kind of thing. In the same sense, Bitcoin maximalism is saying, you know, of course we don't know, there's a lot of uncertainty, but this particular technology seems to be the best representations of some set of ideals that defines progress in the future. But you're drawing a distinction between sort of cult-like obsession about an object of any kind, whether it's keto or Bitcoin, and just sort of believing that a technology is the best representation of a particular set of ideals. And you believe that sort of this moving into the cloud, both the distributed nature of it, but also just the digital nature of it is something that's going to be a positive step for humanity. Yeah, I would even take maximalism a step further, and it's not just the kind of singular viewpoint of this is the best, it's also an element of it's anti-everything else. Right? So, you know, take keto for example, the keto diet is not only the best diet, all the other diets are bad. Yeah. Right? And so it's a very binary view of the world. I think that what's probably most misunderstood about, let's take Bitcoin as a specific example, is that most of the people who are labeled Bitcoin maximalist, they would be open-minded if they believed that something else came along that was a superior technology or had a better kind of probability of achieving, again, that ultimate vision. I think where there's this controversy and kind of clashing of ideas is that the Bitcoin community believes Bitcoin is the best way to do that and has very specific arguments as to why the other things are not. Yeah. Right? And so what ultimately ends up happening, which is very weird in the investing world, right? It's unlikely that you and I are going to sit down and you're going to be like, Apple stock is the best stock and there's no other stock that's worth anything. Yeah. Right? And then also it's very weird if you said to me, this stock is worth zero and that's where everything that I own, I've put on a short on one single company, right? There's diversification, there's much more kind of probabilistic thinking in finance in general. When it comes to this specific world of cryptocurrency and kind of digital assets, if you will, is there's two main groups of people who are trying to build two very, very different things at the onset. But when you unpack it and you start to spend more and more time on it, you realize they're actually trying to accomplish the same thing in two different ways. So Bitcoin is seen, I think, as a digital currency, right? Kind of the idea that this is going to ascend to become the next global reserve currency. It's a programmatic kind of transparent money. And it's essentially just 180 degrees difference than the inflationary, non-transparent fiat currencies that exist in the world. You then look at kind of everything else, right? And you have a lot of smart contract platforms and various things that they're all going after, right? Ethereum with kind of the world computer approach, and you can kind of go down the line with all their other arguments as to what they're trying to build. I think the big difference just comes down to innovation versus security. And when you simplistically look at it via that lens, you actually understand where both people are coming from. When you say security, sorry to interrupt, do you mean financial security or do you mean like literally the security of the particular cryptocurrency? The technical security of a blockchain. So when you look at, let's say Bitcoin versus Ethereum, Bitcoin has decided, and that community has decided, security is the number one thing that you have to optimize for. So decentralization over everything else in terms of transaction speeds, costs, anything that you could come up with that is something that would be important for a currency, the number one thing to optimize for is security. And as we have seen with a lot of technologies, right? Facebook's Libra or now what's known as Diem is a great example, not having decentralization is susceptible to the nation state. And so a lot of these other platforms and blockchains, they say security is important, but it's not the most important thing. We believe there's a trade-off between a little less security and transaction speed or composability or whatever it is. And so take Ethereum as kind of the second largest community and blockchain by market cap. It was created because somebody wanted to, or a group of people wanted to do something on Bitcoin. They felt like they couldn't do it. And so they said, hey, we're gonna go create something that has these smart contracts that we can then go do here. Again, this is technology, right? So the tribalism of like, you're right, you're wrong, to me is a little childish, just in the sense of like the market is going to decide what is most valuable. And then when you go inside of that community, like there's a lot of dumb ideas people are trying to build around Bitcoin. There's also a lot of really, really great ideas that people are trying to build around Bitcoin. Same thing in the Ethereum world. And so what you end up getting, I think, is the tribalism really comes out of the idea that there's a ticker price that is attached to all of this, right? If you go back in history of technology, venture capitalists didn't sit around the table and yell and scream at each other in this like religious zealot way, right? Because you bet on one type of cloud computing platform and I bet on another one, right? Just the market's gonna decide what it's gonna work on and try to make ours successful. Here, I think that the sensitivity, and mainly it comes out of the Bitcoin community, is that a lot of this is being funded not only by venture capitalists and kind of professional money managers and asset allocators. There's also this element of including the retail investor and the public. And so whether it's through ICOs or some other forms of capital raising, there's arguments for it saying, hey, look, this now gives kind of the little guy some sort of access and ability to do it. But there's also arguments against it. Some people say, hey, it's easier to dupe them and it's easier to run scams and kind of all this stuff. And so ultimately, I think that crypto is this like arena of ideas. It is literally the war of attrition. And what will end up happening is 10 years from now, you and I will talk, and we're gonna say, well, the market said X was valuable and Y wasn't. And so all of the tribalism from between here and there, it's fun, it's engaging, whatever, but ultimately it doesn't really matter. Yeah, because the public is involved, so there's a lot of personalities. And so a lot of times we focus on the extreme personalities that do a lot of maybe, pardon the French, shit talking. And so we kind of focus on that, but that's not necessarily representative of the communities involved. Let's talk about Bitcoin first, and then it'll help us use as a kind of a comparison to Ethereum or whatever else. So when you think about what is money, right? That's kind of the first question people really kind of go down the rabbit hole on. And ultimately today, it's a belief system, right? And you may believe that one currency is more value over another because it's backed by a certain military or a certain government has a monetary policy that you believe in or don't believe in, but ultimately it's a belief system. There's nothing backing this other than a government asks you to pay your taxes in it, right? And they can have a monopoly on violence in terms of they can put you in jail if you don't pay your taxes. They can go to other countries and they can invade and do all this stuff. It wasn't always like that, right? It was historically a layer one technology was gold. And so gold was a fantastic store of value. You knew that if you held gold, it wasn't gonna be inflated away. It was sound money. It was outside the system and no one could create more of it. The reason why that's important is because that optimization for store of value served as the bedrock of the entire stack of money for 5,000 years. And so the problem with that, though, again, trade-off between store of value is it was really hard to transact with, right? If I came in here and you said, hey, I want a couple of ounces of gold and I had a whole bar, I'd have to literally shave off the ounces of gold. It's heavy to carry around. If you said to me, hey, you're in one city, mail it to me. Really expensive. There's all these issues with it. And so ultimately what people said was, well, let's create a second layer on top of that gold in order to make it easier to transact. And so we created paper claims on the gold. So, hey, don't carry around the gold in your pocket anymore. Put it in a vault or a bank. They're gonna issue a paper claim. Now you and I can trade these paper claims around. And at any point, if you want the gold, you just show up and you say, hey, give me three ounces of gold or two bars or whatever. And so that actually made the store of value. It allowed that to be the anchor and kind of the most important part, the security of your purchasing power. But now it became easier to transact. And then eventually we built layers even on top of that. So everything from electronic money, you kind of electronic Q-SIPs, all the way to credit and other systems on top of that gold. 1971 comes around and obviously we de-peg from that gold. And it was a temporary measure at the time. We ended up not going back to it. And so what you moved or transitioned from was sound money, which was outside the system. No one could create more. To now the government had full control. They could create as much as they wanted to. They tried to be responsible and disciplined, but obviously hard to do. Sometimes we've been really good at it. Sometimes we've been less good at it. And then you go around the world and some countries have absolutely sucked at it and some have been good at it. And so when you look into the Bitcoin world, I think that when you look at the optimization for security, similar to gold store value, people hold it, purchasing power has gone up a lot year over year. It's like a 200% year over year compound annual growth for over a decade. And so you measure this in kind of the US dollar exchange price, et cetera. But there's still a lot of people who will yell and scream about it's slow, it's costly, all the things around those transactions that are obstacles or challenges. And so there's basically two schools of thought and this is where we kind of get into the bifurcation. Some people just said, hey, this technology is antiquated. We can't use it. It doesn't make sense. And so what we're gonna do is we're gonna go build something new. And so you go get kind of all of the various versions there. The Bitcoin community says, no, just like gold had paper claims and other things built on top and layer two, three, four, five, we're gonna do that here. And so they've already started to build kind of this layer two where it's easier to transact, it's cheaper, it's faster, et cetera. And so I actually think that both of those worlds are gonna coexist in the future. The big question is just which one has more importance. Right, so again, get out of binary, it's just probabilistically. And so my personal belief is that the security, that the store of value component as the bedrock for a monetary system is essential, right? Like that is the most important thing because you can always improve the other components, but you can't go back and fix that kind of core piece. So money is an idea that we all, it's like an emergent idea that we believe in. You're saying that security is one of the most fundamental catalysts or fuels for that idea to sort of take hold and be stable and sort of take over the world. The other stuff is really nice to have, but if you don't have the security, you're not going to, like it's not going to spread in the viral sense in our human brains. Well, and especially in light of the kind of the macro economy, right? So like what's so fascinating about the last 12 months is in investing in general, the best returns, right, I kind of put that in air quotes a little bit, is something that is different than everything else and right. So being different and wrong just means you're an idiot, right? Being different and right means that that's where kind of the outsized returns are. And so if you look around the world at currencies today, they're all the same. They're all inflationary, unlimited supply, controlled by a government, done in decisions made in a very non-transparent process. And what we've watched is the manipulation of all of those currencies over the last 12 months. In direct contrast to that is this thing, Bitcoin, which is outside of the system, has a finite supply, transparent and programmatic monetary policy. And so when you see those two systems kind of in comparison to each other, in the United States, there's a lot of people who say the dollar works great for me. I can go to the ATM, I can get out physical cash. If I want to swipe a card, I could do that. My money in my bank doesn't lose 50% of its value in a day in terms of purchasing power. Like the dollar's pretty good. When you go to other countries, that might not be the case. And so I do think that there's kind of a relative analysis that goes on here. If you compare Bitcoin to the dollar, there's all kinds of arguments to make that the dollar is better as a medium of exchange today. But if I go and I tell you, well, what about in, you know, these kinds of extreme examples of Venezuela, Zimbabwe, Turkey, et cetera. And so I think that that's kind of one perspective to view this through is security versus all of the innovative components of a medium of exchange, et cetera. The second thing though, that I think is really, really important is around censorship. And so when you look at, again, every currency in the world today, every single financial service, they're highly susceptible to censorship. And actually I would argue the United States is in the business of censorship in terms of, you know, how many countries around the world do we sanction and cut them off in either a minimal or a very material way from the global financial system. So when you define, when you talk about censorship, do you mean just the censoring your ability to operate freely in the world? Well, look at it a little bit differently, which is that the United States has kind of the American superiority because we have the bombs, the bullets, the soldiers, and that military might, we basically impose our will around the world. And so there's a very strong argument to be made that there are certain countries around the world that are being sanctioned, that the people of those countries did nothing wrong. Now, the governments are bad, right? In terms of the way that you and I would look at democratic rule or communism or whatever it is, but the people are being hurt as well. So there's a whole group of people who would just argue, listen, we shouldn't hurt anyone at the expense of punishing one person or a group of people. There's other people who argue against that. But I do think that if you really kind of zoom out and you say, I'm gonna take myself out of the Western worldview, and I'm simply gonna look at this as we're all part of the human race, it's censorship. And there might be an argument for censorship, but there also might be an argument against the censorship. And so what Bitcoin does as that specific kind of payment network is it says, anyone in the world with an internet connection, I don't care where you are born, what language you speak, what religion you are, your wealth status, your education status, none of it matters. If you have an internet connection, you can plug into this monetary system and you can move value around the world to anyone else without asking for permission. And in the United States, we basically have that ability in the US dollar kind of traditional banking system. I can pretty much send money to almost anyone I want unless they're a really bad person that's on some list or something. Most people in the world don't have that capability. And so what you're essentially doing is you're democratizing access to a true store value and a medium of exchange, right? And so what you see in many of these countries is that when their currency starts to fail, the first thing that a government or a group of people in power and influence do is they lock the citizens into the currency with capital controls. Why? Because if you let them out, it exasperates the problem. And so now what we're seeing is we basically are giving a tool to billions of people around the world that is a peaceful protest, right? You and I had no say at all when not only the Federal Reserve and elected officials here in the United States, but central banks around the world over the last 12 months decided to create trillions of dollars and inject it into the monetary system, right? They have arguments, and some of them are very good arguments as to why they should do that. They're trying to mitigate short-term pain, long-term they'll figure out the other issues, right? They have very kind of elaborate and well-articulated kind of viewpoint as to why they're doing it, but you and I had no say. And so when you start to look at, we have a very small group of people in this world, both in our country and in countries around the world that make these decisions that have very, very far-reaching kind of impact. And on top of that, in many cases, there's actually not that much kind of accountability because usually these are not elected officials who are making some of these decisions. These are appointed. And you can argue that, hey, we elected somebody who appointed them, but at the same time, that accountability isn't quite there. And so I think ultimately, when you just back out, you say, what is Bitcoin and why is it important to the world? It is giving access to anyone in the world with an internet connection to a store of value and a monetary network that allows them to peacefully protest and to opt out of a system that pretty much is not working for majority of people in the world. So it's moving the power from these centralized places, sometimes unelected, to the individuals and to the people. So the dollar does seem to work for Americans and for many people in the world, but you kind of have a vision. You paint a picture of a future where potentially we move to cryptocurrency. So what kind of trajectory do you see where Bitcoin can become the main currency in the world, or at least cryptocurrency become the main way of storing value in the world and basically overtake the dollar? Yeah, so I always go first to, we don't need to have competition in terms of a direct competition between the dollar and Bitcoin, right? If you look at most technologies in the world, the really valuable ones are actually market-expanding technologies rather than simply just market share-stealing technologies. So if you look at Uber, for example, Uber didn't just say, hey, I'm gonna go take out all the taxis, right? It actually drastically expanded the market for people. Now there's literally millions of people in the United States who don't have cars because they use Uber, right? And so I think that Bitcoin is very similar in that, yes, there is a component of medium of exchange in terms of the dollar, but also there is this component of just store-of-value assets in general. And so when you start to look at Bitcoin specifically, I think that what you're seeing is you're seeing a generational gap where young people say, I grew up with a phone in my hand. I'm digitally native. The whole idea of going to the bank and sending a wire or going to an ATM and getting physical cash is an antiquated idea in their mind, right? I one time asked my brother, he's 24 years old, and I said, hey, how do you send money to your friends? And he gave me one answer, which I expected, which was Venmo. And the second answer I didn't expect, he said Uber. I said, how do you send money via Uber? He said, well, we get in a car together and at the end we split the ride. And so again, you and I have probably both done that, but I never thought of it as a way to send money to each other. And so it is a psychological difference between even me, who's only a decade older than him or so, and his peer group. And so I think as we're watching kind of Bitcoin continue this ascent, ultimately what we're seeing is an entire generation of kids are saying, listen, if I look at financial assets across the board, I have stocks, I have bonds, I have currencies, and I have commodities. I know that bonds from a real rate return perspective is flat to negative, right? I'm gonna make no money on this because I have a belief that my dollar is being devalued. And actually what we're starting to see is again, the internet has broken down these walled gardens and kind of these centralized hubs of information in that if you were to look at, let's say the stock market, from 1971 to today in dollar terms, it's a 45 degree angle right up into the right, right? You know, it's kind of seven, eight, 10% growth every year. And it's amazing. Just get invested in the stock market and you'll make money over a long period of time, regardless of the dips along the way. If you denominate that same stock market in gold, the stock market is down since 1971. And so is it so much that the stock market is accruing true value, or is it that the underlying currency in which it is denominated in is being devalued, right? And now it's being devalued in a very disciplined way, right, in terms of, it's not like it went 50% devaluation in a short period of time, but it's still being devalued. And so I think that people are waking up to this idea that a traditional 60, 40 type global portfolio doesn't work anymore, right? 40% of it in bonds is just not going to get it done. And so when you start to look at this, people first look at Bitcoin via two main ways, in my opinion. They look at it, one, as a store value. Should I actually go and put some of my wealth there, use it as a savings technology, right? We ask people in the traditional world, if you're a teacher, a fireman, an accounting, you know, mid-level manager, we say, hey, go do your job. Be the best in class as a fireman, or as a teacher. And then, oh, by the way, you have to be a professional investor as well, because if you just put your dollars in your bank account, you're literally going to have your wealth devalued away over time. So you can't just save, you have to invest. That is a really tall task for people. They have a hard enough time just doing their job right, taking care of their family, right? Now they gotta go be an investor. So I think savings technology from a Bitcoin standpoint is if you buy Satoshis or Bitcoin, over time it will increase from a purchasing power standpoint, because there's a fixed supply and demand continues to rise. But then you start to look at, well, what other assets do people put in their portfolios? Whether it's art, it's real estate, it's precious metals, or something else. Most of those assets are not because people actually think that they're gonna go up in value over time. They're using them to store value, right? The reason why somebody buys gold is because they store value, right, historically. That's a narrative-driven type asset though, right? We tell people it's scarce. We tell people that it is a store of value. When you look at it though, we don't know how much gold exists in the world. We have a good estimate, right, but we don't actually, we can't prove how much there is. We don't know how much is coming out of the ground every day. Again, great, fantastic estimate, but we can't prove it. And we don't know what the total supply is. And that's what you mean by narrative-driven. We can't really prove it, like mathematically. You, I, and everyone else in the world has lived in a narrative-driven world for the last couple of decades, right? And what the internet and digital technologies have done is it opened up the possibility and the desire from people to have a world now where I can validate things. So when I see that headline, I want to see you say whatever happened in the news, if you're the subject of the news, rather than have somebody else tell me the story. If I see that you say something is scarce, prove to me that it is scarce. And so I think that's kind of a psychological shift the younger generation is starting to understand because ultimately, you and I probably grew up in a world where our parents could tell us a story and we just believed it. You know, dad or mom says it, it must be true. If my brother heard a story, what does he do? He goes to Google and he looks it up, right? He comes back and usually tells my parents, oh, you got the story wrong, right? And so I think that that provability or that validation ends up becoming really, really important. And so, you know, look at something like gold. I think that people are drastically underestimating the shift that's underway right now. Gold is one, down in value since April, or I'm sorry, August of 2020. And so in a timeframe where central banks have had historic quantitative easing, literally $6 trillion in the United States, the one asset that historically has been the best store of value and has, you know, in 2008 financial crisis hit an all time high based on the government response, has actually suffered for a main part of this financial crisis. You then look at central banks around the world who have been very large holders of gold for a long time and net buyers on a monthly basis. For multiple months over the last six months, they've been net sellers of gold. And then you start to look at jewelry demand. So the actual non-monetary value of gold and that demand for gold jewelry peaked in 2013 and has continued to fall since. And so what you start to say to yourself is take just the asset of gold, which about $10 trillion market cap, and you say, okay, well, if jewelry demand continues to fall, even if it's at a slight rate, but it's continues to contract, you have central banks that now at sometimes are net sellers and sometimes net buyers, right? So, okay, again, contraction there. And then from the investment standpoint, the actual price, the daily price of this continues to fall, which is a signal that there's a contracting demand from an investment perspective. That's 93% of all use of gold. Only 7% of it's used for actual technology and metal conduction and things like that. And so you have a $10 trillion asset that it appears, and again, maybe data changes and I'll change my mind and other people change their mind, but it appears is on the decline. And so if that happens, you're gonna get the contraction of a $10 trillion asset. Where's all that value go? And what you're seeing is at the same time that that asset is contracting, you're also seeing a massive influx from not only retail investors, not only kind of the wealthy and the elite, but also from financial institutions, corporations, pension funds, et cetera, into this kind of digital sound money. So you're saying that there's a kind of shift from gold to Bitcoin because they have a lot of the same properties, except one is in the physical space, the other is in the digital space. So do you see like central banks quietly potentially switching out from sort of gold to Bitcoin? Like naturally it's just doing, seeing the pattern that you're referring to now, but more drastically into the future where there's a complete shift. If you line up the gold community and the Bitcoin community next to each other, they'll agree on all the problems that they see in the world, right? They'll actually agree on the solution that sound money is the solution. Where they differentiate is the gold communities believes that it's the analog application of sound money. The physical gold, that is the solution. The Bitcoin community believes the digital application of sound money. Bitcoin is- Can you define sound money, by the way? Sound money is just outside the system and no one can create more of it. So nobody controls it. This is scarcity is fundamental. Exactly. Why is scarcity important in money? I think scarcity just has this very high correlation to value across all assets, not just money, right? Money happens to be the unit of account that we use in terms of daily commerce, but whether it is, as we're seeing now, sneakers, art, whatever it is, scarcity ultimately is that signal of value, I think. And that's just been the way that humans derive value for literally thousands and thousands of years. Yeah, I gotta say, that's my view on life and love in general, is scarcity is what makes it valuable. People talk about immortality. I would like to be immortal, but it does seem that when you let go of the fight nightness of life, I feel like that meals and the experiences you have get devalued significantly. Like the longer you live, the less value there are in infinity if you live forever. I worry that all the meaning will dissipate. And the same thing with love, a quick criticism of sort of dating culture and all that kind of stuff. Like I haven't, a shocking revelation that I've never been on a tinder date or any of those things. I believe that scarcity in dating and interaction is like intensifies the value of when the interactions do happen. So when love does happen. And so in that sense, there's something magical about scarcity in the more subjective psychological social world as well. And perhaps money is just another version of that. It's all about the stories and ideas we tell ourselves. I think they're actually more interconnected than you're giving it credit for, which is what is money? Money is time, ultimately. The pursuit of the acquisition of money, of whether it's a currency or true money is because that should give you more time. And so one of my favorite movies ever is, and it's funny because Justin Timberlake is in it, is this movie, In Time. I lose most people at that part. In Time. In Time. And basically the premise of the movie is that everyone has a clock that's embedded into their arm. And so if you go to work, you basically put your arm underneath when you leave, and there's time that's deposited into your clock. And if your clock ever hits all zeros, you're dead. You die on the spot. And so there's a number of scenes where people are basically running to get to you, and I give you a little bit more time so that you can get to work on Monday, and then you work to acquire time. And so basically time becomes this currency. But what becomes very fascinating about it is there are sections in society where literally there's physical places. If you only have, let's say, 72 hours or less, you're allowed to go to section one. Section five, though, is because you have years and years and years on your clock. And in this movie, everyone at the age of 25 freezes from a biological aging standpoint. So everyone stays the same, but you may have lived for 1,000 years. And so what becomes so fascinating about it is that rich people have time, poor people do not have time. And so in it, Justin Timberlake, the main character, at one point essentially acquires a bunch of time, and he's able to go to one of the higher levels, and now he's attending all of these galas and poker nights and all this stuff. And one of the first things that he learns is that in the lower end of society, everyone is running everywhere at all times in the movie because time is so finite and it is so scarce. And so therefore, why would I walk down the street? I must run down the street. In the highest level of society, no one runs anywhere. And in fact, if you run, you are seen as lower class because wealth is time. And so that movie, it's got a ton of things that you can pull out of it, but to me is the perfect epitome of money is time. And so when you start to think about the acquisition of money, it goes to this whole idea of time billionaire. And I know that there's probably a lot of people who have heard about this already, but if you think of a million seconds, it's about 11 days, a billion seconds is 31 years. And so if I said to somebody, you have to switch lives with Warren Buffett, would you do it? Some people would say, sure. That'd be their initial reaction. I said, but you gotta have to be 92 years old. Is the money worth the lack of time? Most people would say no, right? And there's this guy, Graham Duncan, who really articulated this well. And ultimately what ends up happening is you realize time is more valuable than the money, but you acquire the money to gain more time. And the reason it's valuable is because of the scarcity of time. We currently have the biology, the physics means that this is not just the narrative we tell ourselves, maybe it is, I don't know, but it feels like pretty sure we're mortal. And in that sense, the scarcity there gives value to time. It's fascinating to think about all the thought experiments here of if that could actually be in the economy, if you could actually convert time in a frictionless way to money. Well, and if you start to pull on this a little bit and say, okay, a young person today, let's say somebody in their 20s has about 2 billion seconds left in their life, right? Kind of 60 years, give or take, based on life expectancy. They usually, until they start to understand this concept, think of wealth in dollar terms, but dollars are being devalued. And so a million dollars doesn't get you what it used to get, right? It's kind of an old adage. And so what you're doing is you're pursuing something that ends up losing value. And so it's the constant rat race. It's how do I constantly try to get more? How do I get more dollars? How do I get more dollars? Because even if I say to myself, I'm gonna retire when I get $100,000, when I get the $100,000, the $100,000 five years from now doesn't buy me what I thought it did. So now I need 500,000 or 200,000 or a million or whatever the number is. And so ultimately what ends up occurring is that the Bitcoin community and many people in kind of this idea of sound money is you want to be able to acquire an asset that not only will hold the value, store a value over time, but it will actually appreciate over time. And so when you look at something like Bitcoin against the dollar, against other types of assets, all of these assets are down compared to Bitcoin, right? Now, some of that's just in the early days of kind of the pricing of an asset, you go from very small to something much larger. But now what you start to look at is, well, if you have a finite supply of something, what ends up happening is people begin to value it more. And so in a world where dollars are infinite and other fiat currencies are infinite, Bitcoin becomes very, very interesting, very special, and something that is very aspirational. And so I think that's where you're starting to see people say, wait a second, this is something where that finite, secure store of value is essential to wealth generation and preservation over a long period of time. And if Sam Harris is right, that free will is an illusion, it's really interesting to think about maybe time as a kind of blockchain, because you can't change anything. And then the physical space-time of the universe is a ledger, so maybe it won't be Bitcoin that replaces gold, maybe it'll be time. Once we crack open that, in fact, the universe is fully deterministic. So maybe that's what like Eric Weinstein is afraid of, once you figure out the theories of everything, of physics, we'll be able to then start trading, create a market out of the very fabric of reality, and that way break it. Well, if you look at infinite inflationary-type currencies, you can't do that, right? Because it constantly is losing value. When you look at a finite asset, again, that has the provability of the actual finite element to it, ultimately the wealth is that marketplace. And so I always kind of try to highlight for people, the top 55% of Americans understand something that the bottom 45% don't, they invest, right? The bottom 45% consume, the top 55% invest. And that's why we have a wealth inequality gap, and it continues to get wider and wider and wider, is because the people who are holding the devaluing assets and saving are watching their wealth be devalued away. And there's arguments and controversy over how fast that's happening, but it's happening. The people who are holding the assets that have any level of scarcity, right? Real estate may not be finite, but it's scarce, right? Art may not be finite, but it's scarce. Gold may not be finite, but it's scarce. Those assets continue to appreciate against the devaluing currency. And so when you then say, no, I have complete finite supply with provability and this transparency around it, where everyone knows how much is there and where it's going. Now, all of a sudden, you and I can transact back and forth that value, and it is a representation of time. Because what I can essentially do is, if I gather or acquire more of that wealth, I then can apply leverage to my life. I can use machines, humans, or some other resources, and basically now free up my time. Yeah, and it's not fun about the way you are trading time. Maybe it's a little bit indirect, but maybe not. So just because I brought up Eric and you're on Twitter, I'd love to hear your opinions. I talk to him a lot. He seems to have stepped into the beautiful dance of human communication and the social dynamics that is the Bitcoin cryptocurrency community. Do you have thoughts on gauge theoretic conceptualization of the world or just Eric in general? He's got a lot of love in his heart and he's got grace in the way he communicates, but he's also loves to play with ideas and seems to have touched a sensitive point with the Bitcoin community. Is there anything you could say that's hopeful, inspiring about that whole dynamic that went down? So I don't know all of the details, but what I will say is I've listened to a number of his podcasts, and him and there's a whole bunch of people like him. I basically put them in the bucket of they're an independent thinker who are courageous enough to speak their truth, whatever that may be. They are humble enough to revisit their ideas and say, I got this right, I got this wrong, information changed, I'll change my mind. It's obviously a sign of intelligence to be able to do that type of stuff. And I actually think that one of the most scarce things in our society are those independent thinkers who are able to do all this, right? Speaking of scarcity, yeah. And so to me, I put Eric and the whole host of other people, if you look at the intellectual dark web as a label that's been used, they're actually some of the most important people in our society because they're the people who are willing to stand up against the mass kind of thought process. They're willing to talk about things that others may think are taboo, right? They're willing to change their mind, which all of a sudden has become a bad thing rather than a good thing. And so when I see the exploration of ideas in public, I actually think that those are the people who are most open to the kind of vehement blowback as well, right, because that's part of what they're doing is that they're eliciting, hey, I'm gonna throw an idea into the arena. If it doesn't get attacked, they actually may be more nervous than if there is some level of, kind of war of attrition, if you will. And so what I've seen with a number of the people who have done this, everyone from some of the best hedge fund managers and kind of money managers in the world, all the way to what I'll consider some of the most intellectual people in the world is they play with these ideas and they play with the ideas and they play with them and they play with them. And they all arrive at the same conclusion. And sometimes it takes a month, sometimes it takes years, but they arrive at this Bitcoin thesis. And what's so interesting about it is it highlights something that many people view as a bug, but I think people in the Bitcoin community view as a feature, which is that community. And so what ends up happening is when you have something that is as ambitious as creating a global reserve currency, doesn't mean it needs to unseat any of the existing ones, but become the global reserve currency of the internet, right, this digital economy, you need shepherds of it. And so just like a technology company wants to find those loyal fans that are willing to go out and market and word of mouth and kind of not only promote it, but also protect it, this technology that is this decentralized thing, which uses a financial incentive in order to elicit the buy-in, not from a financial perspective, but from a mental energy standpoint, has built one of the most rabid, powerful, and engaged communities on the internet. And what ends up happening is those people have thought more about these ideas and actually challenged those ideas more than anyone else in the world. And so I've got a lot of folks who will just say, there's this guy Marty Bent, who we'll talk all the time about, the Bitcoin critics haven't done their homework in a lot of cases. So they show up and sometimes it's super intellectual, lazy arguments. Sometimes it's actually very well thought out arguments on the counter to the Bitcoin thesis. But ultimately what ends up happening is you're talking to somebody who's an expert. They've been thinking about this for five, seven, eight, 10 years, right? They've gone through every simulation you possibly can. And they show up with data examples and responses. Now, they're not always right, but they've just done the work. And so what I actually like about folks like Eric and others is as they're kind of going through this journey, they're incredibly smart, right? And they provide or they apply a lot of intellectual rigor to some of these arguments. And so what it does is, what does it do? It's a marketplace. It keeps people honest. So let me sort of make a few comments. It's kind of interesting. So you're exactly right. Maybe the blowback is part of the mechanism that actually develops these ideas and so on. I do want to kind of speak to a little bit of the toxicity that I've experienced in the Bitcoin community. I kind of see it, the Bitcoin community, I think you painted a really nice picture, which I kind of see it as an immune system that protects against sort of the viruses that are bad ideas. That said, the immune system can destroy a body, right? And the thing you mentioned about Eric and maybe about myself and in general, just people exploring ideas, is there is a Dunning-Kruger effect, which is when you first start exploring ideas deeply, you have an overblown level of confidence about how much you understand. And that's actually the process about learning, then you realize you don't understand much. What I've noticed with the Bitcoin community is they're not as patient with the basics of the Dunning-Kruger effect. If I step in and make declarative statements about Bitcoin, I read a long time ago, the white paper, at the cursory level, I felt that I understand the technology, this is basic intuitions. You know, I didn't think about the social dynamics, I didn't think about any financial implications and a lot of the deep, actually the ongoing innovations and all that kind of stuff, but I thought I understood that technology. And so I step in and make declarative statements. I think those are the first time you say, okay, what's the role of Bitcoin in the world? You start thinking about it deeply, and then you make statements. The toxicity that you get in those first few statements is really off-putting to me. I'm somebody that tries to communicate love and live that with everything I do. And there is a level of disrespect that I've experienced, not directly, just observing others. People have been mostly kind to me, and I appreciate that. But if you're going to criticize me about my exploration of ideas in Bitcoin, you have to also acknowledge that I'm a human being that got a PhD in stuff. I did some hard shit. It could be in farming, or it could be in whatever. I've lived life, and I've really thought deeply, and I really care. I know a lot of shit. And it's possible that I actually have a lot of ideas that you can learn from. Now, if it's agriculture, fine, or if it's artificial intelligence, fine. I know what I'm talking about about certain things, and I could be wrong about a lot of things. And there's an exchange of ideas that makes that mechanism that you talked about more efficient. Sometimes when the blowback is too strong too early on, the development of ideas is just inefficient. And I'm not sure if there's a, the way it was explained to me is that for so long, that community was bombarded with just bad ideas, criticisms. They're just overly sensitive now to bullshit. They're triggered by statements. They've heard it all before, and they're like, oh, there they go again with the same old arguments. But that doesn't mean that you have to, sort of, I guess, develop patience and so on, especially when you feel, like in my case, that the person is coming from a good place, right? I don't know if there's something you could say that's positive about the future of this kind of overcoming this toxicity. I think there's a couple of trends that are all kind of coalescing here in these types of experiences. So one is, when you look at a community, there's always a spectrum, right, in terms of, there's some people who over-index on kindness and stupidity, right? And there's some people who over-index on intelligence and basically just being an asshole, right? And then you get everyone in between. And so, naturally, as we know, the extremist ends of any community end up being the loudest, usually, right? The second thing is, there is, from the outsider view, like at the beginning of the exploration of ideas, it's very much a learning process, right? I don't know if I understand this or not, but here's ideas A, B, and C. From the internal perspective, there's a trillion dollars of value at stake and we must protect it with our lives, right? The truth is probably somewhere in between there, right? And again, the world's not black and white. There's this kind of more gray area that I think actually is where most people exist. The other thing that's at play here is, I think the Bitcoin community understands the internet and internet culture and narratives better than almost anyone. And so you see this with kind of the, the just complete destruction of narratives with memes and just the visceral reaction and the use of things like Reddit and Twitter and YouTube, podcasts, just areas where I think a lot about if you are an upstart, right? And you are gonna go challenge the most well-respected elite kind of establishment institutions in the world. If you walk in in a suit and tie and you say, I'm here to debate you with ideas, you're gonna get your clock cleaned, right? Cause they're gonna trot out, they're lawyers, they're regulators, they're lobbyists, right, like all this stuff. If you instead say, I'm gonna meme you to death on the internet and I'm gonna control the public narrative. You've shifted the power, the asymmetry of power is more symmetrical now. It's the ultimate insurgency, right? If you bring it back to the battlefield. Yes, and so when you think about this, you have to lean into the advantage that you have. And so what ends up happening is, you and I would absolutely lose it if we saw JP Morgan or Goldman Sachs or the Federal Reserve start tweeting memes, right? It would almost, the validation it would give to the medium and the even playing field that it would provide would pull these establishments down to the level of what is this upstart? But now what you're starting to see is that the Bitcoin community, even though there's some level of toxicity at times, even though there's this visceral reaction, sometimes there's even what I would call bullying or kind of outward projection of things, right? Even though it may be a small percentage, it'll happen every once in a while. What they do understand though is that these establishments are made up of humans. And what you can actually do, one of the best ways to pick apart an institution is to recruit from inside of them one by one. And so what you're starting to see now is, I get the messages on Twitter and LinkedIn all the time. Hey, I'm a banker by trade, but I'm a Bitcoiner at heart. And so what you're doing is you're essentially infiltrating the organizations, not in physical population, but with the ideas and with the philosophies. Banker in the streets, Bitcoiner in the sheets. Yeah. I like it. That said, in terms of shit posting and memes, I gotta say, like bring it on because I believe in terms of asymmetry of power, I believe in that love will save the world, not memes, or at least good vibe memes as opposed to shit posting. It's an interesting battleground though. It's an interesting battleground to think about. The other thing I would say too is, one of the elements that's always kind of funny to me is how much of the entertainment is love, right? So when you start to think about how many of the memes that are posted, for example, are for outsiders versus insiders. Yes. Laser eyes, right? Which seems absolutely ridiculous, elementary, and frankly, beneath anyone in any level of power or influence in the world. Somehow has congressmen and senators who have done it. They're not trying to convince their colleagues in elected positions to become Bitcoiners. They're speaking directly internally to the Bitcoin community. Yeah, there's some sense in which, yes, memes is love. Even I keep hearing Bitcoin is love. They're trying to convert me. The one that you have to laugh at, right? Probably my favorite one out of all of it is I've seen on multiple occasions, Mark Cuban a couple of years ago, Kevin O'Leary, whoever, wealthy people, billionaires, et cetera, and you have people on anonymous accounts who who knows who they are telling them have fun staying poor, right? And it's just, again, part of a community, and I think it's a feature, not a bug. There's bad aspects to it at times, but I do think it's a net positive. Yeah, just like the immune system. It does a lot of crappy stuff, but overall, it's a major net positive. Maybe this is a bit of a personal question for me, just out of my own curiosity, but I've talked to Ray Dalio a few times. So Ray Dalio, I think, was one of those people that took that journey, the Bitcoin journey. Do you have thoughts about him specifically, about that whole world, and about the journey, maybe of others that are going through the same process? Because Ray is, at least from my perspective, I'm a bit of an outsider. He's one of the most insightful and deep thinkers about investment, about finance, about economics in general, actually about life. So it's interesting to see him go on that journey. Do you have something to comment about Ray, or just those kinds of people in general? So if we look at what I'll just consider the legends of Wall Street in general, right? There's no denying that they're incredibly intelligent. There's no denying that actually, especially in the hedge fund world, they're some of the most open-minded people in terms of they're willing to change their mind when they get new information. There's no doubt that they are historians in the sense of having studied financial markets in cycles over time. And also, one of the things that I really respect about all those guys is almost all of them are willing to put ideas out via various writings that they do, and accept the public criticism, right? Whether it's Howard Marks, Ray, or others, they will put this stuff out in public. And sure, there's a lot of people who are supportive and kind of are part of a fan base, if you will. But there's a lot of people who also think that sometimes they say stupid things. And so putting that out takes kind of courage, right? I think Ray's actually the most fascinating, though, out of all of these kind of legends of Wall Street, in that he understands debt cycles. He understands currencies. He, for a while now, has been all over, and famously said, cash is trash, investable assets, right? He kind of like just knew all of it. And for a long time, Bitcoiners have said, Ray, you understand the Bitcoin argument, you're just missing the last part, which is Bitcoin's the solution, right? And so he was gold and some other ideas. But I think that he's a perfect example of when you are part of the establishment, people view you in a very static way as the leader of a part of an establishment. But whether it's Bill Gates, Ray Dalio, or somebody else, each one of these people were innovators and challengers to a system. They were upstarts at one point. And so it's kind of this idea that if you live long enough, you eventually become the man, right? And so Gates is a good example, right? Warren Buffett is a good example. Ray Dalio is a good example, et cetera. And so you have to give credit, I think, to Dalio in the sense of he kept an open mind about all of this, and more so than many of his peers has continued to do the work and come around to this idea. And now, I don't wanna know if I wanted to say that he's a Bitcoin proponent as much as he believes it is one of a portion of assets that can be a solution. And so to me, when you start to convince those types of people, when it's Paul, when it's Paul Tudor Jones, a Stanley Druckenmiller, a Ray Dalio, Howard Marks now even writing about it saying, hey, I was anti Bitcoin and put a ton of intellectual rigor into it, but thank God my son bought a bunch of our family, right? And kind of we've had exposure to it. I think what it does is more than anything, it's not gonna convince somebody to go and take it seriously or go ahead and make an allocation. It reduces career risk. And so if all of a sudden when Paul Tudor Jones and Stanley Druckenmiller come out and say, hey, I own Bitcoin and here's why, every other investor on Wall Street now can say to an investment committee, well, it's good enough for Paul Tudor Jones. It's good enough for Stanley Druckenmiller. And so I think that it's very interesting because Ray doesn't just represent Wall Street. I think Ray in some weird way represents this like macro economic investor. And so some of those are in hedge funds and some of those people would be like CIOs at organizations. Some of them would be at corporations and some of them are just kind of retail investors. And so you can see this kind of inflection point throughout the adoption of Bitcoin, right? There was infrastructure that got built. Okay, that kind of led to more adoption. There was certain individuals, right? Usually they were kind of technology oriented entrepreneurial billionaires. They would buy it and come out and say it. Okay, that led to inflection points. You started to have some of these kind of Wall Street legends come out. Started to have financial institutions started and now you're seeing corporations start to do it, right? Eventually there's gonna be a central bank that does it. And so you kind of walk through that line and what you understand is like, it's the same thing every time. It's just somebody new, right? That path, right? That Bitcoiners journey, if you will. And I think that that is almost the beauty of it is if you short circuit the journey, it's almost like somebody doesn't appreciate it, right? If you take, let's say, somebody who's a young kid and you just give them a bunch of money and they didn't have to work hard for it, they don't really appreciate it. Well, and Ray actually has a book, Principles, right? And he talks about the hero's journey. So he's like living it in some sense in terms of thinking about digital currency in general, like digital finance. It's one of the big transitions, transformations of our world in some sense. It's not just about money. Or you could argue that money is everything. I mean, it's like money isn't just the narrow definition of money. Money is really everything. So where you could argue that sort of cryptocurrency is like the base layer of this transformation to the digital space and everything else would just be built on top of it. I use a different word that I think is kind of closer to your world, which is it's ultimately automation. And what I mean by that is, before 1970 or 1980, all the assets were analog. And so when you have analog assets, physical stock certificates, physical bonds, physical deed to a home, you had to physically exchange them. When we wanted to increase transactions and increase kind of global finance and access, we took those physical assets and we created electronic Q-SIP assets. So now we have in centralized databases kind of a file represents the asset that's sitting somewhere in custody. And you and I can transact them a little bit easier, but still centralized. There's still some bureaucracy and maybe it takes two days to transact rather than actually mailing it across the world. Now what we're seeing is a transition from those electronic Q-SIPs to these digital assets. And so if you look at, again, just let's say money or currency, every currency in the world is gonna be digital. You're gonna have a digital dollar, a digital Euro, yen, RMB. You're gonna have decentralized kind of open source money like Bitcoin. You're also gonna have private currencies like Facebook's attempt at Diem and there will be others that will try to do this. And so when you get everything digital, right, and I think that's the kind of the first step that everyone focuses on, the competition at the technology layer essentially goes away. You get some level of feature parity and sure there's bells and whistles on each kind of implementation of a digital currency, but at the end of the day, the technology is relatively the same. And ultimately what it will do is it will facilitate the adoption of digital wallets. So you have to have a digital wallet regardless of what digital currency you have. Same with me, same with everybody else in the world. But what it does do is when you kind of push away and reduce the friction of competition at the technology layer, it moves the competition to the monetary policy layer. And so when you get to that layer, now all of a sudden it becomes interesting because all of the currencies are the same except for this one right now. And maybe there'll be others in the future, but for sure Bitcoin today, and people may try to replicate in a private manner or something, but Bitcoin is kind of the only finite, scarce digital sum of money. And so when you then have that pretty big difference in that competition at the monetary policy layer, it's actually not gonna matter where you get paid, right? And what I mean by that is like you and I both live in a single currency environment. I get paid in dollars. I historically have saved in dollars. All of the assets in my life are denominated in dollars, and I owe my debts in dollars, whether it's taxes or in the private market. And I don't have to worry about foreign currencies. I don't exchange anything. The only time I would ever think about another currency is if I'm going to another country in their single currency environment. And in order to change or exchange my currency, I go to the bank or I go get ripped off at the airport. Right? Like those are my two options. So it's high friction to change between currencies. When the competition of technology is kind of innovated away, now I can get paid in dollars, these digital dollars, and with a click of a button, switch into any other currency in the world. And so what ultimately happens is value and liquidity is going to coalesce around the best monetary policy. And so you get in this very weird world where even if the United States says, hey, you're gonna get paid in dollars, you have to pay your taxes in dollars, you're gonna start to see people operate in a multi-currency environment where they say, okay, I got paid my digital dollar, click a button, I save in Bitcoin. It stays there, protects or grows my purchasing power. Oh, I need to pay my taxes. Let me switch back into dollars with a click of a button and pay. When you go to a multi-currency world, it's not just about currency. It's now multi-asset world. Because not only is the currency digitized, but that same technology is used to digitize stocks, bonds, and commodities as well. And so today we live in a very fragmented financial world where basically I have a brokerage account, I have a bank account, I may have an alternative asset account, et cetera. When I can put all of those assets in a single digital wallet, and I can then go from asset to asset without having to go back to a single unit of account. Like frictionless going from asset to asset, yeah. So now what you end up doing is you start to open up the possibility for machine to machine transactions. So today, if you and I write software code for two machines to transact with each other, they can't transact physical currency. And in many cases, they can't actually transact the electronic Q-SIP currencies or assets either because there's too long of a settlement time. So you can't get true automation, right? So the whole idea of like the car's gonna drive over a strip in the road and it's gonna pay the toll, right? Well, that can't happen right now because literally the transaction won't go through, right? And so I always joke that like in an automated world, it's like a CD-ROM, but we're trying to take cassette tape player assets and put it in the CD-ROM. It's just incompatible technology. That's a reference nobody understands at this point. By the way, you need to update your reference. I probably do. It's like taking a CD-ROM, trying to put an MP3 player into a streaming. But I think that the reason why that becomes really interesting is when you start to create these digital assets, now you open up the world of possibilities. So when new technology is created, you can do two things. You can either create new things the world's never seen before, or you can use it to improve the old world. Most people, because it's the easiest thing to think about, wanna improve the old world. So an equivalent of this would be when the internet came along, a media company that had newspapers would say, hey, we should take a PDF of the newspaper and we should put it on a website. And now anyone in the world can go to this website and they can read the newspaper today. That was valuable, but it missed out on the ability to change headlines, to test, to put multimedia, to distribute it differently, to do all kinds of things that today we understand the internet really empowered. And so what I think we're about to watch happen is we're gonna digitize the assets. We're gonna put them all into these digital wallets. You're gonna get automated technologies where machines can now transact with each other. And we're gonna do simple things. Like, why do we pay people once every two weeks? Why don't we just pay them at the end of every day? Or why don't I literally stream payments to you on an hour by hour basis based on the work you do? It would solve incredible economic issues in our country and in countries around the world. But historically, businesses can't do this because of the technology problem. They can't keep track of it all. How do they pay everyone every day? How do they pay everyone every hour? Like, you just can't do it. Yeah, it's funny. The vision of the future you're painting, it's kind of an exciting one, and it almost makes me sad looking into the future when we'll look back at this time. It's like, how incredibly inefficient our financial transactions were, like the transaction of value of any kind. Like how, like, we have to pay each other. Like there has to, like, processes. There's like payroll and all this kind of, just the entirety of the transactions is just like painful. Almost all transactions are painful. And even, and the companies that innovate to make the transactions a little bit more frictionless, like Amazon with the one-click purchase button, like went out huge. But even that's really painful. There's actually a really interesting, especially then you start to move that into the space of data. There's a lot of people thinking about privacy and data. And like, can we put, can we like convert data into like money? It's just so that you can pay for how much you reveal to the companies about your own private data that can then be used to assign value to you. So you can use the service for free if you hand over the data, but there's like explicit transaction going on. So you can empower all those kinds of things that will just like fundamentally change our world. That's really, really, really exciting. One of the most interesting things to me is I invested in a company called Bridget. And what they told me was they said $8 billion was paid to the top four banks last year on overdraft fees. So literally they took $8 billion from people who didn't have money in their bank account. And so when you dig into why is that, a lot of times it's not that the people don't have the money it's actually a mismatch of the payments. So what ends up happening is you get paid on the 1st and the 15th, but on the 12th, your Netflix bill hits, on the 13th, you went grocery shopping and on the 14th, your car payments hit, you overdraft. And then on the 15th, you actually get the check and then you're able to pay not only the overdraft, but for the expenses that you have. And so something as simple as just getting paid at the end of every day, immediately would eliminate some big percentage of those $8 billion of value that flows to large institutions on overdraft fees. Yeah, and also, I mean, this whole process with overdraft fees and just many of the financial transactions we have to live through today, forces many of us to be like accountants, like to understand the different mechanism of financial, like the movement of money, as opposed to you, which is what we wanna do as human beings, operating in higher layers of like providing services for others, of like following your passions and like working for others, like doing cool shit, or basically providing value, exchanging value in the world and not thinking about the money. The money takes care of itself and then you see the results of it. So you're able to think in terms of money, but not have to know how the accounting works. Automation simply frees humans up to do more creative work. Yeah, right. Yeah, yeah. Like that's it. Yeah. Which is why you use the term automation, which I think is kind of brilliant, reframing of all of this. Yeah, because ultimately digital technologies are merely the conduit to usher us into that world. And I think the most fascinating part of this entire industry is people who are trying to figure out, now that we're gonna have these digital technologies, how do we usher in that automated world faster? And so there's people who are building all kinds of incredible things, right? There's literally some technologies where you can stream for paying for consumption of content. Yeah. Right? I saw somebody recently who they basically said, hey, I have created something, but it's not gonna be released until everyone on almost like a GoFundMe type situation pays for it in combination, then it gets unlocked. And so when you start to think about this, it's not only innovation on the technology front, it's innovation around the way that we form capital, it's the way that we organize resources, it's the way that we build companies, it's the business models, right? It's the application of those technologies. All that stuff starts to change and go back to 2007, it's when the iPhone came out, Uber wasn't possible, or I mean, just go down the line, like all these companies that weren't possible before, when the digital technologies are kind of adopted on a global scale, I think that we all, myself included, drastically underestimate how fast and how big innovation can be, because it's just hard, right? Like we like to think linearly and that's not how the world works. Yeah. I do find it kind of interesting. It is NFT based, but I don't think it has to be. This idea of, I think, BitClout it's called or whatever, the idea of sort of investing in individuals, it makes me immediately think about investing in ideas. So even just the words you speak having value, and sort of if you have a frictionless, like automated financial system, then you could do a bunch of interesting things about what it means to add value to the world. I mean, I don't know if BitClout is currently an efficient representation of that, but I am truly happy that, however that thing works, I'm just one notch above Vladimir Putin, which is one of the, that's like one of the bucket list items for me, to have a list where I'm one notch above Putin. What I think you're talking about here is important because there's historical examples. You could invest in a patent in some situations. You could invest in an organization that has an idea, right? So these are super inefficient, given kind of the vision that you're painting in terms of like investing directly in an idea in a super efficient automated fashion. But that's how the technology evolution works, right? Is it's really hard to do at first, and then it slowly kind of becomes easier and easier as technology is more prevalent. The other thing that I think is interesting is this whole idea of investing in people. If you really think about the origination of that is I would hire somebody, right? I pay you money, and then you're gonna create production, but I take the lion's share and you don't. Now there's things like these ISAs, these income sharing agreements, where basically I will educate you on something, train you on something. I'll put up capital, right? And then over time, you'll pay me back plus profits, as some version. Eventually, I don't know what it looks like, but being able to get upside in somebody's success for having risk capital early on, doesn't seem that far off. You see it in professional sports, you see it in a lot of these things. And so I just think that a lot of the focus right now is on the technology, but ultimately these are ideas that are very old and have had lots of success and traction, and we're just merely standing in the way of the evolution of these ideas with new technology. And so it's easy to get caught up in the technology, but when you really zoom out and look at it from the ideological standpoint and kind of the progress of humanity, it's a foregone conclusion that stuff's gonna happen. It's just how. I think the world is waiting, and some of us are trying to create that future world, which is like, what are the applications of this technology that will transform the world? And then, I hate the term, but killer apps, like cool ideas that are implemented effectively at scale that transform the world. And there's been a lot of different ideas popping up. There's a lot of ideas about social networks that are built on top of the technology and all that kind of stuff. But let me actually drag us back down to something basic. If a person wanted to buy Bitcoin, store Bitcoin, how do they actually do it? Yeah, so there's a couple of different ways to kind of acquire Bitcoin. And in every way, you've got to exchange some form of value for Bitcoin, which is part of why it has value, because you're giving up value. So in one way is to exchange energy and computational power for Bitcoin. So you can mine it. You can literally take a computer power that you have, you can rent it to the network and run that software, and then it will pay you a portion of the kind of daily revenue off that system. And you can acquire Bitcoin in exchange for your power and your computational kind of contribution. And that's the fundamental principle behind Bitcoin is the proof of work. So I got a hundred bucks, like I use Cash App. There's Coinbase, there's all these exchanges. Like how do I convert my $100 to Bitcoin? Is there something, disclaimer, this is not financial advice, and this is just us talking, and it's just your opinions. This, do not use this to invest or take as financial expertise. That said, is there something you recommend that's an easy entry point for somebody that's like, hmm, I wonder if I can convert this $100 into whatever amount of Bitcoin? What do you recommend? What are the options? So there's a lot of options. I'm heavily biased. I went out and I scoured the market, looked at all of them. I've invested a lot of money in a company called BlockFi that basically has financial products for crypto investors. So you can go, you can take dollars or other currency you have, you can convert it. You can convert it through an exchange. You can leave it on these interest-bearing accounts. You can earn interest just like you would earn in a traditional account, but higher levels of interest because it's this new thing. Or you can withdraw it and you can put it into cold storage on a hardware device. You can leave it in a software wallet. There's kind of all these storage options. So BlockFi is kind of the one that I'm biased towards because I- So BlockFi, sorry to interrupt. So BlockFi is Bitcoin only, or is it an exchange with other cryptocurrencies? It's got a bunch of different ones, yeah. They basically are agnostic to what it is, but they provide kind of financial products to crypto investors. Okay, so you mentioned a few interesting ideas that'd be nice for people who would not be familiar with it. Cold storage, hot storage, what does that mean? So like I go to a website and I convert dollars to Bitcoin. That's a kind of storage. That's like online banking, right? What else is there? So there's a couple of different things that you can do, right? And let's use the legacy system as kind of an example. So if I want to get currency and I put in my bank account, it sits there. I have to trust that the bank doesn't go under, nobody steals it, all this kind of stuff. There's insurance for it, right? There's all these kinds of benefits in the legacy system to make sure that as long as I don't have, you know, millions and millions of dollars there, I'm gonna be protected pretty much if anything happens through FDIC insurance. If I want to do that, I'm taking that counterparty risk though. So it's mitigated, but there's still counterparty risk. I'm counting on that bank, but it is easier to move it around, right? If all of a sudden you call me up and say, hey, send me some money. I can press a couple of buttons on my computer and it'll send it to you. If I want deeper level of security, I can go and I can get the physical dollars and I can go and I can, you know, put it under my mattress. Right? And I can say, you know what? It's not gonna be as easy to send it to you immediately, but if I really want to, I can go underneath my mattress pretty quickly. I can grab it, I can get it back to the bank, and then I can send you the money. The third thing I could do is I could basically take those physical dollars out of the bank and then I could go and I could go put it literally, you know, in a vault somewhere that I don't have control over, that's behind 10 passwords and biometric scanning. And like, it's really difficult to even get to it. Right? So if you can almost look at it as like, there's three stages of security that you could have in the traditional world. The same thing is true in Bitcoin. So you could buy Bitcoin on any exchange. You can do it on BlockFi, but you also can do it on places like Coinbase, Gemini, Kraken, et cetera. Also Cash App. Cash App. You can do it on Cash App. I think they're still sponsoring this podcast. I'm not biased at all. So once you get Bitcoin on any of these venues, you can leave it there on that venue. Now, the trade-off is you're taking counterparty risk. So somebody else is responsible for the security and the protection of it. In many cases, big, well-known companies who have billions and billions of dollars of assets, they have higher levels of security. That's why they're well-known. That's why people trust them, whatever. But you are taking counterparty risk. It is easier to quickly send to somebody. So the trade-off of like ease of use, but counterparty risk is big. And in the Bitcoin community specifically, there's a huge thing of, they really, really advocate for not leaving the Bitcoin there. Right? For the obvious counterparty. The second thing you can do is you can basically get it off of an exchange and you can put it in some level of kind of what I'll call a second layer of storage. That second layer of storage could be a hardware device that you can quickly just grab off your desk and plug into your computer and immediately use. That's what they call like a hardware wallet. Hardware wallet, yep. Or you can have some sort of software wallet, right? Where it's not on an exchange, but there is some level of in-between between the hardware wallet and the exchange and the software wallet. But the software wallet is connected to the internet. Yeah. And so if you kind of think of it as like the exchange, software wallet, hardware wallet, and then there's something called deep storage, right? Or cold storage. And this is, you know, literally there was a company called Zappo that would put things in deep cold storage and it was literally buried in a mountain. So like the odds that somebody's physically gonna go there, there's armed guards, there's, you know, kind of all of this type of stuff. But again, you're taking some level of counterparty risk because they have your Bitcoin. And so the saying or the phrase is not your keys, not your coins. Or as my buddy, Isaiah Jackson came up with, he said, not your keys, not your cheese, right? In terms of sovereignty is important, right? And ultimately this goes back to kind of the beginning of our conversation around Bitcoin's ethos, sovereignty, right? Giving the power back to people. You don't have to rely on this infrastructure in order to be able to participate in this monetary kind of economy. What you are now able to do is you're able to use digital sound money. You're able to keep control of it. You and you alone are responsible for it. So the idea of personal responsibility. And then also you and you alone make the decisions as to whether you hold onto it or you use it without censorship, right? No one can tell you what you can do with it or can't do with it. And so the purchase and the storage, what I find is depending on who you are, there's varying degrees of kind of concern or decisions that get made there. And a lot of it comes down to personal preference. The Bitcoin community though, absolutely will over-optimize for sovereignty and kind of hardware or cold storage. I wonder if you can sort of comment on that, because you have both sort of a Cash App and a BlockFi and Coinbase. Like you can store it there, you can purchase and trade it there and store it there and so on. But ultimately they're saying, you wanna keep some of it there, but you wanna move it to the hardware wallet. And the cold storage of the hardware wallet is like you can disconnect it from the computer because ultimately stuff that's connected to the internet can be compromised, can be controlled by governments and other parties and so on. What are your thoughts about sort of practically speaking for maybe like a regular citizen, what should be the role of the hardware wallet in their lives? Yeah, so at the highest level, I just think that like learning about it is important, right? So even if you only have $5 equivalent of Bitcoin, going and understanding here's how it works, here's why it's important, here's how I would actually withdraw from an exchange under the hardware wallet, like that alone just as an intellectual exercise is a worthwhile pursuit. I think people should go do that. Actually go through the process of the steps so you feel like you can do it, yeah. Yeah, it's kind of like if I said to you, hey, we're gonna go buy an asset and you never went and you looked at it, you never went and made a decision like, sure, maybe I did or I didn't do it, but like you didn't actually experience it, right? And so I think that that's an important part. The second thing is each person is different from how they view this asset. So there are some people who are speculating, right? There's three use cases for Bitcoin. There's store value, medium of exchange and speculation. And the people who are speculating, they can't put it in deep cold storage because they need to be able to trade it. So what ends up happening is they fall in the bucket of like high risk, high reward. They're trying to trade, they're trying to do all these things and sure, maybe there are profits that they can generate if they're good at it, but also they're introducing a lot of risk. And so that person is very different than the person who says, hey, I bought one Bitcoin and I'm gonna save it for my child, right? And I'm gonna give it to them on their 18th birthday. And so when you start to look at this, what you end up saying is, what are you actually purchasing this for? Kind of like, why are you doing it? And then what's your time horizon? And what ends up happening is more and more people in the Bitcoin community have longer time horizons. One of the advantages to this community, right? If you look at the on-chain metrics, 60% of Bitcoin haven't moved from the digital wallet in which they sit in the last 12 months. So even though it's appreciated hundreds of percent on the upside, there's been lots of volatility, a 50% drop in a single day in terms of the US dollar price, still doesn't move. And so these are kind of the long-term holders, right? These are the iron fist or as recently has become popular, the diamond hands, right? They're just, they're not going anywhere. And so I think that those people are much more likely to not have their Bitcoin on exchanges or in software walls. They've got it in some sort of like highly secure environment and one in which they have deep sovereignty or kind of a prevalent sovereignty. And the reason for that is because they have that long time horizon. They don't want to be kind of convicted around Bitcoin, sound money, macro environment, all this stuff. And then they make a mistake because they trusted, ABCD company and that counterparty risk that ends up actually being fatal or detrimental. So again, this is not financial advice disclaimer, but let me ask, in terms of investment advice on Bitcoin, so you see Bitcoin as potentially not just the thing that you speculate over like buy and sell, buy and sell, buy and sell, but it's something that you can just buy only. And I believe I've heard that you own quite a large percentage of your wealth in Bitcoin and you're basically buying only and storing long-term. So that's something that's a legitimate way to approach Bitcoin in your recommendation. Go to other cultures. So if we remove ourselves from the Western world culture of investing in gamification of financial markets and the financialization of everything, let's say we go to the culture of India. For hundreds, if not thousands of years, families basically saved their wealth in gold and in jewelry and in these hard assets with the expectation to pass it on to the next generation. And so it would be blasphemous to sell the family's gold in that culture. Right? You know, your great-grandfather gave it to your grandfather, your grandfather gave it to your father, your father gave it to you, right? And so in that culture, the long-term kind of holding is the default. I think that what Bitcoin has presented again is a digital application of the exact same thing, which is that while everything else in the world is being devalued, that is denominated in a currency that is being inflated away, whether it's quickly or not, this finite supply, this scarce asset ends up accruing more and more value over time, right? And so I think that for me personally, I've got over 95% of my net worth that's in this. Over 95% of your net worth. There's two important caveats to this. One is I didn't buy some Bitcoin in 2011 or 12, right? And then all of a sudden it appreciated a bunch and it grew into that, but from a cost basis perspective, you know, I put $100 and now it's a ton of money. Instead, what I did was I basically in 2018 saw Bitcoin from a US dollar price standpoint was falling and falling and falling. And in December of 2018, I said take about 50% of my net worth and convert it from dollar denominated assets into Bitcoin. So it was a very kind of intentional decision with a very specific view on the world as to like why I was doing it. I then essentially just let it sit there, grow, whatever, until the spring of 2020. And when I saw the government step in and start to say, hey, we're going to really be aggressive in terms of interest rate manipulation and quantitative easing, I then decided to go ahead and take basically the remainder and start to convert it as well. So it became very aggressive in doing that. And so the way that I look at it is that's actually my savings, right? And so in some weird way, if I said to you, you know, what's the dollar worth? You'd say, well, a $1 bill is worth $1, right? Bitcoin to me, I denominate my wealth in Bitcoin. So I think of one Bitcoin is worth one Bitcoin, not one Bitcoin is worth 60,000 or 55,000 or 70,000, right? I denominate everything in Bitcoin. When I make a purchase in my head, I'm calculating how much Bitcoin am I spending right now? Right? Well, guess what happens? When you have a devaluing currency as the denominator, doesn't matter, right? Like you're financially incentivized to spend or invest, right, to consume. When you have an appreciating currency, all of a sudden you become much less consumptive in your behavior. Because you're actually trading off future purchasing power for the consumption today. It's fascinating to think that if when you move about this world, you think in Bitcoin, you behave differently is if you think in dollars. That's really fascinating. But here's the thing is the last 50 years or so is actually the outlier in history. Most people used to think this way. Yeah. It's only when a fiat currency got introduced that one argument, the positive argument or perspective is there was an explosion in growth. But really it's because there was a financial incentive to consume. Yeah. Right? And there's nobody better in the world than the United States at consuming. And we consume anything and everything. And if you wanna see a great example, look at how big the Coca-Colas are at McDonald's, right? You go to other places, they don't serve them that big. And so the other example though, or the negative argument is we have to consume because if not, you end up being the bottom 45% of Americans that held no investable assets and actually are just having their wealth devalued away. So holding the dollars end up being a very bad economic decision. And so when you then switch to this sound money, you say, wait a second, why would I, if today I can trade one Bitcoin back in October of last year, one Bitcoin for 10,000 US dollars, why would I spend that if at some point in the future, whether it's a month from now or 10 years from now, I could trade it for something much, much more than that. You just become much more of a anti-consumer and much more of a long-term thinker. Yeah, from the individual perspective, that's pretty powerful. I wonder, I mean, I think that's an interesting debate. What's better for the long-term economy? No, better for the growth of the civilization because capitalism is fascinating. It seems to work pretty well. There's this kind of, like Eric Weinstein says that one of the problems is for the past several decades, this whole economy, society is built on the idea that we have to keep growing. Like it depends on that idea. And it's a good question whether that's going to result in huge problems or if like a college student on a deadline, the dependence on growth will mean that we'll have to grow. Like the fear of death will force us to grow. But I think there's a false equivalency between we're dependent on growth and then if the world was denominated in sound money, we don't grow. What I think ends up happening is we remove a lot of the society's bullshit. Because right now, when the money is free, or the currency is free, you can come up with all kinds of crazy stuff and people will give it to you, right? When all of a sudden, it's really, really valued by the population. The decisions are better. Yeah, you have to provide real value in the goods and services you provide in order to get them to give it to you. There's less room for corruption, less room for manipulation. That's not actually productive. Yeah, definitely. So you said you moved a lot of your investment into Bitcoin. When you look, so you're a special human being in many ways. So you're like a strategic thinker, but you're also like a deep thinker about this whole thing. But when you look at a regular pleb like me, in terms of just investing and moving into thinking about cryptocurrency, is there a strategy that you recommend? What are the different options about investing into Bitcoin? Yeah, so I think that there's just kind of timeless advice when it comes to investing or acquiring an asset in general. Dollar cost averaging is usually the best way to think about it. And what I mean by that is most people don't just have a pile of currency sitting there, right? It's not like they have a million dollars sitting in their bank. Like, what do I do with it? That situation aside, what happens is they trade their hours and their effort for currency. And so as they get paid every two weeks, let's say, the best way to acquire Bitcoin without having to worry about timing markets and being a professional trader is to simply take whatever the percentages that you want and to buy Bitcoin when you get your paycheck. So if you get paid on the 1st and 15th of every month, on that day, you should go take, let's say it's 3% of your paycheck. Take 3%, go buy Bitcoin. Don't worry about what the price is. Just do that over time. And the reason why that's important is if in December of 2017, when Bitcoin was at $20,000, it was the height of kind of this last big upwards movement, you had taken all of your money and you had put it into Bitcoin, you would have had to wait almost three years just to get back to quote unquote break even in US dollar terms. If at the same time you had simply bought then and over the next three years bought every two weeks, you would have been up hundreds of percent three years later because what ended up happening was you bought a bunch of Bitcoin when it was at 15, 12, 10, nine, eight, three, four, five, five, five, all the way back up on the other side. And so dollar cost averaging is one of these weird things that it almost sounds too easy. But what we find is in America, we have a lack of financial education. And so rather than try to be smarter than markets, what most people are better off doing is just saying, hey, set your what's called an asset allocation plan. I want 30% in stocks, I want 10% in real estate, I want this, this, whatever. And every time you get your paycheck, just think of it as a savings account, right? Just put it in based on those percentages and don't think about it. And over a long enough period of time, what we find is almost anyone in the United States, right, there's exceptions, but almost anyone in the United States can become a millionaire in their lifetime if they follow these plans and have that long-term view and they allow compounding to work for them. And so don't look at the price of Bitcoin and all that kind of stuff, just pick a specific time, specific day that you just buy, and you just keep buying. That's probably good investment advice across any kind of assets. If you don't believe in Bitcoin and you just wanted, let's say you just wanna do the S&P 500. You shouldn't try to time the market of the S&P 500 either, right? You should just, every two weeks, you should just buy some and over a 20-year period, you're gonna end up buying it at all kinds of different prices, but you're gonna get kind of a blended average. And the more important thing is the compounding and the time in the market than did you buy it at 2% higher or lower than where you bought it, it doesn't really matter. And buying often makes you, I guess, resistant, robust to the volatility of the market or the volatility of the Bitcoin price and so on. That said, Bitcoin price is volatile. And again, the argument I've heard is everything that's going to be a lot more valuable in the future, if you look at the history, companies like Apple, like Tesla is now, I mean, but let's look at companies that have now stabilized, right? Apple is a good example. It's volatile in the beginning. And so the argument for Bitcoin is like, yeah, this is the early stages because it's going to be a lot more valuable. Right now it's volatile. And this is why you have to have these kinds of strategies to ride out the volatility. Of course, everything that goes to zero is also volatile. Like the early days are volatile. Do you see like this volatility is like a feature or a bug, or is this just like a way of life? So Amazon is the one that I know the numbers on in terms of the early volatility. Every year since it has gone public, it's had a double digit drawdown in that year. The average is over 30%. And one time it drew down over 95%. Sounds a lot like Bitcoin, right? Like, oh, wow, this is crazy. But it's one of the best performing stocks in the last 20 years, if not the best performing stock. And so volatility is not positive or negative. It's positive or negative compared to the position you're in. So if you're long and it's volatile to the upside, it's positive. It's positive. If you're long holding something and it's volatile to the downside, you see it as a negative. It's all about perspective. With that said, another way that I look at this is every asset priced in Bitcoin is down significantly. So over the last one, three, five years, the dollar priced in Bitcoin has crashed 99%. If you denominate stocks, it's down like 80%, 85%. If you denominate gold, if you denominate bonds, if you just go down the line, real estate, et cetera, it's all down massively against Bitcoin. Now, you could argue that that's because Bitcoin is appreciating in US dollar terms, or you could actually argue that the world is repricing this asset, it's doing price discovery on this asset. And it's essentially comparing. It's saying, hey, Bitcoin versus this stock or Bitcoin versus this ounce of gold or Bitcoin versus this dollar, which is more valuable. And it continues to move up in the rankings in terms of the value that the world ascribes to this. Some of that is based on Lindy effect, just the longer it persists, the more likely it is to survive. Some of that's based on the underlying fundamentals of how much computing power, the usage, transaction volume, things like that. But some of it also is that as more and more people wake up to the fact that it's a finite supply asset that has a place in the world and demand increases, people just naturally compete and ascribe more value to it. And so the volatility, I think all comes back to like, what do you price your life in? For majority of people, that's dollars. And so you look at the US dollar price, you get all this volatility. The beauty of this is that 60% that doesn't move, regardless of price upward or downward in movement, those people aren't looking at the day-to-day price. What they've basically said is, I've acquired X amount of Bitcoin, and I'm just gonna hold it for years. And every time somebody has done that, right? If you bought Bitcoin at any point in the last 12 years and you held it till today, you are up in US dollar terms. Now, if we had this conversation 18 months ago, couldn't say that. So it's all about not only the acquisition price, if you will, it's also when are you looking at it, right? Because there was a point in 2017, you could have said the same thing, but in 18, you couldn't. And so I tend to think a lot about, humans are really, really bad at short-term decision-making because we're so emotional, especially when something has a price tied to it. Yeah, so in terms of our strategies and decision-making, we should be long-term and have a regular, almost think like an algorithm in that kind of way. So I think you've tweeted that you believe that Bitcoin has a chance of reaching 1 million. I don't know what it is currently. I think it's 60, which is incredible. I think I remember when it was, at least in the double digits, I think I remember it was in the single digits of a dollar. So the fact that it's cross 50 is crazy, but you're even crazier apparently, thinking that it can reach a million. So do you think it's possible for it to reach a million? Is there some kind of transformative effects we'll have to see first? When might it reach a million? Like what are the signs that we would look for what's required for it to reach a million? So let's just look at it from a macro perspective. Gold is a $10 trillion asset. And when you compare the technology of gold to the technology of Bitcoin, Bitcoin is superior in every single way, right? It's more portable, it's more divisible, it's more verifiable, it's more scarce on everything. And so some people would argue it's a 10X improvement. Some people argue it's a 100X improvement from a technology standpoint. And so we don't need Bitcoin to actually kind of capture the full 10X or 100X improvement from a market cap standpoint. If Bitcoin simply captures 2X the value, it'd be a $20 trillion market cap, which would put Bitcoin at about a million dollars, right? So kind of just from a macro perspective, if you have a 10X or 100X improvement from a technology standpoint, and you directionally get some value capture in that direction, you're hitting around a million or more dollar price point. Can I ask a quick question, which is, what's the current market cap for Bitcoin? The current market cap's right around a trillion, just over a trillion dollars. And you're saying gold is 10 trillion. Sorry, where did you get the 20 trillion? 20 trillion would just be 2X gold's market cap. Got it. Right, so if it's a 10X technology improvement, let's just say it only captures 2X the market cap. Got it. And so again, if it was to capture just gold's market cap, kind of the equivalent, puts you around $500,000, right? So you can kind of see there's- Or a single Bitcoin. So if you capture the entirety of the gold market, then it would be value of a single Bitcoin, the price of a single Bitcoin would be $500,000. Okay, to reach a million, it would be double that. That's where the 20 trillion comes from. Correct. Got it. So if you then say to yourself, okay, how does the pricing kind of cycles work, right? Or the boom and bust cycles? Gold is a very kind of linear type supply schedule, meaning that there is a certain amount of gold that comes out of the ground each year. The inter-year variation in that incoming supply is not much, right? Maybe there's an extra mining company that gets set up or a couple of them, or maybe one goes out of business. But for the most part, the kind of inflationary increase to the supply of gold is pretty stagnant. Year over year, Bitcoin has a very unique feature, which every four years, there is a programmatic supply shock, meaning that in the beginning, 50 Bitcoin every 10 minutes was introduced into the supply. After four years of that happening every 10 minutes, it was cut in half. So in a single moment, it went from 50 to now it was 25. Four years, every 10 minutes, 25, got cut in half again to 12 and a half. And then recently in May, 2020, got cut in half again. 12 and a half, and then recently in May, 2020, got cut to 6.25. When you have an asset that is determined, the price based on supply and demand, you normally have two inputs to the equation. What is the supply and what is the demand? In an asset like gold or a stock or anything else, we have to do our best guess at the supply, both the existing supply and the incoming supply, and then do our best guess at the demand. And we're actually pretty good at this a lot of times in terms of directionally saying, it's gonna go up or down, and here's kind of some price point milestones. Bitcoin's unique in that there's 100% verifiable proof of the existing supply, the total supply, and the incoming daily supply. So we know 100% I can show you on the actual blockchain or in the code that there's 21 million Bitcoin. And that's all there will ever be. I can show you that there's 18.6 million, give or take, Bitcoin that actually are in circulation today. Right, and I can go all the way back and show you every single transaction that's ever occurred since January through 2009. And then I can show you on a daily basis that 900 Bitcoin a day are coming into the circulating supply. And so when you have 100% confidence because you can prove the supply side of this equation, you can hold it constant. I know with 100% accuracy, the supply side. So now I've reduced the mathematical equation that I need to do to determine price movements to a 50% reduction. I only have to worry about demand. I don't have to worry about supply. And so when I look at demand, I can do all kinds of things. I can take the demand over the last 10 years and the growth and just extrapolate it out. I can increase it, I can decrease it, whatever. But what you find is that the supply shocks lead to significant price appreciation as the asset gets repriced because there's a supply shock to them. And so probably the best thing that I've done over the last couple of years was in 2019, I started to talk about the idea that we were gonna have both the supply shock and the demand shock in 2021. Or I'm sorry, in 2020. I didn't know when this bull market that we were in was gonna end, nobody knows, right? It's impossible to time these things. But you could tell that we were kind of at late stages of a cycle. There was inverted yield curves, there was re-generations in the repo markets, a lot of CEOs leaving their jobs, you know, all this kind of stuff. And all I said was at some point, when the market turns over, the government's gonna have to step in. We are addicted to stimulus. They're gonna have to manipulate interest rates down and they're gonna have to print money. I had no clue that there was gonna be a global pandemic, that they were gonna have to step in in such an aggressive way and move rates, not down, but down to zero. And that they not only were gonna print hundreds of billions, but they could print trillions of dollars. But the framework that I used to think about this was when they do that, everyone is gonna run to store value assets. They're gonna run the gold, they're gonna run the Bitcoin, et cetera. And right as they do that, it appears at the same time, there's gonna be this supply shock. So you're gonna get a supply shock and a demand shock that are both positive for the price. And I called it rocket fuel for Bitcoin. Well, it happened. And here we are. I now look forward and I say, okay, we are likely going to see 100,000 Bitcoin, $100,000 Bitcoin this year, right? At some point, I don't know when it happens, but we're moving in that direction. So you think in 2021, we'll see 100,000? That would be my most conservative view. I've said $100,000 since 2019 and people thought that was insane and crazy and all stuff. Now I'm the conservative guy in the room because I stick with the $100,000 and people are saying multiples of that number. So we'll see what happens. But I think that there's still a lot of room kind of to run from a US dollar price standpoint. What is on the horizon is in 2024, we will have another supply shock. And so that's what I think will carry us to the million dollar Bitcoin price. From a 625 to whatever. 50% reduction. Yeah. Yeah. And so that's what I think will basically, when we get that next supply shock, that'll carry us up over a $1 million Bitcoin price, which if historical examples persist, and again, sometimes it's hard to use historical examples to look at future events, but if that happens, we would see a million dollars of Bitcoin by the end of 2026. After that wave. So 2024 basically is the supply shock. And within 18 to 24 months, you would see the kind of top of the next market. Hopefully without a coupling to another pandemic. Yes, we would like to do all of this without a public health crisis. So that would take it to 20 trillion. You don't have to compare it to the dollar, essentially, in some sense, that the dollar could also lose value. I mean, there's a lot of kind of dynamics at play here. Now, but like fundamentally, there's going to be a huge move in your prediction of value into Bitcoin. I mean, that's a fascinating world to think about. I mean, but I do have to kind of ask you about the whole space of technology there. Because we're talking about the value of security. We're talking about the future, which Bitcoin will be at the center of. But from my perspective of thinking how, like I and others can build technologies on top of this kind of decentralized world, I'm thinking about different technologies out there, different cryptocurrencies out there, Ethereum being one, but there's a lot of others. So I'd love to get your sort of ideas about some of these. But so first let me ask you about, what the hell is shitcoin? Is this connected to our previous discussion of the meme? Does shitcoin cover basically all coins that are not Bitcoin? Is it mean? Is it a beautiful? Is it a mixture of both? As with most things in life, depends who you ask. The most kind of enthusiastic and parts of the Bitcoin community, shitcoin is anything else, right? Kind of if you ascribe to kind of a maximalistic view of the world, shitcoin would be anything. If you look at people who I would say are Bitcoin proponents yet see value in other things, shitcoin may be the bottom half of the other things, right? So I think, again, it's really important kind of who you ask is how you'll get that answer. So there's tiers and the way you divide those tiers might be different depending on who you ask. Ultimately what it is, is it's a meme and it's used to articulate the idea that whatever you wanna put in that bucket has no value. So shitcoin, right, are coins that have no value. What is fascinating about it, and I think that again speaks to the power of the Bitcoin community, is there was congressional hearings a couple of years ago. And at one point, a congressman from Ohio, Warren Davidson, who was definitely open-minded and excited about Bitcoin, asked an individual on the Congress floor during testimony to talk about these other coins. And at one point basically read into the record the terminology of shitcoin. He said the word shitcoin. I can't remember if he said it first or if the other person did, and then he repeated it. That's awesome. But he definitely, he was trying to get that read into the record for sure. And so you can imagine, one, again, the meme speaking insolently to the Bitcoin community was, made him very well-liked. But also, two, was it does go back to this idea almost of if you and I sat down with 10 CEOs and we interviewed each one of them, and then we went in a room and we deliberated, and we said, we have to pick the person who's gonna be the most successful. One of the inputs, not all of the inputs, but one of the inputs would be, who's the person who we believe has the best ability to raise capital, recruit people, and tell a story to the world that will get them to follow? And so somebody like Elon would probably be the best example of this. When you have decentralized products, you have no kind of leader, right? In the sense of somebody who is financially ascribed to be that leader and kind of the executive decision-maker. So what you have to do is you have to look at these technologies in these communities and say, well, which volunteer teams or which technologies have been able to coalesce these groups around it and in some way build the same level of engagement and protection and things like that? And so you naturally get tribalism, but you also get things like shitcoin, because what it does is it's not only a kind of verbal attack towards others, it's a rallying cry for internal. What's so funny is that it was started with the Bitcoin community talking about everybody, but now you've seen adoption in other communities who basically say, well, we're not a shitcoin, it's the next guy. Yeah, I mean, the meaning, to be honest, it's sometimes misused, I think, like with anything. It's like people adopt memes that used to be brilliant or are still brilliant, and they're just not good at using them, so they become mean. But when you do it with grace, it can tear down an argument, and at the same time have love and respect underneath it. I mean, it's a beautiful dance they have to be good at. People just can suck at communication. And even a powerful weapon like a meme in the wrong hands just fires in a way that doesn't get anything done. But this is like a war of humor and memes. It's kind of fascinating, exactly like you formulated, that there's asymmetry of power, so you have to have guerrilla warfare in this internet game, especially when there's no leader, like you said, in a distributed culture. The other thing I would say here that is really important, I think, is from a society standpoint, we've become very soft and very kind of coddling, and not in a way that's like, I think people take this argument too far sometimes, but what I mean by that is it's almost like if you're the person who holds somebody accountable, you become the bad person, right? If you're the person who says, hey, that's wrong, you're the bad person, right? And so in a world where I think in this kind of influencer-y, all positive, if you have any negative feedback or constructive criticism, like you're the bad person, it's the ultimate echo chamber, right? And so I think that what the Bitcoin world does in some crazy, crazy way to look at it is Bitcoin is ultimately about truth, not about narrative, not about feelings or emotion. It's math. You look at a blockchain and you can prove something or you can't. And so naturally, people who are attracted to that have a very similar approach in life, right? They say, hey, you made X claim, prove it. And as you can imagine, a great example is like the financial media meets Bitcoiners. And it's a bloodbath, right? In kind of the arena of ideas, because what do they do? The financial media is used to the soft opinion pieces, et cetera, and Bitcoiners show up and they're like, here's data point A, B, and C, here's example one, two, and three, and you're wrong. And then all they yell and scream about is like, I'm wrong, I'm wrong, I'm wrong. Like, you can't say I'm wrong. And they're like, no, no, like disprove what I just said. And so you get in this like very, very weird world. It's fascinating, it's a fascinating benefit. But I do wanna say, I've been watching this, it's kind of interesting. I think that the pursuit of truth, like tearing down bad ideas can be done with grace. And to do it with grace requires a lot of skill. Like what people don't realize about disagreement, they think that disagreement is easy. Like they see the lies or the inaccuracies in the statement and they just think they can say wrong. Yes, you can say that, but if you wanna be effective, it requires great skill. Like you look at, I don't know, a beautiful verbal shit poster, which is Christopher Hitchens, right? It requires a lot of skill through your words to tear down an argument, to criticize, and to take a step towards truth. What I'm disheartened by internet culture, like the negative side is people don't put a lot of effort in their tear downs. Like into your shit posting, into your memes, you should put effort and see it as a skill that you wanna, if you want to be a part of this culture, you want to get good at it, like any skill. It's the 10,000 hours. Like get improved, deliberate practice, self-criticism, all of those things. Just because you're anonymous doesn't mean you won't get deep joy and actually have an impact on the world if you get good at shit posting. But I think this is really, really important, right? Because you're right in that it's all about intention versus action. If your intention is to tell somebody that they are wrong in an effort to get them to see the truth, that's very different than if your intention is to tell someone they're wrong and hurt their feelings. Right, and so when you can unpack intention and action, you really quickly can tell what somebody ultimately is trying to accomplish. I also think that one of the craziest things that I've seen play out is memes, when I use that term, I'm not just talking about like a static photo, right? When I'm talking about these elaborate, kind of edited videos and kind of all this stuff, when done right, it is the most articulate way to deliver a blunt message. And it's done in such a way that is humorous and entertaining, yet really hammers the point home. And so it's a skill set that many people don't have. I don't make those. I'm assuming you don't make them either, right? I see them, I share the ones that I like, right? But it does take practice. And you can tell, look, there's people who are fantastic meme lords, right? And there are people who absolutely suck at it. And it's like anything, it's just how good are you at communicating? And I've heard the idea a bunch of times, so I don't know who to kind of credit for it, but whether it's emojis, it's GIFs, it's memes, whatever, this is the extension and evolution of just hieroglyphics. Right? Like, we have been doing this for literally centuries. It's just that now we're doing it on the internet and you can press a button and you can go to millions and millions of people immediately. But speaking of memes, what the heck do you think is up with Elon Musk talking about Dogecoin a lot? Sort of from the cryptocurrency community, I've been talking to a lot of sort of technologists, I guess, and reading papers on cryptocurrency. It's like, nobody really sees Dogecoin as a revolutionary crypto technology that a lot of people talk about. It's security issues. There's a bunch of issues it has. Nevertheless, you did say that money is the kind of social construct, right? And Elon Musk's combination of humor and brilliant engineering and the various companies he runs combines to create a kind of value and excitement behind Dogecoin. It's like, what is it? He says that the most amusing outcome is the most likely kind of idea, which sounds silly, but there could be like profound truth to it. It's like, what do you make of Dogecoin philosophically or technically? Is it possible that Dogecoin will overtake Bitcoin and run the entire world? I can't even, because it could happen. It could happen. But if there's any serious way to answer that question. Well, we have to start with Techno King of Tesla and Master of Coin, as they are so articulately called in the latest SEC filing. He officially changed his title to Techno King. Yes? Techno King of Tesla. And the CFO's new title is Master of Coin. And so when you have a sense of humor and frankly, a level of self-confidence and an element of an appreciation for irony in the world, Dogecoin is actually one of the least crazy things that you could talk about when you're willing to go to Techno King of Tesla, Master of Coin and all this stuff. And so I think that Elon doesn't get enough credit, frankly, for his understanding of internet culture, understanding of memes, and understanding of frankly, human psychology and marketing. And so in some crazy way, every time he talks about Dogecoin, it's a rallying cry for an entire generation of kids. It's a rallying cry for an entire industry in terms of cryptocurrencies and digital technologies. But this is the flag. And this is the thing that he can yell and scream about and tweet about without worry of punishment. So he could be talking about Bitcoin, he could be talking about cryptocurrency, but that's not going to be as beautifully humorous in whatever the hell internet culture is as Dogecoin. He's finding the right language. He's speaking the language of the people in the digital age. If you wanna reach weird people, you can't be serious. And most people are weird. The masses are weird. So he's speaking to the masses, the techno king. And even further than that, I think is, he essentially is, he's using Dogecoin as a way to say, I'm doing this because I can. He couldn't do it with securities. He couldn't do it with certain types of other assets. Like I almost look at it as like a Venn diagram. What's the thing that a bunch of people know about, care about, think are as funny, whatever. And also overlay that with the things that like he could actually talk about they won't get in trouble for. That's a big F you to the SEC. I could see the people just freaking out. I mean, I love it, but I don't know if I would have the guts to do it myself, but I think he's an inspiration to a lot of us to be like, well, maybe you should grow the guts. When you're the techno king, you can do whatever you want, right? And I mean, that's something to aspire to is to be the techno king in your own little world. If you also think about it in the sense of when you're somebody on a mission to create interplanetary life, when you're trying to solve or put a dent in the climate crisis or create electric vehicles and be the first American company in however long, frankly, the SEC or other things in your life that you don't ascribe that much importance to compared to those things, they're almost nuisances. And that's scary, I think, for shareholders of a company when the person that you're trusting to lead you to the promised land and create shareholder value doesn't put value on certain things. But at the same time, I always look at it as a tug of war. How much of the actions of what he's doing and calling attention to actually change the way that regulators, lawmakers, politicians, countries, whatever, act? He may not be able to say, do X, I'm the techno king, and they go do it, but with every step he makes, he changes some of their behavior. And so I think that it's a really kind of game of like 3D chess that frankly I'm not privy to, right? And I'm kind of watching from the sidelines and figuring out alongside everybody else. But I also don't think that it's just Elon bought a bunch of Dogecoin and tweets about it because he thinks it's going to a dollar and he's gonna make money, right? Like, I don't think it's an economic argument as to why he's so interested in it. I think it's much more, it's almost like meta message for a lot of other stuff. Yeah, he's kind of trying to break apart internet communication from first principles like he does so many other problems. It's kind of fascinating to watch. I know he's been, he's taught me quite a bit about communication. And at least for me, it's been liberating to not give a fuck about the old school way of things. I've been always bothered by a place I deeply admire, which is MIT, but there's problems, the bureaucracies and hierarchies that hold back innovation brilliant minds. And in that sense, Doge is a kind of FU to the system. That's kind of positive, but also kind of, but it was also an FU. So in that sense, I think Elon has a perspective on the world that's similar to Bitcoin, folks, which I really like, which is like thinking long-term. It's how visionaries think. It's like, how will, if I take these ideas, and the ideas hold true, what will the world look like in 20, 30, 50 years? And think about everything in that way. Yeah, I like Bezos's view, which is essentially, how do you minimize regret? How do you accelerate your life mentally and go to 80, 90, 100, 150 years, whatever we end up being fortunate enough to live to, and then look backwards and say this decision that I'm gonna make, I have two options. Which one is gonna be the one that I least regret? And if you continue to make decisions that way, one, you have that long-term view kind of built in because you're working backwards. Two, you are ultimately going to optimize for minimal regret. But also three is, even if you only look forward 10 years, that's much, much further than most people do. And so it gives you a significant advantage. And I think that Bitcoin has kind of this, proxy for time, as we talked about, interplanetary travel, where there's multiple steps from creating a reusable rocket to landing it to all this stuff, all the way to simple things just like, if you're simply just trying to figure out where the world's gonna be 30 years from now. Bill Gates says that we overestimate what we can do in one year, underestimate what we can do in 10. Well, to me, it's a kind of degree of mistake, if you will. 10 years, maybe you're off by 10%. Well, if that line of progress continues, 20 years, you may be off by 100%. And 30 years, you may be off by 1000%, right? Like almost the further you go out, the more inaccurate you become. And so I think that people who want to iterate their way to success, right? That's a common thing in like the startup world, end up actually following kind of the breadcrumbs to where the world is taking them. But people like an Elon Musk, a Jeff Bezos, a Jack Dorsey, all the way down the line, all these innovators, they actually say to themselves, there is a point in time in the future where there's a world I want to construct, and then they go and they construct it, regardless of the short-term iterations and incentives. It is just they're driving towards that point. And I think that it's this whole idea of having this like, you know, kind of set vision and this refusal to kind of move or budge off of that. It's what makes them special. One of the things that garnered a lot of excitement in the crypto community is NFTs. I have no idea really the depths, the fundamental technological philosophical depths of this technology, whether this is just like a little bit of a fad or there's some deep lessons to learn, whether it's Bitcoin or cryptocurrency in general about it. Do you have thoughts about like the long lasting fundamental aspects of NFTs? I think there's probably both things happening, fad and things to learn, right? And if we just start with like, what is an NFT? It's a non-fungible token, meaning that there's no fungibility. Fungibility is a fancy word. I always describe it as if I took a hundred dollar bill and I put it on the table with a bunch of other hundred dollar bills and we mixed them up and I just grabbed a hundred dollar bill and left, I'm no worse as long as they're all, you know, official hundred dollar bills, because as long as I have a hundred dollars, I have a hundred dollars. I don't need that exact same bill back. So that means that those hundred dollar bills are fungible. Non-fungible would be like art. If I took a Picasso and I put it down on the table and you brought three artists that no one's ever heard of before and we mixed them up and I just took any random piece of art and it wasn't the Picasso, I lose because the Picasso is really important there, right? So non-fungibility is important in art. What these non-fungible tokens essentially are doing is they are creating scarcity and originality in a digital environment. And what I mean by that is, take a music file. If I had a music file and you wanted it, you said, send it to me, I press send. It essentially creates a copy and you get one music file, I get another. We don't care. You can listen to music, I can listen to music, we're super happy. If I instead though, have a digital file that entire premise is based on scarcity and I hit send and you get a copy and I keep the original or you get the original and I get a copy, there's a problem. And so ultimately what I think is playing out with NFTs is it's a technology, regardless of where it plays out from blockchains or what in communities or environments, that just brings true digital scarcity to the internet. And so naturally what do people do? They look at the legacy world and they say, well, what's scarce there that has value? How do we bring that to the digital world? So art is a perfect example, right? And frankly, last year I started to look at this because it felt like this was gonna be really, really big. And the conclusion I came to was just as Bitcoin is gonna be bigger than gold, right? The digital application of something is gonna be bigger than the analog application, the same thing's gonna be true in art. The digital art world is gonna be bigger than the traditional art world. People think that sounds crazy at first until you start to realize it's very, very similar. The art is more portable. It can be divisible, right? It's got a larger demand market in terms of the internet rather than an auction, right? All this kind of stuff. When you display it, it can have motion and music and all of these aspects to it that are better than the traditional art. What the traditional art market has that the digital art market has not had is the narrative. Narrative-based world, scarcity kind of in digital sense. And so what I think the entire world is going through right now is an exploration of how do we use this technology to create new things? And frankly, we're not gonna be good at it for a while. And so the only place I've really focused on is digital art itself. And I've always been interested in art, but I wasn't gonna go buy a painting and hang it on the wall, right? In the sense of that's how I was gonna store value. What I find fascinating though is that I now can take that concept, which most of the wealthiest people in the world have a significant portion. Some people have 20% in terms of number of billionaires, 20% of their wealth is in art. And you can bring it to this digital realm, which is much more kind of natural to a digital native. And so the best way I know how to describe the importance is imagine a serial number being placed on something. Take the Eiffel Tower. The only Eiffel Tower that has value is the first one. Every replica of it, regardless of size, location, who made it, where they sent it, they have no value. Eiffel Tower 001 is the most important. And so I think that's ultimately what we're starting to see here. And what we're looking at is probably 1% of what it's gonna grow into. Who the players are. You're bullish on this. You're saying it could grow into something for 1%. It could grow into something significant, like all the kinds of different applications. Strip away all of the applications right now and just think about is digital scarcity gonna be important on the internet? Moving all the things that are scarce in the physical world into digital space, us trying to figure out which things can be moved and not. And also there's things in the digital space, just like you're saying, that don't exist in the physical world that might also benefit from gaining scarcity. People are, I guess, creating NFTs out of tweets or whatever. So you have a fun Twitter account. You could say you could put value to a single tweet and then be able to invest in it and trade it and buy parts of it and all those kinds of things. You can invest in people. You can invest in, art can be defined broadly as any kind of creation. And in some sense, this whole idea of scarcity can overtake the entirety of the digital world. It can consume all of the markets we see as financial markets and just turn everything into a market. Well, so if I take you on like a 10 year fast forward and I paint a picture of something today that seems absolutely insane, but there's early signs that people are building this and let's just give them the benefit of the doubt that some of the early iterations will work and some of, or most of them won't. There's a world where you and I are participating in a digital economy, in a virtual world, where whether it is a piece of art, it is a digital sculpture, it is a digital skin from a video game, it is a digital good that we purchased somewhere online and we bring it and we display it in a digital museum or a virtual museum. And so now all of a sudden, you can charge people for entry. You can consign digital goods. It's the replication of what happens in the analog world, now just in digital. And when you do that, what you do is you take the addressable markets of these assets or these mechanisms and they explode in the digital realm. And so now all of a sudden, how fast does the human race accelerate when it comes to human production, intelligence, learning? All in the digital space. Output. It's just if I said to you 20 years ago, I'm gonna give you a global education, it means I'm gonna take you and I'm gonna physically move you to geography after geography after geography. It's gonna take time, it's gonna take resources and ultimately it's gonna take lots of effort. If I now said to you, hey, I'm gonna transport you in this virtual world to multiple geographies but you're going to experience it in this virtual world and you're gonna have digital goods that you can take from economy to economy or from location to location, all of a sudden, maybe you get 90% of the value. You don't get 100% of the same value. We get 90% of the value. But you can do it at a much faster pace. And so in a six month period, you've actually made three times the progress than you would have if you had to do in the physical world. So that's where I think we're heading. So there's digital art being displayed in the digital museum and people are being charged for access and perhaps we plug in our senses, which means we start to operate more and more in a virtual reality, augmented reality, virtual reality way with this digital world and increasingly going to this world. Basically lived most of our productive and social lives in this digital world and increasingly essentially create a simulation where the biological basis is just there to sustain the brain that's used to operate in a virtual world. Taking us back to the original, where we started talking about war, I wonder what conflict looks like in that world. That the people who are born today maybe will be fighting wars in the space, in that museum world, in that digital world. Remember what I said, we're moving from a world of conflict surrounded and determined by bombs, bullets and soldiers to a battlefield that is determined by war of information and cyber capabilities. And so in that virtual world, is it about death and destruction of human life and the physical analog world or will it become more important to attack or defend virtual property and virtual life and some level of virtual sovereignty? In my opinion, the latter is more likely. And so what you start to understand is, well, what do you truly value in your life? Is it the physical analog, materialistic, consumptive goods or is it virtual? And in many cases, something as simple as the ability to connect with somebody is really important. And so one of the most disruptive, combative, violent things that a country may do to another country in the future, simply take down the internet and put people in isolation. I don't need to physically harm you if I can psychologically harm you. I don't need to- It's terrifying. Yeah, I don't need to actually convince you through a monopoly on violence, on physical violence. What if I can psychologically change the way you see the world through misinformation, through all sorts of nefarious activities? And I think that the United States has been struggling with this idea over the last couple of years in the political arena. But what happens when it starts to come to other aspects of our life? And I think it's very likely, it's almost obviously likely that we're moving into the digital world. One of the features of the digital world is that artificial intelligence systems can operate with much more power in a frictionless way in that world, currently as we understand it. It's hard to build robots that operate at scale and do arbitrary large amount of impact, damage or positive in the physical world. It's much easier to do in the digital world. Do you ever think about AI systems just swimming about doing extraordinarily powerful, destructive things in the digital world? Is that something of a concern to you or is this something into a very distant future? I think a lot of artificial intelligence is in the name. It's simply the replication of human intelligence at scale, automated and programmatic, meaning that in the analog world, you could go hire a thousand employees or in an Amazon case, hire millions of employees and set a mission or a goal and push them to go do that. That requires recruiting, retention, training, resources, all that stuff. In the virtual world or in this digital economy, what if you can just program the resources and gain the same leverage and do it at scale and do it in a very programmatic way and then have them actually make decisions in a way that doesn't require you to have thought of every single potential scenario or edge case? That's ultimately what we're talking about when we talk about artificial intelligence. And so when you look at that, when technology's created, everyone uses it for good or bad, but both get used. And so whether we're talking about cell phones, beepers, the internet, guns, whatever, it's always used for good and bad. The big question is, and I think that yourself and many other people have rightfully said this, is the question really becomes, is the negative and nefarious uses of this inadvertent potentially? Or does it actually come from a malicious person? Is the intention malicious? And to me, that's what I, I don't know enough. You know much more about this and there's plenty of other people who do as well, but I do think that there will be nefarious actors and malicious people, but we're gonna treat them the same we've always treated people who use technology poorly. We're gonna understand it, we're gonna identify it, we're gonna control it, and then we're gonna end up reversing it or preventing them from doing that. It's the inadvertent things that I think are actually the most dangerous because when you have something that can think for itself and there is no way to leverage a monopoly on violence for control, it's a very scary thing. And it can, I mean, the thing that's scary to me is that it can scale arbitrarily. So it can outnumber humans very quickly, even if it's dumber than humans. And so I don't know if we're able to reason about a world, like let's look at the physical analog where all of a sudden, let's talk about something kind of like humans, but dumber than humans, like chimps. Okay? Imagine that all of a sudden chimps could multiply arbitrarily quickly and you could have like a trillion chimps the next day when you only had maybe a million the day before. Like how does that world look different? Like where the fuck do all these chimps come from? And then we can pretend to be like, well, let's hope the chimps don't get violent because they don't seem to get violent when the resources aren't constrained. But like, we don't know. And the problem is it all starts by building that first chimp multiplier device. And everyone's like, okay, yeah, there's a lot of good applications you want. You know, you can make all kinds of arguments for why you have more chimps. Maybe they can help you out around the house or something like that in the physical space. But ultimately it's the unintended consequences that you're referring to is you don't know what's gonna happen. I'm really worried about dumb AI agents like having impact when they're multiplied to a million to a billion and are allowed to operate in the digital space, especially as we clearly are moving more and more of our lives into the digital space. So it's kind of terrifying because we, you know, a lot of people are terrified or concerned about super intelligent systems. I think I'm definitely much more concerned about super dumb systems at scale. That's terrifying. I always think about the inadvertent, but as you were talking, what it made me think of is also the irreversible. Irreversible, that's- Right, so it's one thing if there's inadvertent negative impact, but we have reversibility built into a system and we can fix our mistakes. Yeah. I think the really scary part is when you overlay inadvertent mistakes with the irreversible aspect of it and therefore humans have no control. Yeah, if you have the trillion chimps, you can't, they're not gonna like it when you try to start killing them off. All right, but back to Bitcoin. Those chimps in the Bitcoin community. Anytime you bring up chimps, some people say, Joe Rogan entered the chat. Can I ask you about sort of learning about Bitcoin books and resources? You have an amazing podcast that's not just about Bitcoin or cryptocurrency, it's about everything, including life, but you do have a lot of really amazing conversations about this whole digital world, but obviously you also have a newsletter that's incredible on Substack. And, but do you have recommendations? Maybe it would be great if you could talk about, first of all, your podcast and the newsletter, but also other resources that you recommend people should check out in order to learn about Bitcoin. Yeah, so the podcast and email are like the two most selfish things I do, because the podcast is a way for me to learn from other people. So I get them to come on and tell me all the things they're thinking about and I get asked some questions. What's it called, by the way? Just a podcast. And so in doing that, it really is informative for me. And I think that my whole goal is just like, if I'm learning, other people will be learning. And then the email, I read it every morning because it forces me to collect my thoughts and actually articulate them in somewhat of a coherent way. And so it's just something that is like a practice that I probably would do even if no one read it. And then by being able to publish it, what does it do? It elicits both the good and bad responses. And so people will let me know if they think I'm an idiot and they'll usually not respond if they think that it's something smart. And so those two things are really educational for me and I think kind of forced me to be able to articulate a lot of ideas. But a lot of what I share or learn on those things come from these other resources. So I'm definitely subscribing, people should subscribe, but what are Bitcoin resources books that you recommend? I think you gotta start with Bitcoin Standard. That one to me feels like it really lays out the picture nicely. There is Bitcoin Money You Can't Fuck With. It was written by our friend Jason Williams. As you can imagine, it's basically what it talks about. There's another book, Layered Money. It's written by Nick who's done a great job kind of laying it out. There's a book called Bitcoin in Black America written by a guy, Isaiah Jackson. And he basically lays out the argument for why the black community can benefit in a asymmetric way from something like Bitcoin. And there's a whole bunch more, I'm gonna forget them all. There's the, I think it's called The Cost of Tomorrow. A guy, Jeff Booth wrote it. And just, if you get on Twitter, basically, you're gonna see all these books flying around. But I do have to say that from a psychological concept or philosophical concept, the number one book that I've ever read that aligns with Bitcoin ethos but doesn't say a word about Bitcoin is a book called The Dow of Capital by Mark Spitznagel. And so what he essentially does is he just reiterates over and over and over again long-term thinking, outliers, disruption, all this stuff. And so he's a guy who, he runs a fund that essentially they just do a tail risk hedging. And so in March or February of 2020, they're up like 4,000%, right? By the way, they pretty much lose money for eight, nine years, then that happens. But they're still one of the best performing funds if you look at it over years and years. And so it's just this mindset of everyone is so short-term focused. And so I think it's just a great reminder of the long-term thinking. And also, I mean, I've gotten quite a bit of value just reading the papers. And that's perhaps more for technical folks. There's quite an active research community. And also going back to the original white paper and just original documents, old school. Old school is still, like a few years ago, still really interesting to think about, to look at what people were thinking about because the principles are carried through with other cryptocurrencies as well. Like it's all there, even in the early documents. So that's kind of fascinating to see that whole history. If you're more tech savvy. And like you said, Twitter is actually an interesting place. If you can look past all the shitcoin talk, it's a fascinating place for news and resources. Is there books outside of all of this cryptocurrency, sort of technical fiction, philosophical, that impact on your life? Because you have interests that are all over the place. Is there something that you would recommend to others? So, Dow Capital is definitely probably my favorite book. Books that have been impactful. I read when I was 20, actually, sitting in the desert of Iraq, Rich Dad, Poor Dad, Thinking Grow Rich, and The Richest Man in Babylon. And I don't think I took a single thing and implemented it from an execution standpoint, but it was a complete shift in mentality and understanding a relationship with money and just kind of what I wanted to do with my life and stuff like that. So, I think those three books, and I read them in succession, were really impactful. And then I think one of the best books probably ever written is, I think it's called When Breath Becomes Air, or Air Becomes Breath, I can't remember. But it's basically a doctor or a medical professional who's dying, and he essentially writes about the experience and thoughts and kind of all this stuff. And I think that it's just one of these things where if you said to me, you know, what's the number one thing I took out of my experience in Iraq, that a book like that also gives you, is we're all gonna die, right? And you and I can wanna be as immortal as we want, but at some point we're gonna die. And so it really does kind of focus you on time being that scarce asset and use it for enjoyment and happiness more so than anything else. And I think that's part of your message, and it's a great one. Do you think, do you like literally meditate on your own mortality? I don't necessarily think I meditate on it as much as- Are you afraid of death? Were you afraid of death when you were in Iraq? I mean, coming face to face with it, are you afraid of death today? No, I think that it was just one of these things where if you fixate on something and you worry about it, then, at least to me, you become uneasy about it. And so after an experience like going to war, I think that everything is just so not important compared to that, right? Like when I came back, I remember going back into the college environment and things people were worried about, I was like, listen, let me explain to you what the real world's like, right? But I think even today, right, if you talk to people who know me really well, I don't get worked up about a lot of stuff. I don't get in either direction, good or bad, anything, because ultimately it just comes down to if that's the final result, let's enjoy it. It's fascinating to ask you, because this reformulation of money essentially buying time, and there's the old question of does money buy happiness? Do you think money can buy happiness in the context of money being able to buy time? Or is happiness something else that is beyond all of this? When people talk about this question, I think that they really focus on money as a means to getting materialistic things. So they want a big house, they want a boat, they want a fast car, they want whatever. They think that's the stuff that will make them happy. What I think about it is if you have resources, you can have time, and if you have time and you spend it the way that you want to spend it, then that's ultimately happiness. So I always say to people, if you think that money doesn't buy you happiness, what if I told you that if you had more money you could spend more time with your family? It reframes it. And now it's all about I want to do certain things in life, but there's a lot of people who spend their life not doing those things because they feel the need to pursue economic means as a way to provide a living or whatever, and so I explain that. I say, listen, in my opinion, and again, it's my opinion, it's what makes me happy, if I can leverage financial resources to create more time to do the things I like, I'm happier. Might not work for everybody, but that's what works for me, and so there's this element of, I don't care what other people think if they like that or not, because they're not me. There's almost this element of you gotta figure out what works for you, and if it works for me, then sorry. No, I think that will resonate with a lot of people. I think that's a brilliant reframing of it. That said, you kind of imply there's a reason behind this whole existence of ours, there's a meaning to it. So let me ask, what is the meaning of life, Anthony? Do you think about these ridiculous big questions that have no answer every once in a while, or do you just enjoy the shit out of every day? I answer it in a way that isn't meant to be accurate. It's meant to be the right answer for me, which is ultimately, and I talk to a lot of people who always ask, what are you doing? Why are you doing all this? I say, it's to be happy. And the reason why I think of it that way is I've got a friend, Jonathan Geller, who talks about enough being enough, and recently he talked about it in the context of Bitcoin. And so Bitcoiners have two things. Any Bitcoiner, if you talk to them, they believe the same two things. One, they don't want the US dollar price to go up because they actually wanna acquire more Bitcoin, right? And then let it go once they feel like they've got enough. But two is, no matter how much they own, they think that they don't own enough and they wanna acquire more. And so at some point, you say to yourself, what is enough? And I think that the whole meaning of life is to understand kind of what your level of satisfaction is. And for some people, that's a monetary thing. Some people, that's a freedom of time thing. For some people, it's an impact thing, whatever. But just understanding that's important and then going and accomplishing it. And what I've found is that the people who I know who have done this and been intentional about it, they accomplish it on a much shorter timeline than people who don't. There's some people who start thinking about this when they're 60. Naturally, you're not gonna accomplish it before you're 60 if you just start thinking about it at 60. People who start thinking about it earlier can do it. And so I think that's really it. For me, it's just like the meaning of life. The meaning of life is to enjoy it. The way I think about it, that's because this is a really nice formulation. I almost like to sort of oscillate back and forth. So majority of the time is spent in the mode of enough is enough of gratitude, of basically being content with where you're at, like deeply appreciative of every moment and all the Bitcoin, whatever Bitcoin you have, being deeply appreciative of it and that being enough. And then some fraction of time, perhaps it shrinks as you get older. That's maybe there's an optimal trajectory there, but some fraction of time is spent being deeply self-critical and nothing is enough. Nothing you've ever done is worth anything. It's the Marvin Minsky said, the secret to success is hating everything you've ever done. So that mode of just hating everything you've ever done and just trying to improve, trying to make stuff better, nothing is enough, it's never enough, that kind of stuff. And then oscillating back and forth. You don't have to have the same algorithm operating throughout the day. You could just like oscillate back and forth and maybe reserve that gratitude part, the chill part to when you're hanging out with family and friends and loved ones. And then when you're like alone or maybe at work, is that the madman comes out kind of thing. I also think it's kind of purpose-driven in the sense of there's a lot of people who have the, I need to do more, but in a somewhat altruistic way. So take Elon as an example. The idea of colonizing Mars, sure, if he is successful, he will be very rich. I don't think you or I or many people believe he's doing it for the money. There's a lot of other things he could do that would be much easier that would make him tons of money. And so in some weird way, he has enough because he's able to free himself from the constraints of, I need to acquire more resources, and he can focus on what is the thing that I wanna work on regardless of money. And so in that pursuit that is non-economic, you can be as selfish as you want because ultimately you're not tied back to this measurement tool. And so it's this, again, like altruistic non-monetary purpose. And I think that there's a lot of people who spend their whole life looking for that and they don't know what it is. And so again, some people may not think of it that way, but if you can find something to do that, you win. I don't think there's a better way to end it, Anthony. I'm a huge fan. It's a huge honor that you waste all this time with me today. I thank you for just educating the world, for teaching me, inspire me to learn more about this new set of technologies that look like they have a potential to change, transform all of human civilization. So thank you for coming today and thank you for being who you are. Absolutely, thank you so much for having me. Thanks for listening to this conversation with Anthony Pompliano. And thank you to our sponsors, Theragun Muscle Recovery Device, Sun Basket Meal Delivery Service, ExpressVPN, and Indeed Hiring website. Click their links to support this podcast. And now let me leave you with some words from Mahatma Gandhi. Freedom is not worth having if it doesn't include the freedom to make mistakes. Thank you for listening and hope to see you next time.

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The Way Out | Lex Fridman (Original)

My Grandad was a soldier, on the front in 41 The bullets took his brother, this stubborn love held on The sky was filled with fire, millions lost in flames Hate and love were all there, and the world never the same Some days will sink in sadness, the weight of them too tough Don't lose yourself to madness, the way out is love When New York towers crumble, we're all New Yorkers too For a moment all just human, at the same old red or blue And the wicked will go on scheming, for the power in the pain But the heart that longs for freedom, is a fire they'll never tame Some days will sink in sadness, the weight of them too tough Don't lose yourself to madness, the way out is love The virus took our comfort, that was never ours to own When the enemy is inside us, we're together but alone This life is so dim and fragile, a leaf caught in the wind But every breath that's tragic, ignites a hope within Some days will sink in sadness, the weight of them too tough Don't lose yourself to madness, the way out is love www.mooji.org

https://youtu.be/UfMyp1wFgxE

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Manolis Kellis: Origin of Life, Humans, Ideas, Suffering, and Happiness | Lex Fridman Podcast #123

The following is a conversation with Manolis Kellis, his second time on the podcast. He's a professor at MIT and head of the MIT Computational Biology Group. He's one of the most brilliant, productive, and kind people I've had the fortune of talking to. A lot of my colleagues at MIT and former MIT faculty and students wrote to me after our first conversation with some version of, Manolis is awesome, isn't he? I'm glad you guys are now friends. I am too. And I'm happy that he makes time in his insanely busy schedule to sit down and have a chat with me. Quick summary of the sponsors, Public Goods, Magic Spoon, and ExpressVPN. Please check out the sponsors in the description to get a discount and to support this podcast. As a side note, let me say that I just got back from talking to Joe Rogan on his podcast, my fifth time on there. I also got a chance to record a separate conversation with Joe on this podcast. We talked on both quite a bit about his journey and his advice for mine. One of the things that I think made his show special is that he just had fun and made choices that didn't get in the way of him having fun and loving life. I'm learning to do just that. It's tough since I'm naturally full of self-doubt and anxiety, but I'm learning to let go and have fun. Even if my monotone robotic voice sometimes sounds otherwise. For Joe, that involved talking to his friends, comedians, especially ones that brought out the best in him. Duncan Trussell and the five-hour first episode on Spotify comes to mind as an example of that. Duncan has been a guest probably close to, if not more than 50 times on Joe's podcast. My hope with amazing people like Manolis is to find my Duncan Trussell, my Joey Diaz, and yes, even my Eddie Bravo. Obviously Joe and I are very different people, but ultimately both love life. When we can interact often with people we love and who inspire us, make us smile, make us think, and make us have fun when we get behind the mic of a podcast, whether anyone is listening or not. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. I also this time put a link in the description to a survey for this podcast on how I can improve and also an option if you like, I don't know why you would like to, but if you like to join an inner circle of people that help guide the direction of this podcast via email or occasional video chats. If you have a few minutes, please fill it out. As usual, I'll do a few minutes of ads now and no ads in the middle. I try to make these interesting, but I give you timestamps so you can skip, but still, please do check out the sponsors by clicking the links in the description. It's the best way, honestly, to support this podcast. This show is sponsored by Public Goods, an online store for basic health and household stuff. Their products have a minimalist black and white design that I find to be just clean, elegant, and beautiful. It goes nicely, at least I think so, with the design of Crew Dragon and the recent SpaceX NASA mission that sent two humans into space. To me, very few things are as inspiring as us humans reaching out into the unknown, the harsh challenges of space. Colonizing Mars may not have obvious near-term benefits, but I believe it will challenge our scientists and our engineers to create technologies whose impact will be immeasurable for us humans here on Earth, or those of us who choose to stay here on Earth. Personally, I'm kind of a long-time big fan of this planet. Anyway, visit publicgoods.com slash Lex and use code Lex at checkout to get 15 bucks off your first order. This episode is also supported by Magic Spoon, low-carb, keto-friendly cereal. You might have heard on other videos that I eat keto mostly these days, so Magic Spoon is a delicious, healthy treat on a hard workout day that fits into that crazy diet. Also, they're a sponsor of episode 100 with my dad and got my dad to buy the cereal, and he now loves it. Honestly, just loves it. It's kind of funny, actually. The deep, heartfelt nature of that conversation and the silliness of the cereal captures my dad perfectly. Much of the hardship in his life he dealt with using wit and humor. His favorite flavor happens to be cocoa. Mine is, too. He hasn't bought the 8-sleep mattress yet, though my mom wants to, but he's all about this Magic Spoon cereal. I think it's his actually favorite sponsor of this podcast, probably because they chose to sponsor the episode he's on. Anyway, click the magicspoon.com slash Lex link in the description and use code Lex at checkout for free shipping to let them know I sent you, and also indirectly to make my dad happy. This show is also sponsored by ExpressVPN. Get it at expressvpn.com slash LexPod. They gave me a suggested opening line of, using the internet without ExpressVPN is like going to the bathroom and not closing the door. This is like GPT-3 suggesting to me how to be more human-like, and I'll honestly take all the help I can get. By way of life advice, let me tell you that you need a VPN to protect you from Russians like me. In fact, this podcast is a kind of hack of your biological network where I use my monotone, low-energy voice to convince you to buy a kind of expensive cereal as a way to influence the stability of the US economy. I use ExpressVPN on both Windows and Linux to protect myself if I ever do shady things on the internet, which of course I never do and never will. So secure your online activity by going to expressvpn.com slash LexPod to get an extra three months free and to support this podcast. And now here's my conversation with Manolis Kalis. What is beautiful about the human epigenome? Don't get me started. So first of all, as an engineering feat, the human epigenome manages the most compact, the most incredible compaction you could imagine. So every single one of your cells contains two meters worth of DNA. And this is compacted in a radius which is 1,000th of a millimeter. That's six orders of magnitude. To give you a sense of scale, it's as if a string as tall as the Burj al-Khalifa, which is about a kilometer tall, was compacted into a tiny little ball the size of a millimeter. And if you put it all together, if you stretch the trillions of cells that we have, we have about 30 trillion cells in your body. If you stretch the DNA, the two meters worth of DNA in every one of your trillion cells, you would basically reach all the way to Jupiter a hundred times. Yeah, it's all curled up in there. It's 30 trillion cells. 30 trillion cells. In the human body. Every one of them, two meters worth of DNA. So all of that is compacted through the epigenome. The epigenome basically has the ability to compact this massive amount of DNA from here to Jupiter 10 times into one human body, into just the nuclei of one human body. And the vast majority of the human body is not even these nuclei. And that's sort of the structural part. So that's the boring part. That's the structural part. The functional part is way more interesting. So functionally, what the human epigenome allows you to do is basically control the activity patterns of thousands of genes. So 20,000 genes in your human body, every one of your cells only needs a few thousand of those, but a different few thousand of those. And the way that your cells remember what their identity is is basically driven by the epigenome. So the epigenome is both structural in sort of making this dramatic compaction, and it's also functional in being able to actually control the activity patterns of all your cells. Now, can we draw a definition, distinction between the genome and the epigenome? Again, being Greek, epi means on top of. So the genome is the DNA, and the epigenome is anything on top of the DNA. And there's three types of things on top of the DNA. The first is chemical modifications on the DNA itself. So we like to think of four bases of the DNA, ACGT. C has a methyl form, which is sometimes referred to as the fifth base. So methyl C takes a different meaning. So in the same way that you have annotations in a orchestra score that basically say whether you should play something softly or loudly or space it out or interpret basically the score, the human epigenome allows you to modify that primary score. So a modified C basically says, play this one softly. It's basically a sign of repression in a gene regulatory region. I love how you're talking about the function that emerges from the epigenome as a musical score. It is in many ways. And every single cell plays a different part of that score. It's like having all of human knowledge in 23 volumes, like 23 giant books, which are your chromosomes. And every single cell has a different profession, a different role. Some cells play the piano, and they're looking at chapter seven from chromosome 23 and chapter four from chromosome two and so on and so forth. And each of those pieces are all encoding in the same DNA, but what the epigenome allows you to do is effectively conduct the orchestra and sort of coordinate the pieces so that every instrument plays only the things that it needs to play. One thing that kind of blows my mind, maybe you can tell me your thoughts about it is the way evolution works with natural selection is based on the final sort of, the entirety of the orchestra musical performance, right? But there's these incredibly rich structural things, like each one of them doing their own little job that somehow work to get, like the evolution selects based on the final result, and yet all the individual pieces are doing infinitely minuscule specific things. How the heck does that work? That's a very good insight, and you can even go beyond that and basically say evolution doesn't select at the level of an organism, it actually selects at the level of whole environments, whole ecosystems. So let me break this down. So you basically have at the very bottom every single nucleotide being selected, but then that nucleotide's function is selected at the level of each gene, and every, not even each gene, each gene regulatory control element, and then those control elements are basically converging onto the function of the gene, and many genes are converging onto the function of one cell, and many cells are converging onto the function of one tissue or organ, and all of these organs are converging onto the level of an organism. But now that organism is not in isolation. So if you basically think about why is altruism, for example, a thing? Why are people being nice to each other? It was probably selected, and it was probably selected because those species that were just nasty to each other didn't survive as a species. And now if you think about symbiosis of, there's plants, for example, that love CO2, and there's humans that love O2, and we're sort of trading different types of gases to each other. If you look at ecosystems where one organism was just really nasty, that organism actually died because everyone they were being nasty to was killed off, and then that kind of universe of life is gone. So basically what emerges is selection at so many different layers of benefit, including all of these nucleotides within a body interacting for the emergent functions at the body level. Yeah, I wonder if it's possible to break it down into levels. That's selection even beyond humans. Like you said environment, but there's environments that are all different levels too, right? At the minuscule, at the organ level, at the tissue level, like you said, maybe at the microscopic level. It'd be fascinating if there's a kind of selection going on at both the quantum level and the galaxy level. Yeah, yeah, yeah. Of all different forms. Yeah, let's again sort of break down these different layers. So basically if you think about the environment in which a gene operates, that gene, of course, the first definition of environment that we think of is pollution or sunlight or heat or cold and so on and so forth. That's the external environment. But every gene also operates at the level of the internal cellular environment that it's in. If I take a gene from say an African individual and I put it in a European context, will it perform the same way? Probably not, because there's a cellular context of thousands of other genes that that gene has co-evolved with, in the out of Africa event and all of this sort of human history of evolution. So basically, if you look at Neanderthal genes, for example, which again happened long after that out of Africa event, there's incompatibilities between Neanderthal genes and modern human genes that can lead to diseases. So in the context of the Neanderthal genome, that gene version, that allele was fine. But in the context of the modern human genome, that Neanderthal gene version is actually detrimental. So it's, you know, that cellular environment constitutes the genetics of that gene, but also of course, all of the epigenomics of that gene. It's fascinating that the gene has a history. I mean, we talked about this a little bit last time, but, and then some of your research goes into that, but the genes as they are today have a story from the beginning of time. And then sometimes their story was like, their path was useful for survival for the particular organisms and sometimes not. That's fascinating. Let me ask as a tangent, we kind of started talking offline about Neanderthals. Do you have something interesting genetically, biologically, in terms of difference between Neanderthal and like the different branches of human evolution that you find fascinating? Neanderthals are only one of about five branches that we are pretty confident about. One branch. Branches of? Of out of Africa events. So basically there's Neanderthals, there's Denisovans. What is the evidence for Denisovans? One tiny little fragment of one pinky from one cave in Siberia. Recently, relatively recently discovered, right? Less than 10 years ago. Yeah. And those are like little folks, right? No, no, no, no, no. That's yet another one though. Homo florensis, it had the little folks in sort of Indonesia. But then Denisovans are basically another branch that we only know about genetically from that one bone. And eventually we realized that it's one of the three major branches along with Neanderthal, modern human and Denisovan. And then that one branch has now resurfaced in many different areas. And we kind of know about the gene flow that happened in between them. So when I was reading my Greek mythology, it was talking about the age of the heroes. These eras of human-like precursors that were wiped out by Zeus or by all kinds of wars and so on and so forth, like the Titans and the, you know, it's ridiculous to sort of read these stories as a kid because you're like, oh yeah, whatever. And then you're growing up and you're like, whoa, layers and layers of human-like ancestors. And who knows if those stories were inspired by bones that they found that kind of looked human-like but were not quite human-like. Who knows if stories of dragons were inspired by bones of dinosaurs. That basically this archeological evidence has been there and has probably entered the folk imagination, migrated into those stories, but it's not that far removed from what actually happened of massive wars of wiping out Neanderthals as humans are, modern humans are populating, you know, Europe. Do you think what killed the Neanderthals and all those other branches is human conflict or is it genetic conflict? So is it us humans being the opposite of altruistic towards each other, or is it some other, competition at some other level, like as we're discussing? Yeah, so if you look at a lot of human traits today, they're probably not that far removed from the human traits that got us where we are now. So, you know, this whole tribalism, you know, you're my sports team or you're my political party or you're my, you know, tiny little village. And therefore, you know, if you're from that other village, I hate you. But as soon as we're both in the major city, I can't believe we're from the same region, my friend, come here, my family. And like two neighboring countries fighting. And as soon as they're off in another country, you're like, oh, I can't believe that. So it's kind of funny. Like this tribalism is nonsensical in many ways. It's like cognitive incongruent, that basically we like kin. And selection for sort of liking kin is hugely advantageous genetically. Probably across all kinds of organs, across all kinds of life. Yeah. So basically if you now transport that to the sort of humans arriving in Europe and Neanderthals are everywhere, what are you gonna do? You're gonna kill them off. You know, there's this battle for territory and this battle for they're not like us, we have to get rid of them. So basically there's a very interesting mix there. But and yet, and yet, when you look at the genetics, there's tons of gene flow between them. So basically, you know, love, romance between, you know, near species. Yeah, we have tribes, but love spans the gap between the different tribes. It's Romeo and Juliet across species boundaries. Sneaks away from the village to hang out with the musicians. Even before the out of Africa, there's, you know, within Africa selection, which was probably massive battles of larger and larger tribes selecting for our social networking and savviness and, you know, probably all our conspiracy theory genes are, you know, dating back from then. And, you know, so there's a lot of this mischievousness in the history of human evolution that unfortunately is still present in, you know, many ugly forms today, but probably contributed to our success as a species in wiping out other species. It just sucks that we don't have neighboring species that are, you know, intelligent like us, but yet very different than us. So we have like, you know, dogs or wolves, I guess, co-evolved, they figured out how to neighbor up with humans in a friendly way and collaborate and develop in time. You're describing this as if the wolves made a choice. It's possible that the wolves never had a say, that basically humans were just so overpowering that they had captive wolves and then at every generation killed off eight of the nine pups and only kept the one that was milder. Humans. And it only takes a few generations to then sort of have pups that are really mild. And so the Neanderthals weren't useful in the same way that wolves were. I don't know if it's a question of useful. They were probably super useful. My thinking is that they were scary, that basically something that almost resembles you is something that you try to eliminate first. It's too close. Yeah. And speaking of, you know, species that are intelligent and sort of what's left of evolution, it is a shame, exactly like you say, that so many different amazing life forms were extinct and the kind of boring ones remained. So if you look at dinosaurs, I mean, the diversity that they had, if you look at sub, you know, like there's just so many different lineages of life that were just abruptly killed. And yet out of that death emerged, you know, many new kinds of really awesome lineages. Do you think there was in the history of life on earth, species that may be still alive today that are more intelligent than humans? And we just don't know? Like dolphins? These could be made for dolphins. Like if you look at their brains, if you look at the way that they play, if you look at the way that they learn, you know, I mean, they don't have opposable thumbs and we do. So, you know, that probably made a big difference. It's terrifying to think that like, not terrifying, I don't know how to feel about it, that they're more intelligent than us. It's like the hitchhiker's guide. I know, but how do you define intelligence? Basically, like I was saying last time, you know, stupid is as stupid does and smart is as smart does. So if the dolphins are basically super smart, figured out the meaning of life and just go around playing with water all day, which is probably the meaning of life, then we wouldn't know because all they're doing is kicking water just like sharks are and sharks are probably pretty stupid. So basically it's very difficult to sort of judge a species' intelligence unless they kind of go out of their way to demonstrate it. Yeah, and that's instructive for our understanding of any kind of life form. You know, I recently talked to Sarah Seager looking for life out there on other planets. It'd be fascinating to think if we discover a habitable planet, you know, outside of Earth in one day, maybe many centuries away, or be able to travel with like a robot there, how would we actually know that this species would probably be able to detect that it's a living being, but how would we know if it's an intelligent being? I mean, it's both exciting and terrifying to sort of come face to face with a life form that's of another world. Like something that clearly is moving in a, how would you say, like a deliberate way, and to then like ask, well, how do I ask that thing whether it's intelligent? No, but the question that you're asking is applicable to every species on the Earth now. On Earth now, yeah. So basically, you know, dolphins are a great example. We know that they're clearly capable hardware-wise and behavior-wise of intelligence. You know, how do we communicate? So basically, if your question is about crossing species boundaries of communication, the way that I wanna put it is that humans have achieved a level of sophistication in our behaviors, in our communication, in our language, in our ways of expressing ourselves, that I have no doubt that if we encountered a human-like form of intelligence, we'd figure out their language in a few weeks. Like it'd be just fine, as long as, you know, of course, they're both trusting each other, not annihilating each other, and not sort of fearing each other and attacking each other. What about, let me ask, just out of curiosity and into science fiction land a little bit, so clearly you're one of the top scientists in the world, so if we were to discover an alien life form, you would be brought in to study its genetics. Do you think the epigenome that we talked about, the genome, the code, the digital code that underlies that alien life form would be similar to ours? Like in fundamental ways, maybe not exactly, but in fundamental ways, how it's structured? Yeah, so you're getting to the very definition of life. You're getting to the very definition of what makes life life, and how do we decode that life? And it's so easy to think that every life form would basically have to, you know, like oxygen, have to like heat from the sun, and rely on sort of being in the habitable zone of, you know, its solar system, and so on and so forth. But I think we have to sort of go beyond this sort of, oh, life on another planet must be exactly like life is on Earth, because of course life on Earth happens to rely on the proximity to the sun, and benefit from that amount of energy. But we're talking at timescales of human life, where we kind of live, I don't know, between, and I'm gonna be super wide here, we're gonna live between six Earth months, and, you know, 200 Earth months, or 200 Earth years. So basically, if you look at the timescale that we inhabit on Earth, it is very much dictated by the amount of energy that we receive from the sun. If you look at, I don't know, Europa, you know, the smallest, the fourth smallest moon of Jupiter, the smallest of the Galilean moons, and also the smallest in its distance from Jupiter. It has an iron core, it has a rock exterior, it has ice all around it, and it has probably massive liquid oceans underneath. And the gravitational pull of Jupiter is probably creating all kinds of movement under that ice. How did life evolve on Earth? Yes, sure, life now, most of life that we, above the surface, look at, has to do with exploiting the solar energy for, you know, our daily behavior. But that's not the case everywhere on the planet. If you look at the bottom of the ocean, there are hydrothermal vents. There's both black smokers and white smokers, and they are near these volcanic, you know, ducts that basically emanate a massive amount of energy from the core of our planet. What does life need? It needs energy. Does it need energy from the sun? It couldn't care less. Does it need energy from, you know, the Earth itself? Yeah, possibly, it could use that. And if you look at how did life evolve on, you know, on Earth, there are many theories. I mean, a kind of silly theory is that it came from outer space, that basically there's a meteorite out there that sort of landed on Earth and it brought with it DNA material. I think it's a little silly because it kind of pushes the buck down the road. Basically, the next question is how did it evolve over there? Yeah, exactly. Whereas our planet has basically all of the right ingredients. Why wouldn't it evolve here? So basically, let's kind of ignore that one. And now the two other competing hypotheses are from the outside in or from the inside out. What's that mean? From the outside in means from the surface to the bottom of the ocean. Ah. From the inside out means from the bottom of the ocean to the surface. So life on the surface is pretty brutal. Life obviously evolved in the water and then there was an out of water event. But basically, before it exited, it was clearly in the water, which is a much nicer and shielded environment. So just to be clear, on the surface, are you referring to the- The surface of the sea or the bottom of the sea. Versus the bottom of the sea. And you're saying life on the surface is harsh. Chemically- Life outside the water is horrible. It takes huge amounts of evolutionary innovations to sustain living outside the water. What? That's so interesting. Why is that? So it's easier to, life is easier in the water. Maybe, see, I'm telling dolphins- We are 70% water. No, dolphins went back into the water. Really? Oh, because dolphins are mammals. Of course, yeah. Interesting. Well, again, they might be smarter. They went back. They're like, screw this. So if you basically think about the fact that we are 70% water, we're basically transporting the sea with us, outside the sea. You know, if we don't have water for about 24 hours, we're dry. And if you look at life under the sea, I mean, I don't know if you're a diver, but when you go diving, your brain explodes. Again, when I say the boring life forms is what we see all the time, like tetrapods. I mean, what a stupid, boring body plan. Seriously, like just go diving and you'll see that a tiny little minority of the stuff under the sea, under the surface of the sea is actually tetrapods. It's like, you know, snails with all kinds of crazy appendages and colors and, you know, round things and five-way symmetric things and, you know, eight-way symmetric things, all kinds of crazy body plans. And only the tetrapod fish managed to get out. And then they gave rise to all the boring plans we kind of see today of basically, you know, humans with four limbs, birds with four limbs, lizards with four limbs, and, you know, right? It's kind of boring. If you look at, by comparison, life underwater is teeming with diversity. So now let's roll back the clock and basically say where did life in the ocean come from? From the surface or from the bottom? Exactly, those two options you were mentioning. Exactly. So basically, life on the surface is one option. And then the idea there is that there's tides with the moon and the sun sort of causing all this movement. And this movement is basically causing nutrients to sort of, you know, coalesce and, you know, bounce around, et cetera. That's one option. The second option, massive amount of energy under, you know, from the core of our planet, basically exploited, leading to these basic ingredients of life forms. And what are these basic ingredients? Metabolism, being able to take energy from the environment and put it as part of yourself. Metabolism, it basically means transformation, again, in the Greek. It basically means taking stuff from, you know, like nutrients or energy source or anything, and then making it your own. The second one is compartmentalization. If there's no notion of self, there can't be evolution. You have to know where your own boundaries end and where the non-self boundaries begin. And that's basically the lipid bilayer nowadays, which is extremely simple to form. It's basically just a bunch of lipids, and then they eventually just self-organize into a membrane. So that's a very natural way of forming a self. And then the third component is replication. Replication doesn't need to be self-replication. It could be A helps make more of B, B helps make more of C, and C helps make more of A. Any kind of self-reinforcement is what you need to ignite the process of evolution. After you've ignited that process, you know, I don't wanna say all hell breaks loose, but all paradise breaks loose. So basically you then, boom, you know, have life going. And the moment you have A, B, C, some kind of thing looping back onto A, you can make modifications and you can improve, and then you let natural selection work. Is there some element of that that's like, like some state representation that stores information? Maybe I should say information. Is that a fundamental part of life? We like to think of life as the information propagation, which is DNA, the messenger, which is RNA, and then the action, which is protein. So basically DNA, we think, is an essential part of life. That's where the storage is. And therefore that early life forms must have had some kind of storage medium, DNA. If you look at how life actually evolved, DNA was invented much later. Proteins were invented later. And RNA was found by itself, thank you very much, in an RNA world. So the early version of life as we know it today was in fact RNA molecules performing all of the functions. The RNA molecule itself was the protein actuator by creating three-dimensional folds through self-hybridization. Self what? Self-hybridization. So basically the same way that DNA molecules can hybridize with themselves and basically form this double helix. The single-stranded RNA molecule can form partial double helices in various places, creating structure as if you had a long string with complementary parts, and you could then sort of design kind of like origami-like structures that will fold onto themselves. And then you can make any shape from that. That early RNA world eventually got to replication where enzymes encoded in RNA would replicate RNA itself. And then that process basically kicked off evolution. And that process of evolution then led to major innovations. The first innovation was translation. So you start with an RNA molecule and you translate it into another kind of form, and that's the first kind of encoding. You're like, well, do you need some kind of code? Yeah, but the code was in fact one thing. It was conflated with the actuators. The actuators were separated from the code only later on. So you first had the self-replicating code, which was also the actuator, and then you kind of have a functionalization, partitioning of the functionalization, a sub-functionalization of the proteins that are now gonna be the workhorse of life, but they're not self-replicating. The code remains the RNA. So the most beautiful and most complex RNA machine known to man is the RNA molecule. The most beautiful RNA machine known to man is the ribosome. The ribosome is this massive factory that is able to translate RNA into protein. The ribosome, I mean, if you want, I don't know, divine intervention in the history of life, the ribosome is it. That's one of the great invention in the history of life. Yeah, but again, you can't think of great inventions as one-time steps. They're basically the culmination of probably many competing software infrastructures for life preservation that won out, and then when the ribosome was so efficient at making proteins, all the other ones basically died out, and then the life forms that were using the modern ribosome were basically the more successful ones because it could make proteins, and now those proteins are much more versatile because RNA only has four bases. Proteins eventually have 20 amino acids, not initially, but eventually, and then they can form in much more complex shapes and they can create all kinds of additional machines, one of which is reverse transcriptase. So you basically now have RNA. Again, we like to think of transcription as the normal, reverse transcription as the oddball. Well, RNA preceded DNA, so reverse transcription actually was the first invention before transcription itself. So basically, RNA invents proteins. RNA and proteins together invent DNA. So you now have a more stable medium, a more stable backbone with two helices instead of one, two strands instead of one, the double helix, and RNA basically says, listen, I'm tired. I'm gonna delegate all information storage to DNA, and I'm gonna delegate most actuation to proteins. Proteins, but that's, to you, is not like a, that's just an efficiency thing. It's not a fundamentally new invention. That's why when you're asking, is a separate information storage medium a definition of life? I'm like, no, any kind of self-preservation, self-reinforcement, and it didn't need to be RNA-based initially. It didn't need to be self-replication initially. You just need to have enough RNA molecules randomly arising that reinforce each other that ultimately lead to the, you know, the closing of that loop and the ignition of the evolutionary process. Can we just rewind a little bit? Like, if you were to bet all your money on the two options in terms of where life started. Probably the bottom. At the bottom of the ocean. I don't know if this is answerable, but how hard is the first step, or if there's something interesting you can say about that first leap from not life to life? Yeah, I think it's inevitable. On Earth or just? In the universe. I think it's inevitable. If you look at Europa, you know, going back, the moon of Jupiter. It's also a really nice song by Santana. Europa basically has all the ingredients. It has, you know, the core that can emit energy. It has the shielding through the ice sheet, protecting it just like an atmosphere would. It even has a layer of oxygen, probably sufficiently dense to sustain life. So my guess is that there's probably independently arisen life form already teeming in Europa, because as soon as it, today. Is that exciting or terrifying to you? It's, I mean, as a scientist, I can't wait to see non-DNA based life forms. I can't wait because we are so born, you know, sort of born-ay, as I would say in French, but basically we're sort of, you know, we are so narrow-minded in our thinking of what life should look like that I can't wait for all that to just be blown away by the discovery of life elsewhere. Let me bring you into another science fiction. It's a scenario. So on that point, if we discover life on Europa and you were brought in, you seem very excited, but how would you start looking at that life in a way that's useful to you as a scientist, but also not going to kill all of us? So like, to me, it's a little bit scary because not because it's a malevolent life, like it's a dictator petting like a cat, it's evil, but just the way life is, it seems to be very good at conquering other life. So there's a lot of science fiction movies based on that principle. And that's sort of what causes the public to be so scared. But if you think about sort of, would Europa life be scared of humans coming over and taking over? Chances are no, not even like Earth bacteria, because Earth bacteria would be wiped out in an instant in this foreign world because they don't know how to metabolize energy that doesn't come from the types of energy sources that are here. The levels of acidity may just kill us all off. And at the same way, in the converse way, if you bring life from Europa on Earth, it'll die instantly because it's too hot or because it doesn't need to know how to cope with, I don't know, the sun's radiation so close to these completely inhabitable zone by their standards. So what we call the habitable zone might actually be the inhabitable zone. Inhabitable for them. So the difference, if the environments are sufficiently different, you think we'll just not be able to even attack each other and the basic biology. It'll take massive amounts of engineering to create machines that will go there and sample the oceans, basically drill through the layers of ice to basically sample and see what life is like there and detecting it will probably be trivial. It definitely won't be DNA-based. It's not like we're gonna send a sequencer. But it'll be some other kind of combination of chemicals that will look non-random. So if you had to bet, if I took that life form we find in Europa and put it on a sandwich that you're eating and eat that sandwich. It'll taste just fine. And you'll be, well, I know about that. I don't know, I'd say, will it taste fine? That's interesting. So the other question is, do we have taste receptors for this? So where does our taste come from? It's basically adaptations to chemical molecules that we are used to seeing. So you think even the chemistry of the life? We don't have taste buds for things we don't even know about. So we won't, yeah, we won't be able to know that this chemical tastes funny. But you think it won't be, it's likely not to be dangerous. Like it won't know how to even interact. Do you think our immune system will even detect that something weird is going on? Probably. And it'll be very easy to detect because it'll be very different from us. Very weird. But it won't be able to sort of attack. I mean, the scene from, I don't know, Independence Day, where like they're communicating with the alien computer and they're like, ooh, I'm in. I mean, it's hilarious. Because like Macs and PCs have trouble communicating. I mean, let alone an alien technology or even alien DNA. So, okay, now I was talking about you being a scientist on Earth, but say you were a scientist that was shipped over to Europa to investigate if there's life, what would you look for in terms of signs of life? Life is unmistakable, I would say. The way that life transforms a planet surrounding it is not the kind of thing that you would expect from the physical laws alone. So, I would say that as soon as life arises, it creates this compartmentalization, it starts pushing things away, it starts sort of keeping things inside that are self, and there's a whole signature that you can see from that. So, when I was organizing my Meaning of Life Symposium, my friend who's an astrophysicist, basically we were deciding on what would be the themes for the symposium. And then I said, well, we're gonna have biology, we're gonna have physics, and she's like, oh, come on, biology is just a small part of physics. Ha ha ha ha ha. Everything's a small part of physics, right? I mean, in many ways it is, but my immediate answer was, no, no, no, no, wait. Life challenges physics, it supersedes physics, it sort of fights against physics. And that's what I would look for in Europa, I would basically look for this fight against physics, for anything that sort of signatures of, not just entropy at work, not just things diffusing away, not just gravitational pulls, but clear signatures of, you remember when I was talking earlier about this whole selection for environments, selection for biospheres, for ecosystems, for these multi-organism form of life? And I think that's sort of the first thing that you can look for. You know, chemical signatures that are not simply predicted from the reactions you would get randomly. Such a beautiful way to look at life. So you're basically leveraging some energy source to enable you to resist the physics of the universe. Fighting against physics. But that's the first transformation. If you look at humans, we're way past that. What do you mean by transformation? So basically there's layers. I sort of see life, you know, when we talk about the meaning of life, life can be construed at many levels. We talked about life in the simplest form of sort of the ignition of evolution. And that's sort of the basic definition that you can check off. Yes, it's alive. But when Alexander the Great was asked, to whom do you owe your life? To your teachers or to your parents? And Alexander the Great answered, I owe to my parents the zine, the life itself. And I owe to my teachers the F zine, like euphony. F means good, the opposite of cacophony, which means, you know, bad. So F zine in his words was basically living a human life, a proper life. So basically we can go from the zine to the F zine. And that transformation has taken several additional leaps. So basically, you know, life on Europa, I'm pretty sure has gotten to the stage of A makes B makes C makes A again. But getting to the F zine is a whole other level. And that level requires cooperation. That level requires altruism. That level requires specialization. Remember how we were talking about the RNA specializing into DNA for storage, proteins, and then compartmentalizations. And if you look at prokaryotic life, there's no nucleus. It's all one soup of things intermingling. If you look at eukaryotic life, again, you for true good, you know. So a eukaryote basically has a nucleus, and that's where you compartmentalize further the organization of the information storage from all of the daily activities. If you look at a human body plan or any animal, you have a compartmentalization of the germline. You basically have one lineage that will basically be saved for the future generations. And everything outside that lineage is almost superfluous. If you think about it, the rest of your body, all it does is ensure that that lineage will make it to the next generation, that these germlines will make it to the next generation. The rest is packaging. I'm sorry to be so blunt. And if you look at nutrition, we're deuterostomes. What does deuterostome mean? Deutero means second, where this is the second mouth. The first mouth is actually down here, it's the esophagus. So deuterostomes have evolved a second layer of eating, kind of like alien with the two mouths. Yeah. So you can think of us as alien, where the first mouth is up here, and then the second mouth is down there. And of course- Is the first mouth just the physical manipulation of the food to make it more consumable? Correct, correct. And basically, again, if you look at a worm, it's an extremely simple life form. It basically has a mouth, it has an anus, and it has just some organs in between that consume the food and just spit out poo. Humans are basically a fancy form of that. So you basically have the mouth, you have the digestive tract, and then you have limbs to get better at getting food. You have eyesight, hearing, et cetera, to get better at getting food. And then you have, of course, the germline, and all of this food part, it's just auxiliary to the germline. So you basically have layers of addition, of compartmentalization, of specialization, on top of this zine to get all the way to the earth zine. Yeah, so like the worm is like Windows 95, very few features, very basic. And then us humans are like Windows Vista, Windows 10, whatever it is. Well, a few innovations beyond that, but yeah, we're Windows 10,000, at least put it that way. So, okay, that's such a fascinating way to look at life as a set of transformations. Exactly. So is there some interesting transformations through our history here on earth that appeal to you? Of course. And what are the most brilliant innovations and transformations, would you say? Yeah, yeah, yeah. I mean, this is such a fascinating question. Of course, we're talking about basic, basic life forms, and we're talking about eukaryotic life forms. And then the next big transformation is multicellular life forms, where the specialization separates the germline from everything else that accompanies it and sort of carries it. And then that specialization then sort of has this massive new innovation, like above the second mouth, which is this massive brain. And this massive brain is basically something that arises much, much later on. Basically, you know, notochords, like having the first spinal cord, this whole concept that, along with these very simple layers, you basically now have a coordinating agent. And this coordinating agent is starting to make decisions. And remember when we were talking about free will? I mean, you know, as a worm is hunting for food, oh, it has plenty of free will. It can choose to, you know, follow chemotaxis to the left or chemotaxis to the right. And maybe that's free will, because it's unpredictable, beyond a certain level. So you basically now have more and more decision-making and coordination of all of these different body parts and organs by a central operating system, a central machine that basically will control the rest of the body. And the other thing that I love talking about is the different timescales at which things happen. You know, we were talking about the human epigenome before. The human epigenome is basically able to find what genes should be expressed in response to environmental stimuli in the order of minutes and basically receive a stimulus, transfer all that data through these humongously long string of searching, and then sort of find what genes to turn on and then create all that. All of that is happening in the timescale of minutes, basically, you know, three minutes to half an hour. That's the expression response. But our daily life doesn't happen on the order of three minutes to half an hour. It happens on the order of milliseconds. Like I throw a ball at you, you catch it right away. No gene expression changes there. You just don't have time to do that. So you basically have a layer of control built on a hardware that supports it, but that hardware itself lives in a different timescale than the controlling machine on top of that. Is that an accident, by the way? Is that like a feature? Is it, was it possible for life to have evolved where the daily life of the organism as it interacts with its environment was on a timescale similar to the way our internals work? If you look at trees, they look kind of boring and stupid. You're like looking at a tree like stupid. If you speed up the movie of a tree from spring until October, you'll be like, oh my God, it's intelligent. And the reason for that is that at that timescale, the tree is basically saying, oh, I'm looking for a thing to catch onto. Ooh, I just caught onto that. I'm gonna grow more here. I'm gonna spawn there, et cetera. Like I can see the trees in my garden just growing and sort of looping around. It's all a matter of timescale. And if you look at the human timescale, remember we were talking about neoteny the last time around, the whole fact that our young are pretty useless until maybe a few months of age, if not a few years of age, if not, I don't know, getting out of college. And then we basically hold them, enabling their brain to continue being malleable and infusing it with knowledge and thoughts as that period of neoteny increases and expands. If you fast forward, I don't know, another million years. So humans have only been around different from apes for about that long. Jump another unit of that, another human-gem divergence. What could happen? From an evolutionary timescale, a lot. One of the things that's happening already is expansion of human lifespan. We have longer and longer periods before we mature, and we have longer and longer periods before we have babies. So intergenerational distance is grown from, I don't know, 16 years to 40 years. So you're saying that's in the genetics. No, no, not necessarily. But it's sort of an environmental tendency that's happening. But as we medically expand human lifespan, the generations might actually be pushed instead of 40 years to 60 years to 100 years. Like if we look at the long arc of the evolutionary history. Exactly. So as we start thinking about intergalactic travel now. Sorry, that's a heck of a transition. Yeah, so let's talk about intergalactic travel. No, no, no, no, no. As we as a species start thinking about, I'm talking about these transitions that are happening. So continue along these transitions, what does the future hold in the next million years? So the concept of us going to another planet and that taking three human lifetimes might be a joke if the human lifetime starts being 400 years or 800 years. So imagine- It's all timescale. It's all timescale, just different timescales. You asked me offline whether I would like to live forever. I mean, my answer is absolutely. And there's many different types of forevers. One forever is do I want to live today forever? Kind of like Groundhog Day. And the answer is absolutely. The stuff that I want to learn today will probably take a lifetime just to learn, you know, basically to clear my to-do list for the day. You mean like relive the day? Relive the day. And then pick up different things from the richness of the experience that we're all in today. Exactly. There's just so much happening in the world every single day. So much knowledge that has happened already that just to catch up on that will probably take me around forever. On that point, I would just love to see you in the Groundhog movie just, because you're so naturally as a scientist, but just the way your mind works beautifully, just all the richness of the experiences that you will pick up from that. That's a beautiful visual. But you said- I try to live each day as if it was Groundhog Day. I'm basically every single day waking up and saying, all right, how would Bill Murray get out of that one? Well, you know what? On a funny tangent, I got a chance to go to a Neuralink demonstration event. I'm not sure if you're familiar with Neuralink. And I talked to Elon for a while. And one of the funny things he said on this Groundhog Day thing is, it's a beautiful dream to eventually be able to replay our memories. So we're kind of these recording machines. Our brain is kind of maybe a noisy recording machine of memories. And it would be beautiful if we can, someday in the future, maybe far into the future, be able to, like in the Groundhog Day situation, replay that. And the funny comment that stuck with me is he said that maybe this, our conversation now, is a replay of a previous memory. And that stuck with me because it would probably be my replay. Who the hell am I? I'm just some idiot guy. But Elon Musk is, probably because of SpaceX and so on, is probably going to be remembered as a special person, one of our special apes in history. So if I wanted to replay a memory, probably be that one, talking to Elon for a while. That's an interesting possibility from, if we think about time scales, if we think about the richness of the experience through time that we humans take, and be able to replay some aspects of that, of that biology, that's super interesting. But anyway, sorry for the tangent. Yeah, you were talking about time scales and the expansion of the human lifetime and the idea of intergalactic travel. Yeah, no, but you're laughing about it. It's like, I'm laughing about it. You're talking about this. You're talking about exploring alien worlds and going to other planets. I mean, when Sarah was here, she was talking about sort of going to other planets when we find this life. I mean, I'm just very naturally, given the topics that we've approached, talking about the time scale at which this will happen. So you think eventually we will, human or life, life will expand out into the universe. The point that I'm trying to make is that an intergalactic species will probably find ways to engineer its biology in order to expand the way that we experience time, expand the time scale that we experience. And going back to this whole concept of, would I like to live forever? Yes, I'd like to live forever. Even if it was stuck on the same day, I'd love to live forever because I would finally have time to do all these things that I wanna do. But if living forever actually comes with a perk of watching the whole world evolve forever, I mean, that's a huge perk. And it'll never get boring, just a never changing world. And then the mind experiment that I want you to do is to also ask, what if I wanted to live forever one day at a time every year, or one day at a time every decade? Would you choose that? Where you would wake up and the world would be 10 years later every single day you wake up. It's the opposite of Groundhog Day, where basically you always wake up and it's always 10 years later. So you're saying that's such a powerful, interesting concept that life is more interesting if you're of all the life forms on earth, that you're the slowest one. Exactly, exactly. Like trees have it right. Like trees have it right. All of trees, they've been there since the Minoan civilization. And that takes us back to the question you asked about sort of the transformation that have happened in humanity. The Minoan civilization is one of them. There's this paper that was published just a couple of years ago by one of my friends that basically looked at the genetic makeup of the Minoans and the Mycenaeans in ancient Greece and how they relate to modern Greeks. And they found that indeed there was very little gene flow from the outside. And it's fantastic to sort of think about these amazing civilizations that transformed the way that human thought happens, that basically looked for rules in nature, that looked for principles, that looked for the standard of beauty, not human beauty, but beauty in the natural world. This whole concept that the world must be elegant and there must be deeper ways of understanding that world. To me, that's a massive transformation of our species, similar to the earlier transformation that we're talking about of even evolving a brain, of learning how to communicate language or the evolution of eyesight. If you look at sort of, we're talking about these worms crawling around and then sensing which direction are the chemicals more abundant, chemotaxis. So eventually they grow a nose, eventually they grow a, yeah, I mean, when I say nose, I mean ways of sensing chemicals. That's probably one of the earliest senses. We always talk about how deep rooted it is in your brain. That's one of the earliest senses. If you look at hearing, that's a much later sense. If you look at eyesight, that's an intermediate sense where you're basically sensing where the light direction comes from. That's probably something that life didn't need until it got into the surface and so on and so forth. So there's a lot of milestones. And I was talking about the latest milestone, which is LIGO last time, of being able to detect gravitational waves and sort of being able to sort of have a sense that humans haven't had before. So you see that as yet another transformation that gives us an extra little sense. Of course. And now if you go back to this history of ancient Greece, I mean, this transformation that happened, I mean, of course, the Egyptians had this incredible, you know, civilization for thousands of years. But what happened in Greece was this whole concept of, let's break things down and understand the natural world. Let's break things down and understand physics. Let's basically build rules around architecture, about around elegance, around, you know, statues and tragedy. I mean, another question that you asked me in passing was this whole concept of embracing the good and the bad, embracing the full range of human emotions. And if you look at Greek tragedy, it's the definition of that. It's, I mean, drama. I mean, again, it's a Greek word, but the whole concept of some problems that are just so vast and large that dying is the easy way out. That death, oh, that's the easy solution. You know, so I wanna touch a little bit on that point and sort of talk about this concept that life supersedes physics and that the brain supersedes life. That basically we have a brain that can decide to not follow evolution's path. We can decide to not have children. We can decide to not eat. We can decide to suicide. We can decide to sort of abolish communication with the outside world. I mean, all the things that make us human, we can basically decide not to do that. And that is basically when the brain itself is basically superseding what evolution problem is for. Poof! So, okay, so one of the, it's, okay. My mind was already blown at the beautiful formulation of the idea that life is a system that resists physics. And our brain, or perhaps the content of it, or however it may be functionally, our brain is a thing that resists life. Yes, yes. You're so, you're so brilliant. But I want you to see all of that as continuum. Basically, you're sort of talking about the sort of individual transformations, but it's a path that humanity has been taking. It's a path of transformation. And then I want us to think about what it truly means to become human, like the F-zine. And you asked me about what motivated my Meaning of Life Symposium. What motivated it, in part, I mean, of course, it was an inside joke of turning 42, but what motivated it in part was actually a midlife crisis. So the joke that I always like to say is Christos Papadimitriou, a famous Greek professor who was previously at MIT, at Harvard, at Stanford, at Berkeley, everywhere, brilliant, brilliant person. Actually, Costis' advisor. Advisor, yeah. So Christos Papadimitriou likes to say that when you're an undergrad, you work like a rat to get into grad school. And when you're a grad student, you work like a rat to get your PhD. And when you're a postdoc, you work like a rat to get your assistant professor's degree. And when you're an assistant professor, you work like a rat to become a full professor. And then when you're a full professor, well, by then, you're basically a rat. That's brilliant. So basically what happened to me is that I arrived at the end of the rat race. You know, life is a rat race. You constantly have hurdles to jump over. You constantly have tunnels and secret pathways. And I figured it all out. And eventually, as I was turning 42, I looked back and I was like, wow, that was an awesome rat race, but I'm not a rat. I basically got out of the labyrinth and I was like, I'm not a rat, turns out. Is that the first moment where you saw that you were in a rat race? No, no, no, I've known that I'm in a rat race for a long time. It's so easy to be in a rat race. It's so easy to be an undergrad, but you have problem sets. And you know, we're all smart people. You know, problem set, it has a solution. Somebody made it for you. You can just solve it. Everything was made as a test. And you keep passing those tests and tests and tests and tests. And you have tasks that are well-defined. The PhD is a little different because it's more open-ended, but yet you have an advisor who's guiding you. And then you become a professor and tenure is a well-set, defined set of tasks. And you do all that. And at 42, I basically had bought a house, three kids, beautiful wife, tenure, awesome students, tons of grants. Life was basically laid out for me. And that's when I had my main life crisis. That's when people usually buy a Harley Davidson. And they basically say, oh, I need something new. I need something different. I need to be young myself, et cetera. But basically that was my realization that it's not a rat race, that there's no rat race, it's over. That I have to basically think, how do I fully instantiate myself? How do I complete my transformation into an actual human being? Because it's very easy to sort of forget all the intangibles of life. It's very hard to just sort of think about the next task and the next task and it's all metrics. And what is the number of viewers I have? What is the number of publications I have? What is the number of citations? The number of talks, the number of grants? It's very easy to quantify everything. And then at some point you're like, this is real life. It's not a test anymore. And that's something that I told my wife early on. I was like, no, no, no. Our life is not gonna be, let's put the kids through college. And maybe that's when I escaped the rat race. Maybe it continued being a rat race. Maybe the next step would have been, all right, how do I make sure that my kid is first in class? How do I make sure that they're into the greatest college? And then they're into college and then you're like 60. So how do you escape? But what is the, is there a light at the end of the tunnel of a midlife crisis? So you should watch that symposium because the videos were transformative to me and to many others. So basically the advice that I received from all of my friends was so meaningful. There's some advice that basically says you have to constantly maintain unachievable goals. Goals that you can make progress towards, but you can never be fully done with. And I think that's almost playing into the sort of rat race thing. Like basically make sure that there's more obstacles for your little rat persona to jump through. So that's one possibility. So first of all, watch. Is it available somewhere? It's on YouTube. Just Google meaning of life symposium. I should have known this. I mean, you should have told me this. This is awesome. Okay, this is great. But and also like, saying rat race is, if we look at Ratatouille, it's not, I mean, that's a beautiful, that's a beautiful thing of challenges and overcoming challenges. That could be fundamentally the meaning of life is to see life as a set of challenges and to fully engage in the overcoming of those challenges. I would say that that's embracing the rat race view of life. So a joke that we like to have with my wife all the time is we basically say, we pretend that we're in this all inclusive resort, that we've basically hired all these people to go on the Esplanade and play games because we enjoy watching people playing on the Esplanade. And we enjoy sort of laying and looking at life and all the people biking and rollerblading and all of that. And then we've paid all these people in this all inclusive resort that we live in. And then what are we gonna do today? I'm like, oh, I've signed up for professor activities. It's gonna be awesome. They lined up a bunch of super smart MIT students for me to meet with. I'm gonna have a grant writing meeting afterwards. It's gonna be awesome. And then she signed up for a bunch of consulting activities. It's gonna be great. And then in the evening, we just get back together and say, hey, how was your consulting today? So in a way, that's another view of life of basically, wait a minute, if I was a gazillionaire, what would I choose to do? I would probably pay an awesome university to give me an office there and just pay a bunch of super smart people to work with me, even though they don't really want to. And et cetera, et cetera, et cetera. In fact, I would have exactly the life that I have now working my butt off every single day because it's so freaking fulfilling. Well, that's, so let's clarify, it's just a beautiful way. It's almost like a video game view of life that is a set of, I mean, again, game is not perhaps a positive term, but it is a beautiful term. So do you or do you not like the rat race view of life? The rat race view of life. No. Because it is fulfilling in some. The rat race is about the goal. My view of life is about the path. So again, quoting Greece. Those folks have come up with some good stuff. So this Odysseus Elitis basically wrote this beautiful poem about sort of going through life, saying as you go through your journey, impersonating Ulysses of his voyage, he says, wish that the path is long and arduous. Because when you get to Ithaca, you might realize that it was all about the path, not the destination. So the rat race view of life makes it all about the destination. It's like, how do I get through the maze to get there? But the all-inclusive resort view of life is about the path. It's about, wow, today I couldn't wish for a better set of activities all programmed for me to enjoy having my brain, having my body, having my senses and the life that I have. So it's a very different kind of view. It's focused on the journey, not on the destination. So you mentioned kind of the ups and downs of life. And the midlife crisis. And right now you said focusing kind of on the journey. But what the journey involves is ups and downs. Is there advice or any kind of thoughts that you can elucidate about the downs in your life? The hard parts of your life and how you got out or maybe not, or is there, how do you see the dark parts of life? So I'm so glad you're asking this question because it's something that our society does a terrible job at preparing us for. Every Hollywood movie has to have a happy ending. It is ridiculous. You can count on your 10 fingers the number of bad ending movies that you've ever watched. And you probably wouldn't need all 10 fingers. But we strive to tell everyone, yes, you can succeed. Yes, you're a millionaire, just temporarily disabled. And yes, the prince will eventually figure out his princess and they will have a happily ever after ending. And yes, the hero will be beaten and beaten and beaten. But you know that at the end of the movie, the good guys will win. We need more movies where the bad guys win. We need more movies where just everybody dies. Where just, you know, MacGyver doesn't figure out how to disable the bomb and just explodes. You just need more movies that are more realistic about the fact that life kind of sucks sometimes and it's okay. So again, growing up in Greece, I have been exposed to songs that are not just sad, but they're miserable. Miserable. So one of them comes to mind. And it's basically talking about this woman who's lamenting in the early morning about losing the joyful kid, the joyful young man, who basically died in the civil war in the arms of our own fellow citizens. And she's like, if only he had died fighting the foreign forces, if only he had died at the sides of the general, if only he had died with honor, I would be proud to have lost the joyful kid. I mean, it's devastating, right? It's like, he didn't just die, he died without honor. And my friend who was with me was listening to the song and she's like, this is depressing. I'm like, whoa, you have to listen to another one. It's not as sad. And she's like, what, this one died with honor? So that's one example. It's a kind of a celebration of misery. No, no, no, no, no, no, no. So let me give you a couple more examples and then I'll answer that question. So another example is I picked up this book that I had from my childhood and I started reading stories to my kids. And the first story is about these two children. One is really poor living on the street and the other one is really rich, living in the house in the bright light above. And the poor one is wishing, looking at that window and wishing that he could have that house. And the other one is at the window, wishing that he was free, that he wasn't sick all the time, that he could escape outside. It's only four pages long. And at the end, both children die. One of them dies from cold, the other one dies from illness. And you're like, how is that even a children's story? The next story, I'm like, okay, that's fine. Let's skip this one. So I read this to my kids and then I read the next one. And the next one is about this woman whose brother is at war against the Turks and he is gonna die. And she prays to the Virgin, please don't let him die. And the Virgin appears and she's like, no problem. Tell me who to kill instead. And she's like, anyone, anyone. No, no, no, no, choose one. How about this Turk? This one has two kids, a beautiful family waiting for him at home. She's like, no, not this one, choose another one. And then she goes through all the life stories of the others and she's like, no, no, just don't take anyone. She's like, I can't do that. You can choose to bring your brother back and he will be depressed for the rest of his life because he didn't fight at war, because he didn't go to that battle and he will live without honor. She's like, and in the end, the woman decides to have her brother killed instead because he dies without, I mean, this is insane. So why am I giving you these examples? It's not a glorification of misery. It's expanding your emotional range. It's teaching you that, and when I read these stories, I'm not a jerk, I'm crying out loud. I have tears and like my face becomes red from the pain that I'm experiencing through these stories. It's just so deeply touching to embrace the suffering, not because of an accident, but because of a choice, the sacrifice to embrace the fact that not everything is cute and rosy and always ending well. And I think that we don't do a good enough job of teaching our kids that just life sucks and life is unfair sometimes. And that's okay. And sometimes I read a story to my kids. I read a story every night and sometimes the story is horrible and sometimes the story is good and sort of friendly and happy. And my kids always ask, what's the moral of the story? And sometimes there's a moral and it's like, oh, you should be good or you should be nice. You should be helping each other, et cetera. And sometimes there's just no moral. And I tell my kids, you know what? Sometimes just life doesn't make sense and it's okay. And you can't comprehend everything. And I think this concept of how do you deal with bad days comes from the fact that we're taught, we're brainwashed into thinking that every day should be a happy day. And we're not ready to cope with misery. And the other thing that crying through these stories teaches you is that you don't have it nearly half as bad as you think. Do you see what I mean? Basically, it tells you that, I mean, my mom would always tell me about how she was transformed as a teenager when she volunteered in the hospital. And she saw all these people at the brink of death clinging for life and helping them out to best she could and crying her heart out when they were dying. And just sort of how that taught her the appreciation for what we have every day. Waking up every morning and saying, my life doesn't suck. My life is not nearly half as bad as it could be. And sort of embracing the joy that we have of living where we live in the moment we live. And I'm gonna go further. If you look at the arc of human life, human existence through the centuries, there's no better way to be alive than now. I mean, we're complaining about every single little thing, but life expectancy is at an all time high. Sickness, all time low. Poorness, misery, all time low. There's no better time to be alive globally across all of human existence, number one. Number two, here in Boston, there's no better place to be alive. If you think about the amalgamation of science, engineering, technology, the ridiculously awesome people you're bringing every week to your podcast, I mean, this is the ancient Greece of modern society. But the weather still sucks. It just. No, let me put it this way. The weather gives us a range of emotion. The full range. The full scenic range. That's such a fascinating thing about human psychology. I often reread this book, I'm not sure if you're familiar with it. It's Man's Search for Meaning by Viktor Frankl. And he talks about his living through the Holocaust and the concentration camps. And even there where there's human misery is at its highest. Even there he discovers these moments by observing the suffering, by accepting the suffering, he observes moments of true joy of how great his life is relative to others at the camp who have it worse. Yeah, so it's a dangerous slippery slope to think that way because it's basically being better than the Joneses. And if the house next door has a giant car, then you wanna get a bigger car or something like that. It's not comparative misery. I think the way that I see it is slightly different. And it's not even thinking about all the worst possible outcomes that could have happened but didn't. The example, as you were talking about the concentration camps, the most horrible, I mean, one of the most horrible moments of human existence, I was thinking about pictures that I was seeing of kids in Syria in war-torn zones. And you're looking at these kids. And again, I cried out loud, imagining my own son in the van after a bomb explosion, watching his father die or his siblings die or losing his friends. It's something that we are not capable of fathoming. But if you actually put a seven-year-old in that situation, the look that I saw in these kids' eyes basically said, it is what it is. And I've experienced that with my own kid. When he gets, like, my three-year-old, like two years ago, who's now my five-year-old, she was burned really badly with hot chocolate and coffee that just peeled off her skin. So you could actually see just her fragile skin had just peeled off. And she was the happiest little kid. She was just going along with the punches. It is what it is. She accepted it. So it's quite dramatic to sort of realize that children don't say, oh, I could have it better. They sort of embrace the moment, not embrace, but sort of accept the moment. And then they can have moments of pure joy in a horrendous war-torn country. And, you know, like so many people from, you know, these war-torn countries basically say, oh, you think you Americans are gonna just come and just send us a bunch of aid and food, et cetera? Yeah, sure, that's helpful. But what do we dream of? What do we struggle for? We struggle for love. We struggle for meaning. We struggle for, you know, emotions and friendships. We struggle for the same things you guys struggle for. We're not just like every day waking up and saying, oh, I wish I had more food. No, that's just a given. I just don't have enough food. But what we struggle with are basically everything else. And that sort of gives you some perspective on life. It basically says, you know, and another story that my mom told me when I was a kid is this story about sort of this man who's basically, you know, he sees the Christ appear in front of him. And he says, oh, Christ, I'm carrying all these problems. I'm carrying this big bag. Can you please take it from me? And he's like, sure. Let me just give you any other bag. And basically, and of course, the person in the end accepts his own bag. So acceptance, ultimately, the path you recommend is acceptance. Every single other bag is probably worse. It's the evil you don't know versus the evil you know. Like we all struggle with our own problems. But if you look at the bigger picture, it's just your path through life. And if you embrace it, the good and the bad, every single day, it's just joy, elation, sadness, misery. If you don't have both, you're not a complete human being. You know, you can't, I mean, the last example I'm gonna give is the movie Inside Out by Pixar. Beautiful movie. Which one is that? The one with the little characters controlling all the emotions. Oh, the emotion, great movie. So you basically have joy and sadness and fear and disgust, et cetera. And the moral of the story, if you remember the movie, the moral of the story is that in the end, joy is basically trying to fix everything, to make everything happy. And she's failing miserably, and everything else is like crumbling and falling apart. And the little girl basically becomes emotionless because all she knows how to do is fake happiness. And I think it's a very good analogy for our everyday society, where we're always saying, are you happy, are you happy? My mom calls me and she's like, Manolis, are you happy? I'm like, mom, stop asking this stupid question. No, I'm not happy. What you should be asking is if I'm fulfilled. And that's a very different thing. I don't go around being happy. I go- I would love it if your mom called and said, Manolis, are you suffering beautifully, or something like that. That's exactly right. That's what she should be asking. Are you struggling to achieve something great? That's the question that mom should be asking. Not are you happy. Hear that mom call me about the suffering, not about how good are you doing. So what I tell her is that life is not about maximizing happiness. Life is about accomplishing something meaningful. And accomplishing that meaningful thing cannot come from a series of joyful moments. It comes from a series of struggles, of successes and failures, of people being nasty to you, and people being nice to you, and embracing the full thing. And if you supersede that constant need for gratification, if you supersede that constant need for kindness, you suddenly know who you are. And what I like to say to my kid, and my son the other day was telling me, oh, so-and-so called me such and such. And I'm like, are you such and such? He's like, no. I'm like, ha-ha, see, they were wrong. And what I tell him is if you know who you are, what other people say about you only teaches you about them. Yeah. So it has no influence on your self-esteem. If you know where you stand, you embrace the good, but you also embrace the bad. I have plenty of bad, and I'm embracing it. I'm a procrastinator. How do I deal with that? I trick myself into procrastinating about mindless, stupid, little day-to-day things. And in that procrastination time, I'm doing important things for the future. So accepting who you are. Accepting your flaws. Accepting the whole of it. Accepting the struggle, accepting the sleeplessness, accepting the fact that the journey is what matters. Hoping that your path to Ithaca is full of troubles because those troubles are the life you will lead. Accepting that life will not start after the next milestone that life has already started a long time ago. And what you're experiencing now is the life. This is it. It's not some kind of future thing that you work yourself hard to get to. And then after that, you live happily ever after. To me, the happily ever after, that's the end of the story. Nothing happens after that. The struggle and the struggle and the struggle is much more interesting story than the lived happily ever after. So I think we have to embrace that as a society that it's not just about the happy ending, that our kids are brainwashed into expecting that things will be happy and rosy, and it's okay if they're not. And they should keep struggling because the struggle is the journey, and the journey is the meaning of life. It's not the end, it's the journey. What about accepting one of the harder things? We talked a little bit about immortality. What about accepting that life ends? So do you, Manolis, think about your own mortality? We talked about accepting that there's ups and downs to life, what about the ultimate down, which is the finality of it? Do you think about that? Do you fear it? You also asked me if I'm afraid of getting older. Yes. And that's on the path to mortality. So let me talk about that first step, and then the last step. The last step. Okay, the last step. So getting older, what does that mean? When I was 18, when I was 20, my brain, I felt, was at my maximum. I was like, nothing is impossible. I can solve anything. I could take any math puzzle, any logic puzzle, any programming puzzle, and just solve it in milliseconds. I just saw the answer through problems. I was like feeling invincible. I would show up at lecture with my newspaper, lift up my head every now and then, point to errors, just brat, complete brat. I would raise my hand and correct my professors from the whole classroom. Total brat. I have some of those in my class now, and it's awesome. It's like very- I used to be you. Teaches you humility. Yeah. So I felt invincible, and I was like, this is it. This is awesome. I'm living the life. 10 years later, my brain didn't work the same way. I wasn't as good at the tiny little puzzles, but it worked in different ways. And right now, 20 years later, it works in yet different ways. And oh gosh, I love the journey. Can you maybe give some hints of the interesting different ways that your brain works as it aged? Yeah. I went from the phase of sheer speed and hardcore quantitative thinking to sort of stepping back, being able to sort of make more connections and make more connections, being able to sort of say, yeah, but let's use that thing. Sort of a huge new creativity being unleashed. Basically, when you're young, you're sort of thinking about that one problem. You can sort of reconfigure all the variables combinatorially in your head and just wipe it all out. When you're just a little older, you start getting more creative. You start bringing in things from different fields and different contexts and sort of stepping outside the box. Basically, it's like being in the rat race and saying, there's a ceiling. Why are we trying to get through that? So it's sort of thinking outside the box. And then at 40, what I'm going through now is this whole sort of embracing the path of life. And when I say life has started already, it's not a test anymore, this is basically embracing the finality, embracing that the journey is what it's at. So what I like to say is live every day as if it's your last one and make plans as if you'll never die. I always have the long-term that I'm sort of planning out for that will eventually become the short-term. And I always have the sort of short-term. And I think this ability to sort of look at life in the past and look at life in the future jointly and sort of embrace the continuity, both of life in the universe and on our planet, as well as life as a human being from the beginning to the end, just as a path, as a journey, and just embracing every aspect of that. I mean, I was talking about parenthood the other day and how amazingly fulfilling it is to sort of relive childhood through the eyes of my kids, but with the perspective of a parent. So the sheer arrogance of youth, watching this in my kid, I can see myself when I was 18, correcting my professor, I felt so proud. Little did I know that my professor was working on so much more interesting things than the three little things he was putting on the board that day. And I was like, ah, I'm invincible. But in fact, no, it's just a little brat. And basically right now, I sort of can see the sort of journey with a little more humility. I can sort of look at my own students with their unbelievable abilities, being able to do things that I'm no longer able to do, better than I probably was ever able to do, but yet being able to guide them and shape their thinking and blow their minds with new ideas and new directions through my perspective. And I know when something is solvable because I've been there, but I'm not gonna even bother. It's not that I can't do it. I'm sure I could if I tried, but just I'm not interested in that anymore. So what I'm embracing this journey of aging is how my brain is changing and how I'm constantly trying to figure out the niches, the evolutionary niches that I'm best adapted for, for the tasks that I'm best at, while hiring and recruiting both assistants and research scientists and students and postdocs, and that will be the best at those tasks. But someone still has to see the big picture, and I love being in that role. So you're, at the timescale of a human lifespan, you're doing the same thing that the worm did at the evolutionary timescale of growing arms, of the specialization, the compartmentalization. He talks about, I mean, it's fascinating to think of what 80-year-old Manolis would look back at the man that's sitting here today and laugh at the arrogance. He finally figured out something. I was like, no little thing. You didn't figure out anything. I mean, ultimately, it seems that if you're introspective about life, it leads to a kind of acceptance, a deeper and deeper acceptance of the whole of it. There, again, I wanna be cautious about acceptance, because it almost says that you can't change it. Ah, yeah. It's sort of embracing the struggle and embracing the journey, is the way that I would put it. So you ultimately feel that a journey isn't just something that happens to you. Of course, you shape it, you shape it. Remember how I was saying that Boston is the best place and the best time to live in right now? In the history of humanity. I'm exaggerating a little bit, but the way that I think about this is that if you look at the whole of cosmos, where would you rather be? If you're just a bunch of molecules, roughly your biomass, where would you rather be? Would you rather be a rock on Mars? Eh, probably not. Would you rather be in a black hole? Probably not. Would you rather be in an exploding supernova? Maybe, that might be interesting. But being on Earth is an awesome solar system, an awesome planetary system, an awesome place to be in. Across all of space-time, it's a pretty good place to be in as a bunch of molecules. If you are a bunch of molecules on Earth today, being an animal with some kind of awareness of the stuff around you is wonderful. Being a human among all animals is amazing because you have all this introspection. And being a human who's young, fit, athletic, smart, et cetera, you have so much to be happy for. Beyond that, being surrounded by a bunch of awesome people that you interact with all the time. I feel blessed to interact with the people I know, with the friends I have, the dinners that I have, all of this, the students that I interact with. I'm so blessed. And the last little blip in this awesomeness of local maximum, the last little blip comes from being kind. Being grateful and being kind. I don't know if you remember that little prayer that I described last time of, thank you for all the good you've given me and give me strength to give onto others with the same love that you've given to me. And the whole point of that is being grateful and being kind. What does that do? From a purely egoistic perspective, it makes the people around you happier and it takes that little maximum a little bit further because you'll be surrounded by happy people by being kind. That's the purely egoistic view. And the purely altruistic view, or maybe it's egoistic as well, is that it's good to give. It feels good to give. Like basically watching somebody who's touched by what you said, watching somebody who's appreciating a rapid response or a generous offer or just random acts of kindness is so fulfilling. So evolutionarily, we were selected for that. There's just such a good feeling that comes from that. You know, it's fascinating to think you said Boston is the best place and talking about kindness that the very thought that Boston is the best place in the universe is almost, it's a kind of a gravitational field and your thought and your very life in itself is a kind of field that makes that real. So the- It's a self-fulfilling prophecy. Yeah, and it- By claiming it's the best and thinking it's the best, it becomes the best. And you make others, it's not a force that just applies to your own cognition. Exactly. It applies to the others around you. And then suddenly you live in an even better place. Yeah, and it creates the reality, the actual reality, the social reality. Exactly. Then it molds the environment. Exactly. By the way, what's one of the coolest things about you, I think, is you represent the best of MIT, like the spirit of MIT. So I'm so glad that I'm fortunate enough to be able to talk to you because there's a kind of cynicism about academia in parts that I think is undeserved and that there's a, you know, MIT, of course, but academic institutions is a sacred place where ideas can flourish and just in the same very way that you're talking about is both kindness and curiosity and that weird thing that happens when a bunch of curious descendants of apes get together and just like get excited and there's this ripple effect that happens. I mean, that's the most beautiful aspect of MIT. People might think like competition and grants and like position, like you said, the rat race, but like underneath it all is these curious human beings inspiring younger human beings. And there's this ripple effect that happens and I'm so glad that, I mean, I'm glad that I get a chance to record this because it inspires so many other students and so many other people to do the same, to embrace the inner curious creature that's not about the race. So let's talk about the negative. Let's talk about, no, no, no, I'm serious, I'm serious. You know, you have to embrace the good and the bad. So let's talk about the negative. As the Greek comes out. Let's address it. Okay, so why do people want positions of power? Why do people want more money, more power, more this, more that? Remember the part where I was saying, if you know who you are, what other people think about you, it makes no difference to you. It only teaches you about them. Many people feel defined themselves. They feel instantiated through the eyes of others. So being in a position of power makes them feel better about themselves. Who knows what other kind of struggles they might have that creates that need to feel better about themselves. But they have a bunch of struggles and everybody has a bunch of struggles. And every time I see somebody behaving poorly, I'm basically thinking, well, they're in a tough spot right now and it's okay. You know, I can kind of see how I would behave badly in other circumstances as well. So I think if you take away that sort of having to prove yourself in the eyes of others, life becomes so much easier. So when I first became a professor at MIT, I started wearing adult clothes. I had my like, you know, I mean, before- It became a serious person quote-unquote. I basically had, you know, I would always like go around in my roller blades and my shorts and a t-shirt. And eventually I was a professor, like, oh, I bought all these khaki pants and, you know, these nice like, you know, shirts with like, you know, whatever they call it, the patterns. And I was like, you know, dressing with my nice belt every day, showing up. And then a few months later, I was like, I can't stand it. And I just went back to my roller blades and my t-shirts and my shorts. And it was this struggle of sort of not feeling that I fit in. I was so intimidated by all of my colleagues, like just watching their incredible achievements, like persons next to me and the person, you know, the floor below me. I was like, oh my God, like, they clearly made a mistake. What the heck am I doing here? How will I ever live up to these people's standards? And eventually you grow up to realize that the way that I grew up to realize that the way that other people perceived my work was very similar to the way that I perceived other people's work as flawless. I knew all of the flaws in my work. I knew the limitations. I knew what I hadn't managed to achieve. And what I saw was maybe a third of the way of what I was trying to achieve. And I saw everything as flawed. What they saw, what I had achieved, they didn't see what I hadn't achieved. They only saw the one third down, which was pretty good in their eyes. So they all respected me. And I was feeling miserable about myself. I was like, I'm not worthy. And I think that this is a cognitive problem that we have. We kind of, it's kind of like when we're talking about artificial general intelligence, AGI, of sort of, we kind of have this definition that anything that machines can do is not intelligent and anything that they can't do is intelligent. Therefore, we narrow, narrow, narrow, narrow the field of what intelligence truly means. And as soon as machines achieve self-learning, it's not intelligent anymore. I feel like I was doing the same thing with myself. As soon as I could solve something, it was the kind of thing that a kid like me could solve. And therefore it was kind of easy. But to the others, it seemed hard. But to me, it seemed easy. So it was this kind of thing that everything that my colleagues were doing seemed impossible to me. But everything that I was doing seemed impossible to them. So it was that realization that sort of made me mature into sort of a, not more confident, but more comfortable human being. Can you actually linger on that a little bit? I mean, you mentioned Minsky. I remember he said something in an interview where he said the secret to his, like the way he approached life was to never be happy with anything he did. So there's something powerful as a motivator to doing exactly what you're saying, which is everything you've achieved, to see that as easy and unimpressive. What do you do with that? Because clearly that's a useful thing. I think I've kind of matured past that. And I think the maturity past that is to sort of accept what it is and accept that it has helped others build onto it and therefore advance human knowledge. So it's very easy to sort of fall into the trap of, oh, everything I've done is crap. What I told you last time is that I always tell my students that our best work is ahead of us. And I think that's more of my mindset. That's a beautiful way to put it. Exactly. What we've done is strong. It's great. It's great for the time. And it'll become obsolete in 30 years. Not we can't, we are doing even better. We're doing even better. Exactly. So basically our next work, we'll just strive. And again, you can't let the perfect be the enemy of the good. At some point you have to wrap. I was having a meeting with my student yesterday and he was like, listen, we know this is not perfect, but it's way better than anything that's ever been done before. You know how to improve it, but if you try to, your paper's never gonna get published. So there's this balance of we're already at the top of the field, get it out. And then you work on the next improvement. And in my experience, this has never happened. We've never actually worked on the next improvement. And that's okay. It didn't make a difference. Because you're basically putting a new stepping stone that others will be able to step on and surpass you. My advisor in grad school would basically tell me, Manolis, let others write the second paper in that field. Just write the first one, move on. Move on to the next field. You don't wanna be writing the second and the third and the fourth and the fifth paper in the same field. Just, and it's very shocking to a student to hear that. Cause I was like, I was at the top of my game. I was owning that field and I published the first paper. I'm like, I'm ready for two and three and four. He's like, move on. Just let it be. And I was like, whoa. And it's so liberating to sort of not have to surpass everyone, but just put your little stepping stone out there and others will step on it and put their own stones further and eventually cross a bigger river than if you tried to sort of make a giant leap all at once. So you need both. Beautifully put. So the funny thing is, I've, believe I closed the previous episode with a Darwin quote about the power of poetry and music in life. I think your quote, and again, I only heard once, was Darwin basically saying, if I were to live life again, next time I would read more poetry and something about art every week or something like that. Yeah. It's so interesting for somebody who studied life at a very cold, I would say, genetic level, to say that, yeah, the highest form of living is the art. But on that, which made me realize that you write poetry and I forced you or maybe convinced you somehow to maybe share, if it's possible, if it's okay, some of the poetry you've written yourself in your life. So again, being Greek, a lot of my poems have been pretty miserable. And I always like to say that it's very hard for me to write a poem when I'm happy. And I just have to be in a state of deep despair in order to write poems. But the first poem I ever wrote was in English class. I'm Greek, I grew up in Greece, but I was in a French high school and I was taking English as a foreign language. So the English teacher basically asked us to write a poem in English. So this is basically what I'm gonna embarrass myself and read from my 16-year-old self many, many years ago. Can you give a little bit more context about who you were in this moment? So like, just... So here's what's really interesting. In terms of growing up, how do we grow up? It's very difficult to grow up if you're in the same school going from one class to the other and all your friends know you inside out. It's very difficult to change. It's very difficult to grow up because they have a certain set of expectations for who you are and for how you're gonna behave. So in many ways, we kind of tend to get set in our ways and not change very much. I think something that helped me grow up is that when I was 11 years old, I was a kid in Greece in primary school. When I was 12 years old, I was a kid in Greece in a first year of high school. When I was 13, I was in France. So basically moved countries and schools. The next year, I moved schools again because it was a transition in the French educational system from one school to the next. The next year after that, my family moved to New York. In a French high school there. And the next year after that, I'm moving to MIT. So basically between 11 and 19, every single year, I actually had the opportunity to grow. I was not held by people who knew me and I could reinvent myself or reshape myself or reshape my sort of personality, my emotions, my, as I was growing up, especially in such a transformative time of a kid's life from 11 to 17. Okay, first of all, it's so powerful that you think of it that way. Did you think of it that way at the moment? Because it's kind of a source, you said an opportunity to grow, but it's kind of suffering. I mean, you're being torn away from the thing you know into a thing you don't know. So when we moved from South France to New York, I was pissed. I was pissed. I was taking these long bike rides in the countryside, jumping in French swimming pools. And I had all these wonderful friendships going downtown and just staying by the fountains in the dim lit streets of Aix-en-Provence in the South of France. It was magical. And suddenly I moved to New York City, a city of cement, of ugliness, like trash in the streets and every corner. It's just horrible. Snow everywhere. Having never seen snow or like real snow in my life, I moved from Athens to South France to suddenly New York. So I was pissed. But whether I saw it as an opportunity for growth, I don't think so. I don't think that I was that self-reflective. It was just how it happened. Only now do you see it this way. I saw it like that probably pretty early on, but not during those transitions. So basically during those transitions, I was just a kid being a kid, you know. And maybe the time that I started seeing it that way was maybe when I decided to stay at MIT as a professor after having been there as a student. And I kind of saw the struggle of getting professors to not see you as a kid when they're your peers. And I was very flattered when one of my friends basically told me, oh, I remember you in recitation. When you first asked me a question, I said, wow, this kid. I'll pay attention. One day I'll be a peer. So it's, you know, certainly my perception was that many of them could not see me as anything but a kid, but it turns out that some of them saw me as something different than a kid even before I was actually their colleague. So it's kind of an interesting place because what I like to say about MIT is that people treat you as equal no matter what stage. And they respect you for what you say, not for who you are when you're saying it. And if I'm wrong, my students will tell me. They will have no reservation to just be bluntly, you know, sorry, I don't agree with that. Yeah, I mean, the beautiful thing about you, sorry to put it this way, is, you know, maybe people who weren't familiar with your work beforehand might think, like, might not realize that you're a world-class scientist who leads a large group and so on. Because there's a youthful nature to you that it's, I mean, you talk like an undergrad, you know, with the excitement and the fresh eyes and the sort of excitement about the world. And that's, first of all, super contagious and beautiful. You know, it's easy to sort of fall into behaving seriously because then people kind of start putting you on a pedestal more, into a position of power. You wanna sort of act like you're in a position of power as opposed to allowing yourself to be lost in the just the curiosity, the childish view of the world, which is just this open-eyed love of knowledge. And that was the transition that I was describing when I decided to go back to my rollerblades and T-shirt and, you know, baseball cap. Basically, you know, when I met my first postdoc, it was basically, you know, he was interviewing for postdocs at MIT. He already had several first author papers to his name in top journals and my friend, Julia, basically introduced me to Alex Stark, who basically was interviewing at the time with Rick Young and with Eric Lander, just like these massive names in the field. And I was just a first year faculty person with, you know, zero credibility. And she basically says, oh, there's this friend of mine, Alex, who's visiting. He's also German. You know, he wanted to meet you. I'm like, oh, sounds great. I'd love to talk science. I show up, we sit at the amphitheater in Stata, you know, I basically arrive in my rollerblades, you know, jump a few steps, sit down, wearing my blades, we're having these awesome conversation about science and about gene regulation and how the whole thing works and sort of, you know, my perspective and his perspective, and we're just bouncing ideas for 30 minutes. And then I just dash off to my next meeting. And he basically emails me afterwards. And I was giving him advice about how to interview with Eric Lander, how to interview with Rick Young and how to sort of get a position with them. And then after a while, he emails me saying, I would love to become a postdoc in your group. I'm like, what, are you kidding me? Like, wow. So he basically didn't care that I wear rollerblades and T-shirt. All he cared about was my ideas and sort of embracing the me with the childhood excitement about science was basically what attracted him. It wasn't the, wow, this guy runs a big lab or this and that. It was just like, I like his ideas. I wanna work with him. That, by the way, folks, is the best of MIT. That's what MIT stands for. So that's a beautiful story. But take me back to the poem. And where did this poem come from? Where's your mindset? So who is the 17, 16-year-old kid, Manolis? So again, I've just seen Snow for the first time. And I'm in New York. This is New York. So I'm, you know, maybe that's where the sadness in the poem comes from. But anyway, we're asked in class to write an assignment. This is my third language. I'm not very good at it. So pardon me, but here's what I wrote. Children dance now all in row, children laughing at the snow, but in time's endless flow, children sooner or later grow. Men are mortal, we go by. If we know it, we may cry. But I thought a love so sweet was immortal, was so deep. There I told you, darling sweet, that forever love would keep. Blossomed spring and summer shined, then blue autumn, winter died. One year passed, but the clouds still remember all our vows. Never faked and never lied. All we did was stare and smile, all alone, sitting down, to the snow we made our vow. But you told me you were right. Birds who love are birds who cry. Now with laughter children play, yet the sky is so gray. Even if the snow seems bright, without you have lost their light. Sun that sang and moon that smiled, all the stars have ceased to shine. All of nature drew its grace, found its light within your face. Now you're gone and won't return. Let the snow in my heart burn. There's a Greek in there, that's beautiful. That's beautiful, by the way. And the rhyming, the musicality, there's both a simplicity. I'm 16. And a musicality too. I hate my third language. No, no, no, but like, so I really enjoy like Robert Frost poems. I don't mean simplicity in a bad way, in a negative way at all. Again, it's very weird to analyze your own poem, but I think it captures the simplicity of youth and the way that it kind of starts with children dance like only low. It basically, and it kind of shows that snow can be interpreted first in the first verse as a happy thing. Da da da da da snow. And then in the end, you know, now with laughter children play, I'm like, now I've grown basically. It's this transformation that we're actually talking about. This whole men are mortal, we go by. I'm sort of, you know, you're saying, are you comfortable with growing old? I'm like, duh, I was since I was 16. And what's really interesting is that, you know, again, when I was 12 years old in our summer house in Greece, I remember sort of telling my sister my outlook that I would have as a father for how to bring up my own kids. So it's very weird that I've always sort of seen the full path from, you know, a kid. From when you were young. Yeah, I don't know if you like this Jonny Mitchell song. ♪ I've looked at clouds from both sides now ♪ ♪ From up and down and still somehow ♪ ♪ It's snow's illusions I recall ♪ Or it's clouds illusions I recall, I really don't know clouds at all. So it's really beautiful. So I think the Jonny Mitchell song, which again, I heard for the first time much, much after this, and I wouldn't even compare this to that. But what Jonny Mitchell is saying that song is that you can see life from two perspectives. You can see the good or the bad in both, you know, in everything you see. And I think that's the allegory of snow right now. You can see snow as this bright, white, wonderful thing, or you can see snow as this miserable, you know, gray thing. So that's sort of, and what I like about the last verse now with Laughter Children Play is that it's a recall to the first one, where I was the kid enjoying careless life and eventually was making promises that something would be forever. And I think part of that is also the loss of my friendships in France, of being in New York now and sort of everything's gray. And, you know, even though the snow seems bright without you have lost their light, sun that sang and moon that smiled. So it's this concept that if you lose your love, the same thing can be perceived in a very different way. Let me ask you this, because somebody wrote me this long email, and I think you're the perfect person to ask this. Uh-oh. You mentioned love. From a genetic perspective, what is it? What do you make of love? Why do we humans fall in love? In your own life, why did you fall in love? You know, the email that was written to me was you always talk about mortality and fear of mortality, but you don't ask about love. So I don't know if there's some thoughts you could give about the role of love in your own life or the role of love in human life in general. I think love in many ways defines my life. It's basically, I like to say that I'm a human first and a professor second. And I think this passion for life, this passion for everything around us, I mean, the only way to describe that is love. It's basically embracing your emotional self, embracing the non-brainiac in you, embracing the sort of intangible, the not very well-defined. And even in my own research, I'm just very passionate about everything I do. And there's a certain passion that comes through. And what, I'm sorry, again, being Greek, the etymology of the word passion. What was passion? Passion is suffering. The etymology, when we talk about the passion of the Christ, it's the suffering. And in the Greek version of that word, pathos, like pathology, pathos is deep suffering. It's the concept of someone who's sympathetic. Sympathetic means suffering together, experiencing emotions together. So it's funny that you asked me about love and I respond with passion, passion for life, passion for research, passion for my family, for my children, for, you know. So there's a certain passion that defines me and everything else follows rather than the other way around. I'm not first thinking with my brain, what is the most impactful people we could write? And then going after that, I'm thinking with my heart, what am I passionate about? What drives me, what just like, you know, makes me take. And that's a beautiful way to live, but I love it how the Greek part of you just kind of connects it to the suffering. So if you could remove the suffering. No, no, no, no, no, no. When I say suffering, I don't mean suffering as in being miserable. I mean, suffering as in being emotionally invested in something. Remember, I mean, again, if you look at this poem, what is it saying? It's saying birds who love are birds who cry, right? That's the very definition of love. Exposing your fragility. If you're not afraid of suffering, you don't fall in love. As soon as you hold back, you protect, you shield your heart, no love can enter. So there's this Simon and Garfunkel song. I am a rock. I am an island and a rock feels no pain and an island never cries. So again, there's some aspect of that into this poem. The, you know, the fact that, you know, but you told me, you know, there I told you darling sweet that forever love would keep is this intermediate thing. And then there's a recall, but you told me you were right. Birds who love are birds who cry. So it basically says that love is the fragility that you're willing to give to another person. It's opening up your vulnerable spots. It's sort of accepting that there's no safety net. You're just giving yourself fully and you're ready to be hurt. So you've already been way too kind with your time, but I'm gonna force you to stay here just a few minutes longer. As we're talking about goodbyes, you have a really nice other poem here about goodbyes. Can I force you to read it as well? Oh, twist my arm, twist my arm. So the next poem was written specifically for our high school yearbook. So another poem written on demand. The rest of them are just so miserable, written by pure sadness and melancholy. But this one was also written on demand. And it was basically saying goodbye, as is appropriate right now, to my friends. And sort of, again, reflecting this whole journey and transformation through life. And also, I think showing a little bit of introspection about how we kind of had it easy in high school and we're about to go into rougher waters. So the title is actually The Tidewaters. And it's an analogy on that. So here it goes. All this was another lake, where some rest we sailors take. Waters calm and full of fish. We'll find there what we wish. Some seek fruit and others feast. Some of us just look for peace. Some find fresh ships, other love. Some seek both and neither have. We were different when we came. Each his own story and fame. Different people had we been. Different cultures had we seen. Different nature, different face. Each unlike all in this place. We had faced success, defeat, then in one lake came to meet. There, the orders that we followed and the pride that we swallowed made us one, but not the same. Joined us strangers who there came. Sooner, later, groups were made. Tribes where differences will fade. Some attached, more or less. Others fought and made a mess. But again, we have to go. What for? Where to? We don't know. Still, we know it. We will try. There to rush, to flee, to fly. There'll be some who wish to stay, but they'll carry on away. We'll continue on our journey as we came here, strong yet lonely. From the lake, a river flows. From the river, many goals. On that river, we will race. Each will try to find his pace. In that scene, the sailors face, their first fear, defeat, disgrace. Here and there comes out a face that the waters soon embrace. Some get lucky, find their way. Others sink beneath the waves. In this race, we will part. Some will settle near the start. Some set goals beyond the stars because the river carries far. You should know in what we've done, the hard part is still to come. So I'll have to say goodbye. Don't you worry, I won't cry. Neither will they, those who try, till the end to keep their pride. But please know, dearest friends, who are always there to mend, I will always need your hand. I will miss you till the end. I don't think there's a better way to end it. Manolis, like I said last time, you're one of the most special people at MIT, one of the most special people in Boston, and whatever mental force field that you're applying in saying that Boston is the best city in the world, MIT the best university in the world, you're actually making it happen. So thank you so much for talking to me, it's a huge honor. Thank you so much, it's been a pleasure. Thanks for listening to this conversation with Manolis Kellis, and thank you to our sponsors, Public Goods, Magic Spoon, and ExpressVPN. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from another well-known Greek, Alexander III of Macedonia, commonly known as Alexander the Great. There is nothing impossible to him who will try. Thank you for listening, and hope to see you next time.

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David Eagleman: Neuroplasticity and the Livewired Brain | Lex Fridman Podcast #119

The following is a conversation with David Eagleman, a neuroscientist and one of the great science communicators of our time, exploring the beauty and mystery of the human brain. He is an author of a lot of amazing books about the human mind, and his new one called LiveWired. LiveWired is a work of 10 years on a topic that is fascinating to me, which is neuroplasticity or the malleability of the human brain. A quick summary of the sponsors, Athletic Greens, BetterHelp, and Cash App. Click the sponsor links in the description to get a discount and to support this podcast. As a side note, let me say that the adaptability of the human mind at the biological, chemical, cognitive, psychological, and even sociological levels is the very thing that captivated me many years ago when I first began to wonder how we might engineer something like it in the machine. The open question today in the 21st century is what are the limits of this adaptability? As new, smarter and smarter devices and AI systems come to life, or as better and better brain-computer interfaces are engineered, will our brain be able to adapt, to catch up, to excel? I personally believe yes, that we're far from reaching the limitation of the human mind and the human brain, just as we are far from reaching the limitations of our computational systems. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now and no ads in the middle. I try to make these interesting, but I give you timestamps so you can skip, but please do check out the sponsors by clicking the links in the description. It's the best way to support this podcast. This show is brought to you by Athletic Greens, the all-in-one daily drink to support better health and peak performance. Even with a balanced diet, it's difficult to cover all your nutritional bases. That's where Athletic Greens will help. Their daily drink is like nutritional insurance for your body that's delivered straight to your door. As you may know, I fast often, sometimes intermittent fasting for 16 hours, sometimes 24 hours, dinner to dinner, sometimes more. I break the fast with Athletic Greens. It's delicious, refreshing, just makes me feel good. I think it's like 50 calories, less than a gram of sugar, but has a ton of nutrients to make sure my body has what it needs despite what I'm eating. Go to athleticgreens.com slash Lex to claim a special offer of a free vitamin D3K2 for a year. If you listen to the Joe Rogan experience, you might've listened to him rant about how awesome vitamin D is for your immune system. So there you have it. So click the athleticgreens.com slash Lex in the description to get the free stuff and to support this podcast. This show sponsored by BetterHelp, spelled H-E-L-P, help. Check it out at betterhelp.com slash Lex. They figure out what you need and match you with a licensed professional therapist in under 48 hours. It's not a crisis line. It's not self-help. It's professional counseling done securely online. I'm a bit from the David Goggins line of creatures and so have some demons to contend with, usually on long runs or all nights full of self-doubt. I think suffering is essential for creation, but you can suffer beautifully in a way that doesn't destroy you. For most people, I think a good therapist can help in this. So it's at least worth a try. Check out their reviews. They're good. It's easy, private, affordable, available worldwide. You can communicate by text and your time and schedule a weekly audio and video session. Check it out at betterhelp.com slash Lex. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency in the context of the history of money is fascinating. I recommend Ascent of Money as a great book on this history. Davidson credits on ledgers started around 30,000 years ago, and the first decentralized cryptocurrency released just over 10 years ago. So given that history, cryptocurrency is still very much in its early days of development, but it's still aiming to and just might redefine the nature of money. So again, if you get Cash App from the App Store, Google Play, and use code LEXPODCAST, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with David Eagleman. You have a new book coming out on the changing brain. Can you give a high-level overview of the book? It's called LiveWired, by the way. Yeah, the thing is, we typically think about the brain in terms of the metaphors we already have, like hardware and software. That's how we build all our stuff. But what's happening in the brain is fundamentally so different. It's, so I coined this new term LiveWire, which is a system that's constantly reconfiguring itself physically as it learns and adapts to the world around it. It's physically changing. So LiveWire, meaning like hardware but changing? Yeah, exactly. Well, the hardware and the software layers are blended. And so, typically, engineers are praised for their efficiency and making something really clean and clear, like, okay, here's the hardware layer, then I'm going to run software on top of it. And there's all sorts of universality that you get out of a piece of hardware like that that's useful. But what the brain is doing is completely different. And I am so excited about where this is all going, because I feel like this is where our engineering will go. So currently, we build all our devices a particular way. But I can't tear half the circuitry out of your cell phone and expect it to still function. But you can do that with the brain. So just as an example, kids who are under about seven years old can get one half of their brain removed. It's called a hemispherectomy. And they're fine. They have a slight limp on the other side of their body, but they can function just fine that way. And this is generally true. Sometimes, children are born without a hemisphere. And their visual system rewires so that everything is on the single remaining hemisphere. What thousands of cases like this teach us is that it's a very malleable system that is simply trying to accomplish the tasks in front of it by rewiring itself with the available real estate. How much of that is a quirk or a feature of evolution? Like how hard is it to engineer? Because evolution took a lot of work. Trillions of organisms had to die for it to create this thing we have in our skull. Because you said you kind of look forward to the idea that we might be engineering our systems like this in the future, like creating live wire systems. How hard do you think is it to create systems like that? Great question. It has proven itself to be a difficult challenge. What I mean by that is, even though it's taken evolution a really long time to get where it is now, all we have to do now is peek at the blueprints. It's just three pounds, this organ, and we just figure out how to do it. But that's the part that I mean is a difficult challenge because, you know, there are tens of thousands of neuroscientists. We're all poking and prodding and trying to figure this out, but it's an extremely complicated system. But it's only going to be complicated until we figure out the general principles. Exactly like if you, you know, had a magic camera and you could look inside the nucleus of a cell and you'd see hundreds of thousands of things moving around or whatever, and then, you know, it takes Crick and Watson and say, oh, you know, you're just trying to maintain the order of the base pairs and all the rest is details. Then it simplifies it and we come to understand something. That was my goal in live wire, which I've written over 10 years, by the way, is to try to distill things down to the principles of what plastic systems are trying to accomplish. But to even just linger, you said it's possible to be born with just one hemisphere and you still are able to function. First of all, just to pause on that, I mean, that's kind of, that's amazing. That's, I don't know if people quite, I mean, you kind of hear things here and there. This is why I'm kind of, I'm really excited about your book is I don't know if there's definitive sort of popular sources to think about this stuff. I mean, there's a lot of, I think, from my perspective, what I heard is there's like been debates over decades about how much neuroplasticity there is in the brain and so on. And people have learned a lot of things and now it's converging towards people that are understanding this much more neuro, much more plastic than people realize. But just like linger on that topic, like how malleable is the hardware of the human brain? Maybe you said children at each stage of life. Yeah. So here's the whole thing. I think part of the confusion about plasticity has been that there are studies at all sorts of different ages and then people might read that from a distance and they think, oh, well, Fred didn't recover when half his brain was taken out. And so clearly you're not plastic, but then you do it with a child and they are plastic. And so part of my goal here was to pull together the tens of thousands of papers on this, both from clinical work and from, you know, all the way down to the molecular and understand what are the principles here. The principles are that plasticity diminishes. That's no surprise. By the way, we should just define plasticity. You know, it's the ability of a system to mold into a new shape and then hold that shape. That's why, you know, we make things that we call plastic because they are moldable and they can hold that new shape like a plastic toy or something. And so maybe we use, maybe we'll use a lot of terms that are synonymous. So something is plastic, something is malleable, changing, live wire, the name of the book is like synonymous. So I'll tell you, exactly right. But I'll tell you why I chose live wire instead of plasticity. So I use the term plasticity in the book, but sparingly, because that was a term coined by William James over 100 years ago. And he was, of course, very impressed with plastic manufacturing, that you could mold something in shape and then hold that. But that's not what's actually happening in the brain. It's constantly rewiring your entire life. You never hit an end point. The whole point is for it to keep changing. So even in the, you know, few minutes of conversation that we've been having, your brain is changing, my brain is changing. Next time I see your face, I will remember, oh yeah, like that time Lex and I sat together and we did these things. And I wonder if your brain will have like a Lex thing going on for the next few months. Like it'll stay there until you get rid of it. Because it was useful for now. Yeah, no, I'll probably never get rid of it. Let's say for some circumstance, you and I don't see each other for the next 35 years. When I run into you, I'll be like, oh yeah. That looks familiar. Yeah, yeah. And we, yeah, we sat down for a podcast back when there were podcasts. Yeah, right. Exactly. Back when we lived outside virtual reality. Yeah. Exactly. So you're- So you chose live wire over plastic. Exactly. Because plastic implies, I mean, it's the term that's used in the field. And so that's why we need to use it still for a while. But yeah, it implies something gets molded into shape and then holds that shape forever. But in fact, the whole system is completely changing. Then back to how malleable is the human brain at each stage of life. So what, just at a high level, is it malleable? So yes, and plasticity diminishes. But one of the things that I felt like I was able to put together for myself after reading thousands of papers on this issue is that different parts of the brain have different plasticity windows. So for example, with the visual cortex, that cements itself into place pretty quickly over the course of a few years. And I argue that's because of the stability of the data. In other words, what you're getting in from the world, you've got a certain number of angles, colors, shapes. It's essentially the world is visually stable. So that hardens around that data. As opposed to, let's say, the somatosensory cortex, which is the part that's taking information from your body, or the motor cortex right next to it, which is what drives your body. The fact is bodies are always changing. You get taller over time, you get fatter, thinner over time, you might break a leg and have to limp for a while, stuff like that. So because the data there is always changing, by the way, you might get on a bicycle, you might get a surfboard, things like that. Because the data is always changing, that stays more malleable. And when you look through the brain, you find that it appears to be how stable the data is determines how fast something hardens into place. But the point is different parts of the brain harden into place at different times. Do you think it's possible that depending on how much data you get on the different sensors, that it stays more malleable longer? So if you look at different cultures that experience, if you keep your eyes closed, or maybe you're blind, I don't know, but let's say you keep your eyes closed for your entire life, then the visual cortex might be much less malleable. The reason I bring that up is, maybe we'll talk about brain-computer interfaces a little bit down the line, but is the malleability a genetic thing, or is it more about the data, like you said, that comes in? So the malleability itself is a genetic thing. The big trick that Mother Nature discovered with humans is make a system that's really flexible, as opposed to most other creatures to different degrees. So if you take an alligator, it's born, its brain does the same thing every generation. If you compare an alligator 100,000 years ago to an alligator now, they're essentially the same. We, on the other hand, as humans, drop into a world with a half-baked brain, and what we require is to absorb the culture around us, and the language, and the beliefs, and the customs, and so on. That's what Mother Nature has done with us, and it's been a tremendously successful trick we've taken over the whole planet as a result of this. So that's an interesting point. I mean, just to linger on it, that, I mean, this is a nice feature. Like, if you were to design a thing to survive in this world, do you put it at age zero, already equipped to deal with the world in a, like, hard-coded way, or do you put it, do you make it malleable and just throw it in, take the risk that you're maybe going to die, but you're going to learn a lot in the process, and if you don't die, you'll learn a hell of a lot to be able to survive in the environment. So this is the experiment that Mother Nature ran, and it turns out that, for better or worse, we've won. I mean, yeah, we put other animals into zoos, and we, yeah, that's right. AI might do better. Okay, fair enough, that's true. And maybe what the trick Mother Nature did is just the stepping stone to AI, but. So that's a beautiful feature of the human brain, that it's malleable, but let's, on the topic of Mother Nature, what do we start with? Like, how blank is the slate? Ah, so it's not actually a blank slate. What it's, it's terrific engineering that's set up in there, but much of that engineering has to do with, okay, just make sure that things get to the right place. For example, like the fibers from the eyes getting to the visual cortex, or all this very complicated machinery in the ear getting to the auditory cortex, and so on. So things, first of all, there's that, and then what we also come equipped with is the ability to absorb language and culture and beliefs and so on. So you're already set up for that. So no matter what you're exposed to, you will, you will absorb some sort of language. That's the trick is how do you engineer something just enough that it's then a sponge that's ready to take in and fill in the blanks? How much of the malleability is hardware? How much is software? Is that useful at all in the brain? So like, what are we talking about? So there's like, there's neurons, there's synapses, and all kinds of different synapses, and there's chemical communication, like electrical signals, and there's chemical communication from the synapses. What I would say, the software would be the timing and the nature of the electrical signals, I guess, and the hardware would be the actual synapses. So here's the thing. This is why I really, if we can, I want to get away from the hardware and software metaphor, because what happens is as activity passes through the system, it changes things. Now, the thing that computer engineers are really used to thinking about is synapses, where two neurons connect. Of course, each neuron connects with 10,000 of its neighbors. But at a point where they connect, what we're all used to thinking about is the changing of the strength of that connection, the synaptic weight. But in fact, everything is changing. The receptor distribution inside that neuron, so that you're more or less sensitive to the neurotransmitter, then the structure of the neuron itself and what's happening there, all the way down to biochemical cascades inside the cell, all the way down to the nucleus. And for example, the epigenome, which is the, you know, these little proteins that are attached to the DNA that cause conformational changes that cause more genes to be expressed or repressed. All of these things are plastic. The reason that most people only talk about the synaptic weights is because that's really all we can measure well. And all this other stuff is really, really hard to see with our current technology. So essentially, that just gets ignored. But in fact, the system is plastic at all these different levels. And my way of thinking about this is an analogy to pace layers. So pace layers is a concept that Stuart Brand suggested about how to think about cities. So you have fashion, which changes rapidly in cities, you have governance, which changes more slowly, you have the structure, the buildings of a city, which changes more slowly, all the way down to nature. You've got all these different layers of things that are changing at different paces, at different speeds. I've taken that idea and mapped it onto the brain, which is to say you have some biochemical cascades that are just changing really rapidly when something happens, all the way down to things that are more and more cemented in there. And this is actually, this actually allows us to understand a lot about particular kinds of things that happen. For example, one of the oldest, probably the oldest rule in neurology is called Raibow's Law, which is that older memories are more stable than newer memories. So when you get old and demented, you'll be able to remember things from your young life, maybe you'll remember this podcast, but you won't remember what you did a month ago or a year ago. And this is a very weird structure, right? No other system works this way, where older memories are more stable than newer memories. But it's because through time, things get more and more cemented into deeper layers of the system. And so this is, I think, the way we have to think about the brain, not as, okay, you've got neurons, you've got synaptic weights, and that's it. So yeah, so the idea of liveware and livewired, it's like a, it's a gradual, yeah, it's a gradual spectrum between software and hardware. And so the metaphors completely doesn't make sense. Because like, when you talk about software and hardware, it's really hard lines. I mean, of course, software is unlike hardware, but even hardware, but like, so there's two groups, but in the software world, there's levels of abstractions, right? There's the operating system, there's machine code, and then it gets higher and higher levels. But somehow that's actually fundamentally different than the layers of abstractions in the layers of abstractions in the hardware. But in the brain, it's all like the same. And I love the city, the city metaphor. I mean, yeah, it's kind of mind blowing, because it's hard to know what to think about that. Like, if I were to ask the question, this is an important question for machine learning, is how does the brain learn? So essentially, you're saying that, I mean, it just learns on all of these different levels at all different paces. Exactly right. And as a result, what happens is as you practice something, you get good at something, you're physically changing the circuitry, you're adapting your brain around the thing that is relevant to you. So let's say you take up, do you know how to surf? Nope. Okay, great. So let's say you take up surfing. Yeah. Now at this age, what happens is, you know, you'll be terrible at first, you don't know how to operate your body, you don't know how to read the waves, things like that. And through time, you get better and better. What you're doing is you're burning that into the actual circuitry of your brain. You're of course conscious when you're first doing it, you're thinking about, okay, where am I doing? What's my body weight? But eventually, when you become a pro at it, you are not conscious of it at all. In fact, you can't even unpack what it is that you did. Think about riding a bicycle. You can't describe how you're doing it, you're just doing it, you're changing your balance when you come, you know, you do this to go to a stop. So this is what we're constantly doing is actually shaping our own circuitry based on what is relevant for us. Survival, of course, being the top thing that's relevant. But interestingly, especially with humans, we have these particular goals in our lives, computer science, neuroscience, whatever. And so we actually shape our circuitry around that. I mean, you mentioned this gets slower and slower with age, but is there, like, I've, I think I've read and spoken offline, even on this podcast with a developmental neurobiologist, I guess would be the right terminology, is like looking at the very early, like from embryonic stem cells to like, to the creation of the brain. And like, that's like, what, that's mind blowing how much stuff happens there. So it's very malleable at that stage. It's, and then, but after that, at which point does it stop being malleable? So that's the interesting thing is that it remains malleable your whole life. So even when you're an old person, you'll be able to remember new faces and names, you'll be able to learn new sorts of tasks. And thank goodness, because the world is changing rapidly in terms of technology and so on. I just sent my mother and Alexa and she, you know, figured out how to go in the settings, do the thing. And I was really, I was really impressed by that she was able to do it. So there are parts of the brain that remain malleable their whole life. The interesting part is that really your goal is to make an internal model of the world. Your goal is to say, okay, the brain is trapped in silence and darkness, and it's trying to understand how the world works out there, right? I love that image. Yeah, I guess it is. Yeah. You forget, you forget. It's like this lonely thing is sitting in its own container and trying to actually throw a few cents or figure out what the hell's going on. You know what I sometimes think about is that movie, The Martian with Matt Damon. The movie poster shows Matt Damon all alone on the red planet. And I think, God, that's actually what it's like to be inside your head and my head and anybody's head is that you're essentially on your own planet in there. And I'm essentially on my own planet. And everyone's got their own world where you've absorbed all of your experiences up to this moment in your life that made you exactly who you are and same for me and everyone. And we've got this very thin bandwidth of communication. And I'll say something like, oh, yeah, that tastes just like peaches. And you'll say, oh, I know what you mean. But the experience, of course, might be vastly different for us. But anyway, yes, so the brain is trapped in silence and darkness, each one of us. And what it's trying to do, this is the important part, it's trying to make an internal model of what's going on out there, as in how do I function in the world? How do I interact with other people? Do I say something nice and polite? Do I say something aggressive and mean? Do I, you know, all these things that it's putting together about the world. And I think what happens when people get older and older, it may not be that plasticity is diminishing. It may be that their internal model essentially has set itself up in a way where it says, okay, I've pretty much got a really good understanding of the world now, and I don't really need to change. Right? So when much older people find themselves in a situation where they need to change, they can actually are able to do it. It's just that I think this notion that we all have that plasticity diminishes as we grow older is in part because the motivation isn't there. But if you were 80, and you get fired from your job and suddenly had to figure out how to program a WordPress site or something, you'd figure it out. Got it. So the capability, the possibility of change is there. But let me ask the highest challenge, the interesting challenge to this plasticity, to this liveware system. If we could talk about brain-computer interfaces and Neuralink, what are your thoughts about the efforts of Elon Musk, Neuralink, PCI in general in this regard, which is adding a machine, a computer, the capability of a computer to communicate with the brain and the brain to communicate with a computer at the very basic applications and then like the futuristic kind of thoughts? Yeah. First of all, it's terrific that people are jumping into doing that because it's clearly the future. The interesting part is our brains have pretty good methods of interacting with technology. So maybe it's your fat thumbs on a cell phone or something, but, or maybe it's watching a YouTube video and getting into your eye that way. But we have pretty rapid ways of communicating with technology and getting data. So if you actually crack open the skull and go into the inner sanctum of the brain, you might be able to get a little bit faster, but I'll tell you a, I'm not so sanguine on the future of that as a business and I'll tell you why. It's because there are various ways of getting data in and out and an open head surgery is a big deal. Neurosurgeons don't want to do it because there's always risk of death and infection on the table. And also it's not clear how many people would say, I'm going to volunteer to get something in my head so that I can text faster, you know, 20% faster. So I think it's, you know, Mother Nature surrounds the brain with this armored, you know, bunker of the skull because it's a very delicate material. And there's an expression in neurosurgery about the brain is, you know, the person is never the same after you open up their skull. Now, whether or not that's true or whatever, who cares, but it's a big deal to do an open head surgery. So what I'm interested in is how can we get information in and out of the brain without having to crack the skull open? Got it. Without messing with the biological part, like directly connecting or messing with the intricate biological thing that we got going on that seems to be working. Yeah, exactly. And by the way, where Neuralink is going, which is wonderful, is going to be in patient cases. It really matters for all kinds of surgeries that a person needs, whether for Parkinson's or epilepsy or whatever. It's a terrific new technology for essentially sewing electrodes in there and getting more, higher density of electrodes. So that's great. I just don't think as far as the future of BCI goes, I don't suspect that people will go in and say, yeah, drill a hole in my head and do that. Well, it's interesting because I think there's a similar intuition, but say in the world of autonomous vehicles, that folks know how hard it is and it seems damn impossible. The similar intuition about, I'm sticking on the Elon Musk thing is just a good, easy example. Similar intuition about colonizing Mars. If you really think about it, it seems extremely difficult and almost, I mean, just technically difficult to a degree where you want to ask, is it really worth doing, worth trying? And then the same is applied with BCI. But the thing about the future is it's hard to predict. So the exciting thing to me with, so once it does, once if successful, it's able to help patients, it may be able to discover something very surprising about our ability to directly communicate with the brain. So exactly what you're interested in is figuring in is figuring out how to play with this malleable brain, but like help assist it somehow. I mean, it's such a compelling notion to me that we're now working on all these exciting machine learning systems that are able to learn from data. And then if we can have this other brain, that's a learning system that's live wired on the human side and then be able to communicate, it's like a self-play mechanism was able to beat the world champion at Go. So they can play with each other, the computer and the brain, like when you sleep. I mean, there's a lot of futuristic kind of things that it's just exciting possibilities. But I hear you, we understand so little about the actual intricacies of the communication of the brain that it's hard to find the common language. Well, interestingly, the technologies that have been built don't actually require the perfect common language. So for example, hundreds of thousands of people are walking around with artificial ears and artificial eyes, meaning cochlear implants or retinal implants. So this is, you take a essentially digital microphone, you slip an electrode strip into the inner ear and people can learn how to hear that way. Or you take an electrode grid and you plug it into the retina at the back of the eye and people can learn how to see that way. The interesting part is those devices don't speak exactly the natural biological language, they speak the dialect of Silicon Valley. And it turns out that as recently as about 25 years ago, a lot of people thought this was never going to work. They thought it wasn't going to work for that reason, but the brain figures it out. It's really good at saying, okay, look, there's some correlation between what I can touch and feel and hear and so on. And the data that's coming in or between, you know, I clap my hands and I have signals coming in there and it figures out how to speak any language. Oh, that's fascinating. So like, no matter if it's Neuralink, so directly communicating with the brain, or it's a smartphone or Google Glass, or the brain figures out the efficient way of communication. Well, exactly, exactly. And what I propose is the potato head theory of evolution, which is that all, you know, our eyes and nose and mouth and ears and fingertips, all this stuff is just plug and play. And the brain can figure out what to do with the data that comes in. And part of the reason that I think this is right, and I care so deeply about this, is when you look across the animal kingdom, you find all kinds of weird peripheral devices plugged in, and the brain figures out what to do with the data. And I don't believe that Mother Nature has to reinvent the principles of brain operation each time to say, oh, now I'm going to have heat pits to detect infrared. Now I'm going to have something to detect, you know, electroreceptors on the body. Now I'm going to detect something to pick up the magnetic field of the earth with cryptochromes in the eye. And so instead the brain says, oh, I got it. There's data coming in. Is that useful? Can I do something with it? Oh, great. I'm going to mold myself around the data that's coming in. It's kind of fascinating to think that we think of smartphones and all this new technology as novel. It's totally novel as outside of what evolution ever intended or like what nature ever intended. It's fascinating to think that like the entirety of the process of evolution is perfectly fine and ready for the smartphone and the internet. Like it's ready. It's ready to be valuable to that. And whatever comes to cyborgs, to virtual reality, we kind of think like, this is, you know, there's all these like books written about what's natural and we're like destroying our natural selves by like embracing all this technology. It's kind of, you know, we're probably not giving the brain enough credit. Like this thing is just fine with new tech. Oh, exactly. It wraps itself around. And by the way, wait till you have kids. You'll see the ease with which they pick up on stuff. And as Kevin Kelly said, technology is what gets invented after you're born. But the stuff that already exists when you're born, that's not even tech. That's just background furniture. Like the fact that the iPad exists for my son and daughter, like that's just background furniture. So, yeah, it's because we have this incredibly malleable system. It just absorbs whatever is going on in the world and learns what to do with it. So, do you think, just to linger for a little bit more, do you think it's possible to co-adjust? Like what kind of, you know, for the machine to adjust to the brain, for the brain to adjust to the machine. I guess that's what's already happening. Sure. That is what's happening. So, for example, when you put electrodes in the motor cortex to control a robotic arm for somebody who's paralyzed, the engineers do a lot of work to figure out, okay, what can we do with the algorithm here so that we can detect what's going on from these cells and figure out how to best program the robotic arm to move given the data that we're measuring from these cells. But also, the brain is learning too. So, you know, the paralyzed woman says, wait, I'm trying to grab this thing. And by the way, it's all about relevance. So, if there's a piece of food there and she's hungry, she'll figure out how to get this food into her mouth with the robotic arm because that is what matters. Well, that's, okay, first of all, that paints a really promising and beautiful, for some reason, really optimistic picture that, you know, our brain is able to adjust to so much. You know, so many things happened this year, 2020, that you think, like, how we're ever going to deal with it. And it's somehow encouraging and inspiring that, like, we're going to be okay. Well, that's right. I actually think, so 2020 has been an awful year for almost everybody in many ways. But the one silver lining has to do with brain plasticity, which is to say, we've all been on our, you know, on our gerbil wheels, we've all been in our routines. And, you know, as I mentioned, our internal models are all about how do you maximally succeed? How do you optimize your operation in this circumstance where you are, right? And then all of a sudden, bang, 2020 comes, we're completely off our wheels. We're having to create new things all the time and figure out how to do it. And that is terrific for brain plasticity because, and we know this because there are very large studies on older people who stay cognitively active their whole lives. Some fraction of them have Alzheimer's disease physically, but nobody knows that when they're alive. Even though their brain is getting chewed up with the ravages of Alzheimer's, cognitively, they're doing just fine. Why? It's because they're challenged all the time. They've got all these new things going on, all this novelty, all these responsibilities, chores, social life, all these things happening. And as a result, they're constantly building new roadways, even as parts degrade. And that's the only good news is that we are in a situation where suddenly we can't just operate like automaton anymore. We have to think of completely new ways to do things. And that's wonderful. I don't know why this question popped into my head. It's quite absurd, but are we going to be okay? You said this, it's a promising silver lining just from your own, because you've written about this and thought about this outside of maybe even the plasticity of the brain. But just this whole pandemic kind of changed the way it knocked us out of this hamster wheel like that of habit. A lot of people had to reinvent themselves. Unfortunately, and I have a lot of friends who either are ready or are going to lose their business. It's basically, it's taking the dreams that people have had and said, this dream, this particular dream you've had will no longer be possible. You have to find something new. Are we going to be okay? Yeah, we'll be okay in the sense that, I mean, it's going to be a rough time for many or most people, but in the sense that it is sometimes useful to find that what you thought was your dream was not the thing that you're going to do. This is obviously the plot in lots of Hollywood movies that someone says, I'm going to do this, and then that gets foiled and they end up doing something better. But this is true in life. I mean, in general, even though we plan our lives as best we can, it's predicated on our notion of, okay, given everything that's around me, this is what's possible for me next. But it takes 2020 to knock you off that where you think, oh, well, actually, maybe there's something I can be doing that's bigger, that's better. Yeah, you know, for me, one exciting thing, and I just talked to Grant Sanderson, I don't know if you know who he is, it's a 3Blue1Brown, it's a YouTube channel. If you see it, you would recognize it. He's like a really famous math guy. And he's a math educator. And he does these incredible, beautiful videos. And now I see sort of at MIT, folks are struggling to try to figure out, you know, if we do teach remotely, how do we do it effectively? So you have these world-class researchers and professors trying to figure out how to put content online that teaches people. And to me, a possible future of that is, you know, Nobel Prize winning faculty become YouTubers. Like, that to me is so exciting. Like what Grant said, which is like the possibility of creating canonical videos on the thing you're a world expert in. You know, there's so many topics that just, the world doesn't, you know, there's faculty, I mentioned Russ Tedrick, there's all these people in robotics that are experts in a particular beautiful field, on which there's only just papers. There's no popular book. There's no clean canonical video showing the beauty of a subject. And one possibility is they try to create that and share it with the world. This is the beautiful thing. This of course has been happening for a while already. I mean, for example, when I go and I give book talks, often what'll happen is some 13-year-old will come up to me afterwards and say something. And I'll say, my God, that was so smart. Like, how did you know that? And they'll say, oh, I saw it on a TED talk. Well, what an amazing opportunity. Here you got the best person in the world on subject X giving a 15-minute talk as beautifully as he or she can. And the 13-year-old just grows up with that. That's just the mother's milk, right? As opposed to when we grew up, you know, I had whatever homeroom teacher I had and, you know, whatever classmates I had. And hopefully that person knew what he or she was teaching and often didn't and, you know, just made things up. So the opportunity now has become extraordinary to get the best of the world. And the reason this matters, of course, is because obviously, back to plasticity, the way that we, the way our brain gets molded is by absorbing everything from the world, all of the knowledge and the data and so on that it can get, and then springboarding off of that. And we're in a very lucky time now because we grew up with a lot of just-in-case learning. So, you know, just in case you ever need to know these dates in Mongolian history, here they are. But what kids are growing up with now, like my kids, is tons of just-in-time learning. So as soon as they're curious about something, they ask Alexa, they ask Google Home, they get the answer right there in the context of the curiosity. The reason this matters is because for plasticity to happen, you need to care, you need to be curious about something. And this is something, by the way, that the ancient Romans had noted. They had outlined seven different levels of learning and the highest level is when you're curious about a topic. But anyway, so kids now are getting tons of just-in-time learning. And as a result, they're going to be so much smarter than we are. And we can already see that. I mean, my boy is eight years old, my girl is five. But I mean, the things that he knows are amazing. And he's learning so much more amazing because it's not just him having to do the rote memorization stuff that we did. Yeah, it's just fascinating what the brain, what young brains look like now, because of all those TED Talks just loaded in there. And there's also, I mean, a lot of people write kind of, there's a sense that our attention span is growing shorter. But it's complicated because, for example, most people, majority of people, it's the 80 plus percent of people listen to the entirety of these things, two, three hours for the podcast, long form podcasts are becoming more and more popular. So like, that's, it's all really giant, complicated mess. And the point is that the brain is able to adjust to it and somehow like, form a world view within this new medium of like information that we have. You have like these short tweets, and you have these three, four hour podcasts, and you have Netflix movie, I mean, it's just, it's adjusting to the entirety of things, just absorbing it and taking it all in. And then pops up COVID that forces us all to be home, and it all just adjusts and figures it out. Yeah, yeah, exactly. It's fascinating. You know, we've been talking about the brain as if it's something separate from the human that carries it a little bit. Like whenever you talk about the brain, it's easy to forget that that's like, that's us. Like, how much do you, how much is the whole thing, like predetermined? Like, how much is it already encoded in there? And how much is it? What's the it? How much is it? The actions, the decisions, the judgments, the... You mean like who you are? Who you are. Oh, yeah, yeah. Okay, great question. Right. So there used to be a big debate about nature versus nurture. And we now know that it's always both. You can't even separate them, because you come to the table with a certain amount of nature, for example, your whole genome, and so on. The experiences you have in the womb, like whether your mother is smoking or drinking, things like that, whether she's stressed on, those all influence how you're going to pop out of the womb. From there, everything is an interaction between all of your experiences and the nature. What I mean is, I think of it like a space-time cone, where you have, you drop in the world, depending on the experience that you have, you might go off in this direction, that direction, that direction, because there's interaction all the way. Your experiences determine what happens with the expression of your genes. So some genes get repressed, some get expressed, and so on. And you actually become a different person based on your experiences. There's a whole field called epigenomics, which is... or epigenetics, I should say, which is about the epigenome. And that is the, you know, sort of the layer that sits on top of the DNA and causes the genes to express differently. That is directly related to the experiences that you have. So if, you know, just as an example, they take rat pups, and you know, one group is sort of placed away from their parents, and the other group is groomed and licked and taken good care of, that changes their gene expression for the rest of their life. They go off in different directions in this space-time cone. So yeah, this is, of course, why it matters that we take care of children and pour money into things like education and good child care and so on for children broadly, because these formative years matter so much. So is there a free will? This is a great question. I apologize for the absurd high-level philosophical questions. No, no, these are my favorite kind of questions. Here's the thing. Here's the thing. We don't know. If you ask most neuroscientists, they'll say that we can't really think of how you would get free will in there, because as far as we can tell, it's a machine. It's a very complicated machine. Enormously sophisticated, 86 billion neurons, about the same number of glial cells. Each of these things is as complicated as the city of San Francisco. Each neuron in your head has the entire human genome in it. It's expressing millions of gene products. These are incredibly complicated biochemical cascades. Each one is connected to 10,000 of its neighbors, which means you have, you know, like half a quadrillion connections in the brain. So it's an incredibly complicated thing, but it is fundamentally appears to just be a machine. And therefore, if there's nothing in it that's not being driven by something else, then it seems it's hard to understand where free will would come from. So that's the camp that pretty much all of us fall into. But I will say our science is still quite young. And, you know, I'm a fan of the history of science. And the thing that always strikes me as interesting is when you look back at any moment in science, everybody believes something is true. And they just, they simply didn't know about, you know, what Einstein revealed or whatever. And so who knows? And they all feel like that we've, at any moment in history, they all feel like we've converged to the final answer. Exactly, exactly. Like all the pieces of the puzzle are there. And I think that's a funny illusion that's worth getting rid of. And in fact, this is what drives good science is recognizing that we don't have most of the puzzle pieces. So as far as the free will question goes, I don't know, at the moment, it seems, wow, it'd be really impossible to figure out how something else could fit in there. But, you know, a hundred years from now, our textbooks might be very different than they are now. I mean, could I ask you to speculate where do you think free will could be squeezed into there? Like what's that even, is it possible that our brain just creates kinds of illusions that are useful for us? Or like what, where could it possibly be squeezed in? Well, let me give a speculation answer to your very nice question, but, you know, don't, and the listeners to this podcast, don't quote me on this. Yeah, exactly. I'm not saying this is what I believe to be true, but let me just give an example. I give this, at the end of my book, Incognito. So the whole book of Incognito is about, you know, all the, what's happening in the brain. And essentially I'm saying, look, here's all the reasons to think that free will probably does not exist. But at the very end, I say, look, imagine that you are, you know, imagine that you're a Kalahari Bushman and you find a radio in the sand and you've never seen anything like this. And you look at this radio and you realize that when you turn this knob, you hear voices coming from it. There are voices coming from it. So being a, you know, a radio materialist, you try to figure out like, how does this thing operate? So you take off the back cover and you realize there's all these wires. And when you take out some wires, the voices get garbled or stop or whatever. And so what you end up developing is a whole theory about how this connection, this pattern of wires gives rise to voices. But it would never strike you that in distant cities, there's a radio tower and there's invisible stuff beaming. And that's actually the origin of the voices. And this is just necessary for it. So I mentioned this just as a speculation, say, look, how would we know what we know about the brain for absolutely certain is that if, when you damage pieces and parts of it, things get jumbled up. But how would you know if there's something else going on that we can't see, like electromagnetic radiation, that is what's actually generating this? Yeah. You paint a beautiful example of how totally, because we don't know most of how our universe works, how totally off base we might be with our science. Until, I mean, yeah, I mean, that's inspiring. That's beautiful. It's kind of terrifying. It's humbling. It's all of the above. And the important part, just to recognize is that of course, we're in the position of having massive unknowns. And we have, of course, the known unknowns, and that's all the things we're pursuing in our labs, trying to figure out that. But there's this whole space of unknown unknowns, things we haven't even realized we haven't asked yet. Let me kind of ask a weird, maybe a difficult question. Part of it has to do with, I've been recently reading a lot about World War II. I'm currently reading a book I recommend for people, which is, as a Jew, it's been difficult to read, but The Rise and Fall of the Third Reich. So let me just ask about the nature of genius, the nature of evil. If we look at somebody like Einstein, we look at Hitler, Stalin, modern day Jeffrey Epstein, just folks who through their life have done with Einstein, done works of genius, and with the others I mentioned, have done evil on this world. What do we think about that in a live wired brain? How do we think about these extreme people? Here's what I'd say. This is a very big and difficult question, but what I would say briefly on it is, first of all, I saw a cover of Time magazine some years ago, and it was a big sagittal slice of the brain, and it said something like, what makes us good and evil? And there was a little spot pointing to it, and there was a picture of Gandhi, and there was a little spot that was pointing to Hitler. And these Time magazine covers always make me mad, because it's so goofy to think that we're going to find some spot in the brain or something. Instead, the interesting part is, because we're live wired, we are all about the world and the culture around us. So somebody like Adolf Hitler got all this positive feedback about what was going on, and the crazier and crazier the ideas he had, he's like, let's set up death camps and murder a bunch of people and so on. Somehow he was getting positive feedback from that, and all these other people, they're all, you know, spun each other up. And you look at anything like, I mean, look at the, you know, the cultural revolution in China, or the, you know, the Russian Revolution, or things like this, where you look at these and you think, my God, how do people all behave like this? But it's easy to see groups of people spinning themselves up in particular ways where they all say, well, would I have thought this was right in a different circumstance? I don't know, but Fred thinks it's right, and Steve thinks it's right, everyone around me seems to think it's right. And so, part of the maybe downside of having a live wired brain is that you can get crowds of people doing things as a group. So it's interesting to, you know, we would pinpoint Hitler as saying, that's the evil guy. But in a sense, I think it was Tolstoy who said, the king becomes slave to the people. In other words, you know, Hitler was just a representation of whatever was going on with that huge crowd that he was surrounded with. So I only bring that up to say that it's, you know, it's very difficult to say what it is about this person's brain and that person's brain. He obviously got feedback for what he was doing. The other thing, by the way, about what we often think of as being evil in society is, my lab recently published some work on in-groups and out-groups, which is a very important part of this puzzle. So it turns out that we are very, you know, engineered to care about in-groups versus out-groups. And this seems to be like a really fundamental thing. So we did this experiment in my lab where we brought people in, we stick them in the scanner. And we, I don't know, and it's time if you know this, but we show them on the hand, sorry, we show them on the screen, six hands. And the computer goes around, randomly picks a hand, and then you see that hand gets stabbed with a syringe needle. So you actually see a syringe needle enter the hand and come out. And it's really, what that does is that triggers parts of the pain matrix, this areas in your brain that are involved in feeling physical pain. Now, the interesting thing is, it's not your hand that was stabbed. So what you're seeing is empathy. This is you seeing someone else's hand get stabbed, you feel like, oh God, this is awful, right? Okay. We contrast that, by the way, with somebody's hand getting poked at the Q-tip, which is, you know, looks visually the same, but it's, you don't have that same level of response. Now what we do is we label each hand with a one-word label, Christian, Jewish, Muslim, atheist, Scientologist, Hindu. And now, the computer goes around, picks a hand, stabs the hand. And the question is, how much does your brain care about all the people in your out group versus the one label that happens to match you? And it turns out for everybody across all religions, they care much more about their in-group than their out-group. And when I say they care, what I mean is, you get a bigger response from their brain. Everything's the same. It's the same hands. It's just a one-word label. You care much more about your in-group than your out-group. And I wish this weren't true, but this is how humans are. I wonder how fundamental that is, or if it's the emergent thing about culture. Like, if we lived alone, like if it's genetically built into the brain, like this longing for tribe. So I'll tell you, we addressed that. So here's what we did. There are two, actually, there are two other things we did as part of this study that I think matter for this point. One is, so, okay, so we show that you have a much bigger response. And by the way, this is not a cognitive thing. This is a very low level, basic response to seeing pain in somebody. Okay. Great study, by the way. Thanks. Thanks. What we did next is, we next have it where we say, okay, the year is 2025, and these three religions are now in a war against these three religions. And it's all randomized, right? But what you see is your thing, and you have two allies now against these others. And now what happens over the course of many trials is you see everybody gets stabbed at different times. And the question is, do you care more about your allies? And the answer is yes. Suddenly, people who a moment ago, you didn't really care when they got stabbed, now, simply with this one word thing that you're there now, your allies, you care more about them. But then what I wanted to do was look at how ingrained is this or how arbitrary is it? So we brought new participants in. And we said, here's a coin, toss the coin. If it's heads, you're an Augustinian. If it's tails, you're a Justinian. These are totally made up. Okay, so they toss it, they get whatever, we give them a band that says, you know, Augustinian on it, whatever tribe they're in now. And they get in the scanner, and they see a thing on the screen that says the Augustinians and Justinians are two warring tribes. Then you see a bunch of hands, some are labeled Augustinian, some are Justinian. And now you care more about whichever team you're on than the other team, even though it's totally arbitrary, and you know it's arbitrary, because you're the one who tossed the coin. So it's a state that's very easy to find ourselves in. In other words, just before walking in the door, they'd never even heard of Augustinian versus Justinian. And now their brain is representing it simply because they're told they're on this team. You know, now I did my own personal study of this. So once you're an Augustinian, that tends to be sticky, because I've been a Packers fan, a Packers fan my whole life. Now, I'm in Boston with like the Patriots. It's been tough going for my live wire brain to switch to the Patriots. So once you become – it's interesting, once the tribe is sticky. Yeah, I'll bet that's true. You know, we never tried that about saying, okay, now you're a Justinian, you were an Augustinian. We never saw how sticky it is. But there are studies of this, of monkey troops on some island. And what happens is they look at the way monkeys behave when they're part of this tribe and how they treat members of the other tribe of monkeys. And then what they do, I've forgotten how they do that exactly, but they end up switching a monkey so he ends up in the other troop. And very quickly, they end up becoming a part of that other troop and hating and behaving badly towards the original troop. These are fascinating studies, by the way. This is beautiful. In your book, you have a good light bulb joke. How many psychiatrists does it take to change a light bulb? Only one, but the light bulb has to want to change. Sorry. I'm a sucker for a good light bulb joke. Okay. So given, you know, I've been interested in psychiatry my whole life, just maybe tangentially. I've kind of early on dreamed to be a psychiatrist until I understood what it entails. But, you know, is there hope for psychiatry, for somebody else to help this live wire brain to adjust? Oh yeah. I mean, in the sense that, and this has to do with this issue about us being trapped on our own planet. Forget psychiatrists. Just think of like when you're talking with a friend and you say, oh, I'm so upset about this. And your friend says, hey, just look at it this way. You know, all we have access to under normal circumstances is just the way we're seeing something. And so it's super helpful to have friends and communities and psychiatrists and so on to help things change that way. So that's a psychiatrist sort of help to us. But more importantly, the role that psychiatrists have played is that there's this sort of naive assumption that we all come to the table with, which is that everyone is fundamentally just like us. And when you're a kid, you believe this entirely. But as you get older and you start realizing, okay, there's something called schizophrenia and that's a real thing. And to be inside that person's head is totally different than what it is to be inside my head. Or there's psychopathy. And to be inside the psychopath's head, he doesn't care about other people. He doesn't care about hurting other people. He's just doing what he needs to do to get what he needs. That's a different head. There's a million different things going on, and it is different to be inside those heads. This is where the field of psychiatry comes in. Now, I think it's an interesting question about the degree to which neuroscience is leaking into and taking over psychiatry and what the landscape will look like 50 years from now. It may be that psychiatry as a profession, you know, changes a lot or maybe goes away entirely and neuroscience will essentially be able to take over some of these functions. But it has been extremely useful to understand the differences between how people behave and why and what you can tell about what's going on inside their brain just based on observation of their behavior. This might be years ago, but I'm not sure. There's an Atlantic article you've written about moving away from a distinction between neurological disorders, quote unquote, quote unquote, brain problems, and psychiatric disorders or quote unquote, mind problems. So on that topic, how do you think about this gray area? Yeah, this is exactly the evolution that things are going is, you know, there's psychiatry and then there were guys and gals in labs poking cells and so on. Those were the neuroscientists. But yeah, I think these are moving together for exactly the reason you just cited. And where this matters a lot, the Atlantic article that I wrote was called The Brain on Trial, where this matters a lot is it's the legal system because the way we run our legal system now, and this is true everywhere in the world, is, you know, someone shows up in front of the judge's bench or let's say there's, you know, five people in front of the judge's bench and they've all committed the same crime. What we do because we feel like, hey, this is fair, is we say, all right, you're going to get the same sentence. You'll all get three years in prison or whatever it is. But in fact, brains can be so different. This guy's got schizophrenia, this guy's a psychopath, this guy's tweaked down on drugs and so on and so on, that it actually doesn't make sense to keep doing that. And what we do in this country more than anywhere in the world is we imagine that incarceration is a one-size-fits-all solution. And you may know we have the, America has the highest incarceration rate in the whole world in terms of the percentage of our population we put behind bars. So there's a much more refined thing we can do as neuroscience comes in and changes and has the opportunity to change the legal system, which is to say, this doesn't let anybody off the hook. It doesn't say, oh, it's not your fault and so on. But what it does is it changes the equation. So it's not about, hey, how blameworthy are you? But instead is about, hey, what do we do from here? What's the best thing to do from here? So if you take somebody with schizophrenia and you have them break rocks in the hot summer sun in a chain gang, that doesn't help the schizophrenia, that doesn't fix the problem. If you take somebody with a drug addiction who's in jail for being caught with two ounces of some illegal substance and you put them in prison, it doesn't actually fix the addiction, it doesn't help anything. Happily, what neuroscience and psychiatry bring to the table is lots of really useful things you can do with schizophrenia, with drug addiction, things like this. And that's why, so I don't know if you know this, but I run a national nonprofit called the Center for Science and Law. And it's all about this intersection of neuroscience and legal system. And we're trying to implement changes in every county, in every state. I'll just, without going down that rabbit hole, I'll just say one of the very simplest things to do is to set up specialized court systems where you have a mental health court that has judges and juries with expertise in mental illness. Because if you go, by the way, to a regular court and the person says, or the defense lawyer says, this person has schizophrenia, most of the jury will say, meh, I call bullshit on that. Why? Because they don't know about schiz- they don't know what it's about. And it turns out people who know about schizophrenia feel very differently as a juror than someone who happens not to know any about schizophrenia, they think it's an excuse. So, you have judges and juries with expertise in mental illness, and they know the rehabilitative strategies that are available. That's one thing. Having a drug court, where you have judges and juries with expertise in rehabilitative strategies and what can be done and so on. A specialized prostitution court and so on. All these different things. By the way, this is very easy for counties to implement this sort of thing. And this is, this is, I think, where this matters to get neuroscience into public policy. What's the process of injecting expertise into this? So, yeah, I'll tell you exactly what it is. A county needs to run out of money first. I've seen this happen over and over. So, what happens is a county has a completely full jail and they say, you know what, we need to build another jail. And then they realize, God, we don't have any money, we can't afford this, we've got too many people in jail. And that's when they turn to, God, we need something smarter. And that's when they set up specialized court systems. Oh, we're all function best when our back is against the wall. And that's what COVID is good for. It's because we've all had our routines and we are optimized for the things we do. And suddenly our backs are against the wall, all of us. Yeah, it's really, I mean, one of the exciting things about COVID. I mean, I'm a big believer in the possibility of what government can do for the people. And when it becomes too big of a bureaucracy, it starts functioning poorly, it starts wasting money. It's nice to, I mean, COVID reveals that nicely. And lessons to be learned about who gets elected and who goes into government. Hopefully this inspires talented young people to go into government, to revolutionize different aspects of it. Yeah, so that's the positive silver lining of COVID. I mean, I thought it'd be fun to ask you, I don't know if you're paying attention to the machine learning world and GPT-3. So the GPT-3 is this language model, this neural network that's able to, it has 175 billion parameters. So it's very large in its trained and unsupervised way on the internet. It just reads a lot of unstructured texts and it's able to generate some pretty impressive things. The human brain compared to that has about a thousand times more synapses. People get so upset when machine learning people compare the brain. And we know synapses are different. It was very different, very different. But what do you think about GPT-3? Here's what I think, here's what I think, a few things. What GPT-3 is doing is extremely impressive, but it's very different from what the brain does. So it's a good impersonator, but just as one example, everybody takes a passage that GPT-3 has written and they say, wow, look at this and it's pretty good, right? But it's already gone through a filtering process of humans looking at it and saying, okay, well that's crap. That's crap. Okay. Oh, here's what, here's a sentence that's pretty cool. Now here's the thing, human creativity is about absorbing everything around it and remixing that and coming up with stuff. So in that sense, we're sort of like GPT-3, you know, we're, we're remixing what we've gotten in before, but we also know, we also have very good models of what it is to be another human. And so, you know, I don't know if you speak French or something, but I'm not going to start speaking in French because then you'll say, wait, what are you doing? I don't understand you. Instead, everything coming out of my mouth is meant for your ears. I know what you'll understand. I know the vocabulary that you know and don't know. I know what parts you care about. That's a huge part of it. And so of all the possible sentences I could say, I'm navigating this thin bandwidth so that it's something useful for our conversation. Yeah. In real time, but also throughout your life. I mean, you're, you're co-evolving, we're co-evolving together. We're learning how to communicate together. Exactly. But this is the, this is what GPT-3 does not do. All it's doing is saying, okay, I'm going to take all these sentences and remix stuff and pop some stuff out. But it doesn't know how to make it so that you Lex will feel like, oh yeah, that's exactly what I needed to hear. That's the next sentence that I needed to know about for something. Well, of course it could be all the impressive results we'll see. The question is when, if you raise the number of parameters, whether it's going to be after some... It will not be. It will not be. No, raising more parameters won't... Here's the thing. It's not that I don't think neural networks can't be like the human brain, because I suspect they will be at some point 50 years, you know, who knows. But what we are missing in artificial neural networks is we've got this basic structure where you've got units and you've got synapses, they're connected. And that's great. And it's done incredibly mind-blowing, impressive things, but it's not doing the same algorithms as the human brain. So, when I look at my children, as little kids, you know, as infants, they can do things that no GPT-3 can do. They can navigate a complex room. They can navigate social conversation with an adult. They can lie. They can do a million things. They are active thinkers in our world and doing things. And this, of course, I mean, look, we totally agree on how incredibly awesome artificial neural networks are right now, but we also know the things that they can't do well, like, you know, like be generally intelligent, do all these different things. Reason about the world, efficiently learn, efficiently adapt. Exactly. But it's still the rate of improvement. It's, to me, it's possible that we'll be surprised. I agree. Possible we'll be surprised. But what I would assert, and I'm glad I'm getting to say this on your podcast so we can look back at this in two years and 10 years and so on, is that we've got to be much more sophisticated than units and synapses between them. Let me give you an example. And this is something I talk about in LiveWIRE, is despite the amazing impressiveness, mind-blowing impressiveness, computers don't have some basic things, artificial neural networks don't have some basic things that we like, caring about relevance, for example. So as humans, we are confronted with tons of data all the time, and we only encode particular things that are relevant to us. We have this very deep sense of relevance that I mentioned earlier is based on survival at the most basic level, but then all the things about my life and your life, what's relevant to you, that we encode. This is very useful. Computers at the moment don't have that. They don't even have a yen to survive and things like that. So we filter out a bunch of the junk we don't need. We're really good at efficiently zooming in on things we need. Again, could be argued, let me put on my Freud hat, maybe it's, I mean, that's our conscious mind. There's no reason that neural networks aren't doing the same kind of filtration. I mean, in the sense with GPT-3 is doing, so there's a priming step. It's doing an essential kind of filtration when you ask it to generate tweets from, I don't know, from an Elon Musk or something like that. It's doing a filtration of it's throwing away all the parameters it doesn't need for this task. And it's figuring out how to do that successfully. And then ultimately it's not doing a very good job right now, but it's doing a lot better job than we expected. But it won't ever do a really good job. And I'll tell you why. I mean, so let's say we say, hey, produce an Elon Musk tweet and we see like, oh, wow, it produced these three. That's great. But again, we're not seeing the 3000 that produced that didn't really make any sense. It's because it has no idea what it is like to be a human and all the things that you might want to say and all the reasons you wouldn't, like when you go to write a tweet, you might write something you think, nah, it's not going to come off quite right in this modern political climate or whatever, like, you know, you change things. So. And it somehow boils down to fear of mortality and all of these human things at the end of the day, all contained with that tweeting experience. Yeah. Well, interestingly, the fear of mortality is at the bottom of this, but you've got all these more things like, you know, oh, I want to, just in case the chairman of my department reads this, I want it to come off well there. Just in case my mom looks at this tweet, I want to make sure she, you know, and so on. So those are all the things that humans are able to sort of throw into the calculation. I mean. What it requires though is having a model of your chairman, having a model of your mother, having a model of, you know, the person you want to go on a date with who might look at your tweet and so on. All these things are, you're running models of what it is like to be them. So in terms of the structure of the brain, again, this may be going into speculation land. I hope you go along with me. Okay. So the brain seems to be intelligent and our AI systems aren't very currently. So where do you think intelligence arises in the brain? Like what is it about the brain? So if you mean where location-wise, it's no single spot. It would be equivalent to asking, I'm looking at New York City, where is the economy? The answer is you can't point to anywhere. The economy is all about the interaction of all of the pieces and parts of the city. And that's what, you know, intelligence, whatever we mean by that in the brain is interacting from everything going on at once. In terms of a structure. So we look, humans are much smarter than fish, maybe not dolphins, but dolphins are mammals, right? I assert that what we mean by smarter has to do with live wiring. So, what we mean when we say, oh, we're smarter is, oh, we can figure out a new thing and figure out a new pathway to get where we need to go. And that's because fish are essentially coming to the table with, you know, okay, here's the hardware, go, swim, mate, eat. But we have the capacity to say, okay, look, I'm going to absorb, oh, oh, but you know, I saw someone else do this thing and I read once that you could do this other thing and so on. Do you think there's, is there something, I know these are mysteries, but like architecturally speaking, what feature of the brain of the live wire aspect of it that is really useful for intelligence? So like, is it the ability of neurons to reconnect? Like, is there something, is there any lessons about the human brain you think might be inspiring for us to take into the artificial, into the machine learning world? Yeah. I'm actually just trying to write some up on this now called, you know, if you want to build a robot, start with the stomach. And what I mean by that, what I mean by that is a robot has to care, it has to have hunger, it has to care about surviving, that kind of thing. Here's an example. So the penultimate chapter of my book, I titled The Wolf and the Mars Rover. And I just look at this simple comparison of, you look at a wolf, it gets its leg caught in a trap. What does it do? It gnaws its leg off, and then it figures out how to walk on three legs. No problem. Now, the Mars Rover Curiosity got its front wheel stuck in some Martian soil, and it died. This project that cost billions of dollars died because it's got its wheels. Wouldn't it be terrific if we could build a robot that chewed off its front wheel and figured out how to operate with a slightly different body plan? That's the kind of thing that we want to be able to build. And to get there, what we need, the whole reason the wolf is able to do that is because its motor and somatosensory systems are live wired. So it says, oh, you know what? Turns out we've got a body plan that's different than what I thought a few minutes ago. But I have a yen to survive, and I care about relevance, which in this case is getting to food, getting back to my pack, and so on. So I'm just going to figure out how to operate with this. Oh, whoops, that didn't work. Oh, okay, I'm kind of getting it to work. But the Mars Rover doesn't do that. It just says, oh, geez, I was pre-programmed to have four wheels, now I have three, I'm screwed. Yeah, you know, I don't know if you're familiar with a philosopher named Ernest Becker. He wrote a book called Denial of Death. And there's a few psychologists, Sheldon Solomon, I think, I just spoke with him on his podcast, who developed terror management theory, which is, like, Ernest Becker is a philosopher that basically said that fear of mortality is at the core of it. And so I don't know, it sounds compelling as an idea that we're, I mean, that all of the civilization we've constructed is based on this, but it's- I'm familiar with his work. Here's what I think. I think that, yes, fundamentally, this desire to survive is at the core of it, I would agree with that. But how that expresses itself in your life ends up being very different. The reason you do what you do is, I mean, you could list the hundred reasons why you chose to write your tweet this way and that way, and it really has nothing to do with the survival part. It has to do with, you know, trying to impress fellow humans and surprise them and say something. Yeah, so many things built on top of each other. But it's fascinating to think that in artificial intelligence systems, we want to be able to somehow engineer this drive for survival, for immortality. I mean, because as humans, we're not just about survival, we're aware of the fact that we're going to die, which is a very kind of- we're aware like- Most people aren't, by the way. Aren't? Aren't. Confucius said, he said, each person has two lives. The second one begins when you realize that you have just one. But most people, it takes a long time for most people to get there. I mean, you could argue this kind of Freudian thing, which Ernst Becker argues is, they actually figured it out early on, and the terror they felt was like the reason it's been suppressed. The reason most people, when I ask them about whether they're afraid of death, they basically say no. They basically say like, I'm afraid I won't get, like, submit the paper before I die. Like, they kind of see death as a kind of inconvenient deadline for a particular set of- like a book you're writing. As opposed to like, what the hell, this thing ends. At any moment, like, most people, as I've encountered, do not meditate on the idea that, like, right now you could die. Like, right now. Like, in the next five minutes, it could be all over. And, you know, meditate on that idea. I think that somehow brings you closer to, like, the core of the motivations and the core of the human cognition. I think it might be the core, but like I said, it is not what Freud says day to day. There's so many stuff on top of it. Yeah, there's so many things on top of it. But it is interesting. I mean, as the ancient poet said, death whispers at my ear, live for I come. So, it's, it is certainly motivating when we think about that. Okay, I've got some deadline. I don't know exactly what it is, but I better make stuff happen. It is motivating, but I don't think, I mean, I know for just speaking for me personally, that's not what motivates me day to day. It's instead, oh, I want to get this, you know, program up and running before this, or I want to make sure my co-author isn't mad at me because I haven't gotten this in, or I don't want to miss this grant deadline, or, you know, whatever the thing is. Yeah, definitely. It's too distant in a sense. Nevertheless, it is good to reconnect. But for the AI systems, none of that is there. Like a neural network does not fear its mortality. And that seems to be somehow fundamentally missing the point. I think that's missing the point, but I wonder, it's an interesting speculation about whether you can build an AI system that is much closer to being a human without the mortality and survival piece, but just the thing of relevance, just I care about this versus that. Right now, if you have a robot roll into the room, it's going to be frozen because it doesn't have any reason to go there versus there. It doesn't have any particular set of things about this is how I should navigate my next move because I want something. Yeah, there's a, that's the thing about humans is they seem to generate goals. They're like, you said live wired. I mean, it's very flexible in terms of the goals and creative in terms of the goals we generate when we enter a room. You show up to a party without a goal usually, and then you figure it out along the way. Yes, but this goes back to the question about free will, which is when I walk into the party, if you rewound it 10,000 times, would I go and talk to that couple over there versus that person? Like, I might do this exact thing, but I might not. I might not. Like, I might do this exact same thing every time because I've got some goal stack and I think, okay, well, at this party, I really want to meet these kinds of people or I feel awkward or I, whatever, you know, whatever my goals are. By the way, so there was something that I meant to mention earlier, if you don't mind going back, which is this, when we were talking about BCI. So I don't know if you know this, but what I'm spending 90% of my time doing now is running a company. Do you know about this? Yes. I wasn't sure what the company is involved in. Right. So, okay. Can you talk about it? Yeah. Yeah. So when it comes to the future of BCI, you know, you can put stuff into the brain invasively, but my interest has been how you can get data streams into the brain non-invasively. So I run a company called Neosensory and what we build is this little wristband. We've built this in many different form factors. Oh, wow. That's it? Yeah, this is it. And it's got these vibratory motors in it. So these things, as I'm speaking, for example, it's capturing my voice and running algorithms and then turning that into patterns of vibration here. So people who are deaf, for example, learn to hear through their skin. So the information is getting up to their brain this way and they learn how to hear. So it turns out on day one, people are pretty good, like better than you'd expect at being able to say, oh, that's weird. Was that a dog barking? Was that a baby crying? Was that a door knock, a doorbell? Like people are pretty good at it, but with time they get better and better and what it becomes is a new qualia. In other words, a new subjective internal experience. So on day one, they say, whoa, what was it? Oh, that was the dog barking. But by, you know, three months later, they say, oh, there's a dog barking somewhere. Oh, there's the dog. That's fascinating. And by the way, that's exactly how you learn how to use your ears. So what you, of course, you remember this, but when you were an infant, all you have are, you know, your eardrum vibrating causes spikes to go down your auditory nerves and impinging your, you know, auditory cortex. Your brain doesn't know what those mean automatically, but what happens is you learn how to hear by looking for correlations. You know, you clap your hands as a baby, you know, you look at your mother's mouth moving and that correlates with what's going on there. And eventually your brain says, all right, I'm just going to summarize this as an internal experience, as a conscious experience. And that's exactly what happens here. The weird part is that you can feed data into the brain, not through the ears, but through any channel that gets there. As long as the information gets there, your brain figures out what to do with it. That's fascinating. Like expanding the set of sensors, it could be arbitrarily, could expand arbitrarily, which is fascinating. Well, exactly. And by the way, the reason I use this skin, you know, there's all kinds of cool stuff going on in the AR world with glasses and with it. But the fact is your eyes are overtaxed and your ears are overtaxed and you need to be able to see and hear other stuff. But you're covered with the skin, which is this incredible computational material with which you can feed information. And we don't use our skin for much of anything nowadays. My joke in the lab is that I say we don't call this the waste for nothing, because originally we built this as a vest and, you know, you're passing in all this information that way. And what I'm doing here with the deaf community is what's called sensory substitution, where I'm capturing sound and I'm just replacing the ears with the skin and that works. One of the things I talk about in LiveWire is sensory expansion. So what if you took something like your visual system, which picks up on a very thin slice of the electromagnetic spectrum, and you could see infrared or ultraviolet. So we've hooked that up, infrared and ultraviolet detectors, and, you know, I can feel what's going on. So just as an example, the first night I built the infrared, one of my engineers built it, the infrared detector. I was walking in the dark between two houses and suddenly I felt all this infrared radiation. I was like, where does that come from? And I just followed my wrist and I found an infrared camera, night vision camera. But like, you know, I immediately, oh, there's that thing there. Of course, I would have never seen it, but now it's just part of my reality. And then, of course, what I'm really interested in is sensory addition. What if you could pick up on stuff that isn't even part of what we normally pick up on, like, you know, like the magnetic field of the earth or Twitter or stock market or things like that. Or the, I don't know, some weird stuff like the moods of other people or something like that. Sure. Now what you need is a way to measure that. So as long as there's a machine that can measure it, it's easy, it's trivial to feed this in here and you come to be, it comes to be part of your reality. It's like you have another sensor. And that kind of thing is without doing like, if you look at Neuralink, without, I forgot how you put it, but it was eloquent, you know, without getting, cutting into the brain, basically. Yeah, exactly. Exactly. So this costs at the moment, $399. That's not going to kill you. Yeah, it's not going to kill you. It's, you just put it on and when you're done, you take it off. Yeah. And so, and the name of the company, by the way, is Neo Sensory for new senses, because the whole idea is, beautiful. As I said, you know, you come to the table with certain plug and play devices and then that's it. Like I can pick up on this little bit of the electromagnetic radiation, I can pick up on this little frequency band for hearing and so on. But I'm stuck there and there's no reason we have to be stuck there. We can expand our umwelt by adding new senses. Yeah. What's umwelt? Oh, I'm sorry. The umwelt is the slice of reality that you pick up on. So each animal has its own hell of a word. Umwelt. Yeah, exactly. I'm sorry, I forgot to define it before. It's such an important concept, which is to say, for example, if you are a tick, you pick up on butyric gas, you pick up on odor and you pick up on temperature. That's it. That's how you construct your reality is with those two sensors. If you are a blind echolocating bat, you're picking up on air compression waves coming back, you know, echolocation. If you are the black ghost knife fish, you're picking up on changes in the electrical field around you with electro reception. That's how they swim around and tell there's a rock there and so on. But that's all they pick up on. That's their umwelt. That's the signals they get from the world from which to construct their reality. And they can be totally different umwelts. That's fascinating. And so our human umwelt is, you know, we've got little bits that we can pick up on. One of the things I like to do with my students is talk about, imagine that you are a bloodhound dog, right? You are a bloodhound dog with a huge snout with 200 million scent receptors in it and your whole world is about smelling. You've got slits in your nostrils, like big nosefuls of air and so on. Do you have a dog? Nope, used to. Used to. Okay, right. So, you know, you walk your dog around and your dog is smelling everything. The whole world is full of signals that you do not pick up on. And so imagine if you were that dog and you looked at your human master and thought, my god, what is it like to have the pitiful little nose of a human? How could you not know that there's a cat 100 yards away or that your friend was here six hours ago? And so the idea is because we're stuck in our umwelt, because we have this little pitiful nose, is we think, okay, well, yeah, we're seeing reality. But you can have very different sorts of realities depending on the peripheral plug and play devices you're equipped with. It's fascinating to think that, like, if we're being honest, probably our umwelt is, you know, some infinitely tiny percent of the possibilities of how you can sense quote unquote reality. Even if you could, I mean, there's a guy named Donald Hoffman, yeah, who basically says we're really far away from reality in terms of our ability to sense anything. We're almost like we're floating out there that's almost like completely detached from the actual physical reality. It's fascinating that we can have extra senses that could help us get a little bit closer. Exactly. And by the way, this has been the fruits of science is realizing, like, for example, you open your eyes and there's the world around you, right? But of course, depending on how you calculate it, it's less than a 10 trillionth of the electromagnetic spectrum that we could call visible light. The reason I say it depends because, you know, it's actually infinite in all directions presumably. Yeah, and so that's exactly that. And then science allows you to actually look into the rest of it. Exactly. Sort of understanding how big the world is out there. And the same with the world of really small and the world of really large. Exactly. That's beyond our ability to sense. Exactly. And so the reason I think this kind of thing matters is because we now have an opportunity for the first time in human history to say, okay, well, I'm just going to include other things in my umbel. So I'm going to include infrared radiation and have a direct perceptual experience of that. And so I'm very, you know, I mean, so, you know, I've given up my lab and I run this company 90% of my time now. That's what I'm doing. I still teach at Stanford and I'm, you know, teaching courses and stuff like that. But this is like, this is your passion. The fire is on this. Yeah, I feel like this is the most important thing that's happening right now. I mean, I obviously I think that, cause that's what I'm devoting my time in my life too. But, um. I mean, it's a brilliant set of ideas. It certainly is like, it's a step in a very vibrant future, I would say. Like the possibilities there are endless. Exactly. So if you ask what I think about Neuralink, I think it's amazing what those guys are doing and working on, but I think it's not practical for almost everybody. For example, for people who are deaf, they buy this and, you know, every day we're getting tons of emails and tweets and whatever from people saying, wow, I picked up on this. And then I had no idea that was a, I didn't even know that was happening out there. And they're coming to hear. By the way, this is, you know, less than a 10th of the price of a hearing aid and like 250 times less than a cochlear implant. That's amazing. People love hearing about what, you know, brilliant folks like yourself could recommend in terms of books. Of course, you're an author of many books. So I'll, in the introduction, mention all the books you've written. People should definitely read Livewired. I've gotten a chance to read some of it. It's amazing. But is there three books, technical, fiction, philosophical, that had an impact on you when you were younger or today? And books, perhaps some of which you would want to recommend that others read? You know, as an undergraduate, I majored in British and American literature. That was my major because I love literature. I grew up with literature. My father had these extensive book shelves. And so I grew up in the mountains in New Mexico. And so that was mostly where I spent my time was reading books. But, you know, I love, you know, Faulkner, Hemingway. I love many South American authors, Gabriel Garcia Marquez and Italo Calvino. I would actually recommend Invisible Cities. I just, I loved that book. By? Italo Calvino, sorry. It's a book of fiction. Anthony Doar wrote a book called All the Light We Cannot See, which actually was inspired by Incognito by exactly what we were talking about earlier about how you can only see a little bit of the, what we call visible light in the electromagnetic radiation. I wrote about this in Incognito and then he reviewed Incognito for the Washington Post. Oh, no, that's awesome. And then he wrote this book called, the book has nothing to do with that, but that's where the title comes from. All the Light We Cannot See is about the rest of the spectrum. But that's an absolutely gorgeous book. That's a book of fiction. Yeah, it's a book of fiction. One that people are surprised. What's it about? It takes place during World War II about these two young people, one of whom is blind. Anything else? So, what I need, so you mentioned Hemingway. I mean. Old Man and the Sea. What's your favorite? Snows of Kilimanjaro. It's a collection of short stories I love. As far as nonfiction goes, I grew up with Cosmos, both watching the PBS series and then reading the book. And that influenced me a huge amount in terms of what I do. From the time I was a kid, I felt like I want to be Carl Sagan. That's what I loved. And in the end, I studied space physics for a while as an undergrad, but then in my last semester, discovered neuroscience. Last semester and I just thought, well, I'm hooked on that. So, the Carl Sagan of the brain. That was my aspiration. Is the aspiration. I mean, you're doing an incredible job of it. So, you open the book Livewired with a quote by Heidegger, every man is born as many men and dies as a single one. Well, what do you mean? I'll tell you what I meant by it. I'll tell you. So, he had his own reason why he was writing that, but I meant this in terms of brain plasticity, in terms of Livewired, which is this issue that I mentioned before about this, you know, this cone, the space-time cone that we are in, which is that when you dropped into the world, you Lex had all this different potential. You could have been a great surfer or a great chess player, or you could have been thousands of different men when you grew up. But what you did is things that were not your choice and your choice along the way, you know, you ended up navigating a particular path and now you're exactly who you are. You still have lots of potential, but the day you die, you will be exactly Lex. You will be that one person. Yeah. So, in that context, I mean, first of all, it's just a beautiful, it's a humbling picture, but it's a beautiful one because it's all the possible trajectories and you pick one, you walk down that road, and it's the Robert Frost poem. But on that topic, let me ask the biggest and the most ridiculous question. So, in this Livewired brain, when we choose all these different trajectories and end up with one, what's the meaning of it all? What's, is there a why here? What's the meaning of life, David Engelman? I mean, this is the question that everyone has attacked from their own Livewired point of view, by which I mean, culturally, if you grew up in a religious society, you have one way of attacking that question. So, if you grew up in a secular scientific society, you have a different way of attacking that question. Obviously, I don't know. There's no... I abstain on that question. I mean, I think one of the fundamental things, I guess, in that, in all those possible trajectories is you're always asking. I mean, that's the act of asking what the heck is this thing for is equivalent to, or at least runs in parallel to all the choices that you're making. Because it's kind of, that's the underlying question. Well, that's right. And by the way, you know, this is the interesting thing about human psychology, you know, we've got all these layers of things at which we can ask questions. And so, if you keep asking yourself the question about, what is the optimal way for me to be spending my time? What should I be doing? What charity should I get involved with? If you're asking those big questions, that steers you appropriately. If you're the type of person who never asks, hey, is there something better I could be doing with my time, then presumably, you won't optimize whatever it is that is important to you. So, you've, I think, just in your eyes, in your work, there's a passion that just is obvious, and it's inspiring, it's contagious. What, if you were to give advice to us, a young person today, in the crazy chaos that we live today, about life, about how to, how to, how to discover their passion. Is there some words that you could give? First of all, I would say the main thing for a young person is stay adaptable. And this is back to this issue of why COVID is useful for us, because it forces us off our tracks. The fact is, the jobs that will exist 20 years from now, we don't even have names for, we can't even imagine the jobs that are going to exist. And so, when young people that I know go into college, and they say, hey, what should I major in? And so on. College is and should be less and less vocational, as in, oh, I'm going to learn how to do this, and then I'm going to do that the rest of my career. The world just isn't that way anymore with the exponential speed of things. So, the important thing is learning how to learn, learning how to be live-wired and adaptable. That's really key. And what I tell, what I advise young people, what I talk to them is, you know, what you digest, that's what gives you the raw storehouse of things that you can remix and be creative with. And so, eat broadly and widely. And obviously, this is the wonderful thing about the internet world we live in now, is you kind of can't help it. You're constantly, whoa, you go down some molehole of Wikipedia and you think, oh, I didn't even realize that was a thing. I didn't know that existed. And so... Embrace that. Embrace that. Yeah, exactly. And what I tell people is, just always do a gut check about, okay, I'm reading this paper and yeah, I think that, but this paper, wow, that really, I really cared about that. I tell them just keep a real sniff out for that. And when you find those things, keep going down those paths. Yeah, don't be afraid. I mean, that's one of the challenges and the downsides of having so many beautiful options is that sometimes people are a little bit afraid to really commit. But that's very true. If there's something that just sparks your interest, your interest and passion, just run with it. I mean, it goes back to the Heidegger quote. I mean, we only get this one life and that trajectory, it doesn't last forever. So just if something sparks your imagination, your passion, just run with it. Yeah, exactly. I don't think there's a more beautiful way to end it, David. It's a huge honor to finally meet you. Your work is inspiring so many people. I've talked to so many people who are passionate about neuroscience, about the brain, even outside that read your book. So I hope you keep doing so. I think you're already there with Carl Sagan. I hope you continue growing. Yeah, it was an honor talking with you today. Thanks so much. Great. You too, Lex. Wonderful. Thanks for listening to this conversation with David Eagleman. And thank you to our sponsors, Athletic Greens, BetterHelp, and Cash App. Click the sponsor links in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now let me leave you with some words from David Eagleman in his book, Sum, 40 Tales from the Afterlives. Imagine for a moment that we're nothing but the product of billions of years of molecules coming together and ratcheting it up through natural selection. That we're composed only of highways of fluids and chemicals sliding along roadways within billions of dancing cells. That trillions of synaptic connections hum in parallel. That this vast egg-like fabric of micro-thin circuitry runs algorithms undreamt of in modern science. And that these neural programs give rise to our decision-making, loves, desires, fears, and aspirations. To me, understanding this would be a numinous experience, better than anything ever proposed in any holy text. Thank you for listening, and hope to see you next time.

https://youtu.be/386s-y1aRRo

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Jitendra Malik: Computer Vision | Lex Fridman Podcast #110

The following is a conversation with Jitendra Malik, a professor at Berkeley and one of the seminal figures in the field of computer vision, the kind before the deep learning revolution and the kind after. He has been cited over 180,000 times and has mentored many world-class researchers in computer science. Quick summary of the ads. Two sponsors, one new one which is BetterHelp and an old goodie, ExpressVPN. Please consider supporting this podcast by going to betterhelp.com slash Lex and signing up at expressvpn.com slash LexPod. Click the links, buy the stuff. It really is the best way to support this podcast and the journey I'm on. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcast, support it on Patreon or connect with me on Twitter at Lex Friedman, however the heck you spell that. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This show is sponsored by BetterHelp, spelled H-E-L-P, help. Check it out at betterhelp.com slash Lex. They figure out what you need and match you with a licensed professional therapist in under 48 hours. It's not a crisis line, it's not self-help, it's professional counseling done securely online. I'm a bit from the David Goggins line of creatures as you may know and so have some demons to contend with, usually on long runs or all nights working, forever impossibly full of self-doubt. It may be because I'm Russian, but I think suffering is essential for creation. But I also think you can suffer beautifully in a way that doesn't destroy you. For most people, I think a good therapist can help in this, so it's at least worth a try. Check out their reviews, they're good, it's easy, private, affordable, available worldwide. You can communicate by text, stay in your time and schedule weekly audio and video sessions. I highly recommend that you check them out at betterhelp.com slash Lex. This show is also sponsored by ExpressVPN. Get it at expressvpn.com slash LexPod to support this podcast and to get an extra three months free on a one-year package. I've been using ExpressVPN for many years. I love it. I think ExpressVPN is the best VPN out there. They told me to say it, but it happens to be true. It doesn't log your data, it's crazy fast, and it's easy to use. Literally just one big sexy power on button. Again, for obvious reasons, it's really important that they don't log your data. It works on Linux and everywhere else too, but really, why use anything else? Shout out to my favorite flavor of Linux, Ubuntu Mate 2004. Once again, get it at expressvpn.com slash LexPod to support this podcast and to get an extra three months free on a one-year package. And now here's my conversation with Jitendra Malik. In 1966, Seymour Pappert at MIT wrote up a proposal called the Summer Vision Project to be given, as far as we know, to 10 students to work on and solve that summer. So that proposal outlined many of the computer vision tasks we still work on today. Why do you think we underestimate, and perhaps we did underestimate, and perhaps still underestimate how hard computer vision is? Because most of what we do in vision, we do unconsciously or subconsciously. In human vision. In human vision. So that gives us this, that effortlessness gives us the sense that, oh, this must be very easy to implement on a computer. Now, this is why the early researchers in AI got it so wrong. However, if you go into neuroscience or psychology of human vision, then the complexity becomes very clear. The fact is that a very large part of the cerebral cortex is devoted to visual processing. I mean, and this is true in other primates as well. So once we looked at it from a neuroscience or psychology perspective, it becomes quite clear that the problem is very challenging and it will take some time. You said the higher level parts are the harder parts? I think vision appears to be easy because most of what visual processing is subconscious or unconscious. So we underestimate the difficulty. Whereas when you are proving a mathematical theorem or playing chess, the difficulty is much more evident because it is your conscious brain which is processing various aspects of the problem solving behavior. Whereas in vision, all this is happening, but it's not in your awareness. It's operating below that. But it still seems strange. Yes, that's true. But it seems strange that as computer vision researchers, for example, the community broadly, time and time again, makes the mistake of thinking the problem is easier than it is. Or maybe it's not a mistake. We'll talk a little bit about autonomous driving, for example, how hard of a vision task that is. Do you think, I mean, is it just human nature or is there something fundamental to the vision problem that we underestimate? We're still not able to be cognizant of how hard the problem is. Yeah, I think in the early days it could have been excused because in the early days all aspects of AI were regarded as too easy. But I think today it is much less excusable. And I think why people fall for this is because of what I call the fallacy of the successful first step. There are many problems in vision where getting 50% of the solution you can get in one minute, getting to 90% can take you a day, getting to 99% may take you five years and 99.99% may be not in your lifetime. I wonder if that's unique to vision. It seems that language people are not so confident about, so natural language processing. People are a little bit more cautious about our ability to solve that problem. I think for language people intuit that we have to be able to do natural language understanding. For vision, it seems that we're not cognizant or we don't think about how much understanding is required. It's probably still an open problem. But in your sense, how much understanding is required to solve vision? Put another way, how much something called common sense reasoning is required to really be able to interpret even static scenes? Yeah. Vision operates at all levels and there are parts which can be solved with what we could call maybe peripheral processing. In the human vision literature, there used to be these terms, sensation, perception, and cognition, which roughly speaking referred to the front end of processing, middle stages of processing, and higher level of processing. I think they made a big deal out of this and they wanted to study only perception and then dismiss certain problems as being quote cognitive. But really, I think these are artificial divides. The problem is continuous at all levels and there are challenges at all levels. The techniques that we have today, they work better at the lower and mid levels of the problem. I think the higher levels of the problem, quote the cognitive levels of the problem, are there and in many real applications, we have to confront them. Now, how much that is necessary will depend on the application. For some problems, it doesn't matter. For some problems, it matters a lot. So, I am, for example, a pessimist on fully autonomous driving in the near future. The reason is because I think there will be that 0.01% of the cases where quite sophisticated cognitive reasoning is called for. However, there are tasks where you can, first of all, they are much more, they are robust. So, in the sense that error rates, error is not so much of a problem. For example, let's say you're doing image search. You're trying to get images based on some visual description. We are very tolerant of errors there, right? I mean, when Google image search gives you some images back and a few of them are wrong, it's okay. It doesn't hurt anybody. There's no, there's not a matter of life and death, but making mistakes when you are driving at 60 miles per hour and you could potentially kill somebody is much more important. So, just for the fun of it, since you mentioned, let's go there briefly about autonomous vehicles. So, one of the companies in the space, Tesla, is with Andrej Karpathy and Elon Musk are working on a system called Autopilot, which is primarily a vision-based system with eight cameras and basically a single neural network, a multitask neural network. They call it HydroNet, multiple heads. So, it does multiple tasks, but is forming the same representation at the core. Do you think driving can be converted in this way to purely a vision problem and then solved with learning? Or even more specifically in the current approach, what do you think about what Tesla Autopilot team is doing? So, the way I think about it is that there are certainly subsets of the visual-based driving problem, which are quite solvable. So, for example, driving in freeway conditions is quite a solvable problem. I think there were demonstrations of that going back to the 1980s by someone called Ernst Tickmans in Munich. In the 90s, there were approaches from Carnegie Mellon, there were approaches from our team at Berkeley. In the 2000s, there were approaches from Stanford and so on. So, autonomous driving in certain settings is very doable. The challenge is to have an autopilot work under all kinds of driving conditions. At that point, it's not just a question of vision or perception, but really also of control and dealing with all the edge cases. So, where do you think most of the difficult cases, to me, even the highway driving is an open problem because it applies the same 50-90-95-99 rule, where the first step, the fallacy of the first step, I forget how you put it, we fall victim to. I think even highway driving has a lot of elements because to solve autonomous driving, you have to completely relinquish the help of a human being. You're always in control. So, you're really going to feel the edge cases. So, I think even highway driving is really difficult. But in terms of the general driving task, do you think vision is the fundamental problem? Or do you think vision is the fundamental problem? Or is it also your action, the interaction with the environment, the ability to... And then the middle ground, I don't know if you put that under vision, which is trying to predict the behavior of others, which is a little bit in the world of understanding the scene, but it's also trying to form a model of the actors in the scene and predict their behavior. Yeah, I include that in vision because to me, perception blends into cognition and building predictive models of other agents in the world, which could be other agents, could be people, other agents, could be other cars, that is part of the task of perception. Because perception always has to not tell us what is now, but what will happen, because what's now is boring. It's done, it's over with. We care about the future because we act in the future. And we care about the past in as much as it informs what's going to happen in the future. So, I think we have to build predictive models of behaviors of people and those can get quite complicated. So, I mean, I've seen examples of this in, actually, I mean, I own a Tesla and it has various safety features built in. And what I see are these examples where, let's say there is some skateboarder, I mean, and I don't want to be too critical because obviously, these systems are always being improved and any specific criticism I have, maybe the system six months from now will not have that particular failure mode. So, it had the wrong response and it's because it couldn't predict what this skateboarder was going to do. And because it really required that higher level cognitive understanding of what skateboarders typically do as opposed to a normal pedestrian. So, what might have been the correct behavior for a pedestrian, a typical behavior for a pedestrian was not the typical behavior for a skateboarder. Right? Yeah. And so, therefore, to do a good job there, you need to have enough data where you have pedestrians, you also have skateboarders, you've seen enough skateboarders to see what kinds of patterns of behavior they have. So, it is, in principle, with enough data that problem could be solved. But I think our current systems, computer vision systems, they need far, far more data than humans do for learning those same capabilities. So, say that there is going to be a system that solves autonomous driving, do you think it will look similar to what we have today, but have a lot more data, perhaps more compute, but the fundamental architectures involved, like neural, well, in the case of Tesla Autopilot, is neural networks. Do you think it will look similar in that regard and it'll just have more data? That's a scientific hypothesis as to which way is it going to go. I will tell you what I would bet on. So, and this is my general philosophical position on how these learning systems have been. What we have found currently very effective in computer vision, in the deep learning paradigm, is sort of tabula rasa learning, and tabula rasa learning in a supervised way, with lots and lots of examples. What's tabula rasa learning? Tabula rasa in the sense that blank slate. We just have the system which is given a series of experiences in this setting, and then it learns there. Now, if, let's think about human driving, it is not tabula rasa learning. So, at the age of 16, in high school, a teenager goes into driver ed class. And now, at that point, they learn, but at the age of 16, they are already visual geniuses, because from zero to 16, they have built a certain repertoire of vision. In fact, most of it has probably been achieved by age two, right? In this period of age, up to age two, they know that the world is three dimensional. They know how objects look like from different perspectives. They know about occlusion. They know about common dynamics of humans and other bodies. They have some notion of intuitive physics. So, they have built that up from their observations and interactions in early childhood, and of course, reinforced through their growing up to age 16. So, then, at age 16, when they go into driver ed, what are they learning? They are not learning afresh the visual world. They have a mastery of the visual world. What they are learning is control. Okay, they are learning how to be smooth about control, about steering and brakes and so forth. They're learning a sense of typical traffic situations. Now, that education process can be quite short, because they are coming in as visual geniuses. And of course, in their future, they're going to encounter situations which are very novel, right? So, during my driver ed class, I may not have had to deal with a skateboarder. I may not have had to deal with a truck driving in front of me, who's from, who's, where the back opens up and some junk gets dropped from the truck, and I have to deal with it, right? But I can deal with this as a driver, even though I did not encounter this in my driver ed class. And the reason I can deal with it is because I have all this general visual knowledge and expertise. And do you think the learning mechanisms we have today can do that kind of long-term accumulation of knowledge? Or do we have to do some kind of, you know, the work that led up to expert systems with knowledge representation, you know, the broader field of what, of artificial intelligence, worked on this kind of accumulation of knowledge? Do you think neural networks can do the same? I think, I don't see any in-principle problem with neural networks doing it, but I think the learning techniques would need to evolve significantly. So, the current learning techniques that we have are supervised learning. You're given lots of examples, x-y-y pairs, and you learn the functional mapping between them. I think that human learning is far richer than that. It includes many different components. There is a child explores the world and sees, for example, a child takes an object and manipulates it in his hand and therefore gets to see the object from different points of view. And the child has commanded the movement. So, that's a kind of learning data, but the learning data has been arranged by the child. And this is a very rich kind of data. The child can do various experiments with the world. So, there are many aspects of sort of human learning, and these have been studied in in child development by psychologists. And what they tell us is that supervised learning is a very small part of it. There are many different aspects of learning. And what we would need to do is to develop models of all of these and then train our systems in that, with that kind of protocol. So, new methods of learning, some of which might imitate the human brain. But you also, in your talks, have mentioned sort of the compute side of things, in terms of the difference in the human brain, or referencing Hans Marovec. So, do you think there's something interesting, valuable to consider about the difference in the computational power of the human brain versus the computers of today, in terms of instructions per second? Yes. So, if we go back, so this is a point I've been making for 20 years now. And I think, once upon a time, the way I used to argue this was that we just didn't have the computing power of the human brain. Our computers were not quite there. And I mean, there is a well-known trade-off, which we know that neurons are slow compared to transistors, but we have a lot of them, and they have a very high connectivity. Whereas in silicon, you have much faster devices, transistors switch at on the order of nanoseconds, but the connectivity is usually smaller. At this point in time, I mean, we are now talking about 2020, we do have, if you consider the latest GPUs and so on, amazing computing power. And if we look back at Hans Marovec's type of calculations, which he did in the 1990s, we may be there today in terms of computing power comparable to the brain, but it's not of the same style. It's of a very different style. So, I mean, for example, the style of computing that we have in our GPUs is far, far more power hungry than the style of computing that is there in the human brain or other biological entities. Yeah, and that, the efficiency part is, we're going to have to solve that in order to build actual real-world systems of large scale. Let me ask sort of the high-level question, just taking a step back, how would you articulate the general problem of computer vision? Does such a thing exist? So if you look at the computer vision conferences and the work that's been going on, it's often separated into different little segments, breaking the problem of vision apart into whether segmentation, 3D reconstruction, object detection, I don't know, image capturing, whatever, there's benchmarks for each. But if you were to sort of philosophically say, what is the big problem of computer vision? Does such a thing exist? Yes, but it's not in isolation. So if we have to, so for all intelligence tasks, I always go back to sort of biology or humans. And if we think about vision or perception in that setting, we realize that perception is always to guide action. Perception for a biological system does not give any benefits unless it is coupled with action. So we can go back and think about the first multicellular animals, which arose in the Cambrian era, 500 million years ago. And these animals could move and they could see in some way. And the two activities helped each other because how does movement help? Movement helps that because you can get food in different places. But you need to know where to go. And that's really about perception or seeing. I mean, vision is perhaps the single most perception sense, but all the others are equally, are also important. So perception and action kind of go together. So earlier it was in these very simple feedback loops, which were about finding food or avoiding becoming food if there's a predator running, trying to eat you up and so forth. So we must at the fundamental level connect perception to action. Then as we evolved, perception became more and more sophisticated because it served many more purposes. And so today we have what seems like a fairly general purpose capability, which can look at the external world and build a model of the external world inside the head. We do have that capability. That model is not perfect. And psychologists have great fun in pointing out the ways in which the model in your head is not a perfect model of the external world. They create various illusions to show the ways in which it is imperfect. But it's amazing how far it has come from a very simple perception action loop that exists in an animal 500 million years ago. Once we have these very sophisticated visual systems, we can then impose a structure on them. It's we as scientists who are imposing that structure, where we have chosen to characterize this part of the system as this quote, module of object detection or quote, this module of 3D reconstruction. What's going on is really all of these processes are running simultaneously. And they are running simultaneously because originally their purpose was in fact to help guide action. So as a guiding general statement of a problem, do you think we can say that the general problem of computer vision, you said in humans it was tied to action. Do you think we should also say that ultimately the goal, the problem of computer vision is to sense the world in the way that helps you act in the world? Yes, I think that's the most fundamental purpose. We have by now hyper evolved. So we have this visual system which can be used for other things. For example, judging the aesthetic value of a painting. And this is not guiding action. Maybe it's guiding action in terms of how much money you will put in your auction bid, but that's a bit stretched. But the basics are in fact in terms of action. But we have really this hyper, we have hyper evolved our visual system. Actually, just to, sorry to interrupt, but perhaps it is fundamentally about action. You kind of jokingly said about spending, but perhaps the capitalistic drive that drives a lot of the development in this world is about the exchange of money. And the fundamental action is money. If you watch Netflix, if you enjoy watching movies, you're using your perception system to interpret the movie. Ultimately your enjoyment of that movie means you'll subscribe to Netflix. So the action is this extra layer that we've developed in modern society perhaps is fundamentally tied to the action of spending money. Well, certainly with respect to interactions with firms. So in this homo economicus role, when you're interacting with firms, it does become that. What else is there? And that was a rhetorical question. Okay. So to linger on the division between the static and the dynamic, so much of the work in computer vision, so many of the breakthroughs that you've been a part of have been in the static world, in looking at static images. And then you've also worked on starting, but it's a much smaller degree. The community is looking at dynamic, at video, at dynamic scenes. And then there is robotic vision, which is dynamic, but also where you're actually have a robot in the physical world interacting based on that vision. Which problem is harder? The trivial first answer is, well, of course, one image is harder. But if you look at a deeper question there, are we, what's the term, cutting ourselves at the knees or making the problem harder by focusing on images? That's a fair question. I think sometimes we can simplify a problem so much that we essentially lose part of the juice that could enable us to solve the problem. And one could reasonably argue that to some extent this happens when we go from video to single images. Now, historically, you have to consider the limits imposed by the computation capabilities we had. So if we, many of the choices made in the computer vision community through the 70s, 80s, 90s, can be understood as choices which were forced upon us by the fact that we just didn't have access to compute, enough compute. Not enough memory, not enough hard drives. Exactly. Not enough compute, not enough storage. So think of these choices. So one of the choices is focusing on single images rather than video. Okay. Clear question, storage and compute. We had to focus on, we did, we used to detect edges and throw away the image. Right. So you have an image, which is say 256 by 256 pixels. And instead of keeping around the grayscale value, what we did was we detected edges, find the places where the brightness changes a lot. So now that's, and now, and then throw away the rest. So this was a major compression device. And the hope was that this makes it, that you can still work with it. And the logic was humans can interpret a line drawing and yes, and this will save us computation. So many of the choices were dictated by that. I think today we are no longer detecting edges, right? We process images with ConvNets because we don't need to, we don't have that, those compute restrictions anymore. Now video is still understudied because video compute is still quite challenging if you are a university researcher. I think video computing is not so challenging if you are at Google or Facebook or Amazon. Still super challenging. I just spoke with the VP of engineering, Google head of the YouTube search and discovery, and they still struggle doing stuff on video. It's very difficult except doing, except using techniques that are essentially the techniques you used in the nineties, some very basic computer vision techniques. Computer vision techniques. No, that's when you want to do things at scale. So if you want to operate at the scale of all the content of YouTube, it's very challenging. And there are similar issues in Facebook, but as a researcher, you have more opportunities. You can train large networks with relatively large video datasets. Yeah. Yes. So I think that this is part of the reason why we have so emphasized static images. I think that this is changing. And over the next few years, I see a lot more progress happening in video. So I have this generic statement that to me, video recognition feels like 10 years behind object recognition. And you can quantify that because you can take some of the challenging video datasets and their performance on action classification is like, say 30%, which is kind of what we used to have around 2009 in object detection. So it's like about 10 years behind. And whether it'll take 10 years to catch up is a different question. Hopefully it will take less than that. Let me ask a similar question I've already asked, but once again, so for dynamic scenes, do you think some kind of injection of knowledge bases and reasoning is required to help improve like action recognition? If we solve the general action recognition problem, what do you think the solution would look like? That's another way to put it. Yeah. So I completely agree that knowledge is called for and that knowledge can be quite sophisticated. So the way I would say it is that perception blends into cognition and cognition brings in issues of memory and this notion of a schema from psychology, which is, let me use the classic example, which is you go to a restaurant, right? Now that things happen in a certain order, you walk in, somebody takes you to a table, waiter comes, gives you a menu, takes the order, food arrives, eventually bill arrives, etc. There's a classic example of AI from the 1970s. It was called, there was the term frames and scripts and schema. These are all quite similar ideas. Okay. And in the 70s, the way the AI of the time dealt with it was by hand coding this. So they hand coded in this notion of a script and the various stages and the actors and so on and so forth, and use that to interpret, for example, language. I mean, if there's a description of a story involving some people eating at a restaurant there are all these inferences you can make because you know what happens typically at a restaurant. So I think this kind of knowledge is absolutely essential. So I think that when we are going to do long form video understanding, we are going to need to do this. I think the kinds of technology that we have right now with 3D convolutions over a couple of seconds of clip or video, it's very much tailored towards short term video understanding, not that long term understanding. Long term understanding requires a notion of this notion of schemas that I talked about, perhaps some notions of goals, intentionality, functionality, and so on and so forth. Now, how will we bring that in? So we could either revert back to the 70s and say, okay, I'm going to hand code in a script, or we might try to learn it. So I tend to believe that we have to find learning ways of doing this, because I think learning ways land up being more robust. And there must be a learning version of the story because children acquire a lot of this knowledge by observation. So at no moment in a child's life does a, it's possible, but I think it's not so typical that somebody, that a mother coaches a child through all the stages of what happens in a restaurant. They just go as a family, they go to the restaurant, they eat, they go to the restaurant, they eat, come back, and the child goes through 10 such experiences, and the child has got a schema of what happens when you go to a restaurant. So we somehow need to, we need to provide that capability to our systems. You mentioned the following line from the end of the Alan Turing paper, Computing Machinery and Intelligence, that many people, like you said, many people know and very few have read, where he proposes the Turing test. This is how you know, because it's towards the end of the paper. Instead of trying to produce a program to simulate the adult mind, why not rather try to produce one which simulates the child's? So that's a really interesting point. If I think about the benchmarks we have before us, the tests of our computer vision systems, they're often kind of trying to get to the adult. So what kind of benchmarks should we have? What kind of tests for computer vision do you think we should have that mimic the child's in computer vision? Yeah, I think we should have those and we don't have those today. And I think the part of the challenge is that we should really be collecting data of the type that a child experiences. So that gets into issues of privacy and so on and so forth. But there are attempts in this direction to sort of try to collect the kind of data that a child encounters growing up. So what's the child's linguistic environment? What's the child's visual environment? So if we could collect that kind of data and then develop learning schemes based on that data, that would be one way to do it. I think that's a very promising direction myself. There might be people who would argue that we could just short circuit this in some way. And sometimes we have imitated, we have had success by not imitating nature in detail. So the usual example is airplanes, right? We don't build flapping wings, airplanes, right? We don't build flapping wings. So yes, that's one of the points of debate. In my mind, I would bet on this learning like a child approach. So one of the fundamental aspects of learning like a child is the interactivity. So the child gets to play with the data set it's learning from. So it gets to select. I mean, you can call that active learning. In the machine learning world, you can call it a lot of terms. What are your thoughts about this whole space of being able to play with the data set or select what you're learning? Yeah. So I think that I believe in that. And I think that we could achieve it in two ways. And I think we should use both. So one is actually real robotics, right? So real, you know, physical embodiments of agents who are interacting with the world, and they have a physical body with dynamics and mass and moment of inertia and friction and all the rest. And you learn your body, the robot learns its body by doing a series of actions. The second is that simulation environments. So I think simulation environments are getting much, much better. In my life, in Facebook AI research, our group has worked on something called Habitat, which is a simulation environment, which is a visually photorealistic environment of, you know, places like houses or interiors of various urban spaces and so forth. And as you move, you get a picture, which is a pretty accurate picture. So I can now, you can imagine that subsequent generations of these simulators will be accurate, not just visually, but with respect to, you know, forces and masses and haptic interactions and so on. And then we have that environment to play with. I think that, let me state one reason why I think this active, being able to act in the world is important. I think that this is one way to break the correlation versus causation barrier. So this is something which is of a great deal of interest these days. I mean, people like Judea Pearl have talked a lot about that we are neglecting causality and he describes the entire set of successes of deep learning as just curve fitting, right? Because it's, but I don't quite agree. He's a troublemaker, he is. But causality is important, but causality is not like a single silver bullet. It's not like one single principle. There are many different aspects here. And one of the ways in which, one of our most reliable ways of establishing causal links, and this is the way, for example, the medical community does this, is randomized control trials. So you have, you pick some situation and now in some situation you perform an action and for certain others you don't, right? So you have a control experiment. Well, the child is in fact performing controlled experiments all the time, right? Right, right. Okay. Small scale. In a small scale. But that is a way that the child gets to build and refine its causal models of the world. And my colleague, Alison Gopnik has, together with a couple of authors, co-authors has a book called The Scientist in the Crib, referring to his children. So I like, the part that I like about that is the scientist wants to do, wants to build causal models and the scientist does control experiments. And I think the child is doing that. So to enable that, we will need to have these active experiments. And I think those could be done, some in the real world and some in simulation. So you have hope for simulation. I have hope for simulation. That's an exciting possibility if we can get to not just photorealistic, but what's that called? Life realistic simulation. So you don't see any fundamental blocks to why we can't eventually simulate the principles of what it means to exist in the world as a physical object. I don't see any fundamental problems there. I mean, look, the computer graphics community has come a long way. So in the early days, going back to the 80s and 90s, they were focusing on visual realism, right? And then they could do the easy stuff, but they couldn't do stuff like hair or fur and so on. Okay, well, they managed to do that. Then they couldn't do physical actions, right? Like there's a bowl of glass and it falls down and it shatters, but then they could start to do pretty realistic models of that and so on and so forth. So the graphics people have shown that they can do this forward direction, not just for optical interactions, but also for physical interactions. So I think, of course, some of that is very computer intensive, but I think by and by we will find ways of making our models ever more realistic. You break vision apart into, in one of your presentations, early vision, static scene understanding, dynamic scene understanding, and raise a few interesting questions. I thought I could just throw some at you to see if you want to talk about them. So early vision, so it's, what is it that you said? Sensation, perception, and cognition. So this is sensation. Yes. What can we learn from image statistics that we don't already know? So at the lowest level, what can we make from just the statistics, the basics, so there were the variations in the rock pixels, the textures, and so on? Yeah, so what we seem to have learned is that there's a lot of redundancy in these images, and as a result we are able to do a lot of compression. And this compression is very important in biological settings, right? So you might have 10 to the 8 photoreceptors and only 10 to the 6 fibers in the optic nerve, so you have to do this compression by a factor of 100 is to 1. And so there are analogs of that which are happening in our neural net, artificial neural network. At the early layers, so you think there's a lot of compression that can be done in the beginning, just the statistics. Yeah. How much? Well, so I mean, the way to think about it is just how successful is image compression, right? And that's been done with older technologies, but it can be done with, there are several companies which are trying to use sort of these more advanced neural network type techniques for compression, both for static images as well as for video. One of my former students has a company which is trying to do stuff like this. And I think that they are showing quite interesting results, and I think that that's all the success of, that's really about image statistics and video statistics. But that's still not doing compression of the kind when I see a picture of a cat, all I have to say is it's a cat, that's another semantic kind of compression. Yeah. So this is at the lower level, right? So we are, as I said, yeah, that's focusing on low level statistics. So to linger on that for a little bit, you mentioned how far can bottom-up image segmentation go? And in general, what you mentioned that the central question for scene understanding is the interplay of bottom-up and top-down information. Maybe this is a good time to elaborate on that, maybe define what is bottom-up, what is top-down in the context of computer vision? Right. So today what we have are very interesting systems because they were completely bottom-up. What does bottom-up mean, sorry? So bottom-up means, in this case, means a feed-forward neural network. So starting from the raw pixels? Yeah, they start from the raw pixels and they end up with something like cat or not a cat, right? So our systems are running totally feed-forward. They're trained in a very top-down way. So they're trained by saying, okay, this is a cat, this is a cat, this is a dog, this is a zebra, et cetera. And I'm not happy with either of these choices fully. We have gone into, because we have completely separated these processes, right? So I would like the process, so what do we know compared to biology? So in biology, what we know is that the processes at test time, at runtime, those processes are not purely feed-forward, but they involve feedback. So, and they involve much shallower neural networks. So the kinds of neural networks we are using in computer vision, say a ResNet 50 has 50 layers. Well, in the brain, in the visual cortex, going from the retina to IT, maybe we have like seven, right? So they're far shallower, but we have the possibility of feedback. So there are backward connections. Backward connections. And this might enable us to deal with the more ambiguous stimuli, for example. So the biological solution seems to involve feedback. The solution in artificial vision seems to be just feed-forward, but with a much deeper network. And the two are functionally equivalent, because if you have a feedback network, which just has like three rounds of feedback, you can just unroll it and make it three times the depth and create it in a totally feed-forward way. So this is something which, I mean, we have written some papers on this theme, but I really feel that this theme should be pursued further. Some kind of recurrence mechanism. Yeah. Okay. So I want to have a little bit more top-down at test time. Okay. Then at training time, we make use of a lot of top-down knowledge right now. So basically to learn to segment an object, we have to have all these examples of this is the boundary of a cat, and this is the boundary of a chair, and this is the boundary of a horse, and so on. And this is too much top-down knowledge. How do humans do this? We manage with far less supervision, and we do it in a sort of bottom-up way, because for example, we're looking at a video stream, and the horse moves. And that enables me to say that all these pixels are together. So the Gestalt psychologists used to call this the principle of common fate. So there was a bottom-up process by which we were able to segment out these objects, and we have totally focused on this top-down training signal. So in my view, we have currently solved it in machine vision, this top-down, bottom-up interaction, but I don't find the solution fully satisfactory, and I would rather have a bit of both at both stages. For all computer vision problems, not just segmentation. And the question that you can ask is, so for me, I'm inspired a lot by human vision, and I care about that. You could be just a hard-boiled engineer and not give a damn. So to you, I would then argue that you would need far less training data if you could make my research agenda fruitful. Okay, so then maybe taking a step into segmentation, static scene understanding. What is the interaction between segmentation and recognition? You mentioned the movement of objects. So for people who don't know computer vision, segmentation is this weird activity that computer vision folks have all agreed is very important, of drawing outlines around objects versus a bounding box and then classifying that object. What's the value of segmentation? What is it as a problem in computer vision? How is it fundamentally different from detection, recognition, and the other problems? Yeah, so I think segmentation enables us to say that some set of pixels are an object without necessarily even being able to name that object or knowing properties of that object. Oh, so you mean segmentation purely as the act of separating an object from its background, a blob that's united in some way from its background. Yeah, so entityfication, if you will, making an entity out of it. Entityfication, beautifully. So I think that we have that capability and that enables us to, as we are growing up, to acquire names of objects with very little supervision. So suppose the child, let's posit that the child has this ability to separate out objects in the world. Then when the mother says, pick up your bottle, or the cat's behaving funny today. The word cat suggests some object and then the child sort of does the mapping. Right. Right? The mother doesn't have to teach specific object labels by pointing to them. Weak supervision works in the context that you have the ability to create objects. So to me, that's a very fundamental capability. There are applications where this is very important. For example, medical diagnosis. So in medical diagnosis, you have some brain scan. I mean, this is some work that we did in my group where you have CT scans of people who have had traumatic brain injury. And what the radiologist needs to do is to precisely delineate various places where there might be bleeds, for example. And there are clear needs like that. So there's certainly very practical applications of computer vision where segmentation is necessary. But philosophically, segmentation enables the task of recognition to proceed with much weaker supervision than we require today. And you think of segmentation as this kind of task that takes on a visual scene and breaks it apart into interesting entities that might be useful for whatever the task is. Yeah. And it is not semantics free. So I think, I mean, it blends into, it involves perception and cognition. It is not, I think the mistake that we used to make in the early days of computer vision was to treat it as a purely bottom-up perceptual task. It is not just that. Because we do revise our notion of segmentation with more experience, right? Because, for example, there are objects which are non-rigid, like animals or humans. And I think understanding that all the pixels of a human are one entity is actually quite a challenge because the parts of the human, they can move independently. The human wears clothes, so they might be differently colored. So it's all sort of a challenge. You mentioned the three R's of computer vision are recognition, reconstruction, and reorganization. Can you describe these three R's and how they interact? Yeah. So recognition is the easiest one because that's what I think people generally think of as computer vision achieving these days, which is labels. So is this a cat? Is this a dog? Is this a chihuahua? I mean, it could be very fine-grained, like a specific breed of a dog or a specific species of bird, or it could be very abstract, like an animal. But given a part of an image or a whole image, say, put a label on that. Yeah. So that's recognition. Reconstruction is essentially, you can think of it as inverse graphics. I mean, that's one way to think about it. So graphics is you have some internal computer representation, and you have a computer representation of some objects arranged in a scene. And what you do is you produce a picture. You produce the pixels corresponding to a rendering of that scene. So let's do the inverse of this. We are given an image and we say, oh, this image arises from some objects in a scene looked at with a camera from this viewpoint. And we might have more information about the objects, like their shape, maybe their textures, maybe color, etc., etc. So that's the reconstruction problem. In a way, you are in your head creating a model of the external world. Okay, reorganization is to do with essentially finding these entities. So it's organization. The word organization implies structure. So in psychology, we use the term perceptual organization, that the world is not just, an image is not just seen as, is not internally represented as just a collection of pixels, but we make these entities, we create these entities, objects, whatever you want to call them. And the relationship between the entities as well, or is it purely about the entities? It could be about the relationships, but mainly we focus on the fact that there are entities. So I'm trying to pinpoint what the organization means. So organization is that instead of like a uniform grid, we have this structure of objects. So segmentation is the small part of that. So segmentation gets us going towards that. Yeah. And you kind of have this triangle where they all interact together. Yes. So how do you see that interaction in sort of reorganization is yes, defining the entities in the world, the recognition is labeling those entities, and then reconstruction is what filling in the gaps? Well, to, for example, see, impute some 3D objects corresponding to each of these entities. That would be part of the... So adding more information that's not there in the raw data. Correct. I mean, I started pushing this kind of a view in the around 2010 or something like that, because at that time in computer vision, the distinction that people were just working on many different problems, but they treated each of them as a separate isolated problem, with each with its own data set, and then you try to solve that and get good numbers on it. So I didn't like that approach because I wanted to see the connection between these. And if people divided up vision into various modules, the way they would do it is as low level, mid level and high level vision, corresponding roughly to the psychologist's notion of sensation, perception and cognition. And that didn't map to tasks that people cared about. So therefore, I tried to promote this particular framework as a way of considering the problems that people in computer vision were actually working on, and trying to be more explicit about the fact that they actually are connected to each other. And I was at that time, just doing this on the basis of information flow. Now, it turns out, in the last five years or so, in the post the deep learning revolution, that this architecture has turned out to be very conducive to that. Because basically, in these neural networks, we are trying to build multiple representations. There can be multiple output heads sharing common representations. So in a certain sense, today, given the reality of what solutions people have to these, I do not need to preach this anymore. It is just there, it's part of the solution space. So speaking of neural networks, how much of this problem of computer vision, of reorganization, recognition, can be, reconstruction, how much of it can be learned end to end, do you think? Sort of, set it and forget it. Just plug and play, have a giant data set, multiple, perhaps multimodal, and then just learn the entirety of it. Well, so I think that currently what that end to end learning means nowadays is end to end supervised learning. And that, I would argue, is too narrow a view of the problem. I like this child development view, this lifelong learning view, one where there are certain capabilities that are built up, and then there are certain capabilities which are built up on top of that. So that's what I believe in. So I think end to end learning in the supervised setting, for a very precise task, to me is kind of a limited view of the learning process. Got it. So if we think about beyond purely supervised, look back to children. You mentioned six lessons that we can learn from children of be multimodal, be incremental, be physical, explore, be social, use language. Can you speak to these, perhaps picking one that you find most fundamental to our time today? Yeah, so I mean, I should say, to give due credit, this is from a paper by Smith and Gasser. And it reflects, essentially, I would say, common wisdom among child development people. It's just that this is not common wisdom among people in computer vision and AI and machine learning. So I view my role as trying to bridge the two worlds. So let's take an example of a multimodal. I like that. So multimodal, a canonical example is a child interacting with an office. So the child is interacting with an object. So then the child holds a ball and plays with it. So at that point, it's getting a touch signal. So the touch signal is getting a notion of 3D shape, but it is sparse. And then the child is also seeing a visual signal. And these two, so imagine these are two in totally different spaces. Receptors on the skin of the fingers and the thumb and the palm. And then these map onto these neuronal fibers are getting activated somewhere. These lead to some activation in somatosensory cortex. I mean, a similar thing will happen if we have a robot hand. And then we have the pixels corresponding to the visual view. But we know that they correspond to the same object. So that's a very, very strong cross-calibration signal. And it is self-supervisory, which is beautiful. There's nobody assigning a label. The mother doesn't have to come and assign a label. The child doesn't even have to know that this object is called a ball. But the child is learning something about the three-dimensional world from this signal. I think tactile and visual, there is some work on. There is a lot of work currently on audio and visual. And audio-visual, so there is some event that happens in the world. And that event has a visual signature. And it has an auditory signature. So there is this glass bowl on the table. And it falls and breaks. And I hear the smashing sound. And I see the pieces of glass. OK, I've built that connection between the two. Right? We have people, I mean, this has become a hot topic in computer vision in the last couple of years. There are problems like separating out multiple speakers, right? Which was a classic problem in audition. They call this the problem of source separation, or the cocktail party effect, and so on. But just try to do it visually. When you also have, it becomes so much easier and so much more useful. So the multimodal, I mean, there's so much more signal with multimodal. And you can use that for some kind of weak supervision as well. Yes, because they are occurring at the same time in time. So you have time, which links the two, right? So at a certain moment, T1, you've got a certain signal in the auditory domain and a certain signal in the visual domain. But they must be causally related. Yeah, it's an exciting area. Not well studied yet. Yeah, I mean, we have a little bit of work at this, but so much more needs to be done. Yeah. So this is a good example. Be physical, that's to do with, like, the one thing we talked about earlier, that there's an embodied world. To mention language, use language. So Noam Chomsky believes that language may be at the core of cognition, at the core of everything in the human mind. What is the connection between language and vision to you? Like, what's more fundamental? Are they neighbors? Is one the parent and the child, the chicken and the egg? Oh, it's very clear. It is vision versus the parent. The parent. The parent is the fundamental ability. Okay. Wait, wait, wait, wait. So it comes before you think vision is more fundamental than language. Correct. And you can think of it either in phylogeny or in ontogeny. So phylogeny means, if you look at evolutionary time, right, so we have vision that developed 500 million years ago. Okay, then something like when we get to maybe, like, 5 million years ago, you have the first bipedal primate. So when we started to walk, then the hand became free. And so then manipulation, the ability to manipulate objects and build tools and so on and so forth. So you said 500,000 years ago? No, no, sorry. The first multicellular animals, which you can say had some intelligence, arose 500 million years ago. Million. Okay, and now let's fast forward to say the last 7 million years, which is the development of the hominid line, right, where from the other primates, we have the branch which leads on to modern humans. Now, there are many of these hominids, but the ones which, you know, people talk about Lucy, because that's like a skeleton from 3 million years ago, and we know that Lucy walked. Okay, so at this stage, you have that the hand is free for manipulating objects. And then the ability to manipulate objects, build tools, and the brain size grew in this era. So, okay, so now you have manipulation. Now, we don't know exactly when language arose. But after that. But after that. Because no apes have, I mean, so, I mean, Chomsky is correct in that, that it is a uniquely human capability. And we, primates, other primates don't have that. But so it developed somewhere in this era. But it developed, I would, I mean, argue that it probably developed after we had this stage of humans, I mean, the human species already able to manipulate and hands-free, much bigger brain size. And for that, there's a lot of vision has already had to have developed. Yeah. So the sensation and the perception, maybe some of the cognition. Yeah, so we, so those, so that, so the world, so there, so these ancestors of ours, you know, three, four million years ago, they had spatial intelligence. So they knew that the world consists of objects. They knew that the objects were in certain relationships to each other. They had observed causal interactions among objects. They could move in space. So they had space and time and all of that. So language builds on that substrate. So language has a lot of, I mean, I mean, all human languages have constructs which depend on a notion of space and time. Where did that notion of space and time come from? It had to come from perception and action in the world we live in. Yeah, what you've referred to as the spatial intelligence. Yeah. Yeah. So to linger a little bit, we mentioned Turing and his mention of, we should learn from children. Nevertheless, language is the fundamental piece of the test of intelligence that Turing proposed. Yes. What do you think is a good test of intelligence? Are you, what would imply a good test of intelligence? I mean, I'm impressed the heck out of you. Is it fundamentally natural language or is there something in vision? I think I wouldn't, I don't think we should have create a single test of intelligence. So just like I don't believe in IQ as a single number, I think generally there can be many capabilities which are correlated perhaps. So I think that there will be accomplishments which are visual accomplishments, accomplishments which are accomplishments in manipulation or robotics, and then accomplishments in language. I do believe that language will be the hardest nut to crack. Really? Yeah. So what's harder, to pass the spirit of the Turing test, like whatever formulation will make it natural language, convincingly a natural language, like somebody you would want to have a beer with, hang out and have a chat with, or the general natural scene understanding? You think language is the tough problem? I think, I'm not a fan of the, I think Turing test, that Turing as he proposed the test in 1950 was trying to solve a certain problem. Yeah, imitation. Yeah, and I think it made a lot of sense then. Where we are today, 70 years later, I think we should not worry about that. I think the Turing test is no longer the right way to channel research in AI because that, it takes us down this path of this chatbot which can fool us for five minutes or whatever. I think I would rather have a list of 10 different tasks. I think there are tasks which, there are tasks in the manipulation domain, tasks in navigation, tasks in visual scene understanding, tasks in reading a story and answering questions based on that. I mean, so my favorite language understanding task would be reading a novel and being able to answer arbitrary questions from it, okay. Right. I think that to me, and this is not an exhaustive list by any means, so I would, I think that that's where we need to be going to and each of these, on each of these axes there's a fair amount of work to be done. So on the visual understanding side, in this intelligence Olympics that we've set up, what's a good test? One of many of visual scene understanding. Do you think such benchmarks exist? Sorry to interrupt. No, there aren't any. I think essentially to me, a really good aid to the blind. So suppose there was a blind person and I needed to assist the blind person. So ultimately, like we said, vision that aids in the action in the survival in this world. Yeah. Maybe in a simulated world. Maybe easier to measure performance in a simulated world. What we are ultimately after is performance in the real world. So David Hilbert in 1900 proposed 23 open problems in mathematics, some of which are still unsolved. Most important, famous of which is probably the Riemann hypothesis. You've thought about and presented about the Hilbert problems of computer vision. So let me ask, what do you today, I don't know when the last year you presented that, 2015, but versions of it. Yeah. You're kind of the face and the spokesperson for computer vision. So it's your job to state what the open problems are for the field. So what today are the Hilbert problems of computer vision, do you think? Let me pick one which I regard as clearly unsolved, which is what I would call long form video understanding. So we have a video clip and we want to understand the behavior in there in terms of agents, their goals, intentionality, and make predictions about what might happen. So that kind of understanding which goes away from atomic vision, which is the kind of atomic visual action. So in the short range, the question is, are you sitting, are you standing, are you catching a ball? Right? That we can do now. Or even if we can't do it fully accurately, if we can do it at 50%, maybe next year we'll do it at 65 and so forth. But I think the long range video understanding, I don't think we can do today. And that means... And it blends into cognition, that's the reason why it's challenging. And so you have to track, you have to understand the entities, you have to understand the entities, you have to track them, and you have to have some kind of model of their behavior. Correct. And their behavior might be, these are agents, so they are not just like passive objects, but they're agents, so therefore they would exhibit goal-directed behavior. Okay, so this is one area. Then I will talk about, say, understanding the world in 3D. This may seem paradoxical because in a way we have been able to do 3D understanding even like 30 years ago, right? But I don't think we currently have the richness of 3D understanding in our computer vision system that we would like. So let me elaborate on that a bit. So currently we have two kinds of techniques which are not fully unified. So there are the kinds of techniques from multi-view geometry, that you have multiple pictures of a scene and you do a reconstruction using stereoscopic vision or structure from motion. But these techniques do not... They totally fail if you just have a single view, because they are relying on this multiple view geometry. Okay, then we have some techniques that we have developed in the computer vision community which try to guess 3D from single views. And these techniques are based on supervised learning, and they are based on having at training time 3D models of objects available. And this is completely unnatural supervision, right? That's not... CAD models are not injected into your brain. Okay, so what would I like? What I would like would be a kind of learning as you move around the world notion of 3D. So we have our succession of visual experiences. And from those, we... So as part of that, I might see a chair from different viewpoints or a table from different viewpoints and so on. Now, as part, that enables me to build some internal representation. And then next time, I just see a single photograph, and it may not even be of that chair, it's of some other chair. And I have a guess of what its 3D shape is like. So you're almost learning the CAD model, kind of... Yeah, implicitly. I mean, the CAD model need not be in the same form as used by computer graphics programs. Hidden in the representation. It's hidden in the representation, the ability to predict new views, and what I would see if I went to such and such position. By the way, on a small tangent on that, are you okay or comfortable with neural networks that do achieve visual understanding, that do, for example, achieve this kind of 3D understanding, and you don't know how they, you don't know the... You're not able to visualize or understand or interact with the representation. So the fact that they're not or may not be explainable. Yeah, I think that's fine. To me, that is... So let me put some caveats on that. So it depends on the setting. So first of all, I think humans are not explainable. So... That's a really good point. So one human to another human is not fully explainable. I think there are settings where explainability matters, and these might be, for example, questions on medical diagnosis. So I'm in a setting where maybe the doctor, maybe a computer program has made a certain diagnosis. And then depending on the diagnosis, perhaps I should have treatment A or treatment B. Right? So now, is the computer program's diagnosis based on data, which was data collected of American males who are in their 30s and 40s, and maybe not so relevant to me? Maybe it is relevant, you know, et cetera, et cetera. And I mean, in medical diagnosis, we have major issues to do with the reference class. So we may have acquired statistics from one group of people and applying it to a different group of people who may not share all the same characteristics. The data might have, there might be error bars in the prediction. So that prediction should really be taken with a huge grain of salt. And, but this has an impact on what treatments should be picked. Right? So there are settings where I want to know more than just, this is the answer. But what I acknowledge is that, so in that sense, explainability and interpretability may matter. It's about giving error bounds and a better sense of the quality of the decision. Where I'm willing to sacrifice interpretability is that I believe that there can be systems which can be highly performant, but which are not. That there can be systems which can be highly performant, but which are internally black boxes. And that seems to be where it's headed. Some of the best performing systems are essentially black boxes. Yeah. Fundamentally by their construction. You and I are black boxes to each other. Yeah. So the nice thing about the black boxes we are, is so we ourselves are black boxes, but we're also, those of us who are charming, are able to convince others, like explain what's going on inside the black box with narratives, with stories. So in some sense, neural networks don't have to actually explain what's going on inside. They just have to come up with stories, real or fake, that convince you that they know what's going on. And I'm sure we can do that. We can create those stories. Neural networks can create those stories. Yeah. And the transformer will be involved. Do you think we will ever build a system of human level or superhuman level intelligence? We've kind of defined what it takes to try to approach that, but do you think that's within our reach? The thing that we thought we could do, what Turing thought actually we could do by year 2000, right? Do you think we'll ever be able to do? Yeah, so I think there are two answers here. One answer is, in principle, can we do this at some time? And my answer is yes. The second answer is a pragmatic one. Do you think we will be able to do it in the next 20 years or whatever? And to that, my answer is no. So, and of course, that's a wild guess. I think that, you know, Donald Rumsfeld is not a favorite person of mine, but one of his lines is very good, which is about known knowns, known unknowns, and unknown unknowns. So in the business we are in, there are known unknowns and we have unknown unknowns. So I think with respect to a lot of what's the case in vision and robotics, I feel like we have known unknowns. So I have a sense of where we need to go and what the problems that need to be solved are. I feel with respect to natural language, understanding, and high level cognition, it's not just known unknowns, but also unknown unknowns. So it is very difficult to put any kind of a time frame to that. Do you think some of the unknown unknowns might be positive in that they'll surprise us and make the job much easier? So fundamental breakthroughs? I think that is possible because certainly I have been very positively surprised by how effective these deep learning systems have been, because I certainly would not have believed that in 2010. I think what we knew from the mathematical theory was that convex optimization works when there's a single global optima, then these gradient descent techniques would work. Now these are nonlinear systems with non-convex systems. Huge number of variables, so over-parameterized. Over-parameterized. And the people who used to play with this, they were very, very smart. The people who used to play with them a lot, the ones who were totally immersed in the lore and the black magic, they knew that they worked well, even though they were... Really? I thought like everybody... No, the claim that I hear from my friends like Yan LeCun and so forth is... Oh, now, yeah. That they feel that they were comfortable with it. Well, he says that now. But the community as a whole... Well, certainly not. And I think we were... To me, that was the surprise, that they actually worked robustly for a wide range of problems from a wide range of initializations and so on. And so that was certainly more rapid progress than we expected. But then there are certainly lots of times, in fact, most of the history of AI is when we have made less progress at a slower rate than we expected. So we just keep going. I think what I regard as really unwarranted are these fears of AGI in 10 years and 20 years and that kind of stuff. Because that's based on completely unrealistic models of how rapidly we will make progress in this field. So I agree with you, but I've also gotten a chance to interact with very smart people who really worry about the existential threats of AI. And as an open-minded person, I'm sort of taking it in. Do you think if AI systems, in some way, the unknown unknowns, not superintelligent AI, but in ways we don't quite understand the nature of superintelligence, will have a detrimental effect on society? Do you think this is something we should be worried about? Or we need to first allow the unknown unknowns to become known unknowns? I think we need to be worried about AI today. I think that it is not just a worry we need to have when we get that AGI. I think that AI is being used in many systems today. And there might be settings, for example, when it causes biases or decisions which could be harmful. I mean, decisions which could be unfair to some people. Or it could be a self-driving car which kills a pedestrian. So AI systems are being deployed today. And they're being deployed in many different settings, maybe in medical diagnosis, maybe in a self-driving car, maybe in selecting applicants for an interview. So I would argue that when these systems make mistakes, there are consequences. And we are, in a certain sense, responsible for those consequences. So I would argue that this is a continuous effort. It is, we, and this is something that in a way is not so surprising. It's about all engineering and scientific progress, which great power comes great responsibility. So as these systems are deployed, we have to worry about them. And it's a continuous problem. I don't think of it as something which will suddenly happen on some day in 2079 for which I need to design some clever trick. I'm saying that these problems exist today. And we need to be continuously on the lookout for worrying about safety, biases, risks. I mean, a self-driving car kills a pedestrian. And they have. I mean, this Uber incident in Arizona. It has happened. This is not about AGI. In fact, it's about a very dumb intelligence. It's still killing people. The worry people have with AGI is the scale. But I think you're 100% right. The thing that worries me about AI today, and it's happening at a huge scale, is recommender systems, recommendation systems. So if you look at Twitter, or Facebook, or YouTube, they're controlling the ideas that we have access to, the news, and so on. And that's a fundamentally machine learning algorithm behind each of these recommendations. And they, I mean, my life would not be the same without these sources of information. I'm a totally new human being. And the ideas that I know are very much because of the internet, because of the algorithms that recommend those ideas. And so as they get smarter and smarter, I mean, that is the AGI. The algorithm that's recommending the next YouTube video you should watch has control of millions of billions of people. That algorithm is already super intelligent and has complete control of the population. Not a complete, but very strong control. For now, we can turn off YouTube. We can just go have a normal life outside of that. But the more and more that gets into our life, it's that algorithm, we start depending on it and the different companies that are working on the algorithm. So I think it's, you're right, it's already there. And YouTube in particular is using computer vision, doing their hardest to try to understand the content of videos so they could be able to connect videos with the people who would benefit from those videos the most. And so that development could go in a bunch of different directions, some of which might be harmful. So yeah, you're right. The threats of AI are here already and we should be thinking about them. On a philosophical notion, if you could, personal perhaps, if you could relive a moment in your life outside of family because it made you truly happy or it was a profound moment that impacted the direction of your life, what moment would you go to? I don't think of single moments, but I look over the long haul. I feel that I've been very lucky because I feel that, I think that in scientific research, a lot of it is about being at the right place at the right time. And you can work on problems at a time when they're just too premature. You know, you butt your head against them and nothing happens because it's, the prerequisites for success are not there. And then there are times when you are in a field which is all pretty mature and you can only solve curlicues upon curlicues. I've been lucky to have been in this field, which for 34 years, well, actually 34 years as a professor at Berkeley, so longer than that, which when I started in it was just like some little crazy, absolutely useless field. It couldn't really do anything to a time when it's really, really solving a lot of practical problems, has offered a lot of tools for scientific research, right? Because computer vision is impactful for images in biology or astronomy and so on and so forth. And we have, so we have made great scientific progress, which has had real practical impact in the world. And I feel lucky that I got in at a time when the field was very young and at a time when it is now mature, but not fully mature. It's mature, but not done. I mean, it's really still in a productive phase. And this is a, yeah. Yeah, I think people 500 years from now would laugh at you calling this field mature. Yeah, that is very possible. So, but you're also, lest I forget to mention, you've also mentored some of the biggest names of computer vision, computer science, and AI today. So many questions I could ask, but really is, what is it, how did you do it? What does it take to be a good mentor? What does it take to be a good guide? Yeah, I think what I feel, I've been lucky to have had very, very smart and hardworking and creative students. I think some part of the credit just belongs to being at Berkeley. Those of us who are at top universities are blessed because we have very, very smart and capable students coming on, knocking on our door. So I have to be humble enough to acknowledge that. But what have I added? I think I have added something. What I have added is, I think what I've always tried to teach them is a sense of picking the right problems. So I think that in science, in the short run, success is always based on technical competence. You're quick with math or you are whatever. I mean, there's certain technical capabilities which make for short-range progress. Long-range progress is really determined by asking the right questions and focusing on the right problems. And I feel that what I've been able to bring to the table in terms of advising these students is some sense of taste of what are good problems, what are problems that are worth attacking now as opposed to waiting 10 years. What's a good problem, if you could summarize? Is that possible to even summarize? Like what's your sense of a good problem? I think I have a sense of what is a good problem, which is there is a British scientist, in fact, he won a Nobel Prize, Peter Medawar, who has a book on this. And basically, he calls it, research is the art of the soluble. So we need to sort of find problems which are not yet solved, but which are approachable. And he sort of refers to this sense that there is this problem which isn't quite solved yet, but it has a soft underbelly. There is some place where you can spear the beast. Yes. And having that intuition that this problem is ripe is a good thing, because otherwise you can just beat your head and not make progress. So I think that is important. So if I have that and if I can convey that to students, it's not just that they do great research while they're working with me, but that they continue to do great research. So in a sense, I'm proud of my students and their achievements and their great research, even 20 years after they've ceased being my student. So it's in part developing, helping them develop that sense that a problem is not yet solved, but it's solvable. Correct. The other thing which I have, which I think I bring to the table, is a certain kind of certain intellectual breadth. I've spent a fair amount of time studying psychology, neuroscience, relevant areas of applied math and so forth. So I can probably help them see some connections to disparate things which they might not have otherwise. So the smart students coming into Berkeley can be very deep in the sense, they can think very deeply, meaning very hard down one particular path, but where I could help them is the shallow breadth, but they would have the narrow depth. But that's of some value. Well, it was beautifully refreshing just to hear you naturally jump to psychology back to computer science in this conversation back and forth. I mean, that's actually a rare quality, and I think it's certainly for students empowering to think about problems in a new way. So for that and for many other reasons, I really enjoyed this conversation. Thank you so much. It was a huge honor. Thanks for talking today. It's been my pleasure. Thanks for listening to this conversation with Jitendra Malik, and thank you to our sponsors, BetterHelp and ExpressVPN. Please consider supporting this podcast by going to betterhelp.com slash Lex and signing up at expressvpn.com slash LexPod. Click the links, buy the stuff. It's how they know I sent you, and it really is the best way to support this podcast and the journey I'm on. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcasts, support it on Patreon, or connect with me on Twitter at Lex Friedman. Don't ask me how to spell that. I don't remember it myself. And now let me leave you with some words from Prince Mishkin in The Idiot by Dostoyevsky. Beauty will save the world. Thank you for listening, and hope to see you next time.

https://youtu.be/LRYkH-fAVGE

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Escaping the Local Optimum of Low Expectation

It's wonderful to be here, wonderful to see so many faces that I've come to love over the years. My advisor, my family's here, my mom, brother. You know, I did ask security to make sure my dad doesn't, is not allowed in, but he somehow found his way in, so good job. The topic of today's talk reminds me of something my dad once told me. I wrote it down. Few are those who see with their own eyes and feel with their own hearts. No wait, that actually was Albert Einstein, different Jew, similar haircut. You know, there's a saying, there's an old saying that goes, give a man a fish and you feed him for a day, teach a man to fish and you feed him for a lifetime. A little known fact, it actually goes on to say, so that he may never discover how much he loves steak or vegetarian lasagna, for those of you who are vegetarian in the audience. And the key there, the key idea is society tries to impose lessons to teach, to drive the human being, each of us, but it's you discovering your own passion is the key, and that's what the talk I'd like to talk about today, and there'll be a lot of poems throughout. And the central poem by Shel Silverstein called The Voice is one I think that will resonate throughout the talk. There's a voice inside of you that whispers all day long, I feel that this is right for me, I know that this is wrong. No teacher, preacher, parent, friend, or wise man can decide what's right for you, just listen to the voice that speaks inside. This is precisely the voice I'd like to talk about in this brief little time we have together over two small topics, life and artificial intelligence. Now from an optimization perspective, and one of my co-advisors has always told me when you show a plot you have to describe the x-axis and the y-axis as a good engineer. There you go, that's lesson number one. The x-axis is competence, the y-axis is confidence, and there's something called the Dunning-Kruger effect, which is captured by this plot, and that is at the beginning of your journey of competence, when you're not very good at something, when you're first taking the first steps of learning something, as some of you here are in the engineering fields, you're overly confident. It's the peak of confidence and you're at the lowest stage of actually of your abilities, of your expertise. And it's funny that I am speaking here before you today in a place of complete sort of self-doubt and despair and not knowing what I'm doing at all, and I feel like I have zero expertise to impart on you. And so in that sense, it's a funny position to be speaking with, especially some of the lessons, some of the advice I'll try to give, so take that with a grain of salt. And some of you sitting in the audience today may be at the very peak, especially if you're at the beginning of the college journey, university journey, and I'd say to me the biggest positive, the biggest impact of college and university education is the dismantling of the ego that's involved in going from that peak over confidence to the valley of despair that I'm currently in. Oh, and I should mention that this is also the time for me and perhaps for you where folks like Dostoevsky start making a lot of sense, talking about suffering and pain and how the really great men and women must, I think, as he says, have great sadness on earth. This resonates with everybody in their undergraduate years in engineering. Now, the real thing I'd like to talk about is the broader optimization problem formed formed by the Dunning-Kruger effect, which is after the peak of confidence and the valley of despair, there's a gradient provided to you by your advisors, by your parents, by your friends, your loved ones, society in general, the gradient over which you're optimized to achieve some definition of success. This is what I call the local optimum, what everybody else tells you you're supposed to do, what everybody else at the small scale, on a daily scale, and on the weekly scale, monthly, yearly, and for the rest of your life tells you what the definition of success is. That's the local optimum. What I'd like to argue is some ideas of how to break out of that convention, of how to listen just enough to hear the lessons in society, advisors, friends, and parents, but for the rest of it, ignore their voices and only listen to your own voice. And I'll tell you through my own story here. So I was introduced as a research scientist at MIT, and very recently I decided to step down from MIT to do my own startup. I'm still affiliated there, but sort of give up the salary, give up everything, give up what I'm supposed to be, the definition under academic colleagues of what success is, of what the pursuit of the academic life is, because I'm listening to the voice inside. And so I'm speaking to you at the very beginning of this journey, again, full of self-doubt, and so take with it with a grain of salt, but perhaps it's interesting to speak from this position, because I would argue it's the most beautiful position to be in in life. The opportunity, the freedom in the struggles that I'm undergoing now is really a gift that comes at the end of this journey of college. Now, who am I and what is the dream that I mentioned there at the end? The global optimum. For me, that's understanding the human mind and engineering, artificial intelligence, artificial intelligence systems. Visualized on the left here is just three percent of the neurons in the human brain. It's a mysterious, beautiful thing. It's easy to forget how little we know about this mystery that's just between our two ears. And engineering machines that can reason, that can think, that can perceive the world, is one of the ways we can understand this mysterious, beautiful thing that brings to life everything around us. And the dream of creating intelligence systems, companions, ones that you can have a deep connection with, that's what drives me. That's my startup work. That's what my entrepreneurship work, that's my research work is focused on. Most of the work at MIT and before that has been on robotics and autonomous vehicles, but now the dream is to create a system that you can love and that can love you back. A brief history of artificial intelligence to give you a sense, to give you a quick review if this is a totally new field. Again, if you're undergraduate, perhaps this is a field that you want to take on as your journey. So it started on the theoretical end with Alan Turing and many of the ideas from philosophy to mathematics that he presented and from whom the field was born. And on the engineering side, Frank Crosonblatt and building the Perceptron, the first machine. So engineering machines that can do some aspect of learning, some aspect of search that we associate with artificial intelligence. And then there's been accomplishments throughout, none greater, at least to me, than in this, at least for now, in a span of games. There's been two branches of artificial intelligence that have dominated the field. The early days have been, you can think of a search, it's brute force search. It's not quite as captivating to our imagination. It doesn't quite feel like intelligence because it's brute force searching through possible answers until you find one that's optimal. It's converting every single problem into a search problem and then bringing computational power to it to try to solve it. But nevertheless, the peak of that, especially for those who play chess, especially for those who might be a Russian, is when IBM Dblue defeated Garry Kasparov in 1997. This is a seminal moment in artificial intelligence where the game that was associated with thought, with intelligence, with reason, was overcome, was the greatest champion and human champion was defeated by a machine. And the seminal moment on the second branch of artificial intelligence, which is learning systems, systems that learn from scratch, knowing nothing, with zero human assistance, was able to defeat the greatest player in the world. Little side note, the first moment did have human assistance in the AlphaGo system from DeepMind and Google DeepMind. And then the follow on a few months later, the system called AlphaZero was able to learn from scratch by playing itself. This is, to me, the greatest accomplishment of artificial intelligence. And I'll mention when I discuss it about open problems in the field. And then in a real world application, like I said, I worked a lot in autonomous vehicles. This is one of the most exciting applications with autonomous and semi-autonomous vehicles. There's been deployments, lessons, explorations, a lot of different debates. This is the most exciting space of artificial intelligence. If you want to have an impact as an engineer, autonomous vehicles is the space you will do so in the next, in the 2020s. And a quick whirlwind overview of key ideas in artificial intelligence that were key breakthroughs. So neural networks and Perceptron, like I said, was born in the 40s, 50s, and 60s with the algorithms that dominate today's world of deep learning and machine learning have been invented in many, many decades ago in the 70s and 80s with convolutional for the computer vision aspect of things in the 80s and 90s with LSTM, our recurrent neural networks, they work with language, work with sequence of data, were developed in the 90s and proven out in the aughts and then did deep learning, quote unquote, revolution. The term and the ideas of large scale machine learning using neural networks was reborn in 2006 in the early aughts and then proven out in the seminal image net moment when computer vision systems were able to, in the challenge of object recognition, image recognition, and the image net data set, the image net challenge, neural networks were able to far outperform the competition and do so easily from just learning from data. And a few other developments, there's a lot of unsupervised learning, self-supervised learning ideas that were born in the 14, 15, 16, just a few years ago, and a lot of exciting ideas in the past few years. The past few years have been dominated by ideas in natural language processing with ideas of transformers. Anyway, this might be outside the scope of what you're familiar with. I encourage you to look into it. Transformers in particular with natural language is some of the most beautiful and exciting ideas that without any human supervision, you can learn to model language sufficiently well to outperform anything we've done previously, to do things like machine translation to a level that's unprecedented. It's really exciting. And especially exciting is that bigger is better, meaning that as long as we can scale compute, we can perform better and better and better. And it's a totally open question how, what the ceiling of that is. And finally, the most exciting thing in artificial intelligence is the idea, you know, there's a concept of Big Bang for the start of the universe, a silly name for one of the most incredible mysteries of our human existence. Same way self-play is one of the silliest names for one of the most powerful ideas in artificial intelligence. It's the mechanism behind Alpha Zero. It's a system playing against itself to improve continuously without any human supervision. That is the most exciting aspect, the most exciting area that I'm excited and I recommend if you love learning, that you explore. So the open problems in artificial intelligence and possible solutions, and one of the things, and I'll focus on number four, which is something that I am, that is my dream, that is sort of my life aspiration, but I'll give a whirlwind introduction. Learning to learn, learning to understand, learning to act, reason, and a deep connection between humans and AI systems. So learning to understand, there's a lot of exciting possibilities here. This is, a lot of the breakthroughs in machine learning have been in something called supervised learning, where you have a set of data and you have a neural network or a model that's able to learn from that data in order to generalize sufficiently to infer on cases it hasn't seen before. You could recognize cat versus dog. In the case of domain, in the domains of like autonomous driving, you can recognize lane markings, you could recognize other vehicles, pedestrians, all the different subtasks involved in solving a particular problem. Now that's all good, but to solve real world problems, you have to actually, you have to deal with endless edge cases that we human beings effortlessly take care of, that our ability to do reasoning and common sense reasoning effortlessly takes care of. So to be able to learn over all those edge cases, you have to do much larger scale learning, and for that you have to be much more selective and clever about which data you annotate with human beings, and that's the idea of active learning. Same way with, as children, we explore the world, we interact with the world to pick up the lessons from it. The same way you can interact with a data set to select only small parts of it to learn from. And I'll take Tesla, which is a car company that's using autonomous driving and its system autopilot that uses deep learning to learn how to solve all these different problems. I'll use them as a case study. What they're doing is quite interesting in the space of active learning. They're creating a pipeline for each individual task. They take the task of driving and break it apart into now over a hundred different subtasks. Each subtask gets its own pipeline, its own data set, and there's a machine learning system that learns from that data set and is then deployed back into the vehicles, and when the vehicle fails in a particular case, that's an edge case that's marked for the system and is brought back to the pipeline to annotate. So there's an ongoing pipeline that continuously goes on. The system is not very good in the beginning, but the whole purpose of it is to discover edge cases. In the same way that us humans learn something, and you can think of our actual existence in the world as an edge case discovery mechanism. So you learn something, you construct a mental model of the world, and you move about the world until you run up against a case, a situation that you totally didn't expect. And we do that thousands of times a day still, and we learn from those. And that pipeline of active learning is a really exciting area that very few people are working on, especially in the space of research. To me, that's the most exciting in terms of scale impact area in the next few years. Learning to act, the second set of open problems in artificial intelligence. This is where the idea of self-play comes in. Is learning to build systems, whether through a reinforcement learning mechanism or otherwise, that are actually acting in the world. In the case of self-play, the idea is that you have a really dumb system in the beginning that knows nothing. Again, no human supervision. And through randomization, you have other systems that also know nothing, but know a different set of nothing. And they compete against each other. So you formulate the problem as a competitive setting. And when you have two dumb systems that compete against each other, a magical thing happens. The one that's slightly less dumb starts winning. And this little incremental step can be repeated arbitrarily and without any constraints on human supervision, annotation costs, without any constraints on having to sort of bring the human in the loop or bring the physical world in the loop. It can all be done in computation in a distributed sense. So you can, in a matter of hours on a distributed compute setting, create a system that beats the world champion at go. And in fact, with DeepMind and all the games that have they've defeated the world champion in chess, not just the world champion, is the best chess playing program, Stockfish, in a matter of hours of training. And the ceiling hasn't yet been reached. This is both the exciting and the scary thing about self-play is very few times is the ceiling ever reached. What we hit is the limits of our computational power, which is computation power, especially the kind of mechanisms that are happening now, developments happening now. The Moore's law is continuing in many ways. So computation, if you just wait a few years, computation is increasing. So we were yet to see the ceiling of the capabilities that these approaches are able to achieve. This should be both exciting and terrifying. Okay. The total biggest open problem that nobody even knows how to do. There's, this is an example of a state-of-the-art dog intelligence system solving a particular problem. So we know nothing how to do about how to do reasoning systems in artificial intelligence. This is the actually not very often talked about area because nobody knows what to do about it. There's been subsets called program synthesis communities that kind of try to formulate a subset of the reasoning problem and try to solve it. But we don't know much to do, don't know much to do, particularly common sense reasoning, how to formulate enough about the world to be able to reason about the physics of the world, about the basic, especially with human beings, human to human, human to physical world dynamics. Just there's millions of facts seemingly that are intricately connected that we learn and we accumulate in a knowledge base. This process is a really exciting area of research that nobody knows what to do with. The things I've described previously don't really have anything to do with humans necessarily. The, my passion and my interest is that space between machine and human. The community broadly could be called human robot interaction, but there's a lot of different areas in which there's a deep connection between the human and machine that you all experience every day. So recommender systems from Netflix to much more importantly social networks, the recommendation engines behind social networks, recommending what you see next in terms of both advertisement and about the content of your friends that you see, which friends you get to see more from. The personalization of IOT of smart systems, semi-autonomous systems like Tesla autopilot and different semi-autonomous vehicles like the Cadillac super cruise systems. Whenever you have AI systems between you and a machine. So there is a machine that does, that automates some particular task. There's you human that are tasked with sitting there and supervising the machine. And there is an AI system in the middle that manages that and manages the tension, the dance, the uncertainty, the human, all the, the T word, the trust, all the mess of human beings. It manages that, that that's a really exciting space that is in the very early days. What I show there is what where my sense is, where we stand in 1998, there was a lot of search engines. Some of you may even be old enough to have used them. AltaVista, Excite, AskG is like us and so on. Then Google came along the Google search engine and blew them all out of the water. They were all working on a very interesting, very important problem, but the approach and the fundamental ideas behind their approach was flawed. I believe that personal assistance and a personal deep meaningful connection between an AI system and a human being is that's exactly where we're at. Many people have in their home an Alexa device, a Google home device, but most people don't use it for almost anything except to play music or check the weather. Many of you use Twitter and social networks, but artificial intelligence plays a minimal role and understands almost nothing about you in recommending how you interact with the platform or the advertisements you see. And autonomous vehicles, robotics platforms, know almost nothing about you. So shown there is the Tesla vehicle. It knows almost nothing about you except whether your hands are on the steering wheel or not. It's, I believe it'll be obvious in retrospect how much opportunity there is to learn about human beings from the devices and from that to form a deep meaningful connection. So now to return to my valley of despair to give some words of advice and again take them with a grain of salt. So in this context, in this optimization context, my first piece of advice is to listen to your inner voice. I think a lot of people, including a lot of very smart professors, advisors, parents, friends, significant others, have in them a kind of mutually agreed upon gradient along which they push you. It's so difficult for me to articulate this in a clear way, but early on I heard within myself a silly sounding crazy voice that told me to do things, one of which was to try to put a robot in every home. There's dreams that are difficult for me to articulate, but if you allow your mind to be quiet enough you'll hear such voices, you'll hear such dreams, and it's important to really listen and to pursue them. Advice number two is carve your own path, and if that means taking a few detours, take the detours. Again, this is coming from the valley of despair. So I hope this pans out in the end, but I had many detours. In music, I was in a band, I had long hair. I gave a lot of myself to the practice of martial arts, and both music and martial arts have given me, again very difficult to put into words, but have given me something quite profound. It gave flavor and color to the pursuit of that dream that's hard to articulate. It's because I listened to my instinct, listened to my heart in pursuing these detours. From poetry to excessive reading, like I mentioned, I took a James Joyce course here, so pursuing these avenues of knowledge through philosophy and history that seemingly have nothing to do with the main pursuit, and starting the silliest of pursuits, starting a podcast. Advice number three is to measure passion, not progress. So most of us get an average of about 27,000 days of life. I think a good metric by which you should live is to maximize the number of those days that are filled with a passionate pursuit of something, not by how much you've progressed towards a particular goal, because goals are grounded in your comparison to other human beings, to something that's already been done before. A passionate pursuit of something is the way you achieve something totally new. And a quick warning about passion. Again, I'm a little bit Russian, so maybe I romanticize this whole suffering and passion thing. But the people who love you, the people who care for you, like I mentioned, your friends, your family, should not be trusted. Accept their love, but not their advice. Parents and significant others will tell you to find a secure job, because passion looks dangerous. It looks insecure. Advisors, colleagues will tell you to be pragmatic, because passion looks like a distraction from the main effort that you should be focusing on. And society will tell you to be a little bit more pragmatic, because it's a distraction. And society will tell you to find balance, work-life balance in your life, because passion looks unhealthy. Advice number four, continuing on the unhealthy part, is work hard. Make a habit of working hard every day, putting in the hours. There's a lot of books and a lot of advice that have been written on working smart and not working hard. I'm yet to meet anyone who has not truly worked hard for thousands of hours in order to accomplish something great. In order to work smart, you first have to put in those few tens of thousands of hours of really dumb, brute force, hard work of all-nighters. The key there is to minimize stress, not to minimize the amount of hours of work. And to do that, you have to love what you do. And the final piece of advice, I love that picture, okay, is to look up to the stars and appreciate every single moment you're alive, at the mystery of this world, at the beauty of this world, and to appreciate the moments that you're living in. Again, this is my perspective, take it with a grain of salt, but I advise to forever oscillate between deep, profound doubt and self-dissatisfaction and a deep gratitude for the moment, for just being alive, for all the people around you that give you their love, with whom you get to share those moments, you share the love. A poem by Stephen Crane that I especially like in the desert. In the desert I saw a creature, a naked bestial, who squatting upon the ground held his heart in his hands and ate of it. I said, is it good, friend? It is bitter, bitter, he answered, but I like it, because it is bitter and because it is my heart. So I would say the bitter is the self-dissatisfaction, that's the restless energy that drives us forward. And then enjoying that bitterness and enjoying the moment and enjoying the sweetness that comes from eating your own heart in this poem is a thing that makes life worthwhile. And that is, to me, happiness. So with those silly few pieces of advice, I'd like to continue on the gratitude and say thank you. Thank you to my advisor, thank you to this university for giving me a helping hand, there you go. And thank you to my family and all the friends that I've had along the way. Thank you for their love. I appreciate it. I've never been introduced with this much energy, I really appreciate it. You're hanging out at the wrong places, man. Yes. First of all, great to see you in person, Dr. Kristin Peter. Big fan of your lectures, big fan of your show and television podcast. Just listening to your conversation on these small things, I'm so grateful. I'm so grateful for the opportunity to be here. My question for you was, is your perspective in any way influenced by the ultimate meaninglessness of it all? By the way, thank you for that question. How is your daily life affected by the meaninglessness of it all? I'm not sure I can answer that. I'm not sure I can answer that. So the answer is yes, and it's hard to use reason to justify that life is meaningful. I think you have to listen to, like, there's something in you that makes life beautiful. So if you look at somebody like Elon Musk, he believes that interplanetary, so colonizing Mars, is like, that's like one of the most exciting things we human beings can do. And so if you allow yourself to think, what is the most exciting thing that we human beings can do? And see that the work you're doing is part of that. For me, like if I were to psychoanalyze myself, there's something in me that's deeply fulfilling about creating intelligent systems. That's so exciting to me, that we human beings can create intelligent systems. I see artificial intelligence as the next evolution of human civilization. And to me, that makes it somehow deeply exciting, even though eventually the whole universe will collapse on itself or the other, the cold death of the universe. There's something within that that's so exciting. There was an interview with Elon Musk, and he basically said that we're in a civilization, so this might not be actual reality. What's your take on that? So my first take is, I love it how much fellow colleagues and scientists are uncomfortable with this question. So I love it. I love to ask it just because it makes them uncomfortable. Yeah, I appreciate it. It's a good like, I don't know, maybe in like French cuisine, you have to like cleanse the palate. It's a good question to ask, like, we're not now talking about the latest paper. We're now talking about the bigger questions of life. The simulation question is a nice one to do that. In terms of actually practically, I think there's two interesting things to say. So one, it's interesting to me, I'm a big fan of virtual reality. I love entering worlds, even primitive as they are now, that are virtual. I can already imagine that more and more people would want to live in those worlds. It's an interesting question to me. How real do those worlds need to become in order for you to want to stay there and not return to the real world? So the question of the simulation is, how real do we need to simulate the world in order for you to enjoy it better than this one? That's a computer science question. That's really interesting. That's a, it's a, it's like a practical engineering question because you can create virtual reality systems that will make a lot of money, perhaps have a detrimental effect on society by having people want to stay in the virtual world. And then the other question is the physics question of quantum mechanics of like, what is the fundamental fabric of reality? And is it, you know, what does it take to simulate that reality? And that's like a physics question. How is it finite? Is it infinite? What are the mechanisms, the underlying mechanisms? Does it go as low as string theory? Does it go below string theory? And there's actually people that have written papers on how big a computer needs to be in order to simulate that kind of system. And now quantum computers are coming forward, which is one of the exciting applications of quantum computing is to be able to simulate quantum mechanical systems. And this is the question, how big does a quantum computer have to be to simulate the universe? It's a fun, but a real physics question, way out of reach of our engineering capabilities. But it's just it's not it's a nice party over the beer, over beers thing to bring up with scientists. There's two things that make scientists uncomfortable. I love bringing up one is the simulation question. And the other is, what do you think about the idea that's become popular recently that the Earth might be flat? They get really, they get angry, actually. So I want to say, I appreciate your work. I love the podcast and stuff like that. So people talk about athletes and academics being the greatest. People consider Jesse Owens to be one of the greatest runners of all time, even though he's quite outpaced by the runners today. People consider scientists like Isaac Newton, one of the greatest science ever, because of his advancements in classical mechanics and calculus, which is considered pretty basic physics nowadays. What do you define greatness as when it comes to the pursuit of an endeavor? Does it involve looking for the most advancements in the field, given your starting point? Does it come from the journey and the work associated or the destination? Is it a personal concept or is it something you understand across humanity? So thank you for that question. Very well written out and thought out. There's a personal greatness from the perspective of the individual for me. Like for me, greatness is doing what I love. That ignores the rest of society. It's just like to me, I'm the greatest human to have ever lived in my own little world for having to do the things I love. And that's from my perspective. And I love the craftsmanship of it. Anything, it could be anything. It's just doing the skill. So that's not about accomplishment. That's not about anything. That's about just doing the things you love. From the perspective of society, they tend to then tell stories about these pursuits. And they like to like greatness is something that people invent. They give Nobel Prize, they give prizes to accomplishment. They kind of tell stories about human beings, about Steve Jobs, about different icons. And some are completely ignored through history. Some are glorified through history, like over glorified. I recently found out that the Pythagorean theorem was not developed by Pythagoras. I read it on Wikipedia. I don't know if it's true. But, you know, that's an example of somebody I at least thought was kind of an actual entity, an actual human being that was great and associated with this idea. So to me, I think greatness is doing the things you love. And the rest is just luck, whether they tell a good story about you or not. Give it up for our speaker, Dr. Leslie Kemp.

https://youtu.be/5qjA8HPJl_0

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Cristos Goodrow: YouTube Algorithm | Lex Fridman Podcast #68

The following is a conversation with Christos Goudreau, Vice President of Engineering at Google and Head of Search and Discovery at YouTube, also known as the YouTube Algorithm. YouTube has approximately 1.9 billion users, and every day people watch over 1 billion hours of YouTube video. It is the second most popular search engine behind Google itself. For many people, it is not only a source of entertainment, but also how we learn new ideas from math and physics videos, to podcasts, to debates, opinions, ideas, from out-of-the-box thinkers and activists on some of the most tense, challenging, and impactful topics in the world today. YouTube and other content platforms receive criticism from both viewers and creators, as they should, because the engineering task before them is hard, and they don't always succeed, and the impact of their work is truly world-changing. To me, YouTube has been an incredible wellspring of knowledge. I've watched hundreds, if not thousands of lectures that change the way I see many fundamentalist ideas in math, science, engineering, and philosophy. But it does put a mirror to ourselves, and keeps the responsibility of the steps we take in each of our online educational journeys into the hands of each of us. The YouTube algorithm has an important role in that journey of helping us find new, exciting ideas to learn about. That's a difficult and exciting problem for an artificial intelligence system. As I've said in lectures and other forums, recommendation systems will be one of the most impactful areas of AI in the 21st century, and YouTube is one of the biggest recommendation systems in the world. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcasts, follow on Spotify, support it on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. I recently started doing ads at the end of the introduction. I'll do one or two minutes after introducing the episode, and never any ads in the middle that can break the flow of the conversation. I hope that works for you, and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. I personally use Cash App to send money to friends, but you can also use it to buy, sell, and deposit Bitcoin in just seconds. Cash App also has a new investing feature. You can buy fractions of a stock, say $1 worth, no matter what the stock price is. Brokers services are provided by Cash App Investing, a subsidiary of Square and member SIPC. I'm excited to be working with Cash App in the future. I'm also excited to be working with Cash App to support one of my favorite organizations called First, best known for their First Robotics and Lego competitions. They educate and inspire hundreds of thousands of students in over 110 countries, and have a perfect rating, a charity navigator, which means that donated money is used to maximum effectiveness. When you get Cash App from the App Store or Google Play, and use code LEXPODCAST, you can donate $10 and Cash App will also donate $10 to First, which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world. And now, here's my conversation with Christos Goudreau. YouTube is the world's second most popular search engine, behind Google of course. We watch more than 1 billion hours of YouTube videos a day, more than Netflix and Facebook video combined. YouTube creators upload over 500,000 hours of video every day. Average lifespan of a human being just for comparison is about 700,000 hours. So, what's uploaded every single day is just enough for a human to watch in a lifetime. So, let me ask an absurd philosophical question. If from birth, when I was born, and there's many people born today with the internet, I watched YouTube videos nonstop, do you think there are trajectories through YouTube video space that can maximize my average happiness or maybe education or my growth as a human being? I think there are some great trajectories through YouTube videos, but I wouldn't recommend that anyone spend all of their waking hours or all of their hours watching YouTube. I mean, I think about the fact that YouTube has been really great for my kids, for instance. My oldest daughter, she's been watching YouTube for several years. She watches Tyler Oakley and the Vlogbrothers. And I know that it's had a very profound and positive impact on her character. And my younger daughter, she's a ballerina. And her teachers tell her that YouTube is a huge advantage for her because she can practice a routine and watch professional dancers do that same routine and stop and watch it. And the dancers do that same routine and stop it and back it up and rewind and all that stuff. Right? So it's been really good for them. And then even my son is a sophomore in college. He got through his linear algebra class because of a channel called 3Blue1Brown, which helps you understand linear algebra, but in a way that would be very hard for anyone to do on a whiteboard or a chalkboard. And so I think that those experiences, from my point of view, were very good. And so I can imagine really good trajectories through YouTube. Yes. Have you looked at, do you think of broadly about that trajectory over a period? Because YouTube has grown up now. So over a period of years, you just kind of gave a few anecdotal examples. But I used to watch certain shows on YouTube. I don't anymore. I've moved on to other shows. And ultimately, you want people to, from YouTube's perspective, to stay on YouTube, to grow as human beings on YouTube. So you have to think not just what makes them engage today or this month, but also over a period of years. Absolutely. That's right. I mean, if YouTube is going to continue to enrich people's lives, then it has to grow with them and people's interests change over time. And so I think we've been working on this problem. And I'll just say it broadly as like, how to introduce diversity and introduce people who are watching one thing to something else they might like. We've been working on that problem all the eight years I've been at YouTube. It's a hard problem because, I mean, of course, it's trivial to introduce diversity that doesn't help. Yeah. Right. I had a random video. I could just randomly select a video from the billions that we have. It's likely not to even be in your language. So the likelihood that you would watch it and develop a new interest is very, very low. And so what you want to do when you're trying to increase diversity is find something that is not too similar to the things that you've watched, but also something that you might be likely to watch. And that balance, finding that spot between those two things is quite challenging. So the diversity of content, diversity of ideas, it's a really difficult, it's a thing like that's almost impossible to define, right? Like what's different? So how do you think about that? So two examples is I'm a huge fan of three blue, one brown, say, and then one diversity. I wasn't even aware of a channel called Veritasium, which is a great science, physics, whatever channel. So one version of diversity is showing me Derek's Veritasium's channel, which I was really excited to discover. I actually now watch a lot of his videos. Okay. So you're a person who's watching some math channels, and you might be interested in some other science or math channels. So like you mentioned, the first kind of diversity is just show you some things from other channels that are related, but not just, you know, not all the three blue, one brown channel, throw in a couple others. So that's the maybe the first kind of diversity that we started with many, many years ago. Taking a bigger leap is about, I mean, the mechanisms we use for that is, we basically cluster videos and channels together, mostly videos. We do every, almost everything at the video level. And so we'll make some kind of a cluster via some embedding process, and then measure, you know, what is the likelihood that users who watch one cluster might also watch another cluster that's very distinct. So we may come to find that people who watch science videos also like jazz. This is possible, right? And so, because of that relationship that we've identified through the embeddings and then the measurement of the people who watch both, we might recommend a jazz video once in a while. So there's this clustering in the embedding space of jazz videos and science videos. And so you kind of try to look at aggregate statistics where if a lot of people that jump from science cluster to the jazz cluster tend to remain as engaged or become more engaged, then that means those two are, they should hop back and forth and they'll be happy. Right. There's a higher likelihood that a person from, who's watching science would like jazz than the person watching science would like, I don't know, backyard railroads or something else, right? And so we can try to measure these likelihoods and use that to make the best recommendation we can. So, okay. So we'll talk about the machine learning of that, but I have to linger on things that neither you or anyone have an answer to. There's gray areas of truth, which is, for example, now I can't believe I'm going there, but politics. But politics, it happens so that certain people believe certain things and they're very certain about them. Let's move outside the red versus blue politics of today's world. But there's different ideologies. For example, in college, I read quite a lot of Ayn Rand. I studied, and that's a particular philosophical ideology I found interesting to explore. Okay. So that was that kind of space. I've kind of moved on from that cluster intellectually, but it nevertheless is an interesting cluster. I was born in the Soviet Union. Socialism, communism is a certain kind of political ideology that's really interesting to explore. Again, objectively, there's a set of beliefs about how the economy should work and so on. And so it's hard to know what's true or not in terms of people within those communities are often advocating that this is how we achieve utopia in this world. And they're pretty certain about it. So how do you try to manage politics in this chaotic, divisive world? Not positive or any kind of ideas, in terms of filtering what people should watch next and in terms of also not letting certain things be on YouTube. This is exceptionally difficult responsibility. Well, the responsibility to get this right is our top priority. And the first comes down to making sure that we have good, clear rules of the road, right? Like just because we have freedom of speech doesn't mean that you can literally say anything, right? Like we as a society have accepted certain restrictions on our freedom of speech. There are things like libel laws and things like that. And so where we can draw a clear line, we do, and we continue to evolve that line over time. However, as you pointed out, wherever you draw the line, there's going to be a borderline. And in that borderline area, we are going to maybe not remove videos, but we will try to reduce the recommendations of them or the proliferation of them by demoting them. And then alternatively, in those situations, try to raise what we would call authoritative or credible sources of information. So we're not trying to, I mean, you mentioned Ayn Rand and communism. You know, those are two like valid points of view that people are going to debate and discuss. And of course, people who believe in one of those things are going to try to persuade other people to their point of view. And so we're not trying to settle that or choose a side or anything like that. What we're trying to do is make sure that the people who are expressing those point of view and offering those positions are authoritative and credible. So let me ask a question about people I don't like personally. You heard me, I don't care if you leave comments on this. But sometimes they're brilliantly funny, which is trolls. So people who kind of mock, I mean, the internet is full of Reddit of mock style comedy, where people just kind of make fun of, point out that the emperor has no clothes. And there's brilliant comedy in that, but sometimes it can get cruel and mean. So on that, on the mean point, and sorry to linger on these things that have no good answers, but actually I totally hear you that this is really important and you're trying to solve it. But how do you reduce the meanness of people on YouTube? I understand that anyone who uploads YouTube videos has to become resilient to a certain amount of meanness. I've heard that from many, many people. Meanness, like I've heard that from many creators and we are trying in various ways, comment ranking, allowing certain features to block people, to reduce or make that meanness or that trolling behavior less effective on YouTube. And so, I mean, it's very important, but it's something that we're gonna keep having to work on. And as we improve it, like maybe we'll get to a point where people don't have to suffer this sort of meanness when they upload YouTube videos. I hope we do, but it just does seem to be something that you have to be able to deal with as a YouTube creator nowadays. Do you have a hope that, so you mentioned two things that I kind of agree with. So there's like a machine learning approach of ranking comments based on whatever, based on how much they contribute to the healthy conversation, let's put it that way. And the other is almost an interface question of how does the creator filter, so block, or how do humans themselves, the users of YouTube manage their own conversation? Do you have hope that these two tools will create a better society without limiting freedom of speech too much, without sort of, and even like saying that, people are like, what do you mean limiting? Sort of curating speech. I mean, I think that that overall is our whole project here at YouTube. Right. Like we fundamentally believe, and I personally believe very much that YouTube can be great. It's been great for my kids. I think it can be great for society, but it's absolutely critical that we get this responsibility part right. And that's why it's our top priority. Susan Wojcicki, who's the CEO of YouTube, she says something that I personally find very inspiring, which is that we wanna do our jobs today in a manner so that people 20 and 30 years from now will look back and say, you know, YouTube, they really figured this out. They really found a way to strike the right balance between the openness and the value that the openness has, and also making sure that we are meeting our responsibility to users in society. So the burden on YouTube actually is quite incredible. And the one thing that people don't give enough credit to the seriousness and the magnitude of the problem, I think. So I personally hope that you do solve it because a lot is in your hand. A lot is riding on your success or failure. So it's besides, of course, running a successful company, you're also curating the content of the internet and the conversation on the internet. That's a powerful thing. So one thing that people wonder about is how much of it can be solved with pure machine learning. So looking at the data, studying the data and creating algorithms that curate the comments, curate the content, and how much of it needs human intervention. Meaning people here at YouTube in a room sitting and thinking about what is the nature of truth? What are the ideals that we should be promoting? That kind of thing. So algorithm versus human input. What's your sense? I mean, my own experience has demonstrated that you need both of those things. Algorithms, I mean, you're familiar with machine learning algorithms, and the thing they need most is data. And the data is generated by humans. And so for instance, when we're building a system to try to figure out which are the videos that are misinformation or borderline policy violations, well, the first thing we need to do is get human beings to make decisions about which of those videos are in which category. And then we use that data and basically, you know, take that information that's determined and governed by humans and extrapolate it or apply it to the entire set of billions of YouTube videos. And we couldn't get to all the videos on YouTube well without the humans. And we couldn't use the humans to get to all the videos of YouTube. So there's no world in which you have only one or the other of these things. And just as you said, a lot of it comes down to people at YouTube spending a lot of time trying to figure out what are the right policies? What are the outcomes based on those policies? Are they the kinds of things we wanna see? And then once we kind of get an agreement or build some consensus around what the policies are, well, then we've gotta find a way to implement those policies across all of YouTube. And that's where both the human beings, we call them evaluators or reviewers, come into play to help us with that. And then once we get a lot of training data from them, then we apply the machine learning techniques to take it even further. Do you have a sense that these human beings have a bias in some kind of direction? Sort of, I mean, that's an interesting question. We do sort of in autonomous vehicles and computer vision in general, a lot of annotation. And we rarely ask what bias do the annotators have? Even in the sense that they're better at annotating certain things than others. For example, people are much better at, for annotating segmentation, at segmenting cars in a scene versus segmenting bushes or trees. There's specific mechanical reasons for that, but also because it's semantic gray area and just for a lot of reasons, people are just terrible at annotating trees. Okay, so in that same kind of sense, do you think of, in terms of people reviewing videos or annotating the content of videos, is there some kind of bias that you're aware of or seek out in that human input? Well, we take steps to try to overcome these kinds of biases or biases that we think would be problematic. So for instance, we ask people to have a bias towards scientific consensus. That's something that we instruct them to do. We ask them to have a bias towards demonstration of expertise or credibility or authoritativeness. But there are other biases that we wanna make sure to try to remove. And there's many techniques for doing this. One of them is you send the same thing to be reviewed to many people. And so that's one technique. Another is that you make sure that the people that are doing these sorts of tasks are from different backgrounds and different areas of the United States or of the world. But then even with all of that, it's possible for certain kinds of what we would call unfair biases to creep into machine learning systems, primarily, as you said, because maybe the training data itself comes in in a biased way. And so we also have worked very hard on improving the machine learning systems to remove and reduce unfair biases when it goes against or has involved some protected class, for instance. Thank you for exploring with me some of the more challenging things. I'm sure there's a few more that we'll jump back to, but let me jump into the fun part, which is maybe the basics of the quote unquote YouTube algorithm. What does the YouTube algorithm look at to make recommendation for what to watch next? And it's from a machine learning perspective, or when you search for a particular term, how does it know what to show you next? Because it seems to, at least for me, do an incredible job of both. Well, that's kind of you to say, it didn't used to do a very good job, but it's gotten better over the years. Even I observed that it's improved quite a bit. Those are two different situations. Like when you search for something, YouTube uses the best technology we can get from Google to make sure that the YouTube search system finds what someone's looking for. And of course, the very first things that one thinks about is, okay, well, does the word occur in the title, for instance? But there are much more sophisticated things where we're mostly trying to do some syntactic match or maybe a semantic match based on words that we can add to the document itself. For instance, maybe is this video watched a lot after this query, right? That's something that we can observe. And then as a result, make sure that that document would be retrieved for that query. Now, when you talk about what kind of videos would be recommended to watch next, that's something, again, we've been working on for many years. And probably the first real attempt to do that well was to use collaborative filtering. So you- Can you describe what collaborative filtering is? Sure. It's just, basically what we do is we observe which videos get watched close together by the same person. And if you observe that, and if you can imagine creating a graph where the videos that get watched close together by the most people are sort of very close to one another in this graph, and videos that don't frequently get watched close together by the same person or the same people are far apart, then you end up with this graph that we call the related graph that basically represents videos that are very similar or related in some way. And what's amazing about that is that it puts all the videos that are in the same language together, for instance. And we didn't even have to think about language. It just does it, right? And it puts all the videos that are about sports together, and it puts most of the music videos together, and it puts all of these sorts of videos together just because that's sort of the way the people using YouTube behave. So that already cleans up a lot of the problem. It takes care of the lowest hanging fruit, which happens to be a huge one of just managing these millions of videos. That's right. I remember a few years ago, I was talking to someone who was trying to propose that we do a research project concerning people who are bilingual. And this person was making this proposal based on the idea that YouTube could not possibly be good. at recommending videos well to people who are bilingual. And so she was telling me about this, and I said, well, can you give me an example of what problem do you think we have on YouTube with the recommendations? And so she said, well, I'm a researcher in the US, and when I'm looking for academic topics, I want to see them in English. And so she searched for one, found a video, and then looked at the Watch Next suggestions, and they were all in English. And so she said, oh, I see, YouTube must think that I speak only English. And so she said, now, I'm actually originally from Turkey, and sometimes when I'm cooking, let's say I want to make some baklava, I really like to watch videos that are in Turkish. And so she searched for a video about making the baklava, and then selected it, and it was in Turkish, and the Watch Next recommendations were in Turkish. And she just couldn't believe how this was possible. And how is it that you know that I speak both these two languages and put all the videos together, and it's just as a sort of an outcome of this related graph that's created through collaborative filtering? So for me, one of my huge interests is just human psychology, right? And that's such a powerful platform on which to utilize human psychology to discover what people, individual people want to watch next. But it's also be just fascinating to me because it's fascinating to me. You know, I've, Google search has ability to look at your own history. And I've done that before, just what I've searched, three years, for many, many years. And it's a fascinating picture of who I am, actually. And I don't think anyone's ever summarized, I personally would love that, a summary of who I am as a person on the internet to me. Because I think it reveals, I think it puts a mirror to me or to others, you know, that's actually quite revealing and interesting. You know, just maybe the number of, it's a joke, but not really, is the number of cat videos I've watched or videos of people falling, you know, stuff that's absurd, that kind of stuff. It's really interesting. And of course, it's really good for the machine learning aspect to figure out what to show next. But it's interesting. Have you just as a tangent, played around with the idea of giving a map to people, sort of, as opposed to just using this information to show what's next, showing them, here are the clusters you've loved over the years kind of thing. Well, we do provide the history of all the videos that you've watched. Yes. So you can definitely search through that and look through it and search through it to see what it is that you've been watching on YouTube. We have actually, in various times, experimented with this sort of cluster idea, finding ways to demonstrate or show people what topics they've been interested in or what clusters they've watched from. It's interesting that you bring this up because in some sense, the way the recommendation system of YouTube sees a user is exactly as the history of all the videos they've watched on YouTube. And so you can think of yourself or any user on YouTube as kind of like a DNA strand of all your videos, right? That sort of represents you. You can also think of it as maybe a vector in the space of all the videos on YouTube. And so, now once you think of it as a vector in the space of all the videos on YouTube, then you can start to say, okay, well, which other vectors are close to me and to my vector? And that's one of the ways that we generate some diverse recommendations is because you're like, okay, well, these people seem to be close with respect to the videos they watched on YouTube, but here's a topic or a video that one of them has watched and enjoyed, but the other one hasn't. That could be an opportunity to make a good recommendation. I gotta tell you, I mean, I know, I'm gonna ask for things that are impossible, but I would love to cluster them human beings. Like I would love to know who has similar trajectories as me because you probably would wanna hang out, right? There's a social aspect there. Like actually finding some of the most fascinating people I find on YouTube have like no followers and I start following them and they create incredible content. And on that topic, I just love to ask, there's some videos that just blow my mind in terms of quality and depth and just in every regard are amazing videos and they have like 57 views. Okay, how do you get videos of quality to be seen by many eyes? So the measure of quality, is it just something? Yeah, how do you know that something is good? Well, I mean, I think it depends initially on what sort of video we're talking about. So in the realm of let's say, you mentioned politics and news. In that realm, quality news or quality journalism relies on having a journalism department, right? Like you have to have actual journalists and fact checkers and people like that. And so in that situation and in others, maybe science or in medicine, quality has a lot to do with the authoritativeness and the credibility and the expertise of the people who make the video. Now, if you think about the other end of the spectrum, what is the highest quality prank video? Or what is the highest quality Minecraft video? Yeah. That might be the one that people enjoy watching the most and watch to the end. Or it might be the one that when we ask people the next day after they watched it, were they satisfied with it? And so we, especially in the realm of entertainment, have been trying to get at better and better measures of quality or satisfaction or enrichment since I came to YouTube. And we started with, well, the first approximation is the one that gets more views. But we both know that things can get a lot of views and not really be that high quality, especially if people are clicking on something and then immediately realizing that it's not that great and abandoning it. And that's why we move from views to thinking about the amount of time people spend watching it, with the premise that in some sense, the time that someone spends watching a video is related to the value that they get from that video. It may not be perfectly related, but it has something to say about how much value they get. But even that's not good enough, right? Because I myself have spent time clicking through channels on television late at night and ended up watching Under Siege 2 for some reason I don't know. And if you were to ask me the next day, are you glad that you watched that show on YouTube? If you watched that show on TV last night, I'd say, yeah, I wish I would have gone to bed or read a book or almost anything else, really. And so that's why some people got the idea a few years ago to try to survey users afterwards. And so we get feedback data from those surveys and then use that in the machine learning system to try to not just predict what you're going to click on right now, what you might watch for a while, but what when we ask you tomorrow, you'll give four or five stars to. So just to summarize, what are the signals from a machine learning perspective that the user can provide? So you mentioned just clicking on the video views, the time watched, maybe the relative time watched, the clicking like and dislike on the video, maybe commenting on the video. All of those things. All of those things. All of those things and then the one I wasn't actually quite aware of, even though I might've engaged in it, is a survey afterwards, which is a brilliant idea. Is there other signals? I mean, that's already a really rich space of signals to learn from. Is there something else? Well, you mentioned commenting, also sharing the video. If you think it's worthy to be shared with someone else, you know. Within YouTube or outside of YouTube as well? Either. Either. Let's see, you mentioned like, dislike. Yeah, like and dislike. How important is that? It's very important, right? We want, it's predictive of satisfaction, but it's not perfectly predictive. Subscribe. If you subscribe to the channel of the person who made the video, then that also is a piece of information and it signals satisfaction. Although over the years, we've learned that people have a wide range of attitudes about what it means to subscribe. We would ask some users who didn't subscribe very much, but they watched a lot from a few channels, we'd say, well, why didn't you subscribe? And they would say, well, I can't afford to pay for anything. And, you know, we tried to let them understand, like, actually it doesn't cost anything, it's free. It just helps us know that you are very interested in this creator. But then we've asked other people who subscribe to many things and don't really watch any of the videos from those channels. And we say, well, why did you subscribe to this if you weren't really interested in any more videos from that channel? And they might tell us, well, I just, you know, I thought the person did a great job and I just wanted to kind of give him a high five. Yeah. And so. Yeah, that's where I sit. I actually subscribe to channels where I just, this person is amazing. I like this person, but then I like this person, I really want to support them. That's how I click subscribe. Right. Even though, I mean, never actually want to click on their videos when they're releasing it. I just love what they're doing. And it's maybe outside of my interest area and so on, which is probably the wrong way to use the subscribe button. But I just want to say congrats. This is great work. So you have to deal with all the space of people that see the subscribe button is totally different. That's right. And so, you know, we can't just close our eyes and say, sorry, you're using it wrong. You know, we're not going to pay attention to what you've done. We need to embrace all the ways in which all the different people in the world use the subscribe button or the like and the dislike button. So in terms of signals of machine learning, using for the search and for the recognition and for the recommendation, you've mentioned title. So like metadata, like text data that people provide, description and title, and maybe keywords. So maybe you can speak to the value of those things in search and also this incredible, fascinating area of the content itself. So the video content itself, trying to understand what's happening in the video. So YouTube released a data set that, you know, in the machine learning computer vision world, this is just an exciting space. How much is that currently, how much are you playing with that currently? How much is your hope for the future of being able to analyze the content of the video itself? Well, we have been working on that also since I came to YouTube. So analyzing the content. Analyzing the content of the video, right? And what I can tell you is that our ability to do it well is still somewhat crude. We can tell if it's a music video, we can tell if it's a sports video, we can probably tell you that people are playing soccer. We probably can't tell whether it's Manchester United or my daughter's soccer team. So these things are kind of difficult and using them, we can use them in some ways. So for instance, we use that kind of information to understand and inform these clusters that I talked about. And also maybe to add some words like soccer, for instance, to the video, if it doesn't occur in the title or the description, which is remarkable that often it doesn't. One of the things that I ask creators to do is please help us out with the title and the description. For instance, we were a few years ago having a live stream of some competition for World of Warcraft on YouTube. And it was a very important competition, but if you typed World of Warcraft in search, you wouldn't find it. World of Warcraft wasn't in the title? World of Warcraft wasn't in the title. It was match 478, A team versus B team, and World of Warcraft wasn't in the title. I'm just like, come on, give me. But being literal on the internet is actually very uncool, which is the problem. Oh, is that right? Well, I mean, it's a very, very, very, well, I mean, in some sense, well, some of the greatest videos, I mean, there's a humor to just being indirect, being witty and so on, and actually being, you know, machine learning algorithms want you to be, you know, literal, right? You just wanna say what's in the thing, be very, very simple. And in some sense, that gets away from wit and humor. So you have to play with both, right? So, but you're saying that for now, sort of the content of the title, the content of the description, the actual text is one of the best ways to, for the algorithm to find your video and put them in the right cluster. That's right. And I would go further and say that if you want people, human beings, to select your video in search, then it helps to have, let's say, World of Warcraft in the title. Because why would a person, you know, if they're looking at a bunch, they type World of Warcraft and they have a bunch of videos, all of whom say World of Warcraft, except the one that you uploaded. Well, even the person is gonna think, well, maybe this isn't, somehow search made a mistake. This isn't really about World of Warcraft. So it's important, not just for the machine learning systems, but also for the people who might be looking for this sort of thing. They get a clue that it's what they're looking for by seeing that same thing prominently in the title of the video. Okay, let me push back on that. So I think from the algorithm perspective, yes, but if they typed in World of Warcraft and saw a video with the title simply winning and the thumbnail has like a sad orc or something, I don't know, right? I think that's much, it gets your curiosity up. And then if they could trust that the algorithm was smart enough to figure out somehow that this is indeed a World of Warcraft video, that would have created the most beautiful experience. I think in terms of just the wit and the humor and the curiosity that we human beings naturally have. But you're saying, I mean, realistically speaking, it's really hard for the algorithm to figure out that the content of that video will be a World of Warcraft video. And you have to accept that some people are gonna skip it. Yeah. Right? I mean, and so you're right. The people who don't skip it and select it are gonna be delighted. But other people might say, yeah, this is not what I was looking for. And making stuff discoverable, I think is what you're really working on and hoping. So yeah. So from your perspective, put stuff in the title of the description. And remember, the collaborative filtering part of the system starts by the same user watching videos together, right? So the way that they're probably gonna do that is by searching for them. That's a fascinating aspect of it. It's like ant colonies. That's how they find stuff. So, I mean, what degree for collaborative filtering in general is one curious ant, one curious user essential? So just the person who is more willing to click on random videos and sort of explore these cluster spaces. In your sense, how many people are just like watching the same thing over and over and over and over? And how many are just like the explorers? Just kind of like click on stuff and then help the other ant in the ant colony discover the cool stuff. Do you have a sense of that at all? I really don't think I have a sense for the relative sizes of those groups. But I would say that, you know, people come to YouTube with some certain amount of intent. And as long as they, to the extent to which they try to satisfy that intent, that certainly helps our systems, right? Because our systems rely on kind of a faithful amount of behavior, right? Like, and there are people who try to trick us, right? There are people and machines that try to associate videos together that really don't belong together, but they're trying to get that association made because it's profitable for them. And so we have to always be resilient to that sort of attempt at gaming the systems. So speaking to that, there's a lot of people that in a positive way, perhaps, I don't know, I don't like it, but like to want to try to game the system, to get more attention. Everybody, creators in a positive sense want to get attention, right? So how do you work in this space when people create more and more sort of click-baity titles and thumbnails? Sort of very to ask him, Derek has made a video where basically describes that it seems what works is to create a high quality video, really good video where people would want to watch it, wants to click on it, but have click-baity titles and thumbnails to get them to click on it in the first place. And he's saying, I'm embracing this fact, I'm just gonna keep doing it, and I hope you forgive me for doing it. And you will enjoy my videos once you click on them. So in what sense do you see this kind of click-bait style attempt to manipulate, to get people in the door to manipulate the algorithm or play with the algorithm or game the algorithm? I think that you can look at it as an attempt to game the algorithm, but even if you were to take the algorithm out of it and just say, okay, well, all these videos happen to be lined up, which the algorithm didn't make any decision about which one to put at the top or the bottom, but they're all lined up there, which one are the people gonna choose? And I'll tell you the same thing that I told Derek is, I have a bookshelf and they have two kinds of books on them, science books. I have my math books from when I was a student, and they all look identical except for the titles on the covers. They're all yellow, they're all from Springer, and they're every single one of them, the cover is totally the same. Yes. Right? On the other hand, I have other more pop science type books, and they all have very interesting covers, right? And they have provocative titles and things like that. I mean, I wouldn't say that they're clickbaity because they are indeed good books. Yeah. And I don't think that they cross any line, but that's just a decision you have to make, right? Like the people who write classical recursion theory by Pierotti-Fredi, he was fine with the yellow title and nothing more. Whereas I think other people who, who wrote a more popular type book understand that they need to have a compelling cover and a compelling title. And, you know, I don't think there's anything really wrong with that. We do take steps to make sure that there is a line that you don't cross. And if you go too far, maybe your thumbnail is especially racy, or, you know, it's all caps with too many, it's all caps with too many exclamation points. We observe that users are kind of, you know, sometimes offended by that. And so for the users who are offended by that, we will then depress or suppress those videos. And which reminds me, there's also another signal where users can say, I don't know if it was recently added, but I really enjoy it. Just saying, I don't, I didn't, something like, I don't want to see this video anymore, or something like, like this is, like there's certain videos that just cut me the wrong way. Like just, just jump out at me. It's like, I don't want to, I don't want this. And it feels really good to clean that up, to be like, I don't, that's not, that's not for me. I don't know. I think that might've been recently added, but that's also a really strong signal. Yes, absolutely. Right. We don't want to make a recommendation that people are unhappy with. And that makes me, that particular one makes me feel good as a user in general, and as a machine learning person, because I feel like I'm helping the algorithm. My interaction on YouTube don't always feel like I'm helping the algorithm. Like I'm not reminded of that fact. Like for example, Tesla and Autopilot, Elon Musk, create a feeling for their customers, for people that own Tesla's, that they're helping the algorithm of Tesla vehicle. Like they're all like a really proud, they're helping the fleet learn. I think YouTube doesn't always remind people that you're helping the algorithm get smarter. And for me, I love that idea. Like we're all collaboratively, like Wikipedia gives that sense. They're all together creating a beautiful thing. YouTube is, doesn't always remind me of that. It's, this conversation is reminding me of that, but. Well, that's a good tip. We should keep that fact in mind when we design these features. I'm not sure I really thought about it that way, but that's a very interesting perspective. It's an interesting question of personalization that I feel like when I click like on a video, I'm just improving my experience. It would be great, it would make me personally, people are different, but make me feel great if I was helping also the YouTube algorithm broadly say something. You know what I'm saying? Like there's a, I don't know if that's human nature, but you want the products you love, and I certainly love YouTube. Like you want to help it get smarter and smarter and smarter because there's some kind of coupling between our lives together being better. If YouTube was better than I will, my life will be better. And there's that kind of reasoning. I'm not sure what that is. And I'm not sure how many people share that feeling. That could be just a machine learning feeling. But on that point, how much personalization is there in terms of next video recommendations? So is it kind of all really boiling down to clustering? Like if I'm in your clusters to me and so on, and that kind of thing, or how much is personalized to me, the individual completely? It's very, very personalized. So your experience will be quite a bit different from anybody else's who's watching that same video, at least when they're logged in. And the reason is, is that we found that users often want two different kinds of things when they're watching a video. Sometimes they want to keep watching more on that topic or more in that genre. And other times they just are done and they're ready to move on to something else. And so the question is, well, what is the something else? And one of the first things one can imagine is, well, maybe something else is the latest video from some channel to which you've subscribed. And that's going to be very different for you than it is for me, right? And even if it's not something that you subscribe to, it's something that you watch a lot. And again, that'll be very different on a person by person basis. And so even the watch next, as well as the homepage, of course, is quite personalized. So what, we mentioned some of the signals, but what does success look like? What does success look like in terms of the algorithm creating a great long-term experience for a user? Or put another way, if you look at the videos I've watched this month, how do you know the algorithm succeeded for me? I think, first of all, if you come back and watch more YouTube, then that's one indication that you found some value from it. So just the number of hours is a powerful indicator. Well, I mean, not the hours themselves, but the fact that you return on another day. So that's probably the most simple indicator. People don't come back to things that they don't find value in, right? There's a lot of other things that they could do. But like I said, I mean, ideally, we would like everybody to feel that YouTube enriches their lives and that every video they watched is the best one they've ever watched since they've started watching YouTube. And so that's why we survey them and ask them, like, is this one to five stars? And so our version of success is every time someone takes that survey, they say it's five stars. And if we ask them, is this the best video you've ever seen on YouTube? They say yes, every single time. So it's hard to imagine that we would actually achieve that. Maybe asymptotically we would get there, but that would be what we think success is. It's funny, I've recently said somewhere, I don't know, maybe tweeted, but that Ray Dalio has this video on the economic machine, I forget what it's called, but it's a 30 minute video. And I said, it's the greatest video I've ever watched on YouTube. I watched the whole thing and my mind was blown. It's a very crisp, clean description of how at least the American economic system works, it's a beautiful video. And I was just, I wanted to click on something to say this is the best thing. This is the best thing ever, please let me, I can't believe I discovered it. I mean, the views and the likes reflect its quality, but I was almost upset that I haven't found it earlier and wanted to find other things like it. I don't think I've ever felt that this is the best video I've ever watched. And that was that. And to me, the ultimate utopia, the best experience is where every single video, where I don't see any of the videos I regret and every single video I watch is one that actually helps me grow, helps me enjoy life, be happy and so on. Well, so that's a heck of, that's one of the most beautiful and ambitious, I think, machine learning tasks. So when you look at a society as opposed to an individual user, do you think of how YouTube is changing society when you have these millions of people watching videos, growing, learning, changing, having debates? Do you have a sense of, yeah, what the big impact on society is? Because I think it's huge, but do you have a sense of what direction we're taking in this world? Well, I mean, I think, you know, openness has had an impact on society already. There's a lot of- What do you mean by openness? Well, the fact that unlike other mediums, there's not someone sitting at YouTube who decides before you can upload your video, whether it's worth having you upload it or worth anybody seeing it really, right? And so, you know, there are some creators who say, like, I wouldn't have this opportunity to reach an audience. Tyler Oakley often said that, you know, he wouldn't have had this opportunity to reach this audience if it weren't for YouTube. And so I think that's one way in which YouTube has changed society. I know that there are people that I work with from outside the United States, especially from places where literacy is low. And they think that YouTube can help in those places because you don't need to be able to read and write in order to learn something important for your life, maybe, you know, how to do some job or how to fix something. And so that's another way in which I think YouTube is possibly changing society. So I've worked at YouTube for eight years. Eight, almost nine years now. And it's fun because I meet people and, you know, you tell them where you work, you say you work on YouTube, and they immediately say, I love YouTube. Yeah. Right? Which is great. It makes me feel great. But then, of course, when I ask them, well, what is it that you love about YouTube? Not one time ever has anybody said that the search works outstanding or that the recommendations are great. What they always say when I ask them, what do you love about YouTube? Is they immediately start talking about some channel or some creator or some topic or some community that they found on YouTube and that they just love. Yeah. And so that has made me realize that YouTube is really about the video and connecting the people with the videos. And then everything else kind of comes in and everything else kind of gets out of the way. So beyond the video, it's an interesting, because you kind of mentioned creator. What about the connection with just the individual creators as opposed to just individual video? So like I gave the example of Ray Dalio video, that the video itself is incredible, but there's some people who are just creators that I love. One of the cool things about people who call themselves YouTubers or whatever is they have a journey. They usually, almost all of them are, they suck horribly in the beginning and then they kind of grow, and then there's that genuineness in their growth. So YouTube clearly wants to help creators connect with their audience in this kind of way. So how do you think about that process of helping creators grow, helping them connect with their audience, develop not just individual videos, but the entirety of a creator's life on YouTube? Well, I mean, we're trying to help creators find the biggest audience that they can find. And the reason why that's, you brought up creator versus video. The reason why creator channel is so important is because if we have a hope of people coming back to YouTube, well, they have to have in their minds some sense of what they're going to find when they come back to YouTube. If YouTube were just the next viral video, and I have no concept of what the next viral video could be, one time it's a cat playing a piano, and the next day it's some children interrupting a reporter, and the next day it's some other thing happening, then it's hard for me to, to when I'm not watching YouTube say, gosh, I really would like to see something from someone or about something, right? And so that's why I think this connection between fans and creators is so important for both, because it's a way of sort of fostering a relationship that can play out into the future. Let me talk about kind of a dark and interesting question in general. And again, a topic that you or nobody has an answer to, but social media has a sense of, you know, it gives us highs and it gives us lows in the sense that sort of creators often speak about having sort of burnout and having psychological ups and downs and challenges mentally in terms of continuing the creation process. There's a momentum, there's a huge excited audience that makes creators feel great. And I think it's more than just financial. I think it's literally just, they love that sense of community. It's part of the reason I upload to YouTube. I don't care about money, never will. What I care about is the community. But some people feel like this momentum, and even when there's times in their life when they don't feel, you know, for some reason don't feel like creating. So how do you think about burnout, this mental exhaustion that some YouTube creators go through? Is that something we have an answer for? Is it something, how do we even think about that? Well, the first thing is we want to make sure that the YouTube systems are not contributing to this sense, right? And so we've done a fair amount of research to demonstrate that you can absolutely take a break. If you are a creator and you've been uploading a lot, we have just as many examples of people who took a break and came back more popular than they were before as we have examples of going the other way. Yeah, can we pause on that for a second? So the feeling that people have, I think, is if I take a break, everybody, the party will leave, right? So if you could just linger on that. So in your sense that taking a break is okay. Yes, taking a break is absolutely okay. And the reason I say that is because we can observe many examples of being, of creators coming back very strong and even stronger after they have taken some sort of break. And so I just want to dispel the myth that this somehow necessarily means that your channel is going to go down or lose views. That is not the case. We know for sure that this is not a necessary outcome. And so we want to encourage people to make sure that they take care of themselves. That is job one, right? You have to look after yourself and your mental health. And I think that it probably, in some of these cases, contributes to better videos once they come back, right? Because a lot of people, I mean, I know myself, if I'm burned out on something, then I'm probably not doing my best work, even though I can keep working on it. I'm probably not doing my best work, even though I can keep working until I pass out. And so I think that the taking a break may even improve the creative ideas that someone has. Okay, I think it's a really important thing to sort of, to dispel. I think that applies to all of social media. Like literally, I've taken a break for a day every once in a while. Sorry, sorry if that sounds like a short time, but even like, so email, just taking a break from email or only checking email once a day, especially when you're going through something psychologically in your personal life or so on, or really not sleeping much because of work deadlines, it can refresh you in a way that's profound. And so the same applies- And it was there when you came back, right? It's there. And it looks different actually when you come back. You're sort of brighter eyed with some coffee, everything. The world looks better. So it's important to take a break when you need it. So you've mentioned kind of the YouTube algorithm isn't E equals MC squared. It's not a single equation. It's potentially sort of more than a million lines of code. Sort of, is it more akin to what autonomous, successful autonomous vehicles today are, which is they're just basically patches on top of patches of heuristics and human experts really tuning the algorithm and have some machine learning modules, or is it becoming more and more a giant machine learning system with humans just doing a little bit of tweaking here and there? What's your sense? First of all, do you even have a sense of what is the YouTube algorithm at this point? And however much you do have a sense, what does it look like? Well, we don't usually think about it as the algorithm because it's a bunch of systems that work on different services. The other thing that I think people don't understand is that what you might refer to as the YouTube algorithm from outside of YouTube is actually a bunch of code and machine learning systems and heuristics, but that's married with the behavior of all the people who come to YouTube every day. So the people are part of the code, essentially. Exactly, right? Like if there were no people who came to YouTube tomorrow, then the algorithm wouldn't work anymore, right? So that's a critical part of the algorithm. And so when people talk about, well, the algorithm does this, the algorithm does that, it's sometimes hard to understand, well, it could be the viewers are doing that and the algorithm is mostly just keeping track of what the viewers do and then reacting to those things in sort of more fine-grained situations. And I think that this is the way that the recommendation system and the search system and probably many machine learning systems evolve is you start trying to solve a problem and the first way to solve a problem is often with a simple heuristic, right? And you want to say, what are the videos we're going to recommend? Well, how about the most popular ones, right? And then you start to figure out what's the most popular ones, right? And that's where you start. And over time, you collect some data and you refine your situation so that you're making less heuristics and you're building a system that can actually learn what to do in different situations based on some observations of those situations in the past. And you keep chipping away at these heuristics over time. And so I think that just like with diversity, the diversity measure we took was, okay, not more than three videos in a row from the same channel, right? It's a pretty simple heuristic to encourage diversity, but it worked, right? Who needs to see four, five, six videos in a row from the same channel? And over time, we try to chip away at that and make it more fine-grained and basically have it remove the heuristics in favor of something that can react to individuals and individual situations. So how do you, you mentioned, we know that something worked. How do you get a sense when decisions that are kind of A-B testing that this idea was a good one, this was not so good? How do you measure that? And across which time scale, across how many users, that kind of thing? Well, you mentioned that A-B experiments. And so just about every single change we make to YouTube, we do it only after we've run a A-B experiment. And so in those experiments, which run from one week to months, we measure hundreds, literally hundreds of different variables and measure changes with confidence intervals in all of them. Because we really are trying to get a sense for ultimately, does this improve the experience for viewers? That's the question we're trying to answer. And an experiment is one way because we can see certain things go up and down. So for instance, if we noticed in the experiment, people are dismissing videos less frequently, or they're saying that they're more satisfied. They're giving more videos five stars after they watch them. Then those would be indications of that the experiment is successful, that it's improving the situation for viewers. But we can also look at other things. Like we might do user studies where we invite some people in and ask them, like, what do you think about this? What do you think about that? How do you feel about this? And other various kinds of user research. But ultimately, before we launch something, we're gonna wanna run an experiment. So we get a sense for what the impact is gonna be, not just to the viewers, but also to the different channels and all of that. An absurd question. Nobody knows. Well, actually, it's interesting. Maybe there's an answer. But if I want to make a viral video, how do I do it? I don't know how you make a viral video. I know that we have in the past tried to figure out if we could detect when a video was going to go viral. And those were, you take the first and second derivatives of the view count and maybe use that to do some prediction. But I can't say we ever got very good at that. Oftentimes, we look at where the traffic was coming from. If a lot of the viewership is coming from something like Twitter, then maybe it has a higher chance of becoming viral than if it were coming from search or something. But that was just trying to detect a video that might be viral. How to make one, like, I have no idea. I mean, you get your kids to interrupt you while you're on the news or something. Absolutely. But after the fact, on one individual video, sort of ahead of time predicting is a really hard task. But after the video went viral in analysis, can you sometimes understand why it went viral from the perspective of you? From the perspective of YouTube broadly. First of all, is it even interesting for YouTube that a particular video is viral? Or does that not matter for the individual, for the experience of people? Well, I think people expect that if a video is going viral and it's something they would be interested in, then I think they would expect YouTube to recommend it to them. Right. So if something's going viral, it's good to just let the wave, let people ride the wave of its violence. Well, I mean, we want to meet people's expectations in that way, of course. So like I mentioned, I hung out with Derek Mueller a while ago, a couple of months back. He's actually the person who suggested I talk to you on this podcast. All right, well, thank you, Derek. At that time, he just recently posted an awesome science video titled, Why are 96 million black balls on this reservoir? And in a matter of, I don't know how long, but like a few days, you got 38 million views and it's still growing. Is this something you can analyze and understand why it happened, this video and you one particular video like it? I mean, we can surely see where it was recommended, where it was found, who watched it, and those sorts of things. So it's actually, sorry to interrupt. It is the video which helped me discover who Derek is. I didn't know who he is before. So I remember, usually I just have all of these technical, boring MIT Stanford talks in my recommendation, because that's what I watch. And then all of a sudden there's this black balls in reservoir video with like an excited nerd in the, with like just, why is this being recommended to me? So I clicked on it and watched the whole thing. It was awesome. But, and then a lot of people had that experience, like why was I recommended this? But they all of course watched it and enjoyed it, which is, what's your sense of this just wave of recommendation that comes with this viral video that ultimately people get enjoy after they click on it? Well, I think it's the system, you know, basically doing what anybody who's recommending something would do, which is you show it to some people and if they like it, you say, okay, well, can I find some more people who are a little bit like them? Okay, I'm gonna try it with them. Oh, they like it too. Let me expand the circle some more, find some more people. Oh, it turns out they like it too. And you just keep going until you get some feedback that says that, no, now you've gone too far. These people don't like it anymore. And so I think that's basically what happened. Now, you asked me about how to make a video go viral or make a viral video. I don't think that if you or I decided to make a video about 96 million balls, that it would also go viral. It's possible that Derek made like the canonical video about those black balls in the lake. And so- He did actually. Right. And so I don't know whether or not just following along is the secret. Yeah, but it's fascinating. I mean, just like you said, the algorithm sort of expanding that circle and then figuring out that more and more people did enjoy it and that sort of phase shift of just a huge number of people enjoying it and the algorithm quickly, automatically, I assume, figuring that out. That's a, I don't know, the dynamics of psychology, that is a beautiful thing. So what do you think about the idea of clipping? Too many people annoyed me into doing it, which is they were requesting it. They said it would be very beneficial to add clips in like the coolest points and actually have explicit videos. Like I'm re-uploading a video, like a short clip, which is what the podcasts are doing. Do you see, as opposed to, like I also add timestamps for the topics, you know, people want the clip. Do you see YouTube somehow helping creators with that process or helping connect clips to the original videos? Or is that just on a long list of amazing features to work towards? Yeah, I mean, it's not something that I think we've done yet, but I can tell you that I think clipping is great. And I think it's actually great for you as a creator. And here's the reason. If you think about, I mean, let's say the NBA is uploading videos of its games. Well, people might search for Warriors versus Rockets, or they might search for Steph Curry. And so a highlight from the game in which Steph Curry makes an amazing shot is an opportunity for someone to find a portion of that video. And so I think that you never know how people are gonna search for something that you've created. And so you wanna, I would say, you wanna make clips and add titles and things like that so that they can find it as easily as possible. Do you ever dream of a future, perhaps a distant future, when the YouTube algorithm figures that out, sort of automatically detects the parts of the video that are really interesting, exciting, potentially exciting for people, and sort of clip them out in this incredibly rich space? Because if you talk about, if you talk even just this conversation, we probably covered 30, 40 little topics. And there's a huge space of users that would find, you know, 30% of those topics really interesting. And that space is very different. It's something that's beyond my ability to clip out, right? But the algorithm might be able to figure all that out, sort of expand into clips. Do you ever, do you think about this kind of thing? Do you have a hope, a dream that one day the algorithm will be able to do that kind of deep content analysis? Well, we've actually had projects that attempt to achieve this, but it really does depend on understanding the video well and our understanding of the video right now is quite crude. And so I think it would be especially hard to do it with a conversation like this. One might be able to do it with, let's say a soccer match more easily, right? You could probably find out where the goals were scored. And then of course, you need to figure out who it was that scored the goal. And that might require a human to do some annotation. But I think that trying to identify coherent topics in a transcript, like the one of our conversation is not something that we're gonna be very good at right away. And I was speaking more to the general problem, actually, of being able to do both a soccer match and our conversation without explicit, sort of almost, my hope was that there exists an algorithm that's able to find exciting things in video. So Google now on Google search will help you find the segment of the video that you're interested in. So if you search for something like how to change the filter in my dishwasher, then if there's a long video about your dishwasher, and this is the part where the person shows you how to change the filter, then it will highlight that area and provide a link directly to it. And do you know if from your recollection, do you know if the thumbnail reflects, like what's the difference between showing the full video and the shorter clip? Do you know how it's presented in search results? I don't remember how it's presented. And the other thing I would say is that right now, it's based on creator annotations. Ah, got it. So it's not the thing we're talking about. But folks are working on the more automatic version. It's interesting, people might not imagine this, but a lot of our systems start by using almost entirely the audience behavior. And then as they get better, the refinement comes from using the content. And I wish I know there's privacy concerns, but I wish YouTube explored the space, which is sort of putting a camera on the users if they allowed it, right, to study their, like I did a lot of emotion recognition work and so on to study actual sort of richer signal. One of the cool things when you upload 360, like VR video to YouTube, and I've done this a few times, so I've uploaded myself, it's a horrible idea. Some people enjoyed it, but whatever. The video of me giving a lecture in 360, we have a 360 camera. And it's cool because YouTube allows you to then watch where do people look at? There's a heat map of where the center of the VR experience was. And it's interesting because that reveals to you like what people looked at. And it's very- It's not always what you were expecting. It's not. In the case of the lecture, it's pretty boring. It is what we're expecting, but we did a few funny videos where there's a bunch of people doing things and everybody tracks those people. In the beginning, they all look at the main person and they start spreading around and looking at other people. It's fascinating. So that's a really strong signal of what people found exciting in the video. I don't know how you get that from people just watching, except they tuned out at this point. It's hard to measure this moment was super exciting for people. I don't know how you get that signal. Maybe comment, is there a way to get that signal where this was like, this is when their eyes opened up and they're like- Like for me with the Ray Dalio video, right? Like at first I was like, okay, this is another one of these dumb it down for you videos. And then you start watching, it's like, okay, there's really crisp, clean, deep explanation of how the economy works. That's where I set up and started watching. Right, that moment, is there a way to detect that moment? The only way I can think of is by asking people to label it. Yeah. You mentioned that we're quite far away in terms of doing video analysis, deep video analysis. It's like, of course, Google, YouTube, we're quite far away from solving the autonomous driving problem too. I don't know, I think we're closer to that. You never know. And the Wright brothers thought they're not gonna fly for 50 years, three years before they flew. So what are the biggest challenges would you say? Is it the broad challenge of understanding video, understanding natural language, understanding the challenge before the entire machine learning community, or just being able to understand data? Is there something specific to video that's even more challenging than understanding natural language understanding? What's your sense of what the biggest challenge is? I mean, video is just so much information. And so precision becomes a real problem. It's like you're trying to classify something and you've got a million classes. And the distinctions among them, at least from a machine learning perspective, are often pretty small, right? Like, you need to see this person's number in order to know which player it is. And there's a lot of players. Or you need to see the logo on their chest in order to know which team they play for. And that's just figuring out who's who, right? And then you go further and saying, okay, well, was that a goal? Was it not a goal? Like, is that an interesting moment, as you said, or is that not an interesting moment? These things can be pretty hard. So, okay, so Yan LeCun, I'm not sure if you're familiar sort of with his current thinking and work. So he believes that self, what he's referring to as self-supervised learning, self-supervised learning will be the solution sort of to achieving this kind of greater level of intelligence. In fact, the thing he's focusing on is watching video and predicting the next frame. So predicting the future of video, right? So for now, we're very far from that. But his thought is, because it's unsupervised, or he refers to it as self-supervised, you know, if you watch enough video, essentially, if you watch YouTube, you'll be able to learn about the nature of reality, the physics, the common sense reasoning required by just teaching a system to predict the next frame. So he's confident this is the way to go. So for you, from the perspective of just working with this video, how, do you think an algorithm that just watches all of YouTube, stays up all day and night watching YouTube, would be able to understand enough of the physics of the world about the way this world works, be able to do common sense reasoning and so on? Well, I mean, we have systems that already watch all the videos on YouTube, right? But they're just looking for very specific things, right? They're supervised learning systems that are trying to identify something or classify something. And I don't know if predicting the next frame is really gonna get there, because I'm not an expert on compression. I don't know about compression algorithms, but I understand that that's kind of what compression, video compression algorithms do, is they basically try to predict the next frame and then fix up the places where they got it wrong. And that leads to higher compression than if you actually put all the bits for the next frame there. So I don't know if I believe that just being able to predict the next frame is gonna be enough, because there's so many frames and even a tiny bit of air on a per frame basis can lead to wildly different videos. So the thing is, the idea of compression is one way to do compression is to describe through text what's contained in the video. That's the ultimate high level of compression. So the idea is, traditionally when you think of video image compression, you're trying to maintain the same visual quality while reducing the size. But if you think of deep learning from a bigger perspective of what compression is, is you're trying to summarize the video. And the idea there is, if you have a big enough neural network, just by watching the next, trying to predict the next frame, you'll be able to form a compression of actually understanding what's going on in the scene. If there's two people talking, you can just reduce that entire video into the fact that two people are talking and maybe the content of what they're saying and so on. That's kind of the open-ended dream. So I just wanted to sort of express that because it's an interesting, compelling notion, but it is nevertheless true that video, our world is a lot more complicated than we get a credit for. I mean, in terms of search and discovery, we have been working on trying to summarize videos in text or with some kind of labels for eight years at least. And we're kind of so-so. So if you were to say the problem is 100% solved and eight years ago was 0% solved, where are we on that timeline, would you say? Yeah, to summarize a video well, maybe less than a quarter of the way. So on that topic, what does YouTube look like 10, 20, 30 years from now? I mean, I think that YouTube is evolving to take the place of TV. You know, I grew up as a kid in the 70s and I watched a tremendous amount of television. And I feel sorry for my poor mom because people told her at the time that it was going to rot my brain and that she should kill her television. But anyway, I mean, I think that YouTube is, at least for my family, a better version of television, right? It's one that is on demand. It's more tailored to the things that my kids wanna watch. And also they can find things that they would never have found on television. And so I think that at least from just observing my own family, that's where we're headed is that people watch YouTube kind of in the same way that I watched television when I was younger. So from a search and discovery perspective, what are you excited about in the 5, 10, 20, 30 years? Like what kind of things? It's already really good. I think it's achieved a lot of, of course, we don't know what's possible. So it's the task of search, of typing in the text or discovering new videos by the next recommendation. I personally am really happy with the experience. I continuously, I rarely watch a video that's not awesome from my own perspective. But what else is possible? What are you excited about? Well, I think introducing people to more of what's available on YouTube is not only very important to YouTube and to creators, but I think it will help enrich people's lives because there's a lot that I'm still finding out is available on YouTube that I didn't even know. I've been working YouTube eight years and it wasn't until last year that I learned that I could watch USC football games from the 1970s. Oh, wow. Like I didn't even know that was possible until last year and I've been working here quite some time. So what was broken about that? That it took me seven years to learn that this stuff was already on YouTube even when I got here. So I think there's a big opportunity there. And then, as I said before, we wanna make sure that YouTube finds a way to ensure that it's acting responsibly with respect to society and enriching people's lives. So we wanna take all of the great things that it does and make sure that we are eliminating the negative consequences that might happen. And then, lastly, if we could get to a point where all the videos people watch are the best ones they've ever watched, that'd be outstanding too. Do you see in many senses becoming a window into the world for people? Especially with live video, you get to watch events. I mean, it's really, it's the way you experience a lot of the world that's out there is better than TV in many, many ways. So do you see becoming more than just video? Do you see creators creating visual experiences and virtual worlds? So if I'm talking crazy now, but sort of virtual reality and entering that space, or is that at least for now, totally outside of what YouTube is thinking about? I mean, I think Google is thinking about virtual reality. I don't think about virtual reality too much. I know that we would wanna make sure that YouTube is there when virtual reality becomes something or if virtual reality becomes something that a lot of people are interested in, but I haven't seen it really take off yet. Take off. Well, the future is wide open. Christos, I've been really looking forward to this conversation. It's been a huge honor. Thank you for answering some of the more difficult questions I've asked. I'm really excited about what YouTube has in store for us. It's one of the greatest products I've ever used and continues. So thank you so much for talking to me. It's my pleasure. Thanks for asking me. Thanks for listening to this conversation. And thank you to our presenting sponsor, Cash App. Download it, use code LEXPODCAST. You'll get $10 and $10 will go to FIRST, a STEM education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators. If you enjoy this podcast, subscribe on YouTube, get five stars on Apple Podcast, follow on Spotify, support on Patreon, or simply connect with me on Twitter. And now let me leave you with some words of wisdom from Marcel Proust. The real voyage of discovery consists not in seeking new landscapes, but in having new eyes. Thank you for listening. And hope to see you next time.

https://youtu.be/nkWmiNRPU-c

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Steve Viscelli: Trucking and the Decline of the American Dream | Lex Fridman Podcast #237

The following is a conversation with Steve Veselli, formerly a truck driver and now a sociologist at the University of Pennsylvania, who studies freight transportation. His first book, The Big Rig, Trucking and the Decline of the American Dream, explains how long-haul trucking went from being one of the best blue-collar jobs to one of the toughest. His current ongoing book project, Driverless, Autonomous Trucks and the Future of the American Trucker, explores self-driving trucks and their potential impacts on labor and on society. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Steve Veselli. You wrote a book about trucking called The Big Rig, Trucking and the Decline of the American Dream, and you're currently working on a book about autonomous trucking called Driverless, Autonomous Trucks and the Future of the American Trucker. I have to bring up some Johnny Cash to you, because I was just listening to this song. He has a ton of songs about trucking, but one of them I was just listening to, it's called All I Do is Drive, where he's talking to an old truck driver. It goes, I asked him if those trucking songs tell about a life like his. He said, if you want to know the truth about it, here's the way it is. All I do is drive, drive, drive. Try to stay alive, that's the course. And keep my mind on my load, keep my eye upon the road. I got nothing in common with any man who's home every day at five. All I do is drive, drive, drive. Drive, drive, drive, drive. So I gotta ask you, same thing that he asked the trucker. You worked as a trucker for six months while working on the previous book. What's it like to be a truck driver? I think that captures it. It really does. Can you take me through the whole experience, what it takes to become a trucker, what actual day-to-day life was on day one, week one, and then over time, how that changed? Yeah. Well, the book is really about how that changed over time. So my experience, and I'm an ethnographer, so I go in, I live with people, I work with people, I talk to them, try to understand their world. Ethnographer, by the way, what is that? The science and art of capturing the spirit of a people? Yeah, life ways. I think that would be a good way to capture it. Try to understand what makes them unique as a society, maybe as a subculture. What makes them tick that might be different than the way you and I are wired. And to really sort of thickly describe it would be at least one component of it. That's sort of the basic essential. And then for me, I want to exercise what C. Wright Mills called the sociological imagination, which is to put that individual biography into the long historical sweep of humanity, if at all possible. My goals are typically more modest than C. Wright Mills'. And to then put that biography in the larger social structure, to try to understand that person's life and the way they see the world, their decisions in light of their interests relative to others, and conflict and power, and all these things that I find interesting. In the context of society and in the context of history. And a small tangent, what does it take to do that? To capture this particular group, the spirit, the music, the full landscape of experiences that a particular group goes through in the context of everything else? You only have a limited amount of time and you come to the table probably with preconceived notions that are then quickly destroyed, all that whole process. So, I don't know if it's more art or science, but what does it take to be great at this? I do think my first book was a success, relative to my goals of trying to really get at the heart of the central issues and the lives being led by people. If I have a resource, a talent, it's that I'm a good listener. I can talk with anybody. My wife loves to remark on this that I can sit down with anyone. I think I learned that from my dad, who worked at a factory and actually had a lot of truckers go through the gate that he operated. And he always had a story, a joke for everybody, kind of got to know everyone individually. And he just taught me that essentially everyone has something to teach you. And I try to embody that. That's the rule for me, is every single person I interact with can teach me something. I gotta ask you, I'm sorry to interrupt, because I'm clearly of the two of us, the poorer listener. I think you're a great listener. I've been listening to the podcast, I think you're a great listener. I really appreciate that. You've done a large number of interviews, like you said, of truckers for this book. I'm just curious, what are some lessons you've learned about what it takes to listen to a person enough, maybe guide the conversation enough to get to the core of the person, the idea, again, the ethnographer goal, to get to the core? Yeah, I think it doesn't happen in the moment. So I'm a ruminator. I just sit with the data for years. I sat with the trucking data for almost ten full years and just thought about the problems and the questions using everything that I possibly could. And so in the moment, my ideal interview is, I open up and I say, tell me about your life as a trucker. And they never shut up and they keep telling me the things that I'm interested in. Now, it never works out that way because they don't know what you're interested in. And so a lot of it is, as you know, as I think you're a great interviewer, prep. So you try to get to know a little bit about the person and understand the central questions you're interested in that they can help you explore. And so I've done hundreds of interviews with truck drivers at this point. And I should really go back and read the original ones. They're probably terrible. What's the process like? You're sitting down, do you have an audio recorder and also taking notes or do you do no audio recording, just notes? Yeah, audio recorder and social scientists always have to struggle with sampling, right? Like who do you interview? Where do you find them? How do you recruit them? I just happen to have a sort of natural place to go that gave me essentially the population that I was interested in. So all these long haul truck drivers that I was interested in, they have to stop and get fuel and get services at truck stops. So I picked a truck stop at the juncture of a couple of major interstates, went into the lounge that drivers have to walk through with my clipboard. And everybody who came through, I said, hey, are you on break? That was sort of the first criteria was do you have time, right? And if they said yes, I'd say I'm a graduate student at Indiana University. I'm doing a study. I'm trying to understand more about truck drivers. Will you sit down with me? And I think the first, I think I probably asked like 104 or 103 people to get the first hundred interviews. That's pretty good odds. It's amazing, right? For any response rate like that for interview, I mean, these are people who sat down and gave me an hour, sometimes more of their time just randomly at a truck stop. And it just tells you something about like truckers have something to say. They're alone a lot. And so I had to figure out how to kind of turn the spigot on, you know, and I got pretty good at it, I think. So they have good stories to tell and they have an active life in the mind because they spend so much time on the road just basically thinking. Yeah, there's a lot of reflection, a lot of struggles, you know, and it's, they take different forms. You know, one of the things that they talk about is the impact on their families. They say truckers have the same rate of divorce as everybody else. And that's because trucking saves so many marriages because you're not around and ruins so many. And so it ends up being a wash. So, you know, I had this experience. I met another person and he recognized me from a podcast. And he said, you know, I'm a fan of yours and a fan of Joe Rogan, but you guys never talk. You always talk to people with Nobel Prizes. You always talk to these kind of people. You never talk to us regular folk. And that guy really stuck with me. First of all, the idea of regular folk is a silly notion. I think people that win Nobel Prizes are often more boring than the people, these regular folks in terms of stories, in terms of richness of experience, in terms of the ups and downs of life. And, you know, that really stuck with me because I set that as a goal for myself to make sure I talk to regular folk. And you did just this, talking, again, regular folk. It's human beings. All of them have experiences. If you were to recommend to talk to some of these folks with stories, how would you find them? Yeah, so I do do this sometimes for journalists who will come and they want to write about sort of what's happening right now in trucking. And I send them to truck stops. Yeah, there's a town called Effingham, Illinois. And it's just this place where a bunch of huge truck stops, tons of trucks and really nothing else out there. You know, it's in the middle of corn country. And, you know, again, truckers in this, you know, sadly, I think, you know, the politics of the day, it's changing a little bit. I think there's a little, the polarization is getting to the trucking industry in ways that, you know, maybe we're seeing in other parts of our social world. But truckers are generally, you know, real open, sort of friendly folks. Some of them ultimately like to work alone and be alone. That's a relatively small subset, I think. But all of them are generally, you know, kind of open, you know, trusting, willing to have a conversation. And so, you go to the truck stop and you go in the lounge and there's usually a booth down there and somebody's sitting at their laptop or on their phone and willing to strike up a conversation. You should try that. You should, you know. That 100% will try this. Just again, we're just going from tangent to tangent. We'll return to the main question, but what do they listen to? Do they listen to talk radio? Do they listen to podcast audio books? Do they listen to music? Do they listen to silence? Everything. Everything. Everything. Some, I mean, and some still listen to the CB, which, you know, it's an ever-dwindling group. They'll call it the original internet citizens band. You know, they, back in the 70s, they thought it was going to be the medium of democracy. And they love to just get on there and, you know, cruise along one truck after the other and chat away. Usually, you know, it's guys who know each other from the same company or happen to run into each other. But other than that, it's everything under the sun. You know, and that's probably one of the stereotypes. And it's, I think it was more true in the past, you know, about the sort of heterogeneity of truck drivers. They're a really diverse group now. You know, there's definitely a large, still a large component of rural white guys who work in the industry. But there's a huge growing chunk of the industry that's immigrants, people of color, and even some women. Still huge barriers to women entering it, but it's a much more diverse place than most people think. So let's return to your journey as a truck driver. What did it take to become a truck driver? What were the early days like? Yeah, so this is, I mean, this is a central part of the story, right, that I uncovered. And the good part was that I went in without knowing what was going to happen. So I was able to experience it as a new truck driver would. It's one of the important stories in the book is how that experience is constructed by employers to sort of, you know, help you think the way that they would like you to think about the job and about the industry and about the social relations of it. It's super intimidating. I say in the book, you know, pretty handy guy, you know, familiar with tools, machines, like, you know, comfortable operating stuff, like from time I was a kid. The truck was just like a whole nother experience. I mean, as I think most people think about it, it's this big, huge vehicle, right? It's really long. It's 70 feet long. It can weigh 80,000 pounds. You know, it does not stop like a car. It does not turn like a car. But at least when I started, and this is changing, it's part of the technology story of trucking, the first thing you had to do was learn how to shift it. And it doesn't shift like a manual car. The clutch isn't synchronized. So you have to do what's called double clutch. And it's basically the foundational skill that a truck driver used to have to learn. So you would, you know, accelerate, say you're in first gear, you push in the clutch, you pull the shifter out of first gear, you let the clutch out, and then you let the RPMs of the engine drop an exact amount. Then you push the clutch back in and you put it in second gear. If your timing is off, those gears aren't going to go together. So if you're in an intersection, you're just going to get this horrible grinding sound as you coast, you know, to a dead stop in the, you know, underneath the stoplight or whatever it is. So the first thing you have to do is learn to shift it. And so, at least for me and a lot of drivers who are going to private company CDL schools, what happens is it's kind of like a boot camp. They ship me three states away from home, send you a bus ticket and say, hey, we'll put you up for two weeks. You sit in a classroom, you sort of learn the theory of shifting the, you know, theory of kind of how you fill out your logbook, rules of the road. You know, you do that maybe half the day. And then the other half, you're in this giant parking lot with one of these old trucks and just like, you know, destroying what's left of the thing. And it's lurching and belching smoke and just making horrible noises and like rattling. I mean, in these things, like there's a lot of torque. And so if you do manage to get it into gear, but the engine's lugging, I mean, it can throw you right out of the seat. Right. So it's this it's like, you know, this bull you're trying to ride and it's super intimidating. And the thing about it is that for everybody there, it's almost everybody there, it's super high stakes. So trucking has become a job of last resort for a lot of people. And so they, you know, they lose a job in manufacturing. They get too old to do construction any longer. Right. The knees can no longer handle it. They get replaced by a machine. Their job gets, you know, offshored and they end up going to trucking because it's a place where they can maintain their income. And so it's super high stress. Like they've left their family behind. Maybe they quit another job. They're typically being charged a lot of money. So that first couple of weeks, like you might get charged eight thousand dollars by the company that you have to pay back if you don't get hired. And so the stakes are high and this machine is huge and it's intimidating. And so it's super stressful. I mean, I watched, you know, men, grown men break down crying about like how they couldn't go home and tell their son that they had been telling they were going to, you know, go become a long haul truck driver that they'd failed. And it's kind of this super high stress system. It's designed that way partly because as one of my trainers later told me, it's basically a two week job interview. Like they're testing you. They're seeing like, you know, how's this person going to respond when it's tough, you know, when they have to do the right thing and it's slow. And, you know, they need to learn something. Are they going to rush, you know, or are they going to kind of stay calm, figure it out, you know, nose to the grindstone? Because when you're a truck driver, you're unsupervised, you know, and that's what they're really looking for is that kind of quality of conscientious work that's going to carry through to the job. Well, so the truck is such an imposing part of a traffic scenario. So you said like turning, it stresses me out every time I look at a truck because the geometry of the problem is so tricky. And so if you combine the fact that they have to, like everybody, basically all the cars in the scene are staring at the truck and they're waiting, often in frustration. And in that mode, you have to then shift gears perfectly and move perfectly. And when you're new, especially, like you'll probably, for somebody like me, it feels like it would take years to become calm and comfortable in that situation. As opposed to be exceptionally stressed under the eyes of the road, everybody looking at you, waiting for you. Is that the psychological pressure of that? Is that something that was really difficult? Absolutely. Again, I saw people freeze up in that intersection as horns are blaring and the truck's grinding gears and you just can't, you know, and they just shut down. They're like, this isn't for me. I can't do it. You're right. It takes years. If, you know, trucking is not considered a skilled occupation, but, you know, my six months there and I was a pretty good rookie. But when I finished, I was still a rookie, even shifting, definitely backing tight corners and situations. I could drive competently, but the difference between me and someone who had, you know, two, three years of experience was, it was a giant gulf between us. And between that and the really skilled drivers who've been doing it for 20 years, you know, is still another step beyond that. So it is highly skilled. Would it be fair to break trucking into the task of truck, of driving a truck into two categories? One is like the local stuff, getting out of the parking lot, getting into, getting into, you know, driving down local streets and then highway driving. Those two, those two tasks. What are the challenges associated with each task? You kind of emphasized the first one. What about the actual like long haul highway driving? Yeah. So, I mean, and they are very different, right? And the key with the long haul driving is really a set of, the way I came to understand it was a set of habits, right? We have a sense of driving, particularly men, I think, have a sense of driving as like being really skilled is like the goal. And you can kind of maneuver yourself out of in and out of tight spaces with great speed and braking and acceleration, you know. For a really good truck driver, it's about understanding traffic and traffic patterns and making good decisions so you never have to use those skills. And the really good drivers, you know, the mantra is always leave yourself an out, right? So always have that safe place that you can put that truck in case that four-wheeler in front of you who's texting loses control. You know, what are you going to do in that situation? And what really good truck drivers do on the highway is they just keep themselves out of those situations entirely. They see it, they slow down, they, you know, they avoid it. And then the local driving is really something that takes just practice and routine to learn. You know, this quarter turn, it feels like the back of the truck sometimes is on delay when you're backing it up. So it's like, all right, I'm going to do a quarter turn of the wheel now to get the effect that I want like five seconds from now in where that tail of that trailer is going to be. And there's just no, I mean, some people have a natural talent for that, you know, spatial visualization and kind of calculating those angles and everything. But there's really no escaping the fact that you've got to just do it over and over again before you're going to learn how to do it well. Do you mind sharing how much you were getting paid, how much you were making as a truck driver in your time as a truck driver? Yeah, I started out at 25 cents a mile. And then I got bumped up to 26 cents a mile. So we had a minimum pay, which was sort of a new pay scheme that the industry had started to introduce to, you know, because there's lots of unpaid work and time. And so we had a minimum pay of $500 a week that you would get if you didn't drive enough miles to exceed that. You get paid in sort of, so you get paid when you turn the bills in, which is the paperwork that goes with the load. So, you know, you have to get that back to your company and then that's how they bill the customer. And so you might get a bunch of those bills that kind of bunch up in one week. So, you know, I might get a paycheck for, you know, $1,200. And I mean, I was a poor graduate student. So this was real, real money to me. And so I had this sort of natural incentive to, you know, earn a lot or to maximize my pay. Some weeks were that minimum, $500, very few. And then some I'd get $1,200, $1,300. Pay has gone up, you know, typical drivers now starting in the 30s, you know, in the kind of job that I was in. 30s, you know, cents per mile, 30 to 35. So can we try to reverse engineer that math, how that maps to the actual hours? So the hours connected to driving are so widely dispersed, as you said, some of them don't count as actual work. Some of it does. That's a very interesting discussion that we'll then continue when we start talking about autonomous trucking. But, you know, you're saying all these cents per mile kind of thing. How does that map to like average hourly wage? Yeah, so I mean, and this is kind of the this is also an interesting technology story in the end. And it's the technology story that didn't happen. So pay per mile was, you know, invented by companies when you couldn't surveil drivers, you know what they were doing. Right. And you wanted them to have some skin in the game. And so you'd say, you know, here's the load. It's going from, you know, for me, I might start in, you know, the Northeast, maybe in upstate New York with a load of beer. It's a here's this load of beer. Bring it to this address in Michigan. We're going to pay you by the mile. Right. If I was being paid by the hour, I might just pull over at the diner and have breakfast. So you're paid by the mile. But increasingly, over time, the the typical driver is spending more and more time doing non driving tasks. Lots of reasons for that. One of which is railroads captured a lot of freight that goes long distances. Another one is traffic congestion. And the other one is that drivers are pretty cheap and they're they're almost always the low people on the totem pole in some segments. And so their time is used really inefficiently. So I might go to that brewery to pick up that load of Bud Light. And, you know, their dock staff may be busy loading up five other trucks. And they'll say, you know, go over there and sit and wait. We'll call you on the CB when the dock's ready. So you wait there a couple hours. They bring in, you know, you never know what's happening in the truck. Sometimes they're loading it with a forklift. Maybe they're throwing 14 pallets on there full of kegs. But sometimes it'll take them hours, you know, and you're sitting in that truck and you're you're essentially unpaid. You know, then you pull out. You've got control over what you're going to get paid based on how you drive that load. And then on the other end, you've got a similar situation of kind of waiting. So if that's the way truck drivers are paid, then there's a low incentive for the optimization of the supply chain to make them more efficient, right? To utilize truck labor more efficiently. Absolutely. So that's a technology problem that one of several technology problems that could be addressed. I mean, what, so what did, if we just linger on it, what are we talking about in terms of dollars per hour? Is it close to minimum wage? Is it, you know, there's something you talk about. There was a conception or a misconception that truckers get paid a lot for their work. Do they get paid a lot for their work? Some do. And I think that's part of the complexity. So, you know, what interested me as an ethnographer about this was, you know, I'm interested in the kind of economic conceptions that people have in their heads and how they lead to certain decisions in labor markets. You know, why some people become an entrepreneur and other people become a wage laborer or, you know, why some people want to be doctors and other people want to be truck drivers. That conception, right, is getting shaped in these labor markets is the argument of the book. And the fact that drivers can hear or potential drivers can hear about these, you know, workers who make $100,000 plus, which happens regularly in the trucking industry. There are many truck drivers who make more than $100,000 a year, you know, is an attraction. But the industry is highly segmented. And so the entry level segment, and we can probably get into this, but, you know, the industry is dominated by, you know, a few dozen really large companies that are self-insured and can train new drivers. So if you want those good jobs, you've got to have several years up until recently. Now, the labor market's becoming tighter, but you had to have several years of accident-free, you know, perfectly clean record driving to get into them. The other part of the segment, you know, those drivers often don't make minimum wage. But this leads to one of the sort of central issues that has been in the courts and in the legislature in some states is, you know, what should truck drivers get paid for? The industry, you know, for the last 30 years or so has said essentially it's the hours that they log for safety reasons for the Department of Transportation. Right. Now, since the drivers are paid by the mile, they try to minimize those because those hours are limited by the federal government. So the federal government says you can't drive more than 60 hours in a week as a long-haul truck driver. And so you want to drive as many miles as you can in those 60 hours. And so you under-report them. Right. And so what happens is the companies say, well, that guy, you know, he only said he logged 45 hours of work that week or 50 hours of work. That's all we have to pay him minimum wage for. When in fact, typical truck driver in these jobs will work, according to most people, would sort of define it as like, OK, I'm at the customer location, I'm waiting to load, I'm doing some paperwork, you know, I'm inspecting the truck, I'm fueling it, just waiting to, you know, get put in the dock. 80 to 90 hours would be sort of a typical work week for one of these drivers. And just to be clear— And when you look at that, they don't make minimum wage oftentimes. Right. Just to be clear, what we're dancing around here is that a little bit over, a little bit under minimum wage is nevertheless most truck drivers seem to be making close to minimum wage. Like, this is the—so like, we maybe haven't made that clear. There's a few that make quite a bit of money, but like, you're as an entry and for years you're operating essentially minimum wage. And potentially far less than minimum wage if you actually count the number of hours that are taken out of your life due to your dedication to trucking. Well, if you count like the hours taken out of your life, then you gotta go, you know, maybe a full 24. That's right, yeah, from family, from the high quality of life parts of your life. Yeah, and there's a whole nother set of rules that the Department of Labor has, which basically say that a truck driver who's dispatched away from home for more than a day should get minimum wage 24 hours a day. And that could be a state minimum wage. But typically what it would work out to for most drivers is that, you know, a minimum—the minimum wage for a truck driver should be 50s to thousands. You know, 55, $60,000 should be the minimum wage of a truck driver. And you've probably heard about the truck driver shortage. Like, if, you know, which I hope we can talk about, if the minimum wage for truck drivers is as it should be on the books at, you know, around $60,000, we wouldn't have a shortage of truck drivers. Oh, wow. And to me, $60,000 is not a lot of money for this kind of job. Because you're—this isn't—this is essentially two jobs. And two jobs where you don't get to sleep with your wife or see your kids at night. That $60,000 is very little money for that. But you're saying if it was $60,000, you wouldn't even have the shortage? If that was the minimum. And I think that's what—now we have drivers who start in the 30s. Wow. But yeah. And I mean, so we're talking two, three jobs, really, when you look at the total hours that people are working it, you know. They can work over 100. If they're a trainer, you know, training other truck drivers, well over 100 hours a week. So a job of last resort. Maybe you can jump around from tangent to tangent. This is such a fascinating and difficult topic. I heard that there's a shortage of truck drivers. So there's more jobs than truck drivers willing to take on the job. Is that the state of affairs currently? I mean, I think the way that you just put that is right. We don't have a shortage of people who are currently licensed to do the jobs. So I'm working on a project for the state of California to look at the shortage of agricultural drivers. And the first thing that the DMV commissioner of the state wanted to look at was, you know, is there actually a shortage of licensed drivers? He's like, I've got a database here of all the people who have a commercial driver's license who could potentially have the credential to do this. There are about 145,000 jobs in California that require a class A CDL, which would be that commercial driver's license that you need for the big trucks. About 145,000 jobs. The industry in their regular promotion of the idea that there's a shortage is always projecting forward and says, you know, we're going to need 165,000 or so in the next 10 years. They're currently like 435,000 people licensed in the state of California to drive one of these big trucks. So it is not at all an absence of people who I mean, and again, going back to what we were talking about before, getting that license is not something that you just walk down to the DMV and take the test. Like this is somebody who probably quit another job, was unemployed, and took months to go to a training school, paid for that training school oftentimes, left their family for months, invested in what they thought was going to be a long-term career, and then said, you know what, forget it. I can't do it. So yeah, so it's not just skill, it's like they were psychologically invested potentially for months, if not years, into this kind of position as perhaps a position that if they lose their current job, they could fall to. Okay, so that's an indication that there's something deeply wrong with the job if so many licensed people are not willing to take it. What are the biggest problems of the job of truck driver currently? Yeah, the job, there are problems with the job and the labor market, right? But let's start with the job, which is, again, just so much time that's not compensated directly for the amount of time. And that's just psychologically, and this was a big part of what I studied for the first book, was that conception of what's my time worth, right? And what truck drivers love is oftentimes is that tangible outcome-based compensation. So they say, you know what, honest days work, I work hard, I get paid for what I do, I drive 500 miles today, that's what I'm going to get paid for. And then you get to that dock, and they tell you, sorry, the load's not ready, go sit over there, and you stew. And that weight can break you psychologically because your time every second becomes more worthless. Yeah. Or worth less. Yeah, and again, the industry is going to say, for instance, okay, well, you know, they've got skin in the game, right? That argument about sort of compensation based on sort of output, right? But that's a holdover from when you couldn't observe truckers. Now they all have, you know, satellite-linked computers in the trucks that tell these large companies, this driver was, you know, at this GPS location for four and a half hours, right? So if you wanted to compensate them for that time directly, and the trucker can't control what's happening on that customer location, you know, they're waiting for that, you know, firmed, that customer to tell them, hey, pull in there. And so what it becomes is just a way to shift the inefficiencies and the cost of that onto that driver. Now, it's competitive for customers. So if you're Walmart, you might have your choice of a dozen different trucking companies that could move your stuff. And if one of them tells you, hey, you're not moving our trucks in and out of your docks fast enough, we're going to charge you for how long our truck is sitting on your lot. If you're Walmart, you're going to say, I'll go see what the other guy says, right? And so companies are going to allow that customer to essentially waste that driver's time, you know, in order to keep that business. Can you try to describe the economics, the labor market of the situation? You mentioned freight and railroad. What is the sort of the dynamic financials, the economics of this that allow for such low salaries to be paid to truckers? Like what's the competition? What's the alternative to transporting goods via trucks? Like what seems to be broken here from an economics perspective? Yeah, so it's, well, nothing. It's a perfect market. Okay. Right? I mean, so for economists, this is how it should work, right? But the inefficiencies, like you said, sorry to interrupt, are pushed to the truck driver. Doesn't that like spiral, doesn't that lead to poor performance on the part of the truck driver and just like, make the whole thing more and more inefficient? And it results in lower payment to the truck driver and so on. It just feels like in capitalism, you should have a competing solution in terms of truck drivers, like another company that provides transportation via trucks that creates a much better experience for truck drivers, making them more efficient, all those kinds of things. Or how is the competition being suppressed here? Yeah, so it is, the competition is based on who's cheaper. And this is the cheapest way to move the freight. Now, you know, there are externalities, right? So this is the explanation that I think is obvious for this, right? There are lots of costs that, you know, whether it's that driver's time, whether it's the time without their family, whether it's the fact that they drive through congestion and spew lots of diesel particulates into cities where kids have asthma and make our commutes longer, rather than more efficiently use their time by sort of routing them around congestion and rush hour and things like that. This is the cheapest way to move freight. And so it's the most competitive. The big part of this is public subsidy of training. So when those workers are not paying for the training, you and I often are. So if you, you know, lose your job because of, you know, foreign trade, or you're a veteran using your GI benefits, you may very well be offered, you know, training, publicly subsidized training to become a truck driver. And so all these are externalities that, you know, that the companies don't have to pay for. And so this makes it the most profitable way to move freight. So trucks is way cheaper than trains? Well, over the long, so one of the big stories for these companies is that the average length of haul, which becomes very important for self-driving trucks, the average length of haul has been steadily declining over the last 15 years or so. You know, and this industry collected data from sort of the, you know, the big firms that report it, but roughly been cut in half from typically about 1000 miles to under 500. And under 500 is what a driver can move in a day, right? So you can get loaded, drive and unload, you know, around 400 miles or something like that. I want to steal a good question from the Penn Gazette interview you did, which people should read, it's a great interview. Was there a golden age for long haul truckers in America? And if so, this is just a journalistic question, and if so, what enabled it and what brought it to an end? Wow, I might have to have you read my answer to that. That was a few years ago, it'll be interesting to compare what I'll say. I mean, one bigger question to ask, I guess, is like, you know, Johnny Cash wrote a lot of songs about truckers. There used to be a time when perhaps falsely, perhaps it's part of the kind of perception that you study with the labor markets and so on. There was a perception of truckers being, first of all, a lucrative job and second of all, a job to be desired. Yeah, so I mean, this is a, the trucking industry, to me is fascinating, but I think it should be fascinating to a lot of people. So the golden age was really two different kinds of markets as well, right? Today we have really good jobs and some really bad jobs. We had the Teamsters Union that controlled the vast majority of employee jobs, and even where they had something called the National Master Freight Agreement. And this was Jimmy Hoffa, who led the union through its sort of critical period by the mid 60s, had unified essentially the entire nation's trucking labor force under one contract. You were either, you know, covered by that contract, or your employer paid a lot of attention to it. And so by the end of the 1970s, the typical truck driver was making well more than $100,000, typical truck driver was making more than $100,000 in today's dollars, and was home every night. That was without a doubt, and even more than unionized autoworkers, steelworkers, 10-20% more than those workers made. That was the golden age for sort of job quality, wages, Teamster power, they were without a doubt the most powerful union in the United States at that time. At the same time in the 1970s, you had the mythic long-haul trucker. And these were the guys who were, you know, kind of on the margins of the regulated market, which is what the Teamsters controlled. A lot of them were in agriculture, which was never regulated. So in the New Deal, when they decided to regulate trucking, they didn't regulate agriculture because they didn't want to drive up food prices, which would hurt workers in urban areas. So they essentially left agricultural truckers out of it. And that's where a lot of the kind of outlaw, you know, asphalt cowboy, you know, imagery that we get. And, you know, I grew up, I know you didn't grow up in the US, that this sort of, you know, as a young child, when, and I'm a bit older than you, but, you know, in the late 70s, you know, there were movies and TV shows and CBs were craze. And it was all these kind of outlaw truckers who were out there hauling some unregulated freight. They weren't supposed to be trying to avoid the bears, you know, who are the cops and, you know, with all this salty language and these like, you know, terms that only they understood and, you know, the partying at diners and popping pills, you know, the California turnarounds. So asphalt cowboys, truly. Yeah. It's like another form of cowboy movies. Oh, absolutely. Absolutely. And I think that sort of masculine ethos of like, you got 40,000 pounds of something you care about, I'm your guy. You know, you need it to go from New York to California. Don't worry about it. I got it. Yeah. That's appealing. And it's tangible, right? And you think about people who don't want to be paper pusher and sit in the, and deal with office politics, like, just give me what you care about, and I'll take care of it. You know, you just pay me fair, you know, and that appeals. You mentioned unions, Teamsters, Jimmy Hoffa. Big question, maybe difficult question. What are some pros and cons of unions historically and today in the trucking space? Yeah. Well, if you're a worker, there are a lot of pros. And I don't, you know, and this is one of the things I talk to truckers about a lot. Yeah. What's their perception of Jimmy Hoffa, for example, and for of unions? Yeah. So, and this was probably one of the central hypotheses that I had going in there. And it may sound, you know, someone who does hard science, right? You may hear a social scientist, you know, sort of use that terminology, even other social scientists. Hypothesis. Yeah, you know, they don't like it, but I do like to think that way. And my initial hypothesis was that, you know, and it's very simple, that, you know, the tenure of the driver in the industry would have a strong effect on how they viewed unions. That, you know, somebody who had experienced unions would be more favorable, and someone who had not, would not be, right? And that turned out to be the case, without a doubt, but in an interesting way, which was that even the drivers who were not part of the union, who in the kind of public debate of deregulation, were portrayed as these kind of small business truckers who were getting shut out by the big regulated monopolies, and the Teamsters Union, you know, the corrupt Teamsters Union. Even those drivers longed for the days of the Teamsters. Because they recognized the overall market impact that they had, that that trucking just naturally tended toward excessive competition, that meant that there was no profit to be made. And oftentimes, you'd be operating at a loss. And so even these, you know, the asphalt cowboy owner operators from back in the day would tell me, when the Teamsters were in power, I made a lot more money. And, you know, this is, you know, unions, at least those kinds of unions, like, like the Teamsters, you know, there's, I think, a lot of misconceptions today, sort of popularly about what unions did back then. They tied wages to productivity. Like, that was the central thing that the Teamsters Union did. And, you know, there were great accounts of sort of Jimmy Hoffa's perspective for all his portrayal as sort of corrupt and criminal. And there's, you know, I'm not disputing that he broke a lot of laws. He was remarkably open about who he was and what he did. He actually invited a pair, a husband and wife team of Harvard economists to follow him around and like opened up the Teamsters books to them. So that they could see how he was, you know, thinking about negotiating with the employers. And the Teamsters, and this goes back well before Hoffa, back to the, you know, 1800s, they understood that workers did better if their employers did better. And the only way the employers would do better was if they controlled the market. And so oftentimes the corruption in trucking was initiated by employers who wanted to limit competition. And they knew they couldn't limit competition without the support of labor. And so you'd get these collusive arrangements between employers and labor to say, no new trucking companies. There are 10 of us, that's enough. We control Seattle. We're going to set the price and we're not going to be undercut. When there's a shortage of trucks around, it's great, rates go up. But you get too many trucks, it's very often that you end up operating at a loss just to keep the doors open. You know, you don't have any choice. You can't, it's what economists call derived demand. You can't like make up a bunch of trucking services and store it in a warehouse, right? You got to keep those trucks moving to pay the bills. Can we also lay out the kind of jobs that are in trucking? What are the best jobs in trucking? What are the worst jobs in trucking? What are we, how many jobs are we talking about today? Yeah. And what kind of jobs are there? So there are a number of different segments. And the first part would be, you know, are you offering, the first question would be, are you offering services to the public or are you moving your own freight, right? So are you a retailer, say Walmart or, you know, a paper company or something like that that's operating your own fleet of trucks? That's private trucking. For hire are the folks who, you know, offer their services out to other customers. So you have private and for hire. In general, for hire pays less. Is that because of the something you talk about employee versus contractor situation or are they all tricked or led to become contractors? That can become a part of it as a strategy, but the fundamental reason is competition. So those private carriers don't, aren't in competition with other trucking fleets, right, for their own in-house services. So, you know, they tend to, and this, you know, the question of why private versus for hire, because for hire is cheaper, right? And so if you need that, if that trucking service is central to what you do and you cannot afford disruptions or volatility in the price of it, you keep it in-house. You should be willing to pay more for that because it's more valuable to you and you keep it in-house. So that's an interesting distinction. What about, and this is kind of moving towards our conversation, what can and can't be automated? How else does it divide the different trucking jobs? So the next big chunk is kind of how much stuff are you moving, right? And so we have what's called truckload. And truckload means, you know, you can fill up a trailer either by volume or by weight and then less than truckload. Less than truckload, the official definition is like less than 10,000 pounds. You know, this is going to be a couple pallets of this, a couple pallets of that. The process looks really different, right? So that truckload is, you know, point A to point B. I'm buying, you know, a truckload of bounty paper towels. I'm bringing it into, you know, my distribution center. Go pick it up at the bounty plant, bring it to my distribution center, right? Nowhere in between do you stop. At least process that freight. Less than truckload, what you've got is terminal systems. And this is what you had under regulation too. And so these terminal systems, what you do is you do a bunch of local pickup and delivery, maybe with smaller trucks. And you pick up two pallets of this here, four pallets of this there. You bring it to the terminal. You combine it based on the destination. You then create a full truckload, you know, trailer. And you send it to another terminal where it gets broken back down and then out for local delivery. That's going to look a lot like if you send a package by UPS, right? They pick all these parcels, right, figure out where they're all going, put them on planes or in trailers going to the same destination, then break them out to put them in what they call package cars. Before I ask you about autonomous trucks, let's just pause for your experience as a trucker. Did it get lonely? Like can you talk about some of your experiences of what it was actually like? Did it get lonely? Yeah. No, I mean, it was – I didn't have kids at the time. Now I have kids, I can't even imagine it. You know, I've been married for five years at the time. My wife hated it. I hated it. You know, I describe in the book the experience of being stuck, if I remember correctly, it was like Ohio, at this truck stop in the middle of nowhere and like, you know, sitting on this concrete barrier and just watching fireworks in the distance and like eating Chinese food on the 4th of July. And, you know, my wife calls me from like the family barbecue and our anniversary is July 8th. And she's like, are you going to be home? And I'm like, I don't know, you know. I have a cousin whose husband drove truck, as a truck driver would say, drove truck for a while. And he told me before I went into it, he was like, the advantage you have is that you know that you're not going to be doing this long term. Like, and Lex, I can't even like – the emotional content of some of these interviews, I mean, I would sit down at a truck stop with somebody I had never met before and, you know, you open the spigot. And the last question I would ask drivers was – by the time I really sort of figured out how to do it, the last question I would ask them is, you know, what advice would you give to somebody – your nephew, you know, a family friend asks you about what it's like to be a driver and should they do it. What advice would you give them? And this question, some of these, you know, grizzled old drivers, you know, tough, tough guys, would – that question would like – some of them would break down. And they would say – I would say to them, you better have everything that you ever wanted in life already. Because I've had a car that I've had for 10 years, it's got 7,000 miles on it. I own a boat that hasn't seen the water in five years. My kids, I didn't raise them. Like, I'd be out for two weeks at a time. I'd come home. My wife would give me two kids to punish, a list of things to do, you know, on Saturday night. And I might leave out Sunday night or Monday morning, you know. I come home dead tired. My kids don't know who I am. And, you know, it was just like – it was heartbreaking to hear those stories. And before you know it, you know, life is short and just the years run away. Yeah. Hard question to ask in that context, but what's the best – what was the best part of being a truck driver? Was there moments that you truly enjoyed on the road? Oh, absolutely. There was – there's definitely a pride and mastery of, you know, even basic competence of sort of piloting this thing safely. There's a lot of responsibility to it. That thing's dangerous, and you know it. So there's some pride there. For me personally, and I know for a lot of other drivers, it's just like seeing these behind-the-scenes places that you know exist in our economy. And I think we're all much more aware of them now after COVID and supply chain mess that we have. I don't know if we'll talk about that, but, you know, you get to see those places. You know, you get to see those ports. You get to see the place where they make the cardboard boxes that the Huggy diapers go in. Huggy's diapers go in. Or the warehouse full of Bud Light. I moved Bud Light from like upstate New York, and the first load like went to Atlanta, you know. And then a couple months later, I circled back through that same brewery, and I brought a load of Bud Light out to Michigan. And I was like, holy shit, all the Bud Light, like, you know, for this whole giant swath of the United States comes from this one plant, this cavernous plant with like kegs of beer. And you see that part of the economy, and it's like you're almost like you're an economic tourist. And I think all everybody kind of appreciates that, like, kind of, it's almost like a behind the scenes tour that wears off after a few months. You know, you start to see new things less and less frequently. At first, everything's novel and sort of life on the road. And then it becomes just endless miles of white lines and yellow lines and truck stops. And the days just blur together. You know, it's one loading dock after another. So you lose the magic of being on the road. Yeah, it's very rare the driver that doesn't. You mentioned COVID and supply chain. While being this for a brief time, this member of the supply chain, what have you come to understand about our supply chain, United States and global, and its resilience against strategy, scatastrophes in the world, like COVID, for example? Yeah, I mean, we have built really long, really lean supply chains. And just by definition, they're fragile. You know, the current mess that we have, it's not going to clear by Christmas. We'll be lucky if it clears by next Christmas. Can you describe the current mess and supply chain that you're referring to? Yeah, so we've got pileups of ships off the coast of California, Long Beach, and L.A. in particular, in bad shape. You know, last I checked, it was around 60 ships, all of which are holding thousands of containers full of stuff that retailers were hoping was going to be on shelves for the holiday season. Meanwhile, the port itself has stacks and stacks of containers that they can't get rid of. The truckers aren't showing up to pick up the containers that are there, so they can't offload the ships that are waiting. And why aren't the truckers picking it up? Partly because there's a long history of inefficiency in making them wait, but it's because the warehouses are full. So we've had all these perverse outcomes that no one really expected. Like, in the middle of all these shortages, people are stockpiling stuff. So there are suppliers who used to keep two months of supply of bottled water on hand, and after going through COVID and not having supply to send to their customers, they're like, we need three months. Well, our system is not designed for major storage of goods to go up 50% in a category. It's lean. If you're a warehouse operator, you know, you want to be 90% plus. You don't want a lot of open bays sitting around. So we don't have, you know, 10% extra capacity in warehouses. You know, we don't have 10% of them. Trucking capacity can fluctuate a bit, but, you know, you don't have that kind of slack. And now, I mean, and we saw this, right, when people shifted consumption. And I get a little mad when people talk about panic buying as kind of the, you know, the reason that we had all these shortages. And it really, like, it's preventing us from understanding, you know, the real problem there, which is that lean supply chain. Sure, there was some panic buying, you know, no doubt about it, but we had an enormous shift in people's behavior. So I, with my sister and brother-in-law, I own a couple of small businesses and we serve food, right? So we get, you know, food from Cisco. Cisco couldn't get rid of food, right, because nobody's eating out. So they've got, you know, 50-pound sacks of flour, you know, sitting in their warehouse that they can't get rid of. They've got cases of lettuce and meat and everything else that's just going to go bad. So that panic buying certainly exacerbated some things like toilet paper and whatever, but we saw just a massive change in demand. And our supply chains are based on historical data, right? So, you know, that stuff leaves Asia, you know, months before you want to have it on the shelves. And you're predicting based on last year, you know, what you want on that shelf. And so it's a, you know, I guess at its best, it's a beautiful symphony of lots of moving parts. But now everyone can't get on the same page of music. But it's not resilient to changes in en masse human behavior. So even like I read somewhere, maybe you can tell me if it's true in relation to food. It's just the change of human behavior between going out to restaurants versus eating at home. As a species, we consume a lot less food that way. Apparently what I read in restaurants, like there's a lot of food just thrown out. It's part of the business model. And so like you then have to move a lot more food through the whole supply chain. And now because you're consuming, you know, there's leftovers at home, you're consuming much more of the food you're getting when you're eating at home. That's creating these bottleneck situations, problems as you're referring to. Too much in a certain place, not enough in another place. And it's just the supply chain is not robust to those kind of dynamic shifts in who gets what where. Yeah. Yeah. I mean, so I have worked in agriculture a bit on sort of the supply side, you know, and there are product categories, right, where 30 percent of the crop raised does not get used. Right. Just gets plowed under or wasted. But here's the importance of this in sort of getting this right. You know, like that, not that like panic buying, you know, blame the irrational consumer, you know, look at the hard sort of truth of the way we've we've set up our economy. And I'll ask you this, Lex, I know you you're a hopeful, optimistic person. One hundred percent. Yes. Yeah, I am, too. I mean, I write about problems all the time. And so people think I'm sort of like just a Debbie Downer, you know, pessimist. But I'm a I'm a glass half full kind of guy. Like I want I want to identify problems so so we can solve them. So let me ask you this. We've got these long, lean supply chains in the future. Do you see more environmental problems that could disrupt them, more geopolitical problems that could disrupt trade from Asia, you know, other institutional failures? Do you do those things seem, you know, potentially more likely in the future than they have been in, say, the last 20 years? Yeah, it almost absolutely seems to be the case. So you then have to ask the question of how do we change our supply chains, whether it's making more resilient or make them less densely connected? You know, building like what is it, you know, the the Tesla model for in the automotive sector of like trying to build everything, trying to get the factory to do as much as possible with as little reliance on widely distributed sources of the supply chain as possible. So maybe like rethinking how much we rely on the infrastructure of the supply chain. Yeah, I mean, you know, there are some basic and I assume, right, that that there are a lot of folks in corporate boardrooms looking at risk and saying that didn't go well. And maybe it could have even gone worse. Maybe we need to think about reshoring. Right. At the very least, one of the things that I'm hearing about anecdotally is that they're storing stuff up, you know, when they can. Right. Which is that's not that's probably not sustainable. Right. I mean, at some point, somebody in that corporate boardroom is going to say, you know, guys, inventory is getting kind of heavy. The cost of that is like, do we can we really justify that much longer to the shareholders? Right. We should we can back off and start, you know, back. Things are back to normal. Let's lean out. Well, my hope is that there's a technology solution to a lot of aspects of this. So one of them on the supply chain side is collecting a lot more data, like having much more integrated and accurate representation of the inventory all over the place and the available transportation mechanisms, the trucks, the all kinds of freight and how in the different models of the possible catastrophes that can happen. What like how will the system respond? So having a really solid model that you're operating under, as opposed to just kind of being in emergency response mode under poor incomplete information, which is what seems like is more commonly the case. Except for things like you said, Walmart and Amazon, they're trying to internally get their stuff together on that front, but that doesn't help the rest of the economy. So another exciting technological development as you write about as you think about is autonomous trucks. So these are often brought up in different contexts as the examples of AI and robots taking our jobs. How true is this? Should we be concerned? I think they've really come to epitomize this anxiety over automation. It's such a simple idea. Truck that drives itself, classic blue collar job that pays well. Guy maybe with not a lot of other good options to sort of make that same income easily. And you build a robot to take his job away. So I think 2016 or so, that was the sort of big question out there. And that's actually how I started studying it. I just wrapped up the book, just so happened that somebody who was working at Uber, Uber had just bought auto, saw the book and was like, hey, can you come out and talk to our engineering teams about what life is like for truck drivers and maybe how our technology could make it better. And at that time, there were a lot of different ideas about how they were going to play out. So while the press was saying, all truckers are going to lose their jobs. There were a lot of people in these engineering teams who thought, okay, if we've got an individual owner operator, and they can only drive eight or 10 hours a day, they hop in the back, they get their rest and the asset that they own works for them. Right, so perfect, right. And at that time, you know, there were a bunch of reports that came out. And so basically, what people did was they took the category of truck driver, you know, some people took a larger category from BLS of, you know, sales and delivery workers, that was about three and a half million workers and others took the heavy duty truck driver category, which was at the time about 1.8 million or so. And they, you know, picked a start date and a slope. And said, you know, let's assume that all these jobs are just going to disappear. And really smart researcher, Annetta Bernhardt at the Labor Center at UC Berkeley, was sort of looking around for people who were sort of deeply into industries to complicate those analyses, right? And reached out to me and was like, what do you think of this? And I said, the industry is super diverse, you know, this is just, I haven't given a ton of thought, but can't be that, you know, it's not that simple. You know, it never is. And so she was like, will you, you know, will you do this? And I was like, ready to move on to another topic. You know, I'd like been in trucking for 10 years. And that that's how I started looking at it. And it is, it's a lot more complicated. And the initial impacts, and here's the challenge, I think, and it's not just a research challenge, it's the fundamental public policy challenge is we look at the existing industry and the impacts, the potential impacts, they're not, you know, nothing. For some communities and some kinds of drivers, they're going to be hard. And there are a significant number of them, nowhere near what people thought, you know, I estimate like around 300,000. But that's a static picture of the existing industry. And here's the key with this is, at least in my, my conclusion is, this is a transformative technology, we are not going to swap in self driving trucks for human driven trucks, and all else stays the same. This is going to reshape our supply chains, it's going to reshape landscapes, it's going to affect our ability to fight climate change. This is a really important technology in this space. Do you think it's possible to predict the future of the kind of opportunities it will create? How it will change the world? So like when you have the internet, you can start saying like all the kind of ways that office work, all jobs will be lost, because it's easy to network and software engineering allows you to automate a lot of the tasks, like Microsoft Excel does, you know. But it opened up so many opportunities, even with things that are difficult to imagine, like with the internet, I don't know, Wikipedia, which is widely making accessible information. And that increased the general education globally, by a lot, all those kinds of things like and then the the ripple effects of that in terms of your ability to find other jobs is probably immeasurable. So is it, is it just a hopeless pursuit to try to predict? If you talk about these six different trajectories that we might take in automating trucks, but like, as a result of taking those trajectories, is it a hopeless pursuit to predict what the future will result in? Yeah, it absolutely is. Because it's the wrong question. Yeah. The question is, what do we want the future to be? And let's shape it. Right. And I think this is, you know, and this is the only point that I really want to make in my work, you know, for the foreseeable future, is that, you know, we have got to get out of this mindset that we're just going to let technology kind of go and it's a natural process and whatever pops out will fix the problems on the backside. And, and, and we've got to recognize that one, that's not what we do. Right. You know, and self driving vehicles is just such a perfect example, right? We would not be sitting here today if the Defense Department, right, if Congress in 2000, had not written into legislation funding for the DARPA challenges, which followed for actually, I think the funding came a couple years later. But the priority that they wrote in 2000 was, let's get a third of all ground vehicles in our military forces unmanned. Right. And this was before aerial unmanned vehicles had really sort of proven their worth, they would come to be incredibly like, you know, just blow people out of the blow people's minds in terms of their additional capabilities, the lower cost, you know, keeping, you know, soldiers out of harm's way. And of course, they raised other problems and considerations that I think we're still wrestling with. But that was even before that they had this priority. We would not be sitting here today if Congress in 2000 had not said, let's bring this about. So they already had that vision, actually, I didn't know about that. So for people who don't know, the DARPA challenges is the the events that were just kind of like these seemingly small scale challenges that brought together some of the smartest roboticists in the world. And that somehow created enough of a magic, where ideas flourished, both engineering and scientific, that eventually then was the catalyst for creating all these different companies that took over the world. These different companies that took on the challenge, some failed, some succeeded, some are still fighting the good fight. And that somehow just that little bit of challenge was the was the essential spark of progress that now resulted in this beautiful up and down wave of hype and, and profit and all this kind of weird dance where the B word billions of dollars have been thrown being thrown around. And we still don't know and the T word trillions of dollars in terms of transformative effects of autonomous vehicles and all that started from DARPA and those initial that initial vision of I guess, as you're saying, of automating part of the military supply chain. Yeah, I did not know that. That's interesting. So they had the same kind of vision for the military, as we're now talking about a vision for the civilian, whether it's trucking, or whether it's autonomous vehicle, sort of ride sharing kind of application. Yeah, I mean, what an incredible spark, right? And, and it just the story of what it produced, right? I mean, your own work on self driving, right? I mean, you, you've studied it as an academic, right? How many great researchers and minds have been harnessed by this outcome of that spark, right? And I think this is sort of theoretically about technology, right? This is what makes it so great is that this is what makes us human, in my opinion, right? Is that you, you conceive of something in your mind, and then you bring it into reality. Right? I mean, that that's what is so great about it. Sometimes you're too dumb to realize how difficult it is. So you take it. Right. And then eventually you're, you're too, you're in too deep. You might as well solve the problem. Well, and maybe we're in that situation right now with self driving. But, you know, and so let me throw this out there. I'd be curious to hear your thoughts on it. But the truck drivers always always ask me, like, is this for real? Like, is this really do like, it's harder than they think, like, right? And they can't really do this. And, you know, at first I was like, look, you know, this is like the Defense Department, and like, basically the top computer science and robotics departments in the world. And now Silicon Valley with billions of dollars in funding, and just, you know, some of the smartest, hardest working, most visionary people focused on what is clearly, you know, a gigantic market. Right? And what I tell them is like, if self driving vehicles don't happen, I think this will be the biggest technology failure story in human history. I don't know of anything else that is just galvanized. I mean, you've had people in garages or weird inventors work on things their whole lives and come really close, and it never happens. And it's a great failure story. Right? But never have we had like whole, I mean, we're talking about GM, right? And these are not, you know, these are not tech companies, right? These are industrial giants, right? What were in the 20th century, the pinnacle of industrial production in the world in human history, right? And they're focused on it now. So if we don't pull this off, it's like, wow. It's fascinating to think about. I've never thought of it that way. There was a mass hysteria on a level in terms of excitement and hype, on a level that's probably unparalleled in technology space. Like I've seen that kind of hysteria just studying history when you talk about military conflict. So we often wage war with a dream of making a better world and then realize it costs trillions of dollars. And then we step back and like, and go, wait a minute, what do we actually get for this? But in the space of technology, it seems like all these kinds of large efforts have paid off. You're right. It seems like even GM and Ford and all these companies now are a little bit like, hey, or Toyota and even Tesla, like, are we sure about this? And it's fascinating to think about when you tell the story of this, this could be one of the big first, perhaps, but by far the biggest failures of the dream in the space of technology. That's really interesting to think about. I was a skeptic for a long time because of the human factor. Because for business to work in the space, you have to work with humans and you have to work with humans at every level. So in the truck driving space, you have to work with the truck driver, but you also have to work with the society that has a certain conception of what driving means. And also you have to work with businesses that are not used to this extreme level of technology in the basic operation of their business. So I thought it would be really difficult to move to autonomous vehicles in that way. But then I realized that there's certain companies that are just willing to take big risks and really innovate. I think the first impressive company to me was Waymo or what was used to be the Google self-driving car. And I saw, okay, here's a company that's willing to really think long-term and really try to solve this problem, hire great engineers. Then I saw Tesla with Mobileye when they first had, I thought, actually Mobileye is the thing that impressed me. When I sat down, I thought, because I'm a computer vision person, I thought there's no way a system could keep me in lane long enough for it to be a pleasant experience for me. So from a computer vision perspective, I thought there'd be too many failures. It'd be really annoying. It'd be a gimmick, a toy. It wouldn't actually create a pleasant experience. And when I first was gotten a Tesla with Mobileye, the initial Mobileye system, it actually held the lane for quite a long time to where I could relax a little bit. And it was a really pleasant experience. I couldn't exactly explain why it's pleasant, because it's not like I still have to really pay attention, but I can relax my shoulders a little bit. I can look around a little bit more. And for some reason that was really reducing the stress. And then over time, Tesla with a lot of the revolutionary stuff they're doing on the machine learning space, made me believe that there's opportunities here to innovate, to come up with totally new ideas. Another very sad story that I was really excited about is Cadillac's Super Cruise system. It is a sad story because I think I vaguely read in the news they just said they're discontinuing Super Cruise. But it's a nice, innovative way of doing driver attention monitoring and also doing lane keeping. And just innovation could solve this in ways we don't predict. And same with in the trucking space, it might not be as simple as like journalists envisioned a few years ago, where everything is just automated. It might be gradually helping out the truck driver in some ways that make their life more efficient, more effective, more pleasant, remove some of the inefficiencies that we've been talking about in totally innovative ways. And I still have that dream. I believe to solve the fully autonomous driving problem, we're still many years away. But on the way to solving that problem, it feels like there could be, if there's bold risk takers and innovators in the space, there's an opportunity to come up with like subtle technologies that make all the difference. That's actually just what I realized is sometimes little design decisions make all the difference. It's the BlackBerry versus the iPhone. Why is it that you have a glass and you're using your finger for all of the work versus the buttons makes all the difference. This idea that now that you have a giant screen, so that every part of the experience is now a digital experience. So you can have things like apps that change everything. You can't, when you first thinking about do I want a keyboard or not on a smartphone, you think it's just a keyboard decision. But then you later realize by removing the keyboard, you're enabling a whole ecosystem of technologies that are inside the phone. And now you're making the smartphone into a computer. And that same way, who knows how you can transform trucks, right? By like automating some parts of it, maybe adding some displays, maybe giving the truck driver some control in the supply chain to make decisions, all those kinds of things. So I don't know. So where are you on the spectrum of hope for the role of automation in trucking? I think automation is inevitable. And again, I think this is really going to be transformative. And it's going to be, I've studied the history of trucking technology as much as I can. There's not a lot of great stuff written and you kind of have to, there isn't a lot of data and places to know sort of volumes of stuff and how they're changing, etc. But the big revolutionary changes in trucking are because of constellations of factors. It's not just one thing, right? So Daimler builds a motorized truck in, I think it's 1896, right? Intercity trucking, so basically what they use that truck for is just to swap out horses, right? They basically do the same thing. The service doesn't really change, and then World War I really spurs the development of bigger, larger trucks, like spreads air-filled tires. And then we start paving roads, right? And paved roads, right? Air-filled tires and the internal combustion engine. Now you got a winning mix. Now it met with demand for people who wanted to get out from under the thumb of the railroads, right? So there was all of this pent-up demand to get cheaper freight from the countryside into cities and between cities that typically had to go by rail. And so now, you know, 40 years after that internal combustion engine, it becomes this absolutely essential, right? This necessary but not sufficient piece of technology to create the modern trucking industry in the 1930s. And I think self-driving is going to be, self-driving trucks are going to be part of that. And the idea, I don't know, I guess we credit Jeff Bezos. The idea is, you know, okay, so Sam Walton, if we can do it like a slight tangent on sort of the importance of trucking to business strategy and sort of how it has transformed our world. The central insight that Sam Walton had that made him the giant that he was in influencing the way that so many people get stuff was a trucking insight. And so if you look at the way that he developed his system, you build a distribution center and then you ring it with stores. Those stores are never further out from that distribution center than a human-driven truck can drive back and forth in one day. And so rather than the way all of his competitors were doing it with sending trucks all over the place and having people sleep overnight and sort of making the trucking service fit where they had stores, he designed the layout of the stores, right, to fit what trucks could do. And so transportation and logistics, right, become Walmart's, you know, edge, right, and allows them to dominate the space. That's the challenge that Amazon has now. They've mastered the digital part of it, right, and now they've got to figure out, like, how do we, you know, dominate the actual physical movement that complements that? Others are obviously going to follow. But the capabilities of these trucks is completely different than the capability of a human-driven truck. If you're Smith Packing, right, and you've got, you know, a bunch of meat in a warehouse and it's going to grocery distribution centers, you know, you have that trucker probably come in the night before and you make him wait so that he has, you know, a full 10-hour break, which is what the law requires, so that he can get to the furthest reaches that he can of one of those stores, right, so he can drive his full 11 hours and bring that meat so it doesn't have to sit overnight in there. So, he can't sit overnight in that refrigerated trailer, right, and so their system is based on that. Now, what happens when that truck can now travel two times as far, right, three times as far? Now, you don't need the warehouses where they were. Now, you can go super lean with your inventory. Instead of having meat here, meat there, meat there, you can put it all right here, and if it's cheap enough, substitute those transportation costs for all that warehousing costs, right? So, this is going to remake landscapes in the same way that big box supply chains did, right? And then, of course, the further complement of that is, you know, how do you then get it to people at their door, right? And, you know, the big box supply chain, it moves very few items in really large quantities to very few locations pretty slowly, right? E-commerce aspires, you know, to do something completely different, right? Move huge varieties of things in small quantities virtually everywhere as fast as possible, right? And so that is like that intercity trucking under the, you know, in the era of railroad monopolies, right? The demand for that is potentially enormous, right? And so there's such a—so right now, I think a lot of the business plans for sort of automated trucks, right, and sort of the way that the journalistic accounts portray it is like, okay, if we swap out a human for a computer, what are the labor costs per mile? And like, oh, here's the profitability of self-driving trucks. Uh-uh. Like, this is transformative technology. We're going to change the way we get stuff. So we could actually get a lot more trucks, period, with like with autonomous trucks because they would enable a very different kind of transportation networks, you think? Yeah, here's—and this is where it's like, uh-oh. Like, yeah, so we really thought we were going to be electrifying trucks. If they're going twice as far, if they're moving three times as much, if they're going three times as far, right, what does that mean for how far we are behind on batteries, right? We've got sort of these, you know, ideas about like, man, here's how far—how close we could get to meet this demand. That demand is going to radically change, right? These trucks are, you know—so then we've got to think about, all right, if it's not batteries, you know, how are we powering these things? And how many of them are there going to be? Like, right now, we've got 5 million containers that move from L.A. and Long Beach to Chicago on rail. Rail is three or four times at least more efficient than trucks in terms of greenhouse gas emissions. And on that lane, it varies a lot depending on demand, but maybe rail has a 20% advantage in cost, maybe 25%, but it's a couple days slower. So now you cut the cost of that truck transportation per mile by 30%. Now it's cheaper than rail, and it gets the stuff there five days faster than rail. How many millions of containers are going to leave L.A. and Long Beach on self-driving trucks and go to Chicago? And it might look very much like a train if we go with the platooning solution. You have these rows of like—imagine like rows of like 10, like dozens of trucks or like hundreds of trucks, like some absurd situation. Just going from L.A. to Chicago. Just this train but taking up a highway. I mean, this is probably a good place to talk about various scenarios. Before we get there, can I just make one interesting observation that I made as a driver? When you're in a truck, you're up higher, you know, so you can see further and you can see the traffic patterns. And cars move in packs. I'm sure there's academic research on this, right? But they move in packs. They kind of bunch up behind a slower car and then a bunch of them break free. And this is sort of on almost free-flowing highways. They kind of move in packs, and you can kind of see them in the truck. So, you know, rather than platoons, we might have like hives, you know, of trucks, right? So you have like 20 trucks moving in some coordinated fashion, right? And then maybe the self-driving cars are, you know, because people don't like to be around them or whatever it is, right? So we might have a pod of, you know, 20 self-driving cars sort of moving in a packet behind them, you know. This is what if the aliens came down or were just observing cars, which is one of the sort of prevalent characteristics of human civilization, is there seems to be these cars like moving around that would do this kind of analysis of like, huh, what's the interesting clustering of situations here? Especially with autonomous vehicles. I like this. Okay, so what technologically speaking do you see are the different scenarios of increasing automation in trucks? What are some ideas that you think about? For the most part, I have no influence on sort of what these ideas were. So what the project was that I did was I said technology is created by people. They solve for X, and they have some conception of what they want to do. And that's where we should start in sort of thinking about what the impacts might be. So I went and I talked to everybody I could find who was, you know, thinking about developing a self-driving truck. And the question was essentially, you know, what are you trying to build? Like, what do you envision this thing doing? It turned out that that for a lot of them was an afterthought. They knew the sort of technological capabilities that a self-driving vehicle would have, and those were the problems that they were tackling. You know, they were engineers and computer scientists and— Oh, robotics people, I love you so much. This is the—I could talk forever about this, but yes, there's a technology problem. Let's focus on that, and we'll figure out the actual impact on society, how it's actually going to be applied, how it's actually going to be integrated from a policy and from a human perspective, from a business perspective later. First, let's solve the technology problem. That's not how life works, friends, but OK, I'm sorry. Yeah, yeah, so I mean, I'm sure you know the division of labor in these companies, right? There's sort of a business development side, you know, and then there's the engineering side, right? And the engineers are like, oh my God, what are these business development people, you know, why are they involved, you know, sort of like in this process? So I ended up sort of coming up with a few different ideas that people seem to be batting around and then really tried to zero in on a layman's understanding of the limitations, right? And it turns out that's really obvious and quite simple. Highway driving's a lot simpler, right? So, you know, the plan is simplify the problem, right, and focus on highways because city driving is so much more complicated. So from that, I came up with basically six scenarios. Actually, I came up with five that the developers were talking about. And then one that I thought was a good idea that I had read about, I think in like 2013 or 2014, which was actually something that the US military was looking at. I actually first heard about the idea of this kind of automation, at least in sketched out form in like 2011, I guess it was, with Peloton, which was this sort of early technology entrant into the trucking industry, which was working on platooning trucks. And all they were doing was, you know, a cooperative adaptive cruise control, as they came to call it. And we ended up on a panel together, and it's kind of interesting because I was on that panel because I was thinking about how we got the best return on investment for fuel efficient technologies. And if it's cool, I'll sort of set this up because it does, it comes into sort of the story of some of these scenarios. So when I studied the drivers, you had this like complete difference in the driving tasks, like we were talking about before with long haul and city, right? And you're not paid in the city, you've got congestion, the turns are tight. There's lots of, you know, pedestrians, you know, all the things that self driving trucks don't like, truckers don't like, right? And they're not paid, there's lots of waiting time. And then in the highway, they get to cruise, they're getting paid, they have control, they go at their own pace, they're making money, they're happy. Well, it turned out, right, I guess it was around 2010, this is still when we were thinking about regenerative braking, you know, and hybrid trucks being sort of like the solution. The problems with them sort of, and the advantages, you know, also split on what I was thinking of as kind of the rural urban divide at that time, right? So like you got the regenerative braking, right? You can make the truck lighter, you can keep it local, right? You don't get any benefit from that, you know, hybrid electric in the rural highway, you want aerodynamics, right? There, you want low rolling resistance tires and these super aerodynamic sleek trucks, right? Where we know with off the shelf technology today, we could double the fuel economy, more than double the fuel economy of the typical truck in that highway segment, if we segmented the duty cycle, right? And so in the urban environment, you want a clean burning truck, so you're not giving kids asthma, you want it lighter, so it's not destroying those less strong pavements, right? You're not, you can make tighter turns, you don't need a sleeper cab, because the driver, you know, hopefully is getting home at night, right? In the long haul, you want that super aerodynamic stuff. Now, that doesn't get you anything in the city. And in fact, it causes all kinds of problems, because you turn too tight, you crunch up all the aerodynamics that connect the tractor and the trailer. So the idea that I had was like, okay, what if we deliberately segmented it? Like, what if we created these drop lots outside cities, where, you know, a local city driver who's paid by the hour, kind of runs these trailers out once they're loaded, you know, doesn't sit there and wait while it's being loaded, they drop off a trailer, they go pick up one that's loaded, they run it out, when it's loaded, they call them, and they just run them out there and stage them. It's like an Uber driver, but for truckloads. Yeah, and we have like intermodal, we have like, we have basically this would be the equivalent of like rail to truck intermodal, right? So you put it on the rail, and then, you know, a trucker picks it up and delivers it, right? So instead of having the rail, you'd have these super aerodynamic, hopefully, platoons, or what was at the time was called long combination vehicles, which is basically two trailers connected together, right? Because this is like a huge productivity gain, right? And then instead of that driver, like me, I would pick up something in upstate New York, drive to Michigan, drive to Alabama, you know, drive to Wisconsin, drive to Florida, you know, I get home every two weeks, if I'm just running that, you know, that double trailer, I might be able to go back and forth from Chicago to Detroit, right? Take two trailers there, pick up two trailers going back, right? And be home every night. Now, the problem with that at the time, or one of them was, you know, bridge weights, so you can't, not all bridges can handle that, that much weight on them, they can't handle these doubles, right? And some places can, some places can't. So this platooning idea was happening at the same time. And we ended up on the same panel, and the founders were like, hey, so what's it like to follow really close behind another truck, which was kind of the stage that they were at was like, you know, what's that experience going to be like? And I was like, truckers aren't going to like it, you know, I mean, that's just like the cardinal rule is following distance, like, that's the one you really shouldn't violate, right? And when you're out on the road, like you have that trucker, like right on your ass, you know, people remember that, they don't remember the 99.9% of truckers that are not on their ass, you know, like, they're very careful about that. But when the trucks are really close together, there's benefits in terms of aerodynamics. So that's the idea. So like, if you want to get some benefits of a platoon, you want them to be close together, but you're saying that's very uncomfortable for truckers. Yeah, so I mean, I think that ended up at the, I mean, Peloton, I think is sort of winding down their work on this. And I think that ended up being still an open question, like, and I had a chance to interview a couple drivers who, at least one, maybe two of which had actually driven in their platoons. And I got completely different experiences. Some of them were like, it's really cool. You know, I'm like in communication with that other driver. You know, I can see on a screen what's out, you know, the front of his truck. And then some were like, it's too close. And it might be one of those things that's just, you know, takes an adjustment to sort of get there. So you get the aerodynamic advantage, which, you know, saves fuel. There's some problems, though, right? So, you know, you're getting that aerodynamic advantage because there's a low pressure system in front of that following truck. But the engine is designed with higher pressure feeding that engine, right? So there are sort of adjustments that you need to make. And, you know, still the benefits are there. That's one scenario. And that's just the automation of that acceleration and braking. Starsky, which, you know, probably a lot of your listeners heard about, was working on another scenario, which was, you know, to solve that local problem was going to do teleoperation, right? Sort of remote piloting. I had the chance to, you know, sort of watch them do that. It was, you know, they drove a truck in Florida from San Francisco in one of their offices. That was really interesting. And then, in case it's not clear, teleoperation means you're controlling the truck remotely like it's a video game. So you've gotten a chance to witness it. Does it actually work? Yeah. I mean, so it's a. What are the pros and cons? You know, one of the problems with doing research like this with all these Silicon Valley folks is the NDAs. Oh, right. So I don't know what I'm able to say about sort of watching it. But obviously, they're public statements about sort of what the challenges are, right? And it's about the latency and the ability to sort of in real time. There's challenges there. Let me say one thing. So I'm talking to the, you know, I've talked to the Waymo CTO. I'm in conversations with them. I'm talking to the head of trucking, Boris Sofman, in next month, actually. I'm a huge fan of his because he was, I think, the founder of Anki, which is a toy robotics company. So I love cute. I love human robot interaction. And he created one of the most effective and beautiful toy robots. Anyway, I keep complaining to them on email privately that there's way too much marketing in these conversations. And not enough showing off both the challenge and the beauty of the engineering efforts. And that seems to be the case for a lot of these Silicon Valley tech companies. They put up this, you're talking about NDAs. They've, for some reason, rightfully, wrongfully, because there's been so much hype and so much money being made, they don't see the upside in being transparent and educating the public about how difficult the problem is. It's much more effective for them to say, we have everything solved. This will change everything. This will change society as we know it. And just kind of wave their hands. As opposed to exploring together, like these different scenarios, what are the pros and cons? Why is it really difficult? You know, what are the gray areas of where it works and doesn't? What's the role of the human in this picture of both the operators and the other humans on the road? All of that, which are fascinating human problems. Fascinating engineering problems that I wish we could have a conversation about, as opposed to always feeling like it's just marketing talk. Because a lot of what we're talking about now, even you with having private conversations under NDA, you still don't have the full picture of everything, of how difficult this problem is. One of the big questions I've had, still have, is how difficult is driving? I disagree with Elon Musk and Jim Keller on this point. I have a sense that driving is really difficult. You know, the task of driving, just broadly. This is like philosophy talk. How much intelligence is required to drive a car? So, from a Jim Keller, who used to be the head of Autopilot, the idea is that it's just a collision avoidance problem. It's like billiard balls. It's like you have to convert the drive. You have to do some basic perception, like computer vision, to convert driving into a game of pool. And then you just have to get everything into a pocket. To me, there just seems to be some game theoretic dance, combined with the fact that people's life is at stake. And then, when people die at the hands of a robot, the reaction is going to be much more complicated. So, all of that. But that's still an open question. And the cool thing is, all of these companies are struggling with this question. Of how difficult is it to solve this problem sufficiently, such that we can build a business on top of it, and have a product that's going to make a huge amount of money, and compete with the manually driven vehicles. And so, their teleoperation from Starsky is a really interesting idea. There's a few autonomous vehicle companies that tried to integrate teleoperation in the picture. Can we reduce some of the costs, while still having reliability, like a catch when the vehicle fails, by having teleoperation? It's an open question. So, that's for you scenario number two, is to use teleoperation as part of the picture. Yeah. Let me follow up on that question of how hard driving is. Because this becomes a big question for researchers who are thinking about labor market impacts. Because we start from a perspective of what's hard or easy for humans. And so, if you were to look at truck driving prior to a lot, and this has been a lot of thinking and debate in academic research circles around how you estimate labor impacts, what these models look like. And a lot of it is about how automatable is a job. Object recognition, really easy for people. Really hard for computers. And so, there's a whole bunch of things that truck drivers do that we see as super easy. And as it would have been characterized ten years ago, routine. And it's not for a computer. It turns out to be something that we do naturally that is cutting edge, right? Computer science. So, on the teleoperation question, I think this is a more interesting one than people would like to sort of let on, I think, publicly. There are going to be problems, right? And this is one of the complexities of sort of putting these things out in the world. And if you see the real world of trucking, you realize, wow, it's rough. You know? There are dirt lots. There's gravel. There's salt and ice and cold weather. And there's equipment that just gets left out in the middle of nowhere. And the brakes don't get maintained. And somebody was supposed to service something and they didn't. And so, you imagine, okay, we've got this vehicle that can drive itself, which is going to require a whole lot of sensors to tell it that, like, the doors are still closed. And the trailer is still hooked up. And each of the tires has adequate pressure. And, you know, any number of probably hundreds of sensors that are going to be sort of relaying information. And one of them, you know, after 500,000 miles or whatever, goes out. Now, you know, do we have some fleet of technicians sort of continually cruising the highways and sort of servicing these things as they do what? Pull themselves off to the side of the road and say, I've got a sensor fault. I'm pulling over. You know? Or maybe there's some level of, like, critical, safety critical faults or whatever it might be. So, you know, that suggests that there might be a role for teleoperation, even with self-driving. And when I push people on it in the conversations, they all are like, yeah, we kind of have that on the, like, bottom of the list. Figure out how to rescue truck. You know? It's like on the to-do list, right? After solving the self-driving, you know, question is like, yeah, what do we do with the problems? Right? I mean, now, we could imagine, like, all right, we have some, you know, protocol that the truck is not, you know, realizes the system says not safe for operation. Pull to the side. Good. You have a crash, but now you've got a truck stranded on the side of the road. You're going to send out somebody to, like, calibrate things and check out what's going on. That sounds like expensive labor. It sounds like downtime. It sounds like the kind of things that shippers don't like to happen to their freight, you know, in a just-in-time world. And so, wouldn't it be great if you could just sort of, you know, loop your way into the controls of that truck and say, all right, we've got a sensor out. It says that the tire is bad, but I can see visually from the camera. Looks fine. I'm going to drive it to our next depot, you know, maybe the next Ryder or Penske location. Right? Sort of all these service locations around and have a technician take a look at it. So teleoperation often gets this, you know, dismissive, you know, commentary from other folks working on other scenarios. But I think it's potentially more relevant than we hear publicly. But it's a hard problem. Oh, yeah. You know, for me, I've gotten a chance to interact with people that take on hard problems and solve them, and they're rare. What Tesla has done with their data engine. So I thought autonomous driving cannot be solved without collecting a huge amount of data and organizing it well. Not just collecting, but organizing it. And exactly what Tesla is doing now is what I thought it would be. Like, I couldn't see car companies doing that, including Tesla. And now that they're doing that, it's like, oh, okay. So it's possible to take on this huge effort seriously. And teleoperation is another huge effort like that. It's like taking seriously what happens when it fails. What's the, in the case of Waymo for the consumer, like ride sharing, what's the customer experience like? There's a bunch of videos online now where people are like, the car fails and it pulls off to the side. And you call a customer service, and you're basically sitting there for a long time. And there's confusion. And then there's a rescue that comes, and they start to drive. I mean, just the whole experience is a mess that has a ripple effect to how you trust in the entirety of the experience. But like, actually taking on the problem of that failure case and revolutionizing that experience, both for trucking and for ride sharing, that's an amazing opportunity there. Because that feels like it would change everything. If you can reliably know when the failures happen, which they will, you have a clear plan that doesn't significantly affect the efficiency of the whole process. That could be the game changer. And if teleoperation is part of that, it could be, just like you're saying, it could be teleoperation, or it could be like a fleet of rescuers that can come in, which is a similar idea. But teleoperation, obviously, that allows you to just have a network of monitors, of people monitoring this giant fleet of trucks and taking over when needed. And it's a beautiful vision of the future, where there's millions of robots and only thousands of humans monitoring those millions of robots. That seems like a perfect dance of allowing humans to do what they do best and allowing robots to do what they do best. Yeah, yeah. So, I mean, I think there are, and we just applied for an NSF, we didn't get, if anybody's watching. But with some folks from Wisconsin who do teleoperation, right? And, you know, some of this is used for like rovers and, you know, I mean, really, you know, high stakes, difficult problems. But one of the things we wanted to study were these mines, these Rio Tinto mines in Australia, where they remotely pilot the trucks. And there's some autonomy, I guess, but it's overseen by a remote operator. And they, you know, it's near Perth, and it's quite remote. And they retrained the truck drivers to be the remote operators, right? There's autonomy in the port of Rotterdam and places like that, where there are jobs there. And so there, I think, you know, maybe we'll get to this later. But, you know, there's a real policy question about sort of who's going to lose and what we do about it. And, you know, whether or not there are opportunities there that, you know, maybe we need to put our thumb on the scale a little bit to make sure that, you know, there's some give back to the community that's taking the hit, you know. So, for instance, if there were teleoperation centers, you know, maybe they go in these communities that we disproportionately source truck drivers from today. Now, I mean, what does that mean? It may not be the cheapest place to do it if they don't have great connectivity. And it may not be where the upper-level managers want to be, you know, places like that, you know, issues like that, right? So, I do think it's an interesting question, you know, both from sort of a practical scenario situation of how it's going to work, but also from a policy perspective. So, there's platoons, there's teleoperation, and this is taking care of some of the highway driving that we're talking about. Is there other ideas, like, is there other ideas, scenarios that you have for autonomous trucks? Yeah, so, I mean, the most obvious one, actually, is just, you know, facility to facility, right? The sort of, you know, it can't go everywhere, but a lot of logistics facilities are very close to interstates, and they're on big commercial roads without, you know, bikes and parked cars and all that stuff. And some of the jobs that I think are really first on the chopping block are these LTL, that less than truckload, what's called line haul, right? So, these are the drivers who go from terminal to terminal with those full trailers. And those facilities are often located strategically to avoid congestion, right, and to be in big, you know, industrial facilities. So, you could imagine that being, you know, the first place you see a Waymo self-driving, you know, truck rollout might be, you know, sort of direct facility to facility for UPS or FedEx or a less than truckload carrier. And the idea there is fully driverless, so potentially not even a driver in the truck. It's just going from facility to facility empty. Zero occupancy. Yeah, and those, because that labor is expensive, you know, they don't keep those drivers out overnight. Those drivers do a run back and forth, typically, or in a team, go back and forth in one day. So, from the people you've spoken with so far, what's your sense, how far are we away from, which scenario is closest and how far away are we from that scenario of autonomy being a big part of our trucking fleet? Most folks are focused on another scenario, which is the exit to exit, right, which looks like that urban truck ports thing that I laid out earlier. You know, so you have a human driven truck that comes out to a drop lot, it meets up with an autonomous truck, that truck then, you know, drives it on the interstate to another lot, and then a human driver, you know, picks it up. There are a couple variations, maybe on that. So, let me just run through the last two scenarios. Sure. The other thing you could do, right, is to say, all right, I've got a truck that can drive itself, and I refer to this one as autopilot, but, you know, you have a human drive it out to the interstate, but rather than have that transaction where the human driven truck detaches the trailer and gets coupled up to a self-driving truck, they just, that human driver just hops on the interstate with that truck and goes in back and goes off duty while the truck drives itself, and so you have a self-driving truck that's not driverless, right? And just to clarify, because Tesla uses the term autopilot, and so do airplanes, and so everybody uses the word autopilot, we're referring to essentially full autonomy, but because it's exit to exit, the truck driver is on board the truck, but they're sleeping in the back or whatever. Yeah, and this gets to the really weedy policy questions, right? So, basically, for the Department of Transportation, for you to be off duty for safety reasons, you have to be completely relieved of all responsibility. So, that truck has to not, you know, encounter a construction site or inclement weather or whatever it might be and call to you and say, hey, you know, or, I mean, obviously, right, we're imagining connected vehicles as well, right? So, you're in a self-driving truck, you're in the back, and trucks 20 miles ahead experience some problem, right, that may require teleoperation or whatever it is, right? And it signals to your truck, hey, you know, tell the driver 20 miles ahead, he's got to hop in the seat. That would mean that they're on duty according to the way that the current rules are written. They have some responsibility, and part of that is, you know, we need them to get rest, right? They need to have uninterrupted sleep. So, that's what I call autopilot. The final scenario is one that I thought was actually the one scenario that was good for labor, you know, which I proposed, like, well, here's an idea, you know, that would be, like, actually good for workers. And just another brief aside here, the history of trucking over the last, you know, 40 years, there's been a lot of technological change. So, when I learned to drive the truck, I had to learn to manually shift it like I was describing. You had to read these fairly complicated, you know, big sets of laminated maps to figure out where the truck can go and where it couldn't, which is a big deal, you know? I mean, you take these trucks on the wrong road, and you're destroying a bridge, or you're doing a can opener, which is where you try to drive it under a bridge that's too low. You've probably seen that on YouTube. If not, you know, check it out, you know, truck can opener. You know, there's some bridges that are famous for it, right? And there's one I think called the can opener, and you can find it on YouTube. And, you know, you had to log those hours, like, manually and sort of do the math and plan your work routine. And I would do this every day. I'd say, like, okay, I'm going to get up at 5. I've got to think about Buffalo, and there's traffic there, so I want to be through Buffalo by 6.30, you know? And then that'll put me, you know, in Cleveland at, you know, 9.30, which means I'll miss that rush hour, right, which is going to put me in Chicago, you know? And so you do this. And now today, you know, 15 years later, truck drivers don't have to do any of that. You know, you don't have to shift the truck. You don't have to map. You know, you can figure out the least congested route to go on, and your hours of service are recorded, or a good portion of them are recorded automatically. All of that has been a substantial de-skilling that has, you know, put downward pressure on wages and allowed companies to kind of speed up, monitor, and direct. I mean, the key technology, you know, that I did work under is satellite-linked computers. So before, you could kind of go out and plan your own work, and the boss really couldn't see what you were doing and push you and say, you know, you've been on break for 10 hours. Why aren't you moving, you know? And you might tell them, you know, because I'm tired. You know, like, I didn't sleep well. I've got to get a couple more hours. You know, they're only going to accept that so many times, or at least some of those dispatchers are. All this technology has made the job sort of, you know, de-skilled the job, you know, hurt drivers in the labor market, made the work worse. So I think the burden is really on the technologists who are like, oh, this will make truck driver jobs better and sort of envision ways that it would. It's like, the burden's really, a proof is really on you to sort of really clearly lay out what that is going to look like, because it's 30 or 40 years of history suggests that technology into labor markets where workers are really weak and cheap is what wins, that new technology doesn't help workers or raise their wages. So it lowers the bar of entry in terms of skill. Yeah. So that's really interesting. That's tough. That's tough to know what to do with, because yeah, from a technology perspective, you want to make the life of the people doing the job today easier. Is it? Is that what you want? No, but that, like, when you think about like what, exactly. Because the reality is you will make their life potentially a little bit easier, but that will allow the companies that then hire people that are less skilled, get those people that were previously working there fired or lower wages. And so the result of this easier is a lower quality of life. Yeah. That's dark, actually. I know. I'm sorry. But you were saying that was for you initially the hopeful. Well, no, I'll get to that. But one more thing, because this is not stopping. Right. And this is another interesting question about the sort of automation. And I think Uber is an interesting example here, right, where it's like, OK, if we had self-driving trucks or self-driving cars, right, we could automate what used to be taxi service. There's a whole bunch of stuff that's already been automated, like the dispatching. So the dispatchers are already out of work in ride share and the payment is already automated. Right. So you have to automate steps like this. So you have to have that initial link to dispatch the truck. You have to have the automated mapping. And so we've sort of done all this incremental automation that could make the truck completely driverless. There are some important things happening right now with the remaining good jobs. So what you're really paying for when you get a good truck driver is, you know, like I said, you get those kind of local skills of like backing and congested traffic. Those it's really impressive to watch. And there's some value on it, certainly. But it's relatively low value in the actual driving technique. Right. So you bump something, you know, backing into the dock. You know, it might be a couple thousand dollars because you ruin a canopy or something over a dock or tear up a trailer. What you really want, those highly skilled, conscientious drivers. And that's really what it is. And that's what computers are really good at, is about being conscientious. Right. In the sense of like they pay attention continually. Right. And how I was describing those long haul segments where the driver, you know, just keeps out of the situations that could become problematic. And just they don't look at their phone and they take the job seriously and they're safe. And you can give somebody a skills test. Right. In you know, as a CDL examiner, you could take them out and say, all right, I need you to go around these cones and like drive safely through this school zone. But what really proves that you're a safe driver is two years without an accident. Right. Because that means that day after day, hour after hour, mile after mile, you did the right thing. Right. And not when it was like, oh, some situations emerging, but just consistently over time kept yourself out of accident situations. And you can see this with drivers who are, you know, a million or two million safe miles. The value of those drivers for Wal-Mart is they don't run over minivans. The company I ran, I work for, they ran over minivans on a regular basis. So, you know, when I when I was trained, they said we kill 20 people a year. We send someone to the funeral. There's a big check involved. Don't be that. You know, we don't want to go to your funeral and you don't want to be the person who who caused that funeral. OK, so they they just write that off. OK, that's just part of the business model. Now, forward collision avoidance. Can. You know, basically eliminate the vast majority of those accidents. That's what the value of a really expensive conscientious driver is based on. They don't run over minivans. So as soon as you have that forward collision avoidance, what's going to happen to the wages of those drivers? By way of a therapy session, help me understand. Is collision avoidance, automated collision avoidance systems, are they good or bad for society? Yeah, I mean, you know, this this is how they're good. Right. They're good. But in what do we do about the pain of a workforce in the short term because their their wages are going to go down because the job starts acquiring less and less skill? Is that is there a hopeful message here where other jobs are created? So I'm you know, I'm a sociologist. Right. So, you know, so I'm going to think about what's what's the structure behind that that creates that pain and its ownership. Right. You know, we don't call it capitalism for nothing. You know, what capitalists do is they figure out cheaper, more efficient ways to do stuff and they use technology to do that oftentimes. Right. This is the remarkable history of the last couple centuries and all the productivity gains is, you know, people who are in a competitive market saying if I have to do it. Right. I don't have a choice because like my competitor over there is going to eat my lunch if I'm not on my game. I don't have a choice. I've got to invest in this technology to, you know, make it more more efficient, to make it cheaper. And what do you look for? You look for oftentimes you look for labor costs. Right. You look for high value labor. If I can take a hundred and you know, a lot of these truck drivers make good money, $100,000, good benefits, vacation, you know, retirement. If I can replace them with a $35,000 worker when I'm competing with maybe a low wage retail employer rather than some other more expensive employers for, you know, skilled blue collar workers, I'm going to do that. And that's just, that's what we do. And so I think those are the bigger questions around this technology. Right. Is like, you know, are workers going to get screwed by this? Like, yeah, most likely. Like that's what we do. So one of the things you say is, I mean, first of all, the numbers of workers that will be, that will feel this pain is not perhaps as large as the journalists kind of articulate. But nevertheless, the pain is real. And I guess my question here is, do you have an optimistic vision about the transformative effects of autonomous trucks on society? Like, if you look 20 years from now, and perhaps see maybe 30 years from now, perhaps see these autonomous trucks doing the various parts of the scenarios you listed, and they're just hundreds of thousands of them, just like, like veins, like blood throwing through, flowing through veins on the interstate system. What kind of world do you see that's a better world than today that involves these trucks? Yeah. Can I defend myself first? Because I can, I'm reading the comments right now. Yes. Of people, you know, of the economists who are telling me. Dear commenter. Dear PhD in economics. Yes. Yes. Dear PhD in economics. I know that, that higher skilled jobs are created, you know, by, by technological advancement. Right. I mean, there are big questions about how many of them. Right. So the idea that we would create more, you know, expensive labor positions, right, with a new technology, right, you better check your business plan, if your idea is to take, you know, a bunch of low, low wage labor and replace it with the same amount of high wage labor, right. So we there's a question about how many of those jobs. And there's the really important social and political question of, are they the same people? Right. And do they live in the same places? And I think that kind of, you know, geography is a huge issue here with the impacts, right. Lots of rural workers. Interesting politically, lots of red state workers, right. Lots of blue state, maybe union folks who are going to try to slow autonomy and lots of red state, you know, representatives in the house, maybe who want to, you know, stand up for their, for their trucker constituents. So just to defend myself. Yeah. And to elaborate, I think economics as a field is not good at measuring the landscape of human pain and suffering. So, you know, sometimes you can forget in the numbers as real lives that are at stake. That's what I suppose sociology is better at doing. We try sometimes. Sometimes. Well, the problem with, I mean, I'm somebody who loves psychology and psychiatry and a little bit, I guess, of sociology. I realized how little, how tragically flawed the field is not because of lack of trying, but just how difficult the problems are. That to do really thorough studies that understand the fundamentals of human behavior and this, yes, landscape of human suffering, it's just, it's almost an impossible task without the data. And we currently don't, you know, not everybody's richly integrated to where they're fully connected and all their information is being like recorded for sociologists to study. So you have to make a lot of inferences. You have to talk to people. You have to do the interviews as you're doing. And through that, like really difficult work, try to understand, like hear the music that nobody else is hearing. The music of like what people are feeling, their hopes, their dreams, and the crushing of their dreams due to some kind of economic forces. Yeah. I mean, we've just lived that for four and a half years of probably, you know, elites. Let me just go out on a limb and say not understanding the sort of emotional and psychological currents of a large portion of the population. Right. And just being stunned by it and confused. Right. Wasn't confusing for me after having talked to truckers, again, who trucking is a job of last resort. These are people who've already lost that manufacturing job oftentimes, already lost that construction job to just aging. Right. So what, you know, what can we do? Right. What's sort of the positive vision? Because like we've got tons of highway deaths. We've got, and just to, you know, the big picture is, and this is the opportunity, I guess, for investors. It's a hugely inefficient system. So we buy this truck. There's this low wage worker in it oftentimes. And again, I'm setting aside those really good line haul jobs in LTL. Those are a different case. That low wage worker is driving a truck that they might, the wheels might roll seven to eight hours a day. That's what the truck is designed to do. And that's what makes the money for the company. In other seven, eight hours a day, the driver's doing other kinds of work that, you know, is not driving. And then the rest of the day, they're basically living out of the truck. You really can't find a more inefficient use of an asset than that. Right. Now, a big part of that is we pay for the roads and we pay for the rest areas and all this other stuff. So the way that I work and the way that, you know, I think about these problems is I try to find analogies, right, sort of labor processes and things that make economic sense, you know, that seem, you know, in the same area of the economy, but have some different characteristics for workers, right, and sort of try to figure out why does the economics work there. Right. And so if you look at those really good jobs, the most likely way that you as a passenger car driver would know that it's one of those drivers is that there are multiple trailers. Right. So you see these like maybe it's three small trailers, maybe it's two sort of medium sized trailers. Some places you might even see two really big trailers together. Right. You do that because labor is expensive. Right. And it's highly skilled. And so you use it efficiently and you say, all right, you know, rather than having you, you know, haul that little trailer out of the ports, you know, that sort of half sized container, we're going to wait till we get three or we're going to coordinate the movement so that there are three ready. You go do what truckers call make a set, put them together. Right. And you and you go. That's a massive productivity gain. Right. Because, you know, you're hauling two, three times as much freight. So the the positive scenario that I threw out in 2018 was why not have a human driven truck with a self-driving truck that follows it. Right. Just a drone unit. And it was, you know, to me, this seemed as a non-computer scientist, a sociologist. Right. This made a lot of sense because when I got done talking to the, you know, the computer scientists and the engineers, they were like, well, you know, it's like object recognition, decision making, algorithm, all this stuff. It's like, all right, so why don't you leave the human brain in the lead vehicle? Right. You got all that processing. And then all that following. Now, again, this is sort of me being a layperson. You know, I said, why don't you know, then that following truck, right, takes direction from the front. It uses the rear of the trailer as a reference point. It maintains the lane. You've got cooperative adaptive cruise control and that you double the productivity of that driver. You solve that problem that I hated in my, you know, urban truck ports thing about the bridge weight. Because when you get to the bridges, you know, the two trucks can just spread out just enough to make the bridge weight. Right. And you can just program that in and, you know, they're 50 feet further apart, 100 feet further apart. So, interesting sort of, I think, story about this that leads to kind of, I think, the policy questions. In, I guess, 2017, Jack Reed and Susan Collins, you know, requested from the Senate, the Senate requested research on what the impacts of self-driving trucks would be. And the first stage of that was for the GAO to do a report, sort of looking at the lay of the land, talking to some experts. And I was working on my 2018 report, help contribute to that GAO report. And, you know, I had the six scenarios, right? I'm like, okay, you know, here's what Starsky's doing, you know, here's what Embark and Uber are doing, you know, here's what Waymo might be doing. Nobody really knows, right? Here's what Peloton's doing, you know, here's the autopilot scenario. And then here's this one that I think actually could be good for drivers. So now you've got that driver who's got two, you know, two times the freight, their decisions are more important, they're managing a more complex system, right? They're probably gonna have to have some global understanding of how to, you know, the environments in which it can operate safely. Right now we're talking upskilling, right? And so, you know, that the GAO, you know, sort of writes up these different scenarios. And the idea is that it's going to prepare for this Department of Transportation, Department of Labor set of processes to engage stakeholders and sort of get, you know, get industry perspectives, and then do a study on the labor impacts. So, you know, that DOT, DOL process starts to happen. And, you know, I get to the workshop, and a friend was sitting at the table next to me. And he holds up the scenarios that they're going to have us discuss at this workshop. And he's like, hey, these look really familiar, right? They were the, you know, scenarios from the report, but there were only five, instead of six. The sixth scenario, which was the upskilling labor, good for workers scenario, wasn't discussed. So to clarify, that's the integral piece of technology there is platooning. Yeah, I mean, in a sense, it's platooning, but and I, and in fairness, right, the, as I pitched that idea, or sort of ran that idea by the computer scientists and engineers that I would, and product managers that I would talk to, they would say, you know, you know, we thought about that. But that following truck, it's not that simple. You know, that thing, basically, we had to engineer that to be capable of independent self driving, because what if there was a cut in, or, you know, any number of scenarios in which it lost that connection to the lead truck for whatever reason. Now, I mean, I don't know who platooning is hard. There's edge cases, I guarantee the number of edge cases and platooning is orders of magnitude lower than the number of edge cases. In the general solo full self drive, you do not need to solve the full self driving problem. I mean, if you're talking about probability of dangerous events, it just seems with platooning, then like you can deal with cut ins. Yeah, so this is, you know, this is beyond, this is one of the challenge, obviously, of being a researcher who, you know, doesn't really have any background in the technology, right? So I can dream this up. I don't, you know, I have no idea if it's feasible. Well, let me speak, you spoke to the PhDs in economics, let me speak to the PhDs in computer science. If you think platooning is as hard as the full self driving problem, we need to talk, because I think that's ridiculous. I think platooning, in fact, I think platooning is an interesting idea for ride sharing as well, for the general autonomous driving problem, not just trucking, but obviously trucking is the big, big benefit, because the number of A to B points in trucking is much, much lower than the general ride sharing problem. But anyway, I think it's a great idea, but you're saying it was removed. Yeah, and so you can go, you know, and, you know, listeners could go to these reports, they're publicly available, and they explain why in the footnote. And, you know, they note that there was this other scenario suggested by at least me, and I can remember they said someone else did too. But they said, you know, we didn't include it because no developers were working on it. Interesting. Full disclosure, that was the approach that I took in my research, right, which was to go to the developers and say, what's your vision, right? What are you trying to develop? That's what I was trying to do. And maybe, you know, and then I tried to think outside the box at the end by adding that one, right? Like, here's one that I have, you know, people aren't talking about that could be cool. Now, again, it had been proposed in like 2014 for like fuel convoys. So you could just have like one super armored lead fuel truck, right, in a, you know, bringing fuel to forward operating bases in Afghanistan. And then you wouldn't need, you know, the super heavy, you know, you wouldn't have to protect the human life in the following truck. So that's interesting. You're saying like, when you talk to Waymo, when you talk to these kinds of companies, they weren't at least openly saying they're working on this. So then it doesn't make sense to include in the list. Yeah. And so, but here's the thing, right? This is the Department of Transportation, right? And the Department of Labor. Maybe they could consider some scenarios, like, maybe we could say, you know, this technology has got a lot of potential. Here's what we'd like it to do. You know, we'd like it to reduce highway deaths, help us fight climate change, reduce congestion, you know, all these other things. But that's not how our policy conversation around technology is happening. We're not, and people don't think that we should. And I think that's the fundamental shift that we need to have, right? I've been involved with this a little bit, like NHTSA and DOT. The approach they took is saying, we don't know what the heck we're doing. So we're going to just let the innovators do their thing and not regulate it for a while, just to see. You think DOT should provide ideas themselves? Well, so this is the great trick in policy of private actors, is you get narrow mandates for government agencies, right? So, you know, the safety case will be handled by organizations whose mandate is safety. So the Federal Motor Carrier Safety Administration, who is, you know, going to be a key player, I argue in an article that I wrote, you know, they're going to be a key player in actually determining which scenario is most profitable by setting the rules for truck drivers. Their mandate is safety, right? Now, they have lots of good people there who want, you know, who care about truck drivers and who wish truck drivers' jobs were better. But they don't have the authority to say, hey, we're going to write this rule because it's good for truck drivers, right? And so when you, you know, we need to say, you know, as a society, we need to not restrict technology, not stand in the way of things, we need to harness it towards the goals that matter, right? Not whatever comes out the end of the pipeline, because it's the easiest thing to develop or whatever is most profitable for the first actor or whatever. But, you know, and we do, the thing is, we do that, right? I mean, like, when we sent people to the moon, you know, we did that. And there were tremendous benefits that followed from it, right? And we do this all the time in, you know, trying to cure cancer or whatever it is, right? I mean, we can do this, right? Now, the interesting sort of epilogue to that story is, you know, six months or so, I don't know how long it was after those meetings in which that sixth scenario was not considered, a company called Locomation, you know, ends up using that, essentially that basic scenario with a slight variation. So, they leave the human driver in both trucks, and then that following driver goes off duty. And then, you know, I've been trying to think of what the term is, they kind of, I think of it as like slingshotting, they sort of, when one runs out of hours, you know, the one who's off duty goes in front and, you know. And so, you know, if only they had been, you know, around six months earlier, it might have been considered by the DOT. But it just says, you know, who has the authority to propose what these visions of the future are? Well, some of it is also just the company stepping up and just doing it, screw the authority, and showing that it's possible, and then the authority follows. So, that's why I really love innovators in the space. The criticism I have, the very sort of real, I don't know, harsh criticism I have towards autonomous vehicle companies in the space is they've gotten culturally. It's become acceptable somehow to do demos and videos, as opposed to the old school American way of solving problems. There's a culture in Silicon Valley where you're talking to VCs that have lost that kind of love of solving problems. They kind of like envision, if the story you told me in your PowerPoint presentation is true, how many trillions of dollars might I be able to make? There's something lost in that conversation where you're not really taking on the problem in a real way. So, these autonomous vehicle companies realize we don't need to. We just need to make nice PowerPoint presentations and not actually deliver products that everybody looks outside and says, holy shit, this is life changing. This is where I have to give props to Waymo, is they put driverless cars on the road. And like, forget PowerPoint slide presentations, actual cars on the road. Then you can criticize like, is that actually going to work? Who knows? But the thing is, they have cars on the road. That's why I have to give props to Tesla. They have whatever you want to say about risk and all those kinds of things. They have cars on the road that have some level of automation. And soon they have trucks on the road as well. And that kind of, that component, I think is an important part of the policy conversation. Because you start getting data from these companies that are willing to take the big risks, as opposed to making slide decks, they're actually putting cars on the road. And like, real lives are at stake. They could be lost and they could bankrupt the company if they make the wrong decisions. And that's deeply admirable to me. Speaking of which, I have to ask Waymo Trucks, I think it's called Waymo Via. So I'm talking to the head of trucking at Waymo. I don't know if you got any chance to interact with them. What's a good question to ask the guy? What's a good question of Waymo? Because they seem to be one of the leaders in the space. They have the zen-like calm of like being willing to stick with it for the long term in order to solve the problem. Yeah, and I guess they have that luxury, right? Which I don't think I, if I had another life as a researcher, I would love to just study the business strategies of startups and Silicon Valley sort of structure. Would you consider Waymo a startup? No. No, right? I mean, it's at least not in the things that seem to matter in the self-driving space. So you mentioned the demos. And I don't have enough data as a sociologist to really say like, oh, this is why they do what they do. But my hypothesis is, there's a real scarcity of talent and money for this. And there certainly was a scarcity of like partnerships with OEMs and the big trucking companies. And there was a race for it. And the way that if you don't have the backing of Alphabet, you do a demo, right? And you get a few more good engineers who say, hey, look, they did that cool thing. Yeah. Like Anthony Levandowski did with Otto. And that resulted in the Uber purchase of that program. So what would I ask? I mean, I think I would ask a lot of questions, but I think the markets- Well, there's also on record and off record conversations. Unfortunately, I'm asking for an on record conversation. And that, I don't know if these companies are willing to have interesting on record conversations. Yeah. I mean, I assume that, like, there are questions that I don't think you'd have to ask. Like, I assume they're going to be actually driverless, right? They're not going to like keep the driver in there. Yeah. So, I mean, for the industry, I think it would be interesting to know where they see that first adopter, right? Oh, you mean from like the scenarios that laid out, which one are they going to take on? Yeah. I mean, because that's going to, again, it's those really expensive good jobs, right? So those LTL jobs, the like UPS jobs. Now that's going to be, that's where labor is too, right? That's where the Teamsters are. That's the only place they are left, right? So that's going to be the big fight on the hill and public, or if labor can muster it, right? I don't know. There's a really cool, one thing I would recommend to you and your listeners, if you really want to see some, like a remarkable page in sort of the history of labor and automation, there's a report that Harry Bridges, who was the socialist leader of the longshoremen on the West Coast and just, you know, galvanized that union. And they still control the ports today because of the sort of vision that he laid down. In the 1960s, he put out a photo journal report called Men and Machines. And basically what it was, was it was an internal education campaign to convince the membership that they had to go along with automation. Machines were coming for their jobs. And what the photo journal, it's almost like a hundred pages or something like that, is like, here's how we used to do it. Some of you old timers remember it. Like we used to take the barrels of olive oil and we'd stack them in the hold and we'd roll them by hand and we'd put the timber in and we'd, you know, stack the crates tight, you know? And that was the pride of the longshoremen was a tight stow. And now you all know, you know, there are cranes that come down and there's no longer any, you know, rope slings and we're loading bulldozers into the hold to push the ore up into piles and then clamshells are coming down. And he made this case to them and he said, this is why we're signing this agreement to basically allow the employer to automate. And we're going to lose jobs, but we're going to get a share of the benefits. And so our wages are going to go up. We're going to continue to control the hiring and training of workers. Our numbers are going to go down. But you know, basically that last son of a bitch who's working at the ports is going to be one really well paid son of a bitch, you know? He may just be one standing, but he's going to love his job. You should check out that report. That's an interesting vision of a future that probably still holds. That is, I mean, there is some level to which you have to embrace the automation. Yeah. I mean, and who gets, you know, it's the benefits, right? It's like, I mean, think of the public dollars that went into developing self-driving vehicles in the early days, right? Not just the vision of it, right? Which was a public vision to, you know, take soldiers out of harm's way. But, you know, a lot of money. And there's some way, if you are a business that's leveraging that technology from a broad historical ethical perspective, you do owe it to the bigger community to pay back, like for all the investment that was paid to make that technology a reality. In some sense, I don't know how to make that right, right? On one, there's pure capitalism and then there's communism and I'm not sure how to get that balance right. You know, I don't have all the answers in here, you know, and I wouldn't expect, you know, individual private companies to kind of kick back, right? Capitalism doesn't allow that, right? Unless you have a huge monopoly, right? And then you can, on the backside, create music halls and libraries and things like that. But, you know, here's what I think, you know, the basic obligation is, is, you know, come to the table, like, and have an honest conversation with the policy makers, with the truck drivers, you know, with the communities that are at risk. Like, at least let's talk about these things, you know, in a way that doesn't look like the way lobbying works right now, where you send a well-paid lobbyist to the Hill to, you know, convince some representative or senator to stick a sentence or two in that favors you into the, like, let's have a real conversation. Real human conversation. Can we just do that? Yeah, don't play games. Real, real human conversation. Let me ask you, you mentioned Autopilot, gotta ask you about Tesla. This renegade little company that seems to be, from my perspective, revolutionizing autonomous driving or semi-autonomous driving, or at least the problem of perception and control. They've got a semi on the way. They got a truck on the way. What are your thoughts about Tesla's semi? You know, I, and I did have some very preliminary conversations with, you know, policy folks there. You know, nothing really in the tech or business side of it too much. And here's why. I think because electrification and autonomy run in opposite directions. Right. I just, you know, I don't see the application, the value in self-driving for the truck that Tesla's gonna produce in the near term. You know, they're just, you're not gonna have the battery. Now, you could have wonderful safety systems and, you know, reinforcing, you know, the auto, you know, self-driving features supporting a skilled driver, but you're not gonna be able to pull that driver out for long stretches the way that you are with driverless trucks. So do you think, I mean, the reason so that, yeah, the electrification is not obviously coupled with the automation. They have a very interesting approach to semi-autonomous pushing towards autonomous driving, right? It's very unique. No LIDAR, now no radar. It's computer vision alone from a large, they're collecting huge amounts of data from a large fleet. It's an interesting, unique approach, bold and fearless in this direction. If I were to guess whether this approach would work, I would say no. Let's start it. One, you would need a lot of data and two, because you have actual cars deployed on the road using a beta version of this product, you're going to have a system that's far less safe and you're going to run into trouble. It's horrible PR. Like, it just seems like a nightmare. But it seems to not be the case, at least up to this point. It seems to be not, you know, on par, if not safer, and it seems to work really well and the human factors somehow manages, like drivers still pay attention. Now there's a selection of who is inside the Tesla autopilot user base, right? There could be a self-selection mechanism there, but however it works, these things are not running off the road all the time. So it's very interesting whether that can sort of creep into the trucking space. Yes, at first, the long haul problem is not solved. They need to charge. But maybe you can solve, you know, a lot of your scenarios involved small distances. And, you know, that last mile aspect, which is exactly what Tesla is trying to solve for the regular passenger vehicle space, is the city driving. Is it possible that you have these trucks? It's almost like, yeah, you solve the last mile delivery part of some of the scenarios that you mentioned in autonomous driving space. Do you think that's from the people you've spoken with too difficult of a problem? The thing that, you know, keeps me so interested in this space and thinking that it's so important, you know, is again that efficiency question, that safety question, and the way that these economics can push us potentially, you know, toward a more efficient system. So I want to see those Tesla electric trucks running out to those truck ports where you've got those two trucks with a human driver in front. I think that's now what's powering those is that hydrogen. You know, I mean, I don't, you know, again, it's very interesting as a researcher who does not have a background in technology and doesn't have a horse, you know, in this race. I mean, you know, for all I know, self-driving trucks will ultimately be achieved by some biomechanical sensor that uses echolocation because we took stem cells of bats. And, you know, I mean, I don't, you know, I don't, I am completely unable to assess who's, you know, who's ahead or who's behind or who makes sense. But I think one key component there, and this is what I see with Tesla often, and it's quite sad to me that other companies don't do this enough, is that first principles thinking. Like, wait, wait, wait, okay, it's looking at the inefficiencies as opposed to, I worked with quite a few car companies, and they basically have a lot of meetings. There's a lot of meetings. And the discussion is like, how can we make this cheaper, this cheaper, this cheaper, this component cheaper, this cheaper, the cheapification of everything, just like you said, as opposed to saying, wait a minute, let's step back. Let's look at the entirety of the inefficiencies in the system. Like, why have we been doing this like this for the last few decades? Like, start from scratch, can this be 10x, 100x cheaper? Like, if we not just decrease the cost of one component here, this component here, or this component here, but like, let's like, redesign everything. Let's infrastructure, let's have special lanes, or in terms of truck ports, as opposed to having regular human control truck ports, have some kind of weird, like, like sensors, like where everything about the truck connecting at that final destination is automated fully from the ground up, you build the facility from the ground up for the autonomous truck. All those kinds of sort of questions are platooning. Let's say, wait a minute, okay, I know we think platooning is hard, but can we think through exactly why it's hard? And can we actually solve it? Like, if we collect a huge amount of data, can we solve it? And then teleoperation, like, okay, yeah, it's difficult to have good signal, but can we actually, can we have, can we consider the probability of those edge cases and what to do in the edge cases when the teleoperation fails? Like, how difficult is this? What are the costs? How do we actually construct a teleoperation center full of humans that are able to pay attention to a large fleet where the average number of vehicles per human is like 10 or 100? You know, like having that conversation as opposed to kind of having, you know, you show up to work and say, all right, it seems like, you know, because of COVID we, you know, are not making as much money. Can we have a cheaper, can we give less salary to the trucker and can we build, like, decrease the cost or decrease the frequency at which we buy new trucks? And when we do buy new trucks, make them cheaper by making them crappier, like this kind of discussion. This is why, to me, it's like Tesla's like rare in this. And there's some sectors in which innovation is part of the culture. In the automotive sector, for some reason, it's not as much. This is obviously the problem that Ford and GM are struggling with. It's like, they're really good at making cars at scale cheap. And they're like legit good, like Toyota at this, some of the greatest manufacturing people in the world, right? That's incredible. But then when it comes to hiring software people, they're horrible. So it's culture and then it's such a difficult thing for them to sort of embrace. But greatness requires that they embrace this, embrace whatever is required to remove the inefficiencies in the system. And that may require you to do things very differently than you've done in the past. Yeah, I mean, there are certain things that the market can do well in my, this is how I see the world, right? And that's the best way to organize certain kinds of activities is the market and private interest. But I think we go too far in some areas. Transportation is, if we can't have a public debate about the roads that we all pay for, forget about it. Private factories and all these other, healthcare and other places, it's going to be way harder there. Healthcare, I guess, has some direct contact with the consumer where we're probably going to have lots of hands on public policy about concerns around patient rights and things like that. But if we can't figure out how to have a public policy conversation around how technology is going to reform our public roadways and our transportation system, we're really leaving way too much to private companies. It's just, it's not in their, I get asked this question, like, what should companies do? And I'm like, just go about doing what you're doing. I mean, please come to the table and talk about it, but it's not their role. I mean, I appreciate Elon's attempts to have species level goals, like, we're going to go to Mars. I mean, that's amazing. And that's incredible that someone can realize that, have a chance at realizing that vision. It's amazing. But when it comes to so many areas of our economy, we can't wait for a hero. We have to have, and there are way too many interests involved. It's who builds the roads, who, I mean, the money that sloshes around on Capitol Hill to decide what happens in these infrastructure bills and the transportation bill is just obscene. See, I think this is an interesting view of markets. Correct me if I'm wrong, but let me propose a theory to you. That progress in the world is made by heroes and the markets remove the inefficiencies from the work the heroes did. So going to Mars from the perspective of markets probably has no value. Maybe you can argue it's good for hiring to have a vision or something like that. But like those big projects don't seem to have an obvious value, but our world progresses by those big leaps. And then after the leaps are taken, then the markets are very good at removing sort of inefficiencies. But it just feels like the autonomous vehicle space and the autonomous trucking space requires leaps. It doesn't feel like we can sneak up into a good solution that is ultimately good for labor, like for human beings in the system. It feels like some, like probably a bad example, but like a Henry Ford type of character steps in and say, like, we need to do stuff completely differently. Yeah. And you said we can't hope for a hero, but it's like, no, but we can say we need a hero. We need more heroes. So if you're a young kid right now listening to this, we need you to be a hero. It's not like we need you to start a company that makes a lot of money. No. You need to start a company that makes a lot of money so that you can feed your family as you become a hero and take huge risks and potentially go bankrupt. Those risks is how we move society forward, I think, maybe as a romantic view. I don't know. I totally disagree. You disagree. God damn it. And out of the two of us, you're the knowledgeable one. No, no. I think it's a matter of like, do we need those heroes? Absolutely. I mean, I saw the boosters come down from SpaceX's rockets and land nearly simultaneously with my kids after school one day. And I thought, oh my God, like science fiction has been made real. It's incredible. And it's a pinnacle of human achievement, right? It's like this is what we're capable of. But we need to have that, those heroes oriented. We need to allow them to orient toward the right, toward the goals. We got climate change. I mean, all the heroes out there. Right? I mean, it's time. The clock is ticking. It's past. I've been working on climate change issues since the mid 90s. I still remember the first time in 2010 when I got a grant that was completely focused on adaptation rather than prevention. And just when it hit me, that like, wow. So adaptation versus prevention is like acceptance that there's going to be catastrophic impact. We just need to figure out how we at least live with that. Yeah. And the grant was like, okay, our agriculture system is going to move. Our breadbasket is no longer going to be California. It's going to be Illinois. What does that mean for truck transportation? So in terms of a big philosophical societal level, that's kind of like giving up in terms of the big heroic actions. You know, failures in human history. Yeah, that's going to be, let's hope not the biggest, but could be. So let me say why I disagree. Right? Henry Ford, amazing, right? To sort of mass produce cars, right? Daimler to put that first truck on the road without the roads. Right? Like we need that innovation. There's no doubt about it. And there are roles for that, but there's big public stuff that sets the stage that's critical. And what it really is, it's a sociological problem, right? It's a political problem. It's a social problem. We have to say, and we have these screwed up ideas, right? So we have this politics right now where like everybody feels like they're getting screwed and someone undeserving is benefiting. When in fact, like, you know, at least in the middle, right, they're huge. I used to teach this course in rich and poor, you know, in economic inequality. And I would go through, you know, public housing subsidies in Philadelphia, you know, section eight subsidies, you know, and then I would go through my housing subsidies for my mortgage interest deduction. And it worked out to basically the average payment for a section eight housing voucher in my neighborhood. I'm not a welfare recipient, according to the dominant discourse. And so we have this completely screwed up sense of like where our dollars go and, you know, where the, who benefits from the investment. And, you know, we need to, you know, I don't know that we can do it, but, you know, if we're going to survive, we need to figure out how to have honest conversations where private interest is where we need it to be in fostering innovation and, you know, and rewarding the people who do incredible things. Please, you know, we don't want to squash that. But we need to harness that power to solve what I think are some pretty big, you know, existential problems. So you think there's a like government level, national level collaboration required for infrastructure project like that there's we should really have large moonshot projects that are funded by our governments? At least guided by I mean, I think there are ways to finance them and you know other things, but we got to be careful, right? Because that's where you get all these sort of perverse, you know, unintended consequences and whatnot. But if you look at transportation in the United States, and it is the foundation of the, you know, manifest destiny economic growth, right? That built the United States into the world superpower that it became and the industrial power that it became it rested on transportation, right? It was like, you know, the Erie Canal, I grew up a few miles from where they dug the first shovel full of the Erie Canal and everyone thought it was, you know, crazy, right? But those public infrastructure projects, the canals, right? The railroads, yeah, they were privately built, but they wouldn't have been privately built without, you know, Lincoln funding them essentially and giving, you know, the railroads, you know, land in exchange for building them. The highway system, the Eisenhower, the payback that the US economy got from the Dwight D. Eisenhower interstate system is phenomenal, right? No private entity was gonna do that, electrification, dams, water, you know, we need to do this infrastructure, infrastructure. And now more than ever, it's been really upsetting to me on the COVID front, there's one of the solutions to COVID, which seems obvious to me from the very beginning that nobody's opposed to, it's one of the only bipartisan things is at-home testing, rapid at-home testing. There's no reason why at the government level, we couldn't manufacture hundreds of millions of tests a month, there's no reason starting in May, 2020. And that gives power to a country that values freedom, that gives power information to each individual to know whether they have COVID or not. It's possible to manufacture them for under a dollar, it's like an obvious thing, it's kind of like the roads, it's like everybody's invested, let's put countless tests in the hands of every single American citizen, maybe every citizen of the world. The fact that we haven't done that to date, and there's some regulation stuff with the FDA, all the kind of dragging our feet, but there's not actually a good explanation except our leaders and culturally we've lost the sort of, not lost, but it's a little bit dormant. The will to do these big projects that better the world, I still have the hope that when faced with catastrophic events, the more dramatic, the more damaging, the more painful they are, the higher we will rise to meet those. And that's where the infrastructure style projects are really important, but it's certainly a little bit challenging to remain an optimist in the times of COVID because the response of our leaders has not been as great and as historic as I would have hoped. I would hope that the actions of leaders in the past few years in response to COVID would be ones that are written in the history books and we talk about it as we talk about FDR, but sadly I don't know, I think the history books will forget the actions of our leaders. Let me just, to wrap up autonomy, when you look into the future, are you excited about automation in the space of trucking? Is it, when you go to bed at night, do you see a beautiful world in your vision that involves autonomous trucks? Like all of the truckers you've become close with, you've talked to, do you see a better world for them because of autonomous trucks? Damn you, Lex. You know why? Because I mean, I want to be an optimist, and I want to think of myself, I guess, as a half glass full kind of person. But when you ask it like that, and I think about, when I look at the challenges to harnessing that for, just let's take labor and climate, right? There are other issues, congestion, et cetera, infrastructure, that are going to be affected by this. Again, those big transformational issues. I think it's going to take the best of us. Like it's going to take the best of our policy approaches. It's going to take, you know, we need to start investing in rebuilding those institutions. I mean, that's what we've seen in the last four years, right? And the erosion of that was so clear among these truck drivers. Like, you know, when Trump came in and said, like, you know, free trades, good for workers, like, yeah, right. You know, I grew up in the Rust Belt. You know, I watched factory after factory close. All of my ancestors worked at the same factory. It's still holding on by a thread. Like, you know, the Democratic Party told, you know, blue collar workers for years, don't worry about, you know, free trade. It's not bad for you. And I know the economists will probably get in the comment box now. We'll look forward to your comments. We look forward to your comments about how free trade benefits everybody. But, you know, immigration, you know, you go and I'm, you know, I think immigration is great. The United States benefits from it tremendously, right? But there are costs, right? Go down to South Philadelphia and find a drywaller and tell him that immigration hasn't hurt him, right? You know, go to these places where there's competition, right? And yes, we benefit overall, but we have a system that allows some people to pay really high costs. And Trump tapped into that, you know, and there was no, you know, there's more than that too, obviously. And there's lots of really dark stuff that goes along with it, you know, the sort of racialization of others and things like that. But he hit on those core, you know, issues that, you know, if you were to go back over my trucking interviews for 15 years, you would have heard those stories over and over and over again. That sense of voicelessness, that sense of powerlessness, that sense that there's no difference between the Democrats and the Republicans because they're all going to screw us over. And that was there, you know, and you could just ignore it as long as you want and tell people, don't worry, trade's good for you. Don't worry, immigration is good for you. As their communities lose factories and I mean, a lot of them were lost to the South before they were lost to overseas, whatever, but tapped into that, you know, and there's a fundamental distrust of, you know, you look at these like Pew polls on like, you know, whether people trust the media, right? But whether or not they trust higher education, you know, you know, these institutions that I find magical, right? I mean, you look at the vaccine research and stuff that, you know, just, you know, brilliant, you know, people doing incredible things for humanity. Like, you know, the idea that like, you know, we can take these viruses that, you know, used to ravage through the human population and that we had to be terrified of. And, you know, we've, you know, we've suffered, but, you know, we have such power now to defend ourselves, right? Behind these programs, right? And to see those people be like, I'm not sure if higher education is good for the country or not. You know, it's like, where are we? You know, so we need to rebuild the faith and trust in those institutions and have these, but we need to have honest conversations before people are going to buy it. Do you have ideas for rebuilding the trust and giving a voice to the voices? So is the, many of the things we've been talking about is so sort of deeply integrated. You think like, this is the trouble I have with people that work in AI and autonomous vehicles and so on. It's not just a technology problem. It's this human pain problem. It's the robot essentially silencing the voice of a human being, because it's lowering their wage, making them suffer more and giving them no tools of how to escape that suffering. Is there something, I mean, it even gets into the question of meaning, you know, so money is one thing, but it's also what makes us happy in life. You know, a lot of those truckers, the set of jobs they've had in their life were defining to them as human beings. And so, and the question with automation is, is not just how do we have a job that gives you money to feed your family, but also a job that gives you meaning, that gives you pride. Yeah. And for me, the hope is that AI and automation will provide other jobs that will be a source of meaning. But coupled with that hope is that there will not be too much suffering in the transition. And that's not obvious from the people you've spoken with. I mean, I think we need to differentiate between the effects of technology and the effects of capitalism, right? And they are, you know, the fact that workers don't have a lot of power, right, in the system matters. Now, we had a system, right, and that's why I would say, you know, go to that, you know, Harry Bridges report, and, you know, those were workers who had a sense of power. They said, you know what, we can demand some of the benefits, like, yeah, automate our jobs away, but, you know, kick a little down to us, right? And we had, in the golden era of American industrialism in post-World War II, that was the contract. The contract was employers can do what they want in automation and all these things. Yeah, sure, there's some union rules that make things, you know, less efficient in places. But the key compromise is tie wages to productivity. That's what we did. We tied—that's what unions did. They tied wages to productivity, kept demand up, right, it was good for the economy, some economists think, right? And that's what, you know, we need to—I think we need to acknowledge that. We need to acknowledge the fact that it's not just technology, it's technology in a social context in which some people have a lot of power to determine what happens. For me, I don't have all the answers, but I know what my answer is. And my answer is, and I think I started with this, you know, I can learn from every single person, you know. Did I have to talk to the 200th truck driver? In my opinion, yes, because I was going to learn something from that 200th truck driver. Now, people with more power might talk to none, or they might talk to five and say, okay, I got it, you know. People are amazing, and every one of them has a life experience and concerns and, you know, can teach us something. And they're not in the conversation, you know. And I know this because I'm the expert, you know. So I get pulled into these conversations and people want to know, you know, what's going to happen to labor, you know. It's like, well, I try to—so I try to be a sounding board, and I feel a tremendous weight of responsibility, you know, for that. But I'm not those workers, you know. And they may listen to this or, you know, walk in the door sometime, it's about to be like, that guy's full of shit, that's not what I think at all, you know. And they don't get heard over and over and over again. But in a small way, you are providing a voice to them. And that's kind of the—if at scale we apply that empathy and listening, then we could provide the voice to the voiceless through our votes, through our money, through—I mean, that's one way to make capitalism work at not making the powerless more powerless, is by all of us being a community that listens to the pain of others and tries to minimize that, to try to give a voice to the voiceless, to give power to the powerless. I have to ask you, by way of advice, young people, high school students, college students, entering this world full of automation, full of these complex labor markets and markets, period, what would you—what kind of advice would you give to that person about how to have a career, how to have a life they can be proud of? Yeah, I think, you know, this is such a great question. I don't—it's okay to quote Steve Jobs, right? Always. Yeah, I mean, so—and I just heard this recently, it was a commencement speech that he gave, and I can't remember where it was. And he was talking about, you know, he had famously dropped out of school but continued to take classes, right? And he took a calligraphy class, and it influenced the design of the Mac and sort of fonts, and, you know, just was something that he had no, you know, sense of what it was going to be useful for. And his lesson was, you know, you can't connect the dots looking forward. You know, looking back, you can see all the pieces that sort of led you to where you ended up. And for me, studying truck driving, like, I mean, I literally went to graduate school because I was worried about climate change, and like, you know, I had a whole other dissertation planned and then was like driving home and like I had read about all this management literature and sort of like how you get workers to work hard for my qualifying exams, and then read a popular article on satellite-linked computers. And the story in the literature was just a sense of autonomy, and I was like, well, that monitoring must affect the sense of autonomy. And it's just this question that I found interesting, and it never in a million years that I ever thought I was going to like, you know, spend 15 years of my life studying truck driving. And it was like, if you were to map out a career path in academia or research, like, you know, you would do none of the things that I did that many people advise me against, where like, you can't like go spend a year working as a truck driver, you know, like, that's crazy. Or, you know, you can't, you know, spend all this time trying to write like one huge book and, you know. So I mean- By the way, if I could just interrupt, what was the fire that got you to take the leap and go and work as a truck driver and go interview truck drivers? This is what a lot of people would be incapable of doing, just took that leap. What the heck is up with your mind that allowed you to take that big leap? So I think it's probably like Tolkien and Lord of the Rings, you know. I mean, as a teenager, you know, I sort of adopted some sense of needing to, you know, heroically go out in the world and, you know, which I've done at various points in my life. And like looking back in absolutely stupid ways that, you know, where I could have completely ended up dead and traumatized my family, including like, I took a couple week trip in the Pacific, like solo trip on a kayak. And basically my kayaking experience up till that, you know, point had been, you know, on a fairly calm lake and like class one- Solo trip on a kayak in the Pacific. Yeah, yeah. So I was working on forestry issues and we were starting a campaign up in really remote British Columbia. And I was like, okay, if I'm going to work on this, I've got to actually go there myself and see what this is all about and see whether it's worth like devoting my sort of, you know, life right now to. And just drove up there with this kayak and, you know, put into the Pacific and it was insane, you know, like the tides are huge. And, you know, there was one point in which I was going down a fjord and two fjords kind of came up and there was a cross channel. And I had hit the timing completely wrong and the tide was sort of rushing up like, you know, rivers in these, you know, two fjords and then coming through this cross channel and met and created this giant standing wave that I had to paddle through. And now, actually very recently, I've gone out on whitewater with some people who know what the hell they're doing. And I realized like just how absolutely stupid and, you know, ill fit I was, but that's just, I think I've always had that. Were you afraid when you had that wave before you? That wave scared the shit out of me. Yeah. Okay. What about taking a leap and becoming a trucker? Yeah, there was some nervousness for sure. I mean, and, you know, I guess my advantage as an ethnographer is I grew up in a blue collar environment, you know, again, all my ancestors were factory workers. So I can move through spaces. I'm really, I feel comfortable, I can become comfortable in lots and lots of places, you know, not everywhere, but, you know, along class lines for sort of white, you know, even white ethnic workers like that's, you know, I can move in those spaces fairly easily. I mean, not entirely. There was one time where I was like, okay, you know, and I grew up around people worked on cars, I'd been to drag races and NASCAR and I'd been to, you know, Colgate University. And I think that was probably my initial training was, you know, being this just working class kid who ends up in this, you know, sort of blue blood, small liberal arts college and just feeling like, you know, both having the entire world opened up to me like philosophy and Buddhism and things that I never heard of, you know, and just became totally obsessed with and just like, you know, just following my interests. But also culturally perhaps didn't feel like you fit in. Feeling like just a fish out of water. I just, you know, but at the same time that, you know, sort of drove me in the sense that it drove an opening of my mind because I couldn't understand it. You know, I was like, I didn't know that this world existed. I don't understand. And I think maybe that's where my real first step in trying to understand other people because they were my friends, you know, I mean, they were my teammates. I played lacrosse in college. So like, you know, I was close to people who came from such different backgrounds than I did. And I just, I was so confused, you know? And so I think I learned to learn and then, you know, sort of went from there. And then develop your fascination with people. And the funny thing is you went from trucking now to autonomous trucks. I mean, this, speaking of not being able to connect the dots and, you know, your life in the next 10 years could take very interesting directions. This is very difficult to, first of all, us meeting is a funny little thing, given the things I'm working on with robots currently. But, you know, it may not relate to trucks at all. There's, at a certain point, autonomous trucks are just robots. And then it starts getting into a conversation about the roles of robots in society. And the roles of humans and robots. And that interplay is right up your alley. As somebody who deeply cares about humans and have somehow found themselves studying robots. Yeah, no, it's crazy. I mean, even four or five years ago, if you had asked me if I was going to be studying trucking still, I would have said no. And so my advice is, I think if I was going to give advice, you know, is you can't connect the dots looking forward. You just got to follow what interests you, you know? And I think we downplay that when we talk to kids, especially if you have some bright gifted kid that gets identified as like, oh, you could go somewhere. Then we're like, we feed them stuff. We're like, well, learn the piano and learn another language, right? Learn robotics. And then we tell other kids like, oh, learn a trade, you know, like figure out what's going to pay well. And not that there's anything against trades. I think everyone should learn manual skills to make things. I think it's incredibly satisfying and wonderful and we need more of that. But also, you know, tell, you know, all kids it's okay to like take a class in something random that you don't think you're going to get any economic return on. Because maybe you will end up going into a trade, but that class that you took in studio art is going to mean that, you know, you look at buildings differently, right? Or you end up sort of putting your own stamp on, you know, woodworking, you know? And just, I think that's the key is like follow, you know, it's cheesy because everybody says follow your passion. But, you know, we say that and then we just, you know, the 90% of what people hear is, you know, what's the return on investment for that? You know, it's like, you're a human being, like things interest you, music interests you, literature interests you, video games interest you, like follow it, you know? Go grab a kayak and go into the Pacific. Go do something real. No, don't do that. Go do something stupid and something you'll regret a lot later. My foremother, thank God she didn't know. Well, let me ask because for a lot of people, work, for me it is, quote unquote, work is a source of meaning. And at the core of something we've been talking about with jobs is meaning. So the big ridiculous question, what do you think is the meaning of life? Do you think work for us humans in modern society is core to that meaning? And is that something you think about in your work? Sort of the deeper question of meaning, not just financial well-being and the quality of life, but the deeper search for meaning. Yeah, the meaning of life is love. And you can find love in your work. And I don't think everybody can. There are a lot of jobs out there that just, you do it for a paycheck. And I think we do have to be honest about that. There are a lot of people who don't love their jobs, and we don't have jobs that they're going to love. And maybe that's not a sort of realistic, that's a utopia, right? But for those of us that have the luxury, I mean, I think you love what you do, that people say that. I think the key for real happiness is to love what you're trying to achieve. And maybe you love trying to build a company and make a lot of money just for the sake of doing that. But I think the people who are really happy and have great impacts, they love what they do because it has an impact on the world that they think expresses that love. And that could be at a counseling center, that could be in your community, that could be sending people to Mars. Well, I also think it doesn't necessarily, the expression of love isn't necessarily about helping other people directly. There's something about craftsmanship and skill, as we've talked about, that's almost like you're celebrating humanity by searching for mastery in the task. Especially tasks that people outside may see as menial, as not important. Nevertheless, searching for mastery, for excellence in that task. There's something deeply human to that and also fulfilling, that just driving a truck and getting damn good at it. The best who's ever lived driving the truck and taking pride in that, that's deeply meaningful. And also a real celebration of humanity and a real show of love, I think, for humanity. Yeah, I just had my floors redone and the guy who did it was an artist. He sanded these old hundred-year-old floors and made them look gorgeous and this is craft. That's love right there. Yeah, I mean, he showed us some love. The product was just like, it's enriching our lives. Steve, this was an amazing conversation. We've covered a lot of ground. Your work, just like you said, impossible to connect the dots, but I'm glad you did all the amazing work you did. You're exploring human nature at the core of what America is, the blue-collar America. So, thank you for your work. Thank you for the care and the love you put in your work. And thank you so much for spending your valuable time with me. I appreciate it, Lex. I'm a big fan. So, it's just been great to be on. Thanks for listening to this conversation with Steve Viselli. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Napoleon Hill. If you cannot do great things, do small things in a great way. Thank you for listening, and hope to see you next time.

https://youtu.be/a3Wpy6gE4So

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Sara Walker: The Origin of Life on Earth and Alien Worlds | Lex Fridman Podcast #198

The following is a conversation with Sarah Walker, an astrobiologist and theoretical physicist at Arizona State University and the Santa Fe Institute. She's interested in the origin of life, how to find life on other worlds, and in general, the more fundamental question of what even life is. She seeks to discover the universal laws that describe living systems on Earth and elsewhere using physics, biology, and computation. Quick mention of our sponsors, Athletic Greens, NetSuite, Blinkist, and Magic Spoon. Check them out in the description to support this podcast. As a side note, let me say that my hope for this podcast is to try and alternate between technical and non-technical discussions, to jump from the big picture down to specific detailed research and back to the big picture, and to do so with scientists and non-scientists. Long-term, I hope to alternate between discussions of cutting-edge research in AI, physics, biology, to topics of music, sport, and history, and then back to AI. AI is home. I hope you come along with me for that wild, oscillating journey. Some people message me saying to slow down since they're falling behind on the episodes of this podcast. To their disappointment, I have to say that I'll probably do more episodes, not less, but you really don't need to listen to every episode. Just listen to the ones that spark your curiosity. Think about it like a party full of strangers. You don't have to talk to everyone. Just walk over to the ones who look interesting and get to know them. And if you're lucky, that one conversation with a stranger might change the direction of your life. And it's a short life, so be picky with the strangers you talk to at this metaphorical party. This is the Lux Friedman Podcast, and here is my conversation with Sarah Walker. How did life originate on Earth? What are the various hypotheses for how life originated on Earth? Yeah, so I guess you're asking a historical question, which is always a good place to start thinking about life. So there's a lot of ideas about how life started on Earth. Probably the most popular is what's called the RNA world scenario. So this idea is probably the one that you'll see most reported in the news, and is based on the idea that there are molecules in our bodies that relay genetic information. We know those as DNA, obviously, but there's also sort of an intermediary called RNA, ribonucleic acid, that also plays the role of proteins. And people came up with this idea in the 80s that maybe that was the first genetic material because it could play both roles of being genetic and performing catalysis. And then somehow that idea got reduced to this idea that there was a molecule that emerged on early Earth and underwent Darwinian evolution, and that was the start of life. So there's a lot of assumptions packed in there that we could unpack, but that's sort of the leading hypothesis. There's also other ideas about life starting as metabolism, and so that's more connected to the geochemistry of early Earth, and it would be kind of more focused on this idea that you get some kind of catalytic cycle of molecules that can reproduce themselves and form some kind of metabolism, and then life starts basically as self-organization, and then you have to explain how evolution comes later. Right, so that's the difference between sort of energy and genetic code. So like energy and information, are those the two kind of things there? Yeah, I think that's a good way of putting it. It's kind of funny, because I think most of the people that think about these things are really disciplinary biased. So the people that tend to think about genetics come from a biology background, and they're really evolution-focused, and so they're worried about where does the information come from, and how does it change over time, but they're talking about information in a really narrow way where they're talking about a genetic sequence. And then most of the people that think about metabolism, origins of life scenarios, tend to be people like physicists or geochemists that are worried about what are the energy sources, and what kinds of organization can you get out of those energy sources. Okay, so which one's your favorite? I don't like either. Okay, can we talk about them for a little bit longer though? Yeah, no, that's fine. So okay, so there's early Earth. What was that like? Was there just mostly covered by oceans? Was there heat sources, energy sources? So if we talk about the metabolism view of the origin of life, like where was the source of energy? Probably the most popular view for where the original life happened on Earth is hydrothermal vents, because they had sufficient energy. And so we don't really know a lot about early Earth. We have some ideas about when oceans first formed and things like that, but the time of the origin of life is kind of not well understood or pinned down, and the conditions on Earth at that time are not well known. But a lot of people do think that there was probably hydrothermal vents, which are really hot, chemically active regions, say on the sea floor in modern times, which also would have been present on early Earth, and they would have provided energy and organics and basically all of the right conditions for the origins of life, which is one of the reasons that we look for these hydrothermal systems when we're talking about life elsewhere, too. Okay, and for the genetic code, the idea is that the RNA is the first, like why would RNA be the first moment you can say it's life? I guess the idea is it could both have persistent information, and then it can also do some of the work of like what, creating a self-sustaining organism? Yeah, that's the basic idea. So the idea is you have, in an RNA molecule, you have a sequence of characters, say, so you can treat it like a string in a computer, and it can be copied, so information can be propagated, which is important for evolution, because evolution happens by having inheritance of information. So for example, like my eyes are brown because my mother's eyes were brown. So you need that copying of information. But then you also have the ability to perform catalysis, which means that that RNA molecule is not inert in that environment, but it actually interacts with something and could potentially mediate, say, a metabolism that could then fuel the actual reproduction of that molecule. So in some ways, people think that RNA gives you the most bang for your buck in a single molecule, and therefore it gives you all the features that you might think are life. And so this is sort of where this RNA world conjecture came from is because of those two properties. Isn't it amazing that RNA came to be in general? Isn't it? Yes, that is amazing. Okay, so we're not talking down about RNA. No, no, no, I love RNA. It's one of my favorite molecules. I think it's beautiful. It's just not step one. Yeah, I think the issue, it's not even the RNA world is a problem. And actually, if you really dig into it, the RNA world is not one hypothesis. It is a set of hypotheses. And they range from a molecule of RNA spontaneously emerged on the early Earth and started evolving, which is kind of like the hardest RNA world scenario, which is the one I cited. And I get a little animated about because it seems so blatantly wrong to me, but that's a separate story. And then the other one is actually something I agree with, which is that you can say there was an RNA world because RNA was the first genetic material for life on Earth. So an RNA world could just be the earliest organisms that had genetics in a modern sense, didn't have DNA evolved yet, they had RNA. And so that's sort of a softer RNA world scenario in the sense that it doesn't mean it was the first thing that happened, but it was a thing that definitely was part of the lineage of events that led to us. So if life was like a best of album, it would be one of the songs on there. Yes. One of the early songs. Okay. It's on the greatest hits. Greatest hits, that's the word I was looking for. Okay, did life, do you think, originate once, twice, three times on Earth, multiple times, what do you think? I think that's a really difficult question. Is it an important question? It's a super important question, no. No, it's a really important question. And so there's a lot of questions in that question. So one of the first ones that I think needs to be addressed is is the original life a continuous process on our planet? So we think about the original life as something that happened on Earth, say, almost four billion years ago, because we have evidence of life emerging very early on our planet. And then an original life event, quote unquote, a singular event, whatever that was, happened. And then all life on Earth that we know is a descendant of that particular event in our universe. And so, but we don't have any idea one way or the other if the original life is happening repeatedly, and maybe it's just not taking off because life is already established. That's an argument that people will make. Or maybe there are alternative forms of life on Earth that we don't even recognize. So this is the idea of a shadow biosphere, that there actually might just be completely other life on Earth, but it's so alien that we don't even know what it is. I'm gonna have to talk to you about the shadow biosphere. Yeah, that's a fun one. In a second, but first let me ask for the other alternative, which is panspermia. Right. So that's the idea, the hypothesis that life exists elsewhere in the universe and got to us, or like an asteroid or a planetoid, or some, according to Wikipedia, space dust, whatever the heck that is. It sounds fun. So basically it rode along whatever kind of rock and got to us. Do you think that's at all a possibility? Sure. So I think the reason that most original life scientists are interested in the original life on Earth, and say not the original life on Mars, and then panspermia, the exchange of life between planets being the explanation, is once you start removing the original life from Earth, you know even less about it than you do if you study it on Earth. Although I think there are ways of reformulating the problem. This is why I said earlier, oh, you mean the historical original life problem, you don't mean the problem of how does life arise in the universe and what the universal principles are, because there's this historic problem, how did it happen on early Earth? And there's a more tractable general problem of how does it happen? And how does it happen is something we can actually ask in the lab. How did it happen on early Earth is a much more detailed and nuanced question. It requires detailed knowledge of what was happening on early Earth that we don't have. And I'm personally more interested in general mechanisms. So to me it doesn't matter if it happened on Earth or it happened on Mars. It just matters that it happened. We have evidence it happened. The question is, did it happen more than once in our universe? And so the reason I don't find panspermia as a particularly, I think it's a fascinating hypothesis. I definitely think it's possible. And I in particular think it's possible once you get to the stage of life where you have technology, because then you obviously can spread out into the cosmos. But it's also possible for microbes because we know that certain microorganisms can survive the journey in space. And they can live in a rock and go between Mars and Earth. People have done experiments to try to prove that could work. So in that scenario, it's super cool because then you get planetary exchange. But say we go look for life on Mars and it ends up being exactly the same life we have on Earth, biochemically speaking, then we haven't really discovered something new about the universe. What kind of aliens are possible? Were there other original life events? If all the life we ever find is the same original life event in the universe, it doesn't help me solve my problem. But it's possible that that would be a sign that you could separate the environment from the basic ingredients. Yes, that's true. You can have a life gun that you shoot throughout the universe. And then once you shoot it, it's like the Simpsons with a makeup gun. That was a great episode. When you shoot this life gun, it'll find the Earth's. It'll get sticky. It'll stick to the Earth's. And that kind of reduces the barrier of the time it takes, the luck it takes to actually, from nothing, from the basic chemistry, from the basic physics of the universe, for the life to spring up. Yeah, I think this is actually super important to just think about, does life getting seated on a planet have to be geochemically compatible with that planet? So you're suggesting we could just shoot guns in space and life could go to Mars and that it would just live there and be happy there. But that's actually an open question. So one of the things I was gonna say in response to your question about whether the origin of life happened once or multiple times is for me personally right now, in my thinking, although this changes on a weekly basis, but is that I think of life more as a planetary phenomena. So I think the origin of life, because life is so intimately tied to planetary cycles and planetary processes, and this goes all the way back through the history of our planet, that the origin of life itself grew out of geochemistry and became coupled and controlled geochemistry. And when we start to talk about life existing on the planet is when we have evidence of life actually influencing properties of the planet. And so if life is a planetary property, then going to Mars is not a trivial thing because you basically have to make Mars more Earth-like. And so in some sense, like when I think about sort of long-term vision of humans in space, for example, really what you're talking about when you're saying, let's send our civilization to Mars is you're not saying let's send our civilization to Mars, you're saying let's reproduce our planet on Mars. Like the information from our planet actually has to go to Mars and make Mars more Earth-like, which means that you're now having a reproduction process, like a cell reproduces itself to propagate information in the future. Planets have to figure out how to reproduce their conditions including geochemical conditions on other planets in order to actually reproduce life in the universe, which is kind of a little bit radical, but I think for long-term sustainability of life on a planet, that's absolutely essential. Okay, so if we were to think about life as a planetary phenomena, and so life on Mars would be best if it's way different than life on Earth, we have to ask the very basic question of what is life? I actually don't think that's the right question to ask. It took me a long time to get there, right? So I- You cross it out? Yeah, you cross it off your list, it's wrong. Next question. No, no, no, no. I mean, I think it has an answer, but I think part of the problem is, most of the places in science where we get really stuck is because we don't know what questions to ask. And so you can't answer a question if you're asking the wrong question. And I think the way I think about it is obviously I'm interested in what life is, so I'm being a little cheeky when I say that's the wrong question to ask. That's exactly like the question that's like the core of my existence. But I think the way of framing that is, what is it about our universe that allows features that we associate life to be there? And so really what I guess when I'm asking that question, what I'm after is an explanatory framework for what life is, right? And so most people, they try to go in and define life, and they say, well, life is, say, a self-reproducing chemical system capable of Darwinian evolution. That's a very popular definition for life. Or life is something that metabolizes and eats. That is not how I think about life. What I think about life is there are principles and laws that govern our universe that we don't understand yet that have something to do with how information interacts with the physical world. I don't know exactly what I mean even when I say that because we don't know these rules. But it's a little bit like, I like to use analogies. You'll give me time to be like a little long-winded for a second, even in essay. But sort of like, if you look at the history of physics, for example, this is like, so we are in the period of the development of thought on our planet where we don't understand what we are yet, right? There was a period of thought in the history of our planet where we didn't understand what gravity was. And we didn't understand, for example, that the planets in the heavens were actually planets or that they operated by the same laws that we did. And so there has been this sort of progression of getting a deeper understanding of explaining basic phenomena like, I'm not gonna drop the cup, I'll drop the water bottle. There you go. Okay, that fell, right? But why did that fall? This is why I'm a theorist, not an experimentalist. I could have gone wrong in so many ways. I know, we could have, especially if I did the cup and it smashed. Anyway. So if you think, take this view that there's sort of some missing principles. I associate them to information. And what the sort of feeling there is, there's some missing explanatory framework for how our universe works. And if we understood that physics, it would explain what we are. It might also explain a lot of other features we don't associate to life. And so it's a little like people accept the fact that gravity is a universal phenomena. But when we wanna study gravity, we study things like large scale, you know, galactic structures or black holes or planets. If we wanna understand information and how it operates in the physical world, we study intelligent systems or living systems because they are the manifestation of that physics. And the fact that we can't see that clearly yet, or we don't have that explanatory framework, I think it's just because we haven't been thinking about the problem deeply enough. But I feel like if you're explaining something, you're deriving it from some more fundamental property. And of course, I have to say I'm wearing my physicist hat. So I have a huge bias of liking simple, elegant explanations of the universe that really are compelling. But I think one of the things that I've sort of maybe in some ways rejected my training as a physicist is that most of the elegant explanations that we have so far don't include us in the universe. And I can't help but think there's something really special about what we are, and there have to be some deep principles at play there. And so that's sort of my perspective on it. Now, when you ask me what life is, I have some ideas of what I think it is. But I think that we haven't gotten there yet because we haven't been able to see that structure. And just to go back to the gravity example, it's a little like, in ancient times, they didn't know, I was talking about stars and heavens and things, they didn't know those were governed by the same principles as that darned experiment. Here's where I was going with it. Once you realize, like Newton did, that heavenly motions and earthly motions are governed by the same principles, and you unify terrestrial and celestial motion, you get these more powerful ideas. And I think where life is is somehow unifying these abstract ideas of computation and information with the physical world, with matter, and realizing that there's some explanatory framework that's not physics and it's not computation, but it's something that's deeper. So answering the question of what is life requires deeply understanding something about the universe as information processing, the universe as computation. Sort of. Like something about, like would, once you come up with an answer to what is life, will the words information and computation be in the paragraph? No, I don't think so. Oh, damn it, okay. I know, it doesn't help, does it? I know, I hate, actually I hate this about what I do because it's so hard to communicate, right, with words. Like when you have words that are ideas that have historically described one thing and you're trying to describe something people haven't seen yet, and the words just don't fit. So what's wrong? Is it too ambiguous, the word information? We could switch to binary if you want. Yeah, no, I don't think it's binary either. I think information's just loaded. I use it, so the other way I might talk about it is the physics of causation, but I think that's worse because causation is even more loaded word than information. So causation is fundamental, you think? I do, yeah, and in some sense I think the physics, so this is the really radical part. Some sense, like when I really think about it sort of most deeply, what I think life is is actually the physics of existence. What gets to exist and why? And for simple elementary particles, that's not very complicated because the interactions are simple, but for things like you and me and human civilizations, what comes next in the universe is really dependent on what came before, and there's a huge space of possibilities of things that can exist. And when I say information and causation, what I mean is why is it that cups evolved in the universe and not some other object that could deliver water and not spill it? I don't know what you would call it. Maybe it wouldn't be a cup, but it's a huge, people talk about the space of things that could exist as being actually infinitely large. I don't know if I believe in infinity, but I do think that there is something very interesting about the problem of what exists in its relationship to life. So do you think the set of things that could exist is finite? It's very large, but if we were to think about the physics of existence, like how many shapes of mugs can there be? Like is, in the initial programming- I should go to the math department for that. So that's not a topology question. I just mean, maybe another way to ask is, what do you think is fundamental to the universe and what is emergent? So if existence, are we supposed to think of that as somehow fundamental, you think? So there's a couple problems in physics that I think this is related to. One is why does mathematics work at describing reality so well? And then there is this problem of we don't understand why the laws of physics are the way they are or why certain things get to exist or what put in place the initial condition of our universe, right? There's all of these sort of really deep and big problems and they all indirectly are related, I think, to the same kind of thing that, you know, our physics is really good if you specify the initial condition at specifying a certain sequence of events, but it doesn't deal with the fact that other things could have happened, which is kind of an informational property, like a counterfactual property. And it's not good at explaining, you know, this conversation right now. It's just, there are certain things that are outside the explanatory reach of current physics. And I think they require looking at it from a completely different direction. And so I don't wanna have to fine tune the initial condition of the universe to specify precisely all the information in this conversation. I think that's a ridiculous assertion, but that's sort of like how people wanna frame it when they're talking about, you know, the standard model is sufficient if we had computing power to basically explain all of life in our existence. An interesting thing you said is the way we think about information computation is by observing a particular kind of systems on earth that exhibits something we think of as intelligence. But that's like looking at, I guess, the tip of an iceberg and we should be really looking at the fundamentals of like the iceberg, like what makes water and ice and the chemistry that from which intelligence emerges essentially. Yes, yes. We can't just couple the information from the physics. And I think that's what we've gotten really good at doing, especially with sort of the modern age where, you know, software is so abstracted from hardware. But the entire process of biological evolution has basically been built, like been building layers of increasing abstraction. And so it's really hard to see that physics in us, but it's much clearer to see it in molecules. Yeah, but I guess I'm trying to figure out what do you think are the best tools to look at it? What do you think? An open mind, is that a tool? What's the physics of an open mind? I think if we solve that, we'll solve everything. I'm saying an open mind because I think that's the biggest stumbling block to understanding sort of the things I've been trying to articulate. Or, and when I talk also with colleagues that are thinking deeply about these same issues, is none of it is inconsistent with what we know. It's just such a radically different perception of the way we understand things now that it's hard for people to get there. And in some ways you have to almost forget what you've learned in order to learn something new, right? So I feel like most of my career trying to understand the problem of life has been variously forgetting and then relearning things that I learned in physics. And I think you have to have a capacity to learn things, but then accept that things that you learned might not be true, or might need refinement or reframing. And the best way I can say that is just like with a physics education, there are just certain things you're told in undergrad that are like facts about the world. And your physics professors never tell you that those facts actually emerge from a human mind, right? So we're taught to think about, say the laws of physics, for example, as this like autonomous thing that exists outside of our universe and tells our universe how it works. But the laws of physics were invented by human minds to describe things that are regularities in our everyday experience. They don't exist autonomous to the universe. Right, so it's like turtles on top of turtles, but eventually it gets to the human mind, and then you have to explain the human mind with the turtles. So you have to, it comes from humans, this understanding, this simplification of the universe, these models. There's a guy named Stephen Wolfram, there's a concept called cellular automata. So there's some mysteries in these systems that are computational in nature that have maybe echoes of the kind of mysteries we should need to solve to understand what is life. So if we could talk, take a computational view of things, do you think there's something compelling to reducing everything down to computation, like the universe is computation, and then trying to understand life? So throw away the biology, throw away the chemistry, throw away even the physics that you learn undergrad and graduate school, and more look at these simple little systems, whether it's cellular automata or whatever the heck kind of computational systems that operate on simple local rules, and then create complexity as they evolve. Is it at all, do you think, productive to focus on those kinds of systems to get an inkling of what is life? And if it is, do you think it's possible to come up with some kind of laws and principles about what makes life in those computational systems? So I like cellular automata, I think they're good toy models, but mostly where I've thought about them and used them is to actually, let's say, poke at sort of the current conceptual framework that we have and see where the flaws are. So I think the part that you're talking about that people find intriguing is that if you have a fairly simple rule and you specify some initial condition and you run that rule on that initial condition, you could get really complex patterns emerging. And ooh, doesn't that look lifelike? Yeah. Yeah. Well, it's like really surprising, isn't it really surprising? It is really surprising, and they're beautiful. And I think they have a lot of nice features associated to them. I think the things that I find, yeah, so I do think as a proof of principle that you can get complex things emerging from simple rules. They're great. As a sort of proof of principle about some of the ways that we might think of computation as being sort of a fundamental principle for dynamical systems and maybe the evolution of the universe as a whole, they're a great model system. As an explanatory framework for life, I think they're a bit problematic for the same reason that the laws of physics are a bit problematic. And the clearest way I can articulate that is like cellular automata are actually cast in sort of a conceptual framework for how the universe should be described that goes all the way back to Newton, in fact, with this idea that we can have a fixed law of motion, which exists sort of, it's given to you. You know, the great programmer in the sky gave you this equation or this rule, and then you just run with it. And the rule doesn't have, so a good feature of the rule is it doesn't have specified in the rule information about the patterns it generates. So you wouldn't want, for example, my cup or my water bottle or me sitting here to be specified in the laws of physics. That would be ridiculous because it wouldn't be a very simple explanation of all the things happening. It'd have to explain everything. So, and cellular automata have that feature, and the laws of physics have that feature. But you also need to specify the initial condition. And it also, it basically means that everything that happens is sort of a consequence of that initial condition. And I think this kind of framework is just not the right one for biology. And part of the way that it's easiest to see this is a lot of people talk about self-reference being important in life. The fact that, you know, like the genome has information encoded in it, that information gets read out. It specifies something about the architecture of a cell. The architecture of the cell includes the genome. So the genome has basically self-referential information. Self-reference obviously comes up in computational law because it's kind of foundational to Turing's work and what Gödel did with the incompleteness theorems and things. So there's a lot of parallels there, and people have talked about that at depth. But the other way of kind of thinking about it in terms of like a more physics-y way of talking about it is that what it looks like in biology is that the rules or the laws depend on the state. This is typical in computer science. This is obvious to you. You know, the update rule depends on the state of the machine, right? But you don't think about that being sort of the dynamic in physics. It's, you know, the rule is given to you, and then it's a very special subclass, say, of computations if you don't ever change the update. But in biology, it seems to be that the state and the law change together as a function of time, and we don't have that as a paradigm in physics. And so a lot of people talked about this as being kind of a perplexing feature, that maybe there are certain scenarios where the laws of physics or the laws that govern a particular system actually change as a function of state of that system. That's trippy. So yeah, the hope of physics, it's a hope, I guess, but often stated as a underlying assumption is that the law is static. Right. Okay. And even having laws that vary in time, not even as a function of the state, is very radical when you- The time in general. Like, you wanna remove time from the equation as much as possible. Yeah, I do. There's some interesting things in this, like when we think more deeply about the actual physics that we're trying to propose governs life, with me with collaborators, and then also other people that think about similar things, that time might actually be fundamental, and there really is an ordering to time, and that events in the universe are unique because they have a particular, they happen, like an object in the universe requires a certain history of events in order to exist, which therefore suggests that time really does have an ordering. I'm not talking about the flow of time and our perception of time, just the ordering of events. Causation of things. Yes, causation, there's that word again. So causation, when you say time, you mean causation. Yes. In your proposed model of the physics of life, the fundamental thing would be causation. If you were to bet your money on one particular horse or whatever. Yes. And then space is emergent? Yes. So everything's emergent except time. Kind of, yeah, or causation. And laws change all the time. Why does it look like laws are the same? Well, because, well, one way, and I actually, this idea comes from Lee Cronin, because I work with him very closely on these things, is that the laws of physics look the way they do because they're low memory laws. So they don't require a lot of information to specify them. They're very easy for the universe to implement. But if you get something like me, for example, I require a four billion year history to exist in the universe. I come with a lot of historical baggage. And that's part of what I am, is a set of causes that exist in the universe. So I have local rules that apply to me that are associated with sort of the information in my history that aren't universal to every object in the universe. And there are some things that are very easy to implement, low memory rules, that apply to everything in the universe. So there's no shortcuts to you? No. So yeah, I don't believe in things like Boltzmann brains or fluctuations out of the vacuum that can produce things like your desk ornaments. I actually think they require a particular causal chain of events to exist. Well, I appreciate the togetherness of that. But so how does that, if we have to simulate the entire universe to create the ornaments and the two of us, how are we supposed to create engineer life in a lab? This goes back to sort of the critique of the RNA world. I think one of the problems, and I'll get to answering your question, but I think this is kind of relevant here. One of the problems with the RNA world, when we test it in the laboratory, is how much information we're putting into the experiment. We specify the flask, we make pure reagents, we mix them, we take them out, we put them in the next flask, we change the pH, we change the UV light, and then we get a molecule. And it's not even an RNA molecule necessarily, it might just be a base. And so people don't usually think about the fact that we're agents in the universe making that experiment, and therefore we put a little bit of life into that experiment. Because it's part of our biological lineage in the same sense that a cup or I am a part of the biological lineage. The experiment is- Our ideas are injecting life. Yes. And the constraints that we put on the experiments. Because those conditions wouldn't exist in the universe on planet Earth at that time without us as the boundary condition, right? So- Even though we're not actually adding any actual chemistry or biology that could be identified as life, are the constraints we're adding to the experiment, the design of the experiment- Yeah, you can think of the design experiment as a program, you put information in. It's an algorithmic procedure that you design the experiment. And so the origin of life problem becomes one of minimizing the information we put into physics to actually watch the spontaneous origin of life. Can we have, so can, is it possible in the lab to have an information vacuum then? So like- If we could, we would, that would be amazing. I don't know. That's a good question for, more for Lee. Yeah, you guys, by the way, for people who don't know Lee Cronin, is you guys are colleagues. Yeah. And I've gotten the chance to listen to the two of you talking. There's great chemistry and you're brilliant brainstorming together. And there's a really exciting community here of brilliant people from different disciplines working on the problem of life, of complexity, of, I don't know, whatever. The words fail us to describe the exact problem we're trying to actually understand here. Intelligence, all those kinds of things. Okay, so what, from a lab perspective, so Lee, I guess, would you call him a chemist? No? I think by training he's a chemist, but I think most of the people that work in the field we do have lost their discipline. And that's my trying to answer your question normally. I don't know what you call him. I don't know what I call myself. I don't know what I call any of my friends. So why is it so hard to create, and it's an interesting question, to create biological life in the lab. Like from your perspective, is that an important problem to work on, to try to recreate the historical origin of life on Earth, or echoes of the historical origin? I think echoes is more appropriate. I don't think asking the question of what was the exact historical sequence of events and engineering every step in the process to make exactly the chemistry of life on Earth as we know it is a meaningful way of asking the question. And it's a little bit like, since you're in computer science, like if you know the answer to a problem, it's easier to find a program to specify the output, right? But if you don't know the answer a priori, finding an algorithm for like, say finding a prime or something, it's easy to verify it's a prime number. It's hard to find the next prime. And the way the original life is structured right now in the historical problem is you know the answer and you're trying to retrodict it by breaking it down into the set of procedures where you're putting a lot of information in. And what we need to do is ask the question of how is it that the rules of how our universe is structured permits things like life to exist and what is the phenomena of life? And those questions are obviously essentially the same question. And so you're looking essentially for this missing physics, this missing explanation for what we are and you need to set up proper experiments that are gonna allow you to probe the vast complexity of chemistry in an unconstrained way with as little information put in as possible to see when does information actually emerge? How does it emerge? What is it? And part of the sort of conjecture we have is that this physics only becomes relevant or at least this is my personal conjecture and it's sort of validated by this kind of theory experiment collaboration that we have working in this area. I made the point about like gravity existing everywhere. But when you study an atomic nucleus, you don't care about gravity. It's not relevant physics there, right? It's weak, it doesn't matter. And so this idea that there's kind of a physics associated with information, for me, it's very evident that that physics doesn't become relevant until you need information to specify the existence of a particular object. And the scale of reality where that happens is in chemistry because the combinatorial diversity of chemical objects that can exist far exceeds the amount of resources in our universe. So if you want it, you can't make every possible protein of length 200 amino acids, there's not enough resources. So in order for this particular protein to exist and this protein to exist in high abundance means that you have to have a system that has knowledge of the existence of that protein and can build it. So existence comes to be at the chemical level. So existence is most, is best understood at the chemical level. It's most evident. It's a little bit like, nobody argues that gravity doesn't exist in an atomic nucleus. It's just not relevant physics there, right? So the physics of information. Is everywhere, it exists at every combinatorial scale, but it becomes more and more relevant the more set of possibilities that could exist because you have to specify more and more about why this thing exists and not the infinite, it's not an infinite set, but the set of, undefined set of other things that could exist. So can I ask a weird question? Which is, so let's look into the future. I try that every day, it never works. So say a Nobel Prize is given in physics, maybe chemistry for discovering the origin of life. No, but not the historical origin. Some kind of thing that we're talking about. What exactly would, what do you think that, what do you think that person, maybe you, did to get that Nobel Prize? Like what would they have to have done? Because you could do a bunch of experiments that go like with an aha moment. Like you rarely get the Nobel Prize for like, you've solved everything, we're done. It's like some inkling of some deep truth. Like what do you think that would actually look like? Would it be an experimental result? I mean, it will have to have some kind of experimental, maybe validation component. So what would that look like? This is an excellent question. I want to, sorry, I'm gonna make a quick point, which is just a slight tangent, but you know, like when people ask about the origin of mass, you know, and like looking for the Higgs mechanism and things, they never are like, we need to find the historical origins of life in the early, although those things are related, right? So this problem of origins of life in the lab, I think is really important, but the Higgs is a good example because you had theory to guide it. So somehow you need to have an explanatory framework that can say that we should be looking for these features and explain why they might be there and then be able to do the experiment and demonstrate that it matches with the theory. But it has to be something that is outside sort of the paradigm of what we might expect based on what we know, right? So this is a really sort of tall order. And I think, I mean, I guess the way people would think about it is like, you know, if you had a bacteria that climbed out of your test tube or something, and it was like, you know, moving around on the surface, that would be ultimate validation. You saw the original life in an experiment, but I don't think that's quite what we're looking for. I think what we're looking for is evidence of when information that originated within the balance of your experiment, and you can demonstrably prove emerged spontaneously in your experiment, wasn't put in by you, actually started to govern the future dynamics of that system and specify it. And you could somehow relate those two features directly. So you know that the program specifying what's happening in that system is actually internal to that system. Like say you have a chemical thing in a box. Well, so that's one Nobel Prize winning experiment, which is like information in some fundamental way originated within the constraints of the system without you injecting anything. But another experiment is you injected something and got out information. Yes. So like you injected, I don't know, like some sugar and like something, something that doesn't necessarily feel like it should be information. Yeah, so actually no, I mean, sugar is information, right? So part of the argument here is that every physical object is, well, it's information, but it's a set of causal histories and also a set of possible futures. So there is an experiment that I've talked a lot about with Lee Cronin, but also with Michael Lachman and Chris Kempfes who are at Santa Fe about this idea that sometimes we talk about as like seeding assembly, which is you take a high complexity, like an object that exists in the universe because of a long causal history, and you seed it into a system of lower causal history, and then suddenly you see all of this complexity being generated. So I think another validation of the physics would be say you engineer an organism by purposefully introducing something where you understand the relationship between the causal history of the organism and the say very complex chemical set of ingredients you're adding to it. And then you can predict the future evolution of that system to some statistical set of constraints and possibilities for what it will look like in the future. You know, I'm a physical structure, obviously, like I'm composed of atoms, the configuration of them and the fact that they happen to be me is because I'm not actually my atoms, I am a informational pattern that keeps repatterning those atoms into Sarah. And I have also associated to me like a space of possible things that could exist that I can help mediate come into existence because of the information in my history. And so when you understand sort of that time is a real thing embedded in a physical object, then it becomes possible to talk about how histories when they interact, and a history is not a unique thing, it's a set of possibilities, when they interact, how do they specify what's coming next? And then where does the novelty come from in that structure? Because some of it is kind of things that haven't existed in the past can exist in the future. Let me ask about this entity that you call Sarah. Yes. I talk to myself about myself in third person sometimes, I don't know why. So maybe this is a good time to bring up consciousness. Sure. It's been here all along. Well, has it? So, I mean that's- At least in this conversation, I think I've been conscious most of it, but maybe I haven't. Well, yeah, so speak for yourself. You're projecting your consciousness onto me. You don't know if I'm conscious or not. Is that- No, I don't. You're right. Is that, you talked about the physics of existence, you talked about the emergence of causality, sorry, you talked about causality in time being fundamental to the universe. Where does consciousness fit into all of this? Like, do you draw any kind of inspiration or value with the idea of panpsychism that maybe one of the things that we ought to understand is the physics of consciousness? Like, one of the missing pieces in the physics view of the world is understanding the physics of consciousness. Or like that word has so many concepts underneath it, but let's put it, let's put consciousness as a label on a black box of mystery that we don't understand. Do you think that black box holds the key to finally answering the question of the physics of life? The problems are absolutely related. I think most, and I'm interested in both because I'm just interested in what we are. And to me, the most interesting feature of what we are is our minds and the way they interact with other minds. Like, minds are the most beautiful thing that exists in the universe. So how do they come to be? Sorry to interrupt. So when you say we, you mean humans. I mean humans right now, but that's because I'm a human, or at least I think I am. You think there's something special to this particular? No, no, no, no, no. No, I'm not a human-centric thinker. But are you one entity? You said a bunch of stuff came together to make a Sarah. Like, do you think of yourself as one entity, or are you just a bunch of different components? Like, is there any value to understand the physics of Sarah? Or are you just a bunch of different things that are like a nice little temporary side effect? Yeah, you could think of me as a bundle of information that just became temporarily aggregated into your individual. Yeah, that's fine. I agree with that view. I'll take that as a compliment, actually. But nevertheless, that bundle of information has become conscious, or at least keeps calling herself conscious. Yeah, I think I'm conscious right now, but I might not be, but that's okay. Or you wouldn't know. So yeah, so this is the problem. So yeah, usually people, when they're talking about consciousness, are worried about the subjective experience. And so I think that's why you're saying, I don't know if you're conscious, because I don't know if you're experiencing this conversation right now. And nor do you know if I'm experiencing the conversation right now. And so this is why this is called the hard problem of consciousness, because it seems impenetrable from the outside to know if something's having a conscious experience. And I really like the idea of also the hard problem of matter, which is related to the hard problem of consciousness, which is you don't know the intrinsic properties of an electron not interacting, say, for example, with anything else in the universe. All the properties of anything that exists in the universe are defined by its interaction, because you have to interact with it in order to be able to observe it. So we can only actually know the things that are observable from the outside. And so this is one of the reasons that consciousness is hard for science, because you're asking questions about something that's subjective and supposed to be intrinsic to what that thing is as it exists and how it feels about existing. And so I have thought a lot about this problem and its relationship to the problem of life. And the only thing I can come up with to try to make that problem scientifically tractable and also relate it to how I think about the physics of life is to ask the question, are there things that can only happen in the universe because there are physical systems that have subjective experience? So does subjective experience have different causes, things that it can cause to occur that would happen in the absence of that? I don't know the answer to that question, but I think that's a meaningful way of asking the question of consciousness. I can't ask if you're having experience right now, but I can ask if you having experience right now changes something about you and the way you interact with the world. So does stuff happen? It's a good question to ask, does stuff happen if consciousness is? Then it's a real physical thing, right? It has physical consequences. I'm a physicist, I'm biased. So I can't get rid of that bias. It's really deeply ingrained. I've tried, but it's hard. But I mean, you're saying information is physical too. So like virtual reality and simulation, all that program is physical too in the sense that- Yes, everything's physical. It's just not physical the way it's represented in our minds. Right, so you, I love your Twitter. So you tweet these like deep thoughts. Deep thoughts. That's what a theorist does when she's trying to experiment. Is tweet? It's just like sitting there. I mean, I can just imagine you sitting there for like hours and all of a sudden, just like this thought comes out and you get a little like inkling into the thought process. Yeah, usually it's like when I'm running between things and I'm like, I'm gonna say deep thoughts. Well, yeah. Deep thoughts are hard to articulate. One of the things you tweet is ideologically, there are many parallels between the search for neural correlates of consciousness and for chemical correlates of life. How the neuroscience and astrobiology communities treat those correlates is entirely different. Can you elaborate against this kind of, the parallels? It has to do a little bit with the consciousness and the matter thing you're talking about. Yeah, it does. And I can't remember what state of mind I was when I was actually thinking about that. But I think part of it is- I bet you never thought you were gonna have to analyze your own tweets. No, I didn't. It's an interesting historical juxtaposition of thinking. So the tweet is a historical- Hey, you're doing an assembly experiment right now because you're bringing a thought from the past into the present and trying to actually- In a lab. Yeah, yeah, yeah. This is experimental science right here on the podcast live. So go, let's see how the consciousness evolves on this one. Yeah, so in neuroscience, it's kind of accepted that we can't get at the subjective aspect of consciousness. So people are very interested in what would be a correlate of consciousness. What's a correlate? A correlate is a feature that relates to conscious activity. So for example, a verbal report is a correlate of consciousness because I can tell you when I'm conscious. And then when I'm sleeping, for example, I can't tell you I'm conscious. So we have this assumption that you're not conscious when you're sleeping and you're conscious when you're awake. And so that's sort of like a very obvious example, but neuroscientists, which I'm no neuroscientist and I'm not an expert in this field, but they have very sophisticated ways of measuring activity in our brain and trying to relate that to verbal report and other proxies for whether someone is experiencing something. And that's what is meant by neural correlates. And then so when people are trying to think about studying consciousness or developing theories for consciousness, they often are trying to build an experimental bridge to these neural correlates, recognizing the fact that a neural correlate may or may not correspond to consciousness because that problem's hard and there's all these associated issues to it. So that's from a neuroscience perspective, it's like fake it till you make it. So you fake whatever the correlates are and hopefully that's going to summon the thing that is consciousness. And so the same thing on the chemical correlates of life, that sounds like that's an awesome concept. Is that something that people? No, I just made that up. That was original to that tweet, you can cite the tweet. Maybe I'll write it in a paper someday. Chemical correlates of life, that's a good title. I mean, first of all, your papers too that people should check out have great titles. The more papers you're involved with. So your tweets and titles are stellar and also your ideas, but the tweets and titles are much more important. Of course, ideas will live longer. Yeah. They're much more diffuse though. Well, yeah, the tweet is the Trojan horse for the idea that sticks on for a long time. Okay, so is there anything to say about the chemical correlates of life? You're saying there are similar kind of ways of thinking about it, but you mentioned about the communities. Yeah, so I think in astrobiology, there's no concept of chemical correlates of life. We don't think about it that way. We think if we find molecules that are involved in biology, we found life. So I think one of my motivations there was just to separate the fact that life has abstract properties associated to it. They become imprinted in material substrates and those substrates are correlates for that thing, but they are not necessarily the thing we're actually looking for. The thing that we're looking for is the physics that's organizing that system to begin with, not the particular molecules. In the same sense that your consciousness is not your brain. It's instantiated in your brain. It has to have a physical substrate, but the matter is not the thing that you're looking at. It's some other, at least not in the way that we have come to look at matter, with traditional physics and things. There's something else there and it might be this feature of history I was talking about or time being actually physically represented there. Do you think consciousness can be engineered? Yes. In the same way that life can be engineered? Wow, that was a fast answer. I didn't even think about that. That's interesting. You don't have a free will. No, I do have free will, but it's interesting because I mean, you know. Now you're backtracking. No, no. And that was predestined. Yeah, no, no. No, I do believe in free will, but I also think that there's kind of an interesting, speaking about consciousness, what are you consciously aware of versus what is your subconscious brain actually processing and doing? And sometimes there's conflict between your consciousness and your subconsciousness or your consciousness is a little slower than your subconscious. And intuition is a really important feature of that. And so a lot of the ways I do my science is guided by intuition. So when I get fast answers like that, I think it's usually because I haven't really thought about them. And therefore that's probably telling me something. Let's continue the deep analysis of your tweets. You said that determinism in a tweet, determinism and randomness play important roles in understanding what life is. So let me ask on this topic of free will, what is determinism? What is randomness? And why the heck do they have anything to do with understanding life? Yeah, and you threw free will in there. You're just throwing all the stuff in the bag. Are they not related? Determinism or randomness? No, no, they are related. No, no, sorry, I was being unfair. You didn't even capitalize the tweet, by the way. It was all lowercase. I must have been angry. Oh, that was, can you analyze the emotion behind that? No, I actually, Is it frustration or is it hope? Yeah, maybe. So I already argued that I don't think that can happen without that whole causal history. And so I guess in some sense, the determinism for me arises because of the causal history. And I'm not really sure actually about whether the universe is random or deterministic. I just had this sort of intuition for a long time. I'm not sure if I agree with it anymore, but it's still kind of lingering and I don't know what to do with this question. But it seems to me, so you asked the question, what is life? But you could also, why life? Why does life exist? What does the universe need life for? Not that the universe has needs, but we have to anthropocentrize things sometimes to talk about them. And I had this feeling that if it was possible for a cup or a desk ornament or a phone on Mars to spontaneously fluctuate into existence, the universe didn't need life to create those objects. It wasn't necessary for their existence. It was just a random fluke event. And so somehow to me, it seems that it can't be that those things form by random processes. They actually have to have a set of causes that accrue and form those things and they have to have that history. And so it seems to me that life was somehow deeply related to the question of whether the underlying rules of our universe had randomness in them or they were fully deterministic. And in some ways you can think about life as being the most deterministic part of physics because it's where the causes are precise in some sense. Or most stable? So like- Most stable, yes. Most reliable. Most reliable for the tools of physics. But what- Right, well, so- Where does randomness come from then? Okay, so you were speaking with- I've gone in a tangent, so I'm not sure where we are in the, yeah. All of the universe is a kind of tangent, so we're embracing the tangent. So free will, you believe- Yes. At this current time that you have free will- I believe my whole life I have free will. What is illusion? No, just kidding. I still believe it. You still believe it. So at the same time, you think that in your conception of the universe, causality seems to be pretty fundamental. That's right. Which kind of wants the universe to be deterministic. So how the heck- Because I'm a determ- Do you think you have a free will and yet you value causality? Because I depart from the conception of physics that you can write down an initial condition and a fixed law of motion, and that will describe everything. There's no incompatibility if you are willing to reject that assertion. So where's the randomness? Where's the magic that gives birth to the free will? Is it the randomness of the laws of physics? No, in my mind what free will is is the fact that I, as a physical system, have causal control over certain things. I don't have causal control over everything, but I have a certain set of things. And I'm also, as I described, sort of a nexus of a particular set of histories that exist in the universe and a particular set of futures that might exist. And those futures that might exist are in part specified by my physical configuration as me. And therefore, it may not be free will in the traditional sense. I don't even know what people mean when they're talking about free will, honestly. It's like the whole discussion's really muddled. But in the sense that I am a causal agent, if you wanna call it that, that exists in the universe, and there are certain things that happen because I exist as me, then yes, I have free will. No, but do you, Sarah, have a choice about what's going to happen next? Oh, I see. If the universe, could I have, if I run this universe again. Yes, I think so. You have a choice. Where does the choice come from? I think that's related to the physics of consciousness. So one of the things I didn't say about that, I don't know, maybe this is me just being hopeful because maybe I just wanna have free will, but I don't think that we can rule out the possibility because I don't think that we understand enough about any of these problems. But I think one of the things that's interesting for me about the sort of inversion of the question of consciousness that I proposed is one of the features that we do is we have imagination, right? And people don't think about imagination as a physical thing, but it is a physical thing. It exists in the universe, right? And so I'm really intrigued by the fact that, say, humans for, another physical system could do this too, it's not special to humans, but for centuries imagined flying machines and rockets, and then we finally built them, right? So they were represented in our minds and on the pages of things that we drew for hundreds of years before we could build those physical objects in the universe. But certainly the existence of rockets is in part causally caused by the fact that we could imagine them. And so there seems to be this property that some things don't exist, they've never physically existed in the universe, but we can imagine the possibility of them existing and then cause them to exist, maybe individually or collectively. And I think that property is related to what I would say about having choice or free will, because that set of possibilities, that set of things that you can imagine is not constrained to your local physical environment and history. And this is what's a little bit different about intelligence as we see it in humans and AI that we wanna build than biological intelligence, because biological intelligence is predicated completely on the history of things it's seen in the past. But something happened with the neural architectures that evolved in multicellular organisms that they don't just have access to the past history of their particular set of events, but they can imagine things that haven't happened, aren't on their timeline, and as long as they're consistent with the laws of physics, make them happen. So this is fascinating. In some sense- It's trippy physics, but it exists, so there you go. I mean, in some sense, if you look at like general relativity and gravity, morphing space-time, in that same way, maybe whatever the physics of consciousness might be, it might be morphing, that's like what free will is. It's morphing like the space, just like ideas make rockets come to life. It's somehow changing the space of possible realizations of like whatever's... Yeah, okay, but that's- Life is kind of basically, if you wanna think about it, like life is sort of changing the probability distributions over what can exist. That's the physics of what life is. And then consciousness is this sort of layered property, your imagination on top of it, that kind of scrambles that a little bit more and like has access to, I don't know, it's kind of, we don't know how to describe it, right? Like that's why it's interesting, but- But it's probabilistic, so you do think like God plays dice. So let me- No, I think the description's probabilistic. I don't necessarily think the underlying physics is probabilistic. I think the way that we can describe this physics is going to be probabilistic and statistical, but the under, like when we take measurements in the lab, but the underlying physics itself might still be deterministic. I don't know, maybe I'm... It's hard to know what concepts to hold onto, so I find myself constantly rejecting concepts, but then I have to grab another one and try to hold onto something from intellectual history. Well, it's possible that our mind is not able to hold the correct concepts in mind at all. Like we're not able to even conceive of them correctly. Maybe the words deterministic or random are not the right even words, concepts to be holding. But maybe you can talk to the theory of everything, this attempt in the current set of physical laws to try to unify them. Is there any hope that once a theory of everything is developed, and by theory of everything, I mean in a narrow sense of unifying quantum field theory and general relativity, do you think that will contain some... Like in order to do that unification, you would have to get something that would then give hints about the physics of life, the physics of existence, physics of consciousness. Yeah, I used to not, but I actually... I have become increasingly convinced that it probably will. And part of the reason is, I think I've talked a little bit already about these holes in physics. Like the theories we have in physics, they have problems, they have lots of problems, and they're very deep problems, and we don't know how to patch them. And some of those problems become very evident when you try to patch quantum mechanics and general relativity together. So there is this kind of interesting feature that some of the ways of patching that might actually closely resemble the physics of life. And so the place where that actually comes up most, and actually we just had a workshop in the Beyond Center where I work at Arizona State University, and Lee Smolin made this point that he thinks that the theory of quantum gravity, when we solve it, is gonna be the same theory that gives rise to life. And I think that I agree with him on some levels because there's something very interesting where if you look at these sort of causal set theories of gravity where they're looking for space as being emergent, and so space-time is an emergent concept from a causal set, which is also sort of related, I think, to what Wolfram's doing with his physics project. It's the same kind of underlying math that we have in this theory that we've been developing related to life called assembly theory, which is basically trying to look at complex objects like molecules and bacteria and living things as sort of, as basically being assembled from a set of component parts and that they actually encode all the possible histories that they could have in that physical object. So mathematically, all these ideas, I think, are related. I think a lot of people are thinking about this from different perspectives. And then constructor theory that David Deutsch and Chiara Marletto have been developing is a totally different angle on it, but I think getting at some similar ideas. So it's a really interesting time right now, I think, for the frontiers of physics and how it's relating to maybe deeper principles about what life is. So short answer, yes. Long-winded answer, rewind. Can we talk about aliens? Anytime. So one, I think one interesting way to sneak up on the question of what is life is to ask what should we look for in alien life? You know, if we were to look out into our galaxy and enter the universe and come up with a framework of how to detect alien life, what should we be looking for? Is there like set of rules? Like it's both the tools and the tools that are service sensors for certain kind of properties of life. So what should we look for in alien life? Yeah, so we have a paper actually coming out on Monday, which is collaboration. It's actually really Lee Cronin's lab, but my group worked with him on it and we're working on the theory, which is this idea that we should look for life as high assembly objects. What we mean by that is, which is actually observationally measurable. And this is one of the reasons that I started working with Lee on these ideas is because being a theorist, it's easy to work in a vacuum. It's very hard to connect abstract ideas about the nature of life to anything that's experimentally tractable. But what his lab has been able to do is develop this method where they look at a molecule and they break it apart into all its component parts. And so you say you have some elementary building blocks and you can build up all the ways of putting those together to make the original object. And then you look for the shortest path in that space. And you say that's sort of the assembly number associated to that object. And if that number's higher, it assumes that a longer causal history is necessary to produce that object or more information is necessary to specify the creation of that object in the universe. Now that kind of idea at a superficial level has existed for a long time. That kind of idea as a physical observable of molecules is completely novel. And what his lab has been able to show is that if you look at a bunch of samples of non-biological things and biological things, there's this kind of threshold of assembly where as far as the experimental evidence is and also your intuition would suggest that non-biological systems don't produce things with high assembly number. So this goes back to the idea like a protein's not gonna spontaneously fluctuate into existence on the surface of Mars. It requires an evolutionary process and a biological architecture to produce a protein. You generalize that argument, a complex molecule or a cup or a desk ornament in this sort of abstract idea of assembly spaces as being the causal history of objects. And you can talk about the shortest path from elementary objects to an object given an elementary set of operations. And you can experimentally measure that with mass spec. And that's basically sort of the idea. That's really fascinating. I can't get out of my head. I'd start imagining Legos and all the Legos I've ever built and how many steps. What is the shortest path to the final little Lego castles? So yeah, so then like asking about going to look for alien life, the idea is most of the instruments that NASA builds, for example, or any of the space agencies looking for life in the universe are looking for chemical correlates of life, right? But here we have something that is based on properties of molecules. It's not a chemical correlate. It's agnostic. It doesn't care about the molecule. It cares about what is the history necessary to produce this molecule. How complex is it in terms of how much time is needing, how much information is required to produce it? So when you observe a thing on another planet, you're essentially, the process looks like reverse engineering, trying to figure out what is the shortest path to create that thing. Yeah, so most, yeah, and I would say most, like most examples of biology or technology don't take the shortest path, right? But the shortest path is a bound on how hard it is for the universe to make that. Yeah, and I guess you and Lee are saying that there's a heuristic that's a good metric for like better perhaps than chemical correlates. Yes, because it's not contingent on looking for the chemistry of life on Earth on other planets. And it also has a deeper explanatory framework associated to it as far as the kind of theory that we're trying to develop associated to what life is. And I think this is one of the problems I have in my field personally in astrobiology is people observe something on Earth, say oxygen in the atmosphere or an amino acid in a cell, and then they say, let's go look for that on another planet. Let's look for oxygen on exoplanets or let's look for amino acids on Mars. And then they assume that's a way of looking for life. Or even phosphine on Venus. But you know, like there's all these examples of let's look for one molecule. A molecule is not life. Life is a system that patterns particular structures into matter, that's like, that's what it is. And it doesn't care what molecules are there. It's something about the patterns and that structure and that history. And if you're looking for a molecule, you're not testing any hypotheses about the nature of what life is. It doesn't tell me anything if we discover oxygen on an exoplanet about what kind of life is there. Just oxygen on an exoplanet. I guess I think like when you think about the question, are we alone in the universe? That's a pretty fricking deep question. It should have a fricking deep answer. It shouldn't just be there's a molecule on an exoplanet. Wow, we solved the problem. It should tell us something meaningful about our existence. And I feel like we've fallen short on how we're searching for life in terms of actually searching for things like us in this kind of deeper way. But how do you do that initial kind of, say I'm walking down the street and I'm looking for that double take test of like what the hell is that? Like that initial, like how do we look for the possibility of weirdness, the possibility of high assembly number? Like what would aliens look like if they don't have two eyes and are green? If I knew, I would have probably already solved the problem. Right, there's another Nobel prize in there somewhere. Yeah, somewhere in there. Well, I think it's kind of, so there is a bias here, right? So we've evolved to recognize life on earth, right? Like I, you know, children at a very early age can tell the difference between a puppy and a plant and then the plant and a chair, for example. You know, like it just, it seems innate. And so I think, and also because we're life, you know, I think like there's this implicit bias that we should know it when we see it and it should be completely obvious to us. But there are a lot of features of our universe that are not completely obvious to us, like the fact that this table is made of atoms and that I'm sitting in a gravitational potential well right now. And I guess my point with this is I think life is much less obvious than we think it is. And so it could be in many more forms than we think it is. And I guess this goes back to the point about being open-minded that we may not know what alien life looks like. It might not even be possible to interact with alien life because maybe something about, you know, our informational lineage, it makes it impossible for information from an alien to be copied to us. Therefore, there's no, you know, so to speak communication channel. And I don't mean, you know, verbal communication, just it's not in our observational space. Like, you know, like, you know, there's fundamental questions about why we observe the universe in position rather than momentum. But we also, you know, observe it in terms of certain informational patterns and things like that's what our brain constructs. And maybe aliens just interact with a different part of reality than we do. That's wildly speculative. But I think, I think- But it's possible. It's possible. And I think it's consistent with the physics. So I think the best ways we can ask questions are about life and chemistry and asking questions about if information is a real physical thing, what would its signatures be in matter? And how do we recognize those? And I think the ones that are most obvious are the ones I've already articulated. You have these objects that seem completely improbable for the universe to produce because the universe doesn't have the design of that object in the laws. So therefore, an object had to evolve. We talk, we call it evolution, but it had to be produced by the universe that then had all of the possible tasks to make that object specified. I mean, there's some, like there's an engineering question here of are there sensors we can create that can give us, can help us discover certain pockets of high assemblies? Yeah. Aliens. Like, I mean, there is a hope, setting dogs and chairs aside, there's a hope that visually, and we could detect, like because our universe, I mean, at least the way we look at it now, like this three-dimensional like space time, we can visually comprehend it. It's interesting to think like, if we got to hang out, if there's an alien in this room, like would we be able to detect it with our current sensors? Not the fancy kinds, but like webcams. Like say standing over there. Yeah, standing over there. Or maybe like in this carpet, see there's all these kinds of patterns, right? Yeah. I don't know if this carpet is an alien. Well, so I see what you're saying. So assembly theory is pretty general. Like, I mean, we've been applying it to molecules because it makes sense to apply it to molecules, but it's supposed to explain life, you know, like the physics of life. So it should explain, you know, the things in this room in addition to molecules. So I guess, and you can apply it to images and things. So I guess the idea, you know, you could explore is just looking at everything on planet Earth in terms of its assembly structure, and then looking for things that aren't part of our biological lineage. If they have high assembly, they might be aliens on Earth. I mean, that is a very kind of rigorous computer vision question. Can we visually, is there a strong correlation between certain kind of high assembly objects when they get to the scale where they're visually observable and some, like when it's, say, projected onto a 2D plane, can we figure out something? Right, I'm glad you brought up the computer vision point, because for a while I had this kind of thought in my mind that we can't even see ourselves clearly. So one of the things, you know, people are worried about artificial intelligence for a lot of reasons, but I think it's really fascinating because it's like the first time in history that we're building a system that can help us understand ourselves. So like, you know, people talk about AI physics, but like, you know, when I look at another person, I don't see them as a four billion year lineage, but that's what they are, and so is everything here, right? So imagine that we built artificial systems that could actually see that feature of us. What else would they see? And I think that's what you're asking. And I think that would be so cool. I want that to happen, but I think we're a little ways off from it, but yeah. We're going there, I hope. Okay, let me ask you, I apologize ahead of time, but let me ask you the internet question. So you're a physicist, you ask rigorous questions about the physics of existence and these models of high assembly objects. Now, when the internet would see an alien, they would ask two questions. One, can I eat it? And two, can I have sex with it? Yes. So. All the existential questions. Those are very important. The internet is very sophisticated. It really is. It's gotten our basal cognition pretty good. So you kind of mentioned that it's very difficult. It's possible that we may not be even able to communicate with it. Right. I think the internet has more hope than we do. Yeah, it's a hopeful place, yes. Do you think in terms of interacting on this very primal level of sharing resources, like what would aliens eat? What would we eat? Would we eat the same thing? Could we potentially eat each other? One person eats the other or the aliens eat us. And the same thing with not sex in general, or reproduction, but genetically mixing stuff. Like would we be able to mix genetic information? Maybe not genetic, but maybe information, right? And I think part of your question is like, so if you think of life as like this history of events that happen in the universe, like there's this question of like, how divergent are those histories, right? So when we get to the scale of technology, it's possible to imagine, although we can't even do it, like imagine all the possible technologies that could exist in the universe. But if you think about all the possible chemistries, somehow that seems like a lower dimensional space and a lower set of possibilities. So it might be that like when we interact with aliens, we do have to go back to those more basal levels to figure out sort of what the map is, right? Like the sort of where we have a common history. We must have a common history somewhere in the universe. But in order to be able to actually interact in a meaningful way, you have to have some shared history. I mean, the reason we can exchange genetic information in each other's food or eat each other as food is because we have a shared history. So we have to find that shared history. We have to find the common ancestor in this causality map, this causality tree. Yes, and we have a last universal common ancestor for all life on Earth, which I think is sort of the nexus of that causality map for life on Earth. But the question is, where would other aliens diverge on that map? That's really interesting. Yeah, so say there's a lot of aliens out there in the universe, each set of organisms will probably have like a number, you know, like Erdos number of like how far, like how far our common ancestor is. And so the closer the common ancestor, like it is on Earth, the more like each other, the more likely we are to be able to have sexual reproduction. Well, it's like sort of like humans having common culture and languages, right? Yeah, exactly. Like communication. It might take a lot of work though with an alien because you really have to get over a language barrier. Oh boy, so it's communication, it's resources. I mean, it's the whole. And I think tied into that is the questions of like who's gonna harm who. Right. And actually definitions of harm. And whether your parents approve, you know, all those kind of questions. Whether the common ancestor approves, yeah. That's just very true. How many alien civilizations do you think are out there? I don't have intuition for that, which I have always thought was deeply intriguing. So, and part of this, I mean, I say it specifically as I don't have intuition for that because it's like one of those questions that you feel around for a while and you really just, you can't see it, even though it might be right there. And in that sense, it's a little like the quantum to classical transition. You're like really talking about two different kinds of physics. And I think that's kind of part of the problem. Once we understand the physics, that question might become more meaningful. But there's also this other issue. And this was really instilled on me by my mentor, Paul Davies, when I was a postdoc, because he always talks about how, you know, whether aliens are common or rare is kind of just, you know, it follows a wave of popularity and it just depends on like the mood of, you know, what the culture is at the time. And I always thought that was kind of an intriguing observation, but also there's this, you know, set of points about if you go by the observational evidence, which we're supposed to do as scientists, right? You know, we have evidence of us and one original life event from which we emerged. And people wanna make arguments that because that event was rapid or because there's other planets that have properties similar to ours, that that event should be common. But you actually can't reason on that because our existence observing that event is contingent on that event happening, which means it could have been completely improbable or very common. And Brandon Carter like clearly articulated that in terms of anthropic arguments a few decades ago. So there is this kind of issue that we have to contend with dealing with life that's closer to home than we have to deal with with any other problems in physics, which we're talking about the physics of ourselves. And when you're asking about the original life event, that event happening in the universe, at least as like our existence is contingent on it. And so you can think about sort of fine tuning arguments that way too. But the sort of other part of it is like when I think about how likely it is, I think it's because we don't understand this mechanism yet about how information can be generated spontaneously. Cause I can't see that physics clearly yet, even though I have a lot of, you know, like some things around the space of it in my mind, I can't articulate how likely that process is. So my honest answer is, I don't know. And sometimes that feels like a cop out, but I feel like that's a more honest answer and a more meaningful way of making progress than what a lot of people wanna do, which is say, oh, well, we have a one in 10 chance of having on an exoplanet with Earth-like properties because there's lots of Earth-like planets out there and life happened fast on Earth. Well, so, kind of a follow up question, but as a side comment, what I really am enjoying about the way you're talking about human beings is you always say, and not to make yourself conscious about it, cause I really, really enjoy it, you say we. You don't say humans. You say, cause oftentimes, like, you know, I don't know, evolutionary biologists will kind of put yourself out as an observer, but it's kind of fascinating to think that you as a human are struggling about your own origins. Yes, that's the problem. And yeah, and I think, I don't do that deliberately, but I do think that way, and this is sort of the inversion from the logic of physics, because physics, as it's always been constructed, has treated us as external observers of the universe, and we are not part of the universe, and this is why the problem of life, I think, demands completely new thinking, because we have to think about ourselves as minds that exist in the universe and are at this particular moment in history and looking out at the things around us and trying to understand what we are inside the system, not outside the system. We don't have descriptions at a fundamental level that describe us as inside the system. And this was my problem with cellular automata also. You're always an external observer for a cellular automata. You're not in the system. What does a cellular automata look like from the inside? I think you just broke my brain with that question. Exactly, but that's the fundamental. I thought about that for a long time. But. I'm gonna, yeah, that's a really clean formulation of a very fundamental question, because you can only, to understand cellular automata, you have to be inside of it. But as a human, sort of a poetic, romantic question, does it make you sad? Does it make you hopeful, whether we're alone or not? Like, in the different possible versions of that, if we're the highest assembly object in the entire universe, does that give you. At this moment in time, maybe. At this moment in the causal. Cause we may, I assume we have a future. Well, we definitely have a future. The question is where that future decreases the assembly. Like, it could be we're at the peak, or we could be just. That would be inconsistent with the physics in my mind. But, so I should give a caveat. I've given the caveat that I'm biased as a physicist, but I'm also biased as an eternal optimist. So pretty much all of my modes of operation for building theories about the world are not like an Occam's razor, what's the simplest explanation, but what's the most optimistic explanation? And part of the reason for that is if you really think explanations have causal power, in the sense that our, like the fact that we have theories about the world has enabled technologies and physically transformed the world around us. I think I have to take seriously that as a part of the physics I wanna describe, and try to build theories of reality that are optimistic about what's coming next, because the theories are in part the causes of what comes next. So there could be a physics of hope, or physics of optimism in there too. Yes. That seems like also, I mean, optimism does seem to be a kind of engine that results in innovation. Yes. So this is, like, why the hell are we trying to come up with new stuff? Oh, so I made this point about thinking life is the physics of existence, and it's not just the physics of existence, it's the physics of more things existing. So I think one of these drives of like- Creativity. Yeah, creativity, like optimism. So if you like, people like entropy. I don't like entropy as it was formulated in the 1800s. I think it's an antiquated concept, but this idea of maximizing over the possible number of states that could exist. Imagine the universe is actually trying to maximize over the number of things that could physically exist. What would be the best way to do that? The best way to do that would be evolve intelligent technological things that could explore that space. So, okay, that's talking about alien life out there in the universe, but you've also earlier in the conversation mentioned the shadow biosphere. So is it possible that we have weird life here on Earth that we're just not, like, even in a high assembly formulation of life, that we're just not paying attention to, we're blind to? Like life we're potentially able to detect, but we're blind to? And maybe you could say, what is the shadow biosphere? Sure, sure. Yeah, the shadow biosphere is this idea that there might've been other original life events that happened on Earth that were independent from the original life event that led to us and all of the life that we know on Earth. And therefore, there could be aliens in the sense they have a different origin event. Living among us. And it was proposed by a number of people, but one of them was Paul Davies that I mentioned earlier is my mentor. And he has a really cute way of saying that aliens could be right under our noses or even in our noses. With a British accent, it sounds better. But anyway, so the idea is like, it could literally be anywhere around us. And if you think actually about the discovery of like viruses and bacteria, for a long time, they were kind of a shadow biosphere. It was life that was around us, but invisible. But this takes it a little bit further in saying that all of those examples, viruses, bacteria, and everything that we've discovered so far has this common ancestry and the last universal common ancestor of life on Earth. So maybe there was a different origin event and that life is weirder still and might be among us and we could find it. We don't have to go out and in stars look for aliens just here on Earth. Do you think that's a serious possibility that we should explore with the tools of science? Like this should be a serious effort. I think yes and no. And I mean, yes, because I think it's a serious hypothesis and I think it's worth exploring and it is certainly more economical to look for signs of alien life on Earth than it is to go and build spacecraft and send robots to other planets. And that was one of the reasons it was proposed is, well, if we do find an example of another original life on Earth, it's hugely informative because it means the original life is not a rare event. If it happened twice on the same planet, that means it's probably pretty probable given conditions are right. So it has huge potential scientific impact, not to mention the fact that you might have like biochemistry and stuff that's informative for like medicine and stuff like that. But I think that the thing for me that's challenging about it, and this really comes from my own work, like thinking about life as a planetary scale process and also trying to understand sometimes what I call like the statistical mechanics of biochemistry, but large scale statistical patterns in the chemistry that life uses on Earth. There are a lot of regularities there and life does seem to have planetary scale organization that's consistent even with some of the patterns that we see at the individual scale. So if you think life is a planetary scale phenomena and the chemistry of life has to be sort of not just, it's not, an individual is not necessarily the fundamental unit of life, right? The fundamental unit of life is these informational lineages and they're kind of, they intersect over spatial scales. So everything on Earth is kind of related by that common causal history. So it's hard for me based on the way I think about the physics and also some of the stuff that my group has done to really think that there could be evidence or there could be a second sample of life on Earth. But I think there are ways that we need to be more concrete about that. And I have thought a little bit about, like you can represent the chemistry in an individual cell as a network and then those networks, something my group has shown, actually scale with the same property. So ecosystems have the same properties as individuals as planetary scale. And then you could imagine if you had alien chemistry intermixed in there, that scaling would be broken. So if there's some robustness property or something associated to it and you get alien chemistry in there, it just breaks everything. And you don't have a planetary ecosystem functioning and individuals functioning across all these scales. So I guess what I'm arguing is life is not a scale-dependent phenomenon. It's not just cellular life. So if you have a shadow biosphere, it has to be integrated with all of these other scales. And it- And that would lose the meaning of the word shadow biosphere, I guess. I think so, yeah. So it's an open question, right? And I think it would tell us a lot. So there has been very minimal effort of people to look for a shadow biosphere. But then the question, it could be possible that there's like sufficiently distinct planets within one planet, meaning like environments within one planet. Yeah. Like, I don't know. I've been looking recently because of having a chat with Catherine DeCleer about Io, the moon of Jupiter, that's like all volcanoes and volcanoes are badass. But like imagining- Io's badass. Like, imagining life inside volcanoes, right? Like it seems like sufficiently chemically different like to be living in the darkness where there's a lot of heat. And maybe you can have different earths on like a planet. Yeah. Or like if you go deep enough in the crust, maybe there's like a layer where there's no life and then there's suddenly life again. And maybe those lizard men or whatever they are that people dream about are really down there. I know that's a little flippant, but really like there could be like chemical cycles deep in the earth's crust that might be alive and are completely distinct in chemical origin to surface life. Right, that they wouldn't be interacting with each other. Yeah, and that's one of the proposals for the shadow biosphere is like, sometimes people talk about it as being geologically or geographically distinct, that it might be, you have no life for this region and then a different example. And then sometimes people talk about it being chemically distinct, that the chemistry is sufficiently different, that it's completely orthogonal or non-interacting with our chemistry. It seems to me at least the chemistry is a more powerful boundary. Yes, maybe. Than geographic. It just seems like life finds a way literally to travel. Yeah, it does. What do you think about all these UFO sightings? So to me, it's really inspiring. It's yet another localized way to dream about the mysterious that is out there. Yeah, so I've actually been more intrigued by the cultural phenomena UFOs than the phenomena UFOs themselves, because I think it's intriguing about how we are preparing ourselves mentally for understanding others and how we have thought about that historically and what the sort of modern incarnations of that are. It's more like I want an explanation for us. That's my motivation. And having some streaks across the sky or something and saying that's aliens, it doesn't tell you anything. So unless you have a deeper explanation and you have more lines of where is this gonna take us in the future, it's just not as interesting to me as the problem of understanding life itself and aliens as a more general phenomena. I do think it's just, as you said, a good way to psychologically and sociologically prepare ourselves to sort of like, what would that look like? And very importantly, which is what a lot of people talk about politically, sort of there's this idea from the, so I came from the Soviet Union of like the Cold War and we have to hide secrets. There's some way in us searching for life on other planets or searching for life in general, but the way we've done government in the past, we tend to think of all new things as potential military secrets, so we want to hide them. And one of the ways that people kind of look at UFO sightings is like maybe we shouldn't hide this stuff. Like what is the government hiding? I think that's a really, in one sense it's a conspiratorial question, but I think in another it's an inspiration to change the way we do government to where secrets don't, maybe there are times when you want to keep secrets as military secrets, but maybe we need to release a lot more stuff and see us as a human species as together in this whole search. Yeah, the public engagement part there is really interesting. And it's almost like a challenge to the way we've done stuff in the past in terms of keeping secrets. When they're not, so like the first step, if you don't know how something works, if there's a mysterious thing, the first instinct should not be like, let's hide it, let's put it in the closet. So that the Chinese or the Russian government or whatever government doesn't find it. Maybe the first instinct should be let's understand it. Perhaps let's understand it together. Right, no, I think that's good. And something I realized recently that I never thought was gonna be a problem, but I think this actually helps with quite a bit is because so many people nowadays believe we've already made contact that as an astrobiologist, if we actually wanna understand life and make contact, we kind of have to deconstruct the narratives we've already built from ourselves and kind of unteach ourselves that we've learned about aliens and then reteach ourselves. So there's this really interesting sort of dialogue there and making it open to the public that they actually have to think critically about it and they see the evidence for themselves, I think is really important for that process. Yeah, the reteaching, that aliens might be way weirder than we can imagine. Yes, yes, I'm pretty sure they're probably weirder than we can imagine. Okay, we've in 2020 and still living through a pandemic, setting the political and all those kinds of things aside, I've always found viruses fascinating as dynamical systems, I was gonna say living systems, but I've always kind of thought of them as living, but that's a whole nother kind of discussion. Maybe it'd be great to put that on the table. One, do you find viruses beautiful slash terrifying and two, do you think they're living things or there's some aspect to them per our discussion of life that makes them living? I mean, living in a pandemic saying viruses are beautiful is probably a hard thing, but I do find them beautiful to a degree. I think even in the sense of mediating a global pandemic, there's something like deeply intriguing there because these are tiny, tiny little things, right? And yet they can essentially cause a seizure or handicap an entire civilization at a global scale. So just that intersection between our perceived invincibility and our susceptibility to things and also the interaction across scales of those things is just a really amazing feature of our world. Most technology, whether it's viruses or AI, that can scale in an exponential way, like kind of run as opposed to like one thing makes another thing makes another thing. It's one thing makes two things and those two things make four things. And then like that kind of process also seems to be fundamental to life. Yes. And it's terrifying because in a matter of, in a very short timescale, it can, if it's good at being life, whatever that is, it can quickly overtake the other competing forms of life. Right. And that's scary both for AI and for viruses. And it seems like understanding these processes that are underlying viruses. And I don't mean like on the virology or biology side, but on some kind of more computational physics perspective as we've been talking about, it seems to be really important to figure out how humans can survive. Right. Along with these kinds of, all this kind of life and perhaps becoming a multi-planetary species is a part of that. Like there's no, maybe like we'll figure out from a physics perspective is like, there's no way any living system can be stable for prolonged period of time and survive unless it expands exponentially throughout. Like we have to multiply. Otherwise anything that doesn't multiply exponentially will die eventually. Maybe that's a fundamental law. Maybe, I don't know. I always get really bothered by these Darwinian narratives that are like the fittest replicator wins and things. And I don't, I just don't feel like that's exactly what's going on. I think like the copying of information is sort of ancillary to this other process of creativity. Right, so like the drive is actually, the drive is creativity. But if you wanna keep the creativity that's existed in the past, it has to be copied into the future. So replication, like if you, so that for me is, so I had this set of arguments with Michael Lachman and Lee Cronin about the like life being about persistence. They thought it was about persistence and like survival of the fittest kind of thing. And I'm like, no, it's about existence. It's like, cause when you're talking about that, it's easy to say that in retrospect, you can post select on the things that survived and then say why they survived. But you can't do that going forward. That's really profound. That survival is just a nice little side effect feature of maximizing creativity, but it doesn't need to be there. Yeah. That's really beautiful. I like that, yeah. Yeah, that's really- Like I said, I like optimistic theories. Well, I don't know if that's optimistic. That could be terrifying to people because, Yeah. Because a system that maximizes creativity may very quickly get rid of humans for some reason, if it comes up with some other creative, I mean, forms of existence. Yeah. Right, this is the AI thing. It's like the moment you have an AI system that can flourish in the space of ideas or in some other space much more effectively than humans and is sufficiently integrated into the physical space to be able to modify the environment. I think we'll just be like the core genetic architecture or something. We'll be like the DNA for AI, right? Yeah. It's like we haven't lost the past informational architectures on this planet. They're still there. Yeah, so the AI will use our brains in some part to like ride, like it'll accelerate the exchange of ideas. That's the neural language dream, is that, well, the humans will be still around because you're saying architecture. Yeah, but I don't even think they necessarily need to tap in our brains. I mean, just collectively we do interesting things. What if they were just using like the patterns in our communication or something? Oh, without controlling it, just observing? Well, I don't know. In what sense do you control the chemistry happening in your body? Hmm, yeah. I mean, obviously I don't know. I'm just, like the way I look at, like people look at AI and then they look at this thing that's bigger than us and is coming in the future and is smarter than us. And I think though that looking at the past history of life on the planet and what information has been doing for the last 4 billion years is probably very informative to asking questions about what's coming next. And I don't, one is planetary scale transitions are really important for new phases. So the global internet and sort of global integration of our technology I think is an important thing. So that's again, life as a planetary scale phenomena. But we're an integrated component of that phenomena. I don't really see that the technology is gonna replace us in that way. It's just gonna keep scaffolding and building. And I also don't have an idea that we're gonna build AI in a box. I think AI is gonna emerge. AGI to me is a planetary scale phenomena that's gonna emerge from our technology. Planetary scale phenomena. But do you think, and AGI is not distinct from humans. The whole package. The whole package, yeah. Comes as a planetary scale phenomena. And that goes back to the fact that you were asking questions about you as an individual. Like what are you as an individual? You're like a packet of information that exists in the particular physical thing that is you. We're all just packets of information. And some of us are aggregates in certain ways, but it's all just kind of exchanging and propagating, right, and processing. Is your packet of information that you've continually referred to as Sarah afraid of the dissipation of the death of that packet? Are you afraid of death? Do you ponder death? Does death have meaning in this process of creativity? I think I have the natural biological urge that everyone has to fear death. I think the thing that I think is interesting is if I think about it rationally, I'm not necessarily afraid of death for me because I won't be aware of being dead. But I am afraid for my kids because it matters to them if I die. So again, I think death becomes more significant as a collective property, not as an individual one. But isn't there something to fear about the fact that the way, like the creative, the complexity of information that's been created in you, the fact that it kind of breaks apart and disappears? But I don't think it disappears, it's just not me anymore. Right, but that process of it being not you anymore, that doesn't scare you? Of course it does. The mystery of it, I mean the... Yeah, but I guess I'm heartened by the fact that there will be some imprints of the fact that I existed still in the universe after I leave it as me. There'll be, okay. And also that has to do with my perception of time, right? So I perceive time as flowing, but that might not be the case. I mean this is, standard physicist comfort is every moment exists, and there's no, and the flow of time is just our perception of us changing. So you can travel back in time and that's comforting? Like from a physicist's perspective? No, no, no, I'm not talking about traveling back in time, I'm just saying that the moments in the past still exist. Now whether the moments in the future exist or not is a different question. That's not comforting to me in terms of death. The flow of time does not... I think there's no comfort in the face of death for what we are, because we like existing. And I think it's especially true if you love life and you love what life is. Do you think there's a certain sense in which the fear of death or the fear of non-existence, maybe fear is not the right word, is the actual very phenomena that gives birth to existence? Like death is fundamental, like this, it just feels like freaking out, oh shit, this ride ends, is actually like, that's the thing that gives birth to this whole thing. That like, it's constantly, it's matter constantly freaking out about the fact that it's gonna be much more so. No, I think things like to exist, I think they wanna exist. Yeah, there's a desire or whatever to exist. Yeah, there's a drive to exist and there's a drive for more things to exist. I guess, yeah, I like existing, I like it a lot. And I don't know it any other way. See, I don't even know if I like existing, I think I really don't like not existing. Yes, yeah, that too. Yeah, maybe it's that. Some days I might like existing less than others. Yes, but I think those are like surface feelings. There is some, seems like there's something fundamental about wanting to exist. No, I think that's right, but I think to your point, that might go back to the more fundamental idea that if life is the physics of existence and maximizing existence, individual organisms, of course, wanna maximize their existence and everything wants to exist. But I guess for me, the small comfort is my existence matters to future existence. Speaking of future existence, is there advice you can give to future pockets of existences, aka young people, about life? You've had, you've worn many hats, you've taken on some of the biggest problems in the universe. Is there advice you can give to young people about life, about career, about existing? Maybe not about the last one. A lot of people ask me this question about like working on such hard problems, like how can you make a successful career out of that? But I think for me, it couldn't be otherwise. Like I have to, to be fulfilled, you have to work on things you care about and that's always kind of driven me. And that's been discipline, department, and sort of superficial level problem independent because I started at community college actually and I was taking a physics class and I learned about magnetic monopoles and we didn't know if they existed in the universe but we could predict them and we could go look for them. And I was so deeply intrigued by this idea that we had this mathematical formula to go look for things. And then I wanted to become a theoretical physicist because of that, but that actually wasn't my driving question I think I realized my driving question is the nature of the correspondence between our minds and physical reality and what we are. And that question is very deep so you can work across a lot of fields doing that. But I think without that driving question, I never would have been able to do all the things that I've done. It's really the passion that drives it. And usually when students ask me these kinds of questions, I tell them like, you have to find something you really care about working on because if you don't really care about it, A, you're not gonna be your best at it and B, it's not gonna be worth your time. Why would you spend your time working on something you're not interested in? So find the driving questions. Yeah, find the driving question, find your passion. I mean, I think passion makes a huge difference in terms of creativity, talent and potential and also being able to tolerate all the hard things that come with any career or life. Yeah, I've had a bunch of moments in my life where I've just been captivated by some beautiful phenomena and I guess being rigorous about it and asking what is the question underlying this phenomenon. Like robots bring a smile to my face and forming a question of like, why the hell is this so fascinating? Why is this specifically the human robot interaction question that something beautiful is brought to life when humans and robots interact? Understanding that deeply. Yeah. I was like, okay, so this is gonna be my life work then. I don't know what the hell it is, but that's what I wanna do. Interesting. And doing that for whatever the hell gives you that kind of feeling, I guess is the point. Yeah. Am I allowed to ask you a question? Sure. Okay, on that point, because I had this colleague that suggests the idea that like consciousness might be contagious and so interacting with things, you know, isn't it? That's funny. No, yeah, yeah, it's a beautiful way of putting it. It's an interesting idea, right? So I'm wondering like sort of, you know, the motivation there. Is it the motivation that you want more of the universe to appreciate things the way we do and appreciate those interactions? Or is it really more the enjoyment of the human in those interactions? Like is it, do you know what I'm asking? Yeah, yeah. See, I think consciousness is created in the interaction between things. Yes, I agree. So the joy is in the creation of consciousness. I see. I really like the idea that it doesn't just have to be two humans creating consciousness together. It could be humans and other entities. We talked offline about dogs and other pets and so on. There's a magic, I mean, I've been calling it love. It's this beauty of the human experience that's created. And it just feels like fascinating that you could do that with a robotic system. Right. And there's something really powerful, at least to me, about engineering systems that allow you to create some of the magic of the human experience. Because then you get to understand what it takes, at least get inklings of what it takes to create consciousness. And I don't get this, philosophers get really upset about this idea that sort of the illusion of consciousness is consciousness. But I really like the idea of engineering systems that fool you into thinking they're conscious. Right. Because that's sufficient to create the magical experience. Right, because it's the interaction, yeah. It's the interaction, yeah. Right. And this is the Russian hat I wear, which is like, I think there's an ocean of loneliness in the world. I think we're deeply lonely. We're not even allowing ourselves to acknowledge that. And I kind of think that's what love is between, romantic love and friendship is two people kind of getting a little bit like alleviating for a brief moment. That loneliness. That loneliness, but we're not, it's not the full aspect of that loneliness. Like we're desperately alone. We're desperately afraid of non-existing. Right. I have that kind of sense. And I just wanna explore that ocean of loneliness more. Right. When engineering, like create a submarine that goes into the depth of that loneliness. So creating systems that can truly hear you. Right. And truly listen. Make the universe a less lonely place. Exactly. Let me ask you about the meaning. You've brought up why. Yeah. The physics of why. What do you think is the meaning of our particular planets, set of existences and the universe in general? The meaning of life. Yes. Someone once told me as a physicist, I'm not allowed to ask why questions, but I don't believe that. So I think what we are is the creative process in the universe, I think. And for me, that's the meaning. The ability to create more possibilities and more things to exist. What is, does the S.G. has the saying, beauty will save the world. What is, is there a connection between creation and beauty? I think so. So is that like, is beauty a correlate of creation? It might be, I don't know. I mean, why is it, a lot of people have asked these kinds of questions, but like, why is it we have such an emotional response to intellectual activity or creativity? And that seems kind of a deep question to me. Like it seems very intrinsic to what we are. So I do have an interest in the questions I ask because I think they're beautiful and I think the universe is beautiful. And I'm just so deeply fascinated by the fact that I exist at all. And so maybe it's that intrinsic feeling of beauty that's in part driving the physics of creating more things. So they could be deeply related in that way. Well, I don't think there's a better way to end it. I think this conversation was beautiful. Thank you so much for wasting all your valuable time with me today. I really, really appreciate it, Sarah. This is an honor. I hope we get the chance to talk again. I hope, like I mentioned to you offline, to get a chance to talk with Lee. You guys have a beautiful, like intellectual chemistry that's fascinating to listen to. So I'm a huge fan of both of you and I can't wait to see what you do next. Thanks so much. Great to be here. Bye. I am. Thanks for listening to this conversation with Sarah Walker. A thank you to Athletic Greens, NetSuite, Blinkist, and Magic Spoon. Check them out in the description to support this podcast. And now let me leave you with some words from Robert Frost, one of my favorite poets. In three words, I can sum up everything I've learned about life. It goes on. Thank you for listening. I hope to see you next time.

https://youtu.be/-tDQ74I3Ovs

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Elon Musk: Neuralink, AI, Autopilot, and the Pale Blue Dot | Lex Fridman Podcast #49

The following is a conversation with Elon Musk, part two, the second time we spoke on the podcast, with parallels, if not in quality, then in outfit, to the objectively speaking greatest sequel of all time, Godfather part two. As many people know, Elon Musk is a leader of Tesla, SpaceX, Neuralink, and the Boring Company. What may be less known is that he's a world-class engineer and designer, constantly emphasizing first principles thinking and taking on big engineering problems that many before him would consider impossible. As scientists and engineers, most of us don't question the way things are done, we simply follow the momentum of the crowd. But revolutionary ideas that change the world on the small and large scales happen when you return to the fundamentals and ask, is there a better way? This conversation focuses on the incredible engineering and innovation done in brain-computer interfaces at Neuralink. This work promises to help treat neurobiological diseases to help us further understand the connection between the individual neuron to the high-level function of the human brain, and finally, to one day expand the capacity of the brain through two-way communication with computational devices, the internet, and artificial intelligence systems. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, Apple Podcasts, Spotify, support on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. And now, as an anonymous YouTube commenter, refer to our previous conversation as the quote, historical first video of two robots conversing without supervision. Here's the second time, the second conversation with Elon Musk. Let's start with an easy question about consciousness. In your view, is consciousness something that's unique to humans, or is it something that permeates all matter, almost like a fundamental force of physics? I don't think consciousness permeates all matter. Panpsychics believe that. There's a philosophical... How would you tell? That's true. That's a good point. I believe in scientific methods. I don't blow your mind or anything, but the scientific method is like, if you cannot test the hypothesis, then you cannot reach a meaningful conclusion that it is true. Do you think consciousness, understanding consciousness, is within the reach of science, of the scientific method? We can dramatically improve our understanding of consciousness. I would be hard-pressed to say that we understand anything with complete accuracy, but can we dramatically improve our understanding of consciousness? I believe the answer is yes. Does an AI system, in your view, have to have consciousness in order to achieve human level or superhuman level intelligence? Does it need to have some of these human qualities, like consciousness, maybe a body, maybe a fear of mortality, capacity to love, those kinds of silly human things? There's this scientific method, which I very much believe in, where something is true to the degree that it is testably so. And otherwise, you're really just talking about preferences or untestable beliefs or that kind of thing. So, it ends up being somewhat of a semantic question where we are conflating a lot of things with the word intelligence. If we parse them out and say, are we headed towards a future where an AI will be able to outthink us in every way? Then the answer is unequivocally yes. In order for an AI system that needs to outthink us in every way, it also needs to have a capacity to have consciousness, self-awareness, and understanding. It will be self-aware, yes. That's different from consciousness. I mean, to me, in terms of what consciousness feels like, it feels like consciousness is a part of you. It's a part of you. It feels like consciousness is in a different dimension. But this could be just an illusion. You know, if you damage your brain in some way physically, you damage your consciousness, which implies that consciousness is a physical phenomenon, in my view. The thing is that I think are really quite likely is that digital intelligence will be able to outthink us in every way. And it will still be able to simulate what we consider consciousness to a degree that you would not be able to tell the difference. And from the aspect of the scientific method, it might as well be consciousness, if we can simulate it perfectly. If you can't tell the difference, and this is sort of the Turing test, but think of a more sort of advanced version of the Turing test. If you're talking to a digital superintelligence and can't tell if that is a computer or a human, like let's say you're just having a conversation over a phone or a video conference or something where you think you're talking, looks like a person makes all of the right inflections and movements and all the small subtleties that constitute a human and talks like a human, makes mistakes like a human, like at that, and you literally just can't tell, is this, are you video conferencing with a person or an AI? Might as well. Might as well. Be human. So on a darker topic, you've expressed serious concern about existential threats of AI. It's perhaps one of the greatest challenges that our civilization faces. But since I would say we're kind of an optimistic descendants of apes, perhaps we can find several paths of escaping the harm of AI. So if I can give you three options, maybe you can comment which do you think is the most promising. So one is scaling up efforts on AI safety and beneficial AI research in hope of finding an algorithmic or maybe a policy solution. Two is becoming a multi-planetary species as quickly as possible. And three is merging with AI and riding the wave of that increasing intelligence as it continuously improves. What do you think is most promising, most interesting as a civilization that we should invest in? I think there's a tremendous amount of investment going on in AI. Where there's a lack of investment is in AI safety. And there should be, in my view, a government agency that oversees anything related to AI to confirm that it does not represent a public safety risk. Just as there is a regulatory authority for the Food and Drug Administration, there's NHTSA for automotive safety, there's the FAA for aircraft safety. We generally come to the conclusion that it is important to have a government referee or a referee that is serving the public interest in ensuring that things are safe when there's a potential danger to the public. I would argue that AI is unequivocally something that has potential to be dangerous to the public and therefore should have a regulatory agency just as other things that are dangerous to the public have a regulatory agency. But let me tell you the problem with this is that the government moves very slowly. And the rate of, the usually way a regulatory agency comes into being is that something terrible happens. There's a huge public outcry. And years after that, there's a regulatory agency or a rule put in place. Take something like seatbelts. It was known for a decade or more that seatbelts would have a massive impact on safety and save so many lives and serious injuries. And the car industry fought the requirement to put seatbelts in tooth and nail. That's crazy. And hundreds of thousands of people probably died because of that. And they said people wouldn't buy cars if they had seatbelts, which is obviously absurd. Or look at the tobacco industry and how long they fought anything about smoking. That's part of why I helped make that movie, Thank You for Smoking. You can sort of see just how pernicious it can be when you have these companies effectively achieve regulatory capture of government. It's bad. People in the AI community refer to the advent of digital superintelligence as a singularity. That is not to say that it is good or bad, but that it is very difficult to predict what will happen after that point. And that there's some probability it will be bad, some probability it will be good. But obviously, I want to affect that probability and have it be more good than bad. Well, let me, on the merger with AI question and the incredible work that's being done at Neuralink, there's a lot of fascinating innovation here across different disciplines going on. So the flexible wires, the robotic sewing machine, the response to brain movement, everything around ensuring safety and so on. So we currently understand very little about the human brain. Do you also hope that the work at Neuralink will help us understand more about the human mind, about the brain? Yeah, I think the work at Neuralink will definitely shed a lot of insight into how the brain and the mind works. Right now, just the data we have regarding how the brain works is very limited. But I think that the work at Neuralink will definitely help us understand how the brain works is very limited. We've got fMRI, which is that's kind of like putting a stethoscope on the outside of a factory wall and then putting it all over the factory wall. And you can sort of hear the sounds, but you don't know what the machines are doing, really. It's hard. You can infer a few things, but it's very broad brushstroke. In order to really know what's going on in the brain, you have to have high precision sensors. And then you want to have stimulus and response. Like if you trigger a neuron, how do you feel? What do you see? How does it change your perception of the world? You're speaking to physically just getting close to the brain, being able to measure signals from the brain will give us sort of open the door inside the factory. Yes, exactly. Being able to have high precision sensors that tell you what individual neurons are doing and then being able to trigger a neuron and see what the response is in the brain. So you can see the consequences of if you fire this neuron, what happens? How do you feel? What does it change? It'll be really profound to have this in people because people can articulate their change. Like if there's a change in mood or if they can tell you if they can see better or hear better or be able to form sentences better or worse or their memories are jogged or that kind of thing. So on the human side, there's this incredible general malleability plasticity of the human brain. The human brain adapts, adjusts and so on. It's not that plastic to be totally frank. So there's a firm structure, but nevertheless, there is some plasticity. And the open question is, so if I could ask a broad question is how much that plasticity can be utilized. Sort of on the human side, there's some plasticity in the human brain. And on the machine side, we have neural networks, machine learning, artificial intelligence, it's able to adjust and figure out signals. So there's a mysterious language that we don't perfectly understand that's within the human brain. And then we're trying to understand that language to communicate both directions. So the brain is adjusting a little bit. We don't know how much. And the machine is adjusting. Where do you see as they try to sort of reach together, almost like with an alien species, try to find a protocol, communication protocol that works? Where do you see the biggest benefit arriving from on the machine side or the human side? Do you see both of them working together? I actually think the machine side is far more malleable than the biological side, by a huge amount. So it'll be the machine that adapts to the brain. That's the only thing that's possible. The brain can't adapt that well to the machine. You can't have neurons start to regard an electrode as another neuron, because a neuron just, there's like the pulse. And so something else is pulsing. So there is that elasticity in the interface, which we believe is something that can happen. But the vast majority of the malleability will have to be on the machine side. But it's interesting when you look at that synaptic plasticity at the interface side, there might be like an emergent plasticity. Because it's a whole nother, it's not like in the brain, it's a whole nother extension of the brain. We might have to redefine what it means to be malleable for the brain. So maybe the brain is able to adjust to external interfaces. There will be some adjustment to the brain, because there's going to be something reading and simulating the brain. And so it will adjust to that thing. But most, the vast majority of the adjustment will be on the machine side. This is just, it has to be that, otherwise it will not work. Ultimately, we currently operate on two layers. We have sort of a limbic, like prime primitive brain layer, which is where all of our kind of impulses are coming from. It's sort of like we've got like a monkey brain with a computer stuck on it. That's the human brain. And a lot of our impulses and everything are driven by the monkey brain. And the computer, the cortex is constantly trying to make the monkey brain happy. It's not the cortex that's steering the monkey brains, the monkey brain is steering the cortex. But the cortex is the part that tells the story of the whole thing. So we convince ourselves it's more interesting than just the monkey brain. The cortex is like what we call human intelligence. That's like the advanced computer relative to other creatures. Other creatures do not have either, really, they don't have the computer, or they have a very weak computer relative to humans. But it's like, it sort of seems like surely the really smart thing should control the dumb thing, but actually the dumb thing controls the smart thing. So do you think some of the same kind of machine learning methods, whether that's natural language processing applications, are going to be applied for the communication between the machine and the brain? To learn how to do certain things like movement of the body, how to process visual stimuli, and so on. Do you see the value of using machine learning to understand the language of the two-way communication with the brain? Sure, yeah, absolutely. I mean, we're a neural net, and AI is basically neural net. So it's like digital neural net will interface with biological neural net. And hopefully bring us along for the ride. But the vast majority of our brain the vast majority of our intelligence will be digital. Like think of the difference in intelligence between your cortex and your limbic system is gigantic. Your limbic system really has no comprehension of what the hell the cortex is doing. It's just literally hungry, or tired, or angry, or sexy, or something. And then in that case, that impulse to the cortex and tells the cortex to go satisfy that. Then a great deal of like a massive amount of thinking, like truly stupendous amount of thinking has gone into sex without purpose, without procreation. Which is actually quite a silly action in the absence of procreation. It's a bit silly. So why are you doing it? Because it makes the limbic system happy, that's why. But it's pretty absurd, really. Well, the whole of existence is pretty absurd in some kind of sense. Yeah. But I mean, this is a lot of computation has gone into how can I do more of that with procreation not even being a factor? This is, I think, a very important area of research by NSFW. An agency that should receive a lot of funding, especially after this conversation. I propose the formation of a new agency. Oh, boy. What is the most exciting or some of the most exciting things that you see in the future impact of Neuralink, both on the science, the engineering and societal broad impact? So Neuralink, I think, at first will solve a lot of brain related diseases. So it could be anything from like autism, schizophrenia, memory loss, like everyone experiences memory loss at certain points in age. Parents can't remember their kids' names and that kind of thing. So there's a tremendous amount of good that Neuralink can do in solving critical damage to the brain or the spinal cord. There's a lot that can be done to improve quality of life of individuals. And that will be, those will be steps along the way. And then ultimately, it's intended to address the existential risk associated with that. Intended to address the existential risk associated with digital superintelligence. Like we will not be able to be smarter than a digital supercomputer. So therefore, if you cannot beat them, join them. And at least we won't have that option. So you have hope that Neuralink will be able to be a kind of connection to allow us to to merge, to ride the wave of the improving AI systems? I think the chance is above 0%. So it's non-zero. There's a chance. And that's... So what I'm saying, have you seen Dumb and Dumber? Yes. So I'm saying there's a chance. He's saying one in a billion or one in a million, whatever it was, at Dumb and Dumber. You know, it went from maybe one in a million to improving, maybe it'll be one in a thousand, and then one in a hundred, then one in ten. It depends on the rate of improvement of Neuralink and how fast we're able to make progress. Well, I've talked to a few folks here, they're quite brilliant engineers. So I'm excited. Yeah, I think it's like fundamentally good, you know, giving somebody back full motor control after they've had a spinal cord injury, you know, restoring brain functionality after a stroke, solving debilitating genetically oriented brain diseases. These are all incredibly great, I think. And in order to do these, you have to be able to interface with neurons at a detailed level and you need to be able to fire the right neurons, read the right neurons. And then effectively you can create a circuit, replace what's broken with with silicon and essentially fill in the missing functionality. And then over time, we can have, we develop a tertiary layer. So if like the limbic system is a primary layer, then the cortex is like the second layer. And I said that, you know, obviously the cortex is vastly more intelligent than the limbic system, but people generally like the fact that they have a limbic system and a cortex. I haven't met anyone who wants to delete either one of them. They're like, okay, I'll keep them both. That's cool. The limbic system is kind of fun. It does. Well, the fun is, absolutely. And then people generally don't want to lose the cortex either. Right? So they like having the cortex and the limbic system. Yeah. And then there's a tertiary layer, which will be digital super intelligence. And I think there's room for optimism, given that the cortex, the cortex is very intelligent and limbic system is not, and yet they work together well. Perhaps there can be a tertiary layer where digital super intelligence lies. And that will be vastly more intelligent than the cortex, but still coexist peacefully and in a benign manner with the cortex and limbic system. That's a super exciting future, both in low level engineering that I saw is being done here and actual possibility in the next few decades. It's important that Neuralink solve this problem sooner rather than later, because the point at which we have digital super intelligence, that's when we pass singularity and things become just very uncertain. It doesn't mean that they're necessarily bad or good, but the point at which we pass singularity, things become extremely unstable. So we want to have a human brain interface before the singularity, or at least not long after it, to minimize existential risk for humanity and consciousness as we know it. But there's a lot of fascinating actual engineering, low level problems here at Neuralink that are quite exciting. What... The problems that we face in Neuralink are material science, electrical engineering, software, mechanical engineering, micro fabrication. It's a bunch of engineering disciplines, essentially. That's what it comes down to is you have to have a tiny electrode. It's so small, it doesn't hurt neurons, but it's got to last for as long as a person. So it's going to last for decades. And then you've got to take that signal, you've got to process that single signal locally at low power. So we need a lot of chip design engineers because we're going to do signal processing and do so in a very power efficient way so that we don't heat your brain up, because the brain is very heat sensitive. And then we've got to take those signals and we're going to do something with them. And then we've got to stimulate the back to... So you could... Bidirectional communication. So if somebody's good at material science, software, mechanical engineering, electrical engineering, chip design, micro fabrication, those are the things we need to work on. We need to be good at material science so that we can have tiny electrodes that last a long time. And it's a tough thing with the material science problem, it's a tough one because you're trying to read and simulate electrically in an electrically active area. Your brain is very electrically active and electrochemically active. So how do you have a coating on the electrode that doesn't dissolve over time and is safe in the brain? This is a very hard problem. And then how do you collect those signals in a way that is most efficient? Because you really just have very tiny amounts of power to process those signals. And then we need to automate the whole thing so it's like Lasik. So it's not... If this is done by neurosurgeons, there's no way it can scale to a large number of people. And it needs to scale to large numbers of people because I think ultimately we want the future to be determined by a large number of humans. Do you think this has a chance to revolutionize surgery period? So neurosurgery and surgery all across? Yeah, for sure. It's got to be like Lasik. Like if Lasik had to be hand done, done by hand by a person, that wouldn't be great. It's done by a robot. And the ophthalmologist kind of just needs to make sure your head's in the right position and then they can just press a button and go. So Smart Summon and soon AutoPark takes on the full beautiful mess of parking lots and their human to human nonverbal communication. I think it has actually the potential to have a profound impact in changing how our civilization looks at AI and robotics because this is the first time human beings, people that don't own a Tesla, may have never seen a Tesla or heard about a Tesla, get to watch hundreds of thousands of cars without a driver. Do you see it this way, almost like an education tool for the world about AI? Do you feel the burden of that, the excitement of that? Or do you just think it's a smart parking feature? I do think you are getting at something important, which is most people have never really seen a robot. And what is the car that is autonomous? It's a four wheel drive. Yeah, it communicates a certain sort of message with everything from safety to the possibility of what AI could bring, its current limitations, its current challenges, what's possible. Do you feel the burden of that, almost like a communicator, educator to the world about AI? We're just really trying to make people's lives easier with autonomy. But now that you mention it, I think it will be an eye opener to people about robotics because they've really never seen a robot before. And there are hundreds of thousands of Teslas, won't be long before there's a million of them that have autonomous capability and the drive without a person in it. And you can see the evolution of the car's personality and thinking with each iteration of autopilot. You can see it's uncertain about this, or it gets... But now it's more certain, now it's moving in a slightly different way. I can tell immediately if a car is on Tesla autopilot because it's got just little nuances of movement. It just moves in a slightly different way. Cars on Tesla autopilot, for example, on the highway are far more precise about being in the center of the lane than a person. If you drive down the highway and look at where cars are parked, you can see that the cars are moving in a slightly different way than a person. If you drive down the highway and look at where cars are, the human driven cars are within their lane. They're like bumper cars. They're moving all over the place. The car on autopilot, dead center. Yeah, so the incredible work that's going into that neural network, it's learning fast. Autonomy is still very, very hard. We don't actually know how hard it is fully, of course. At most problems you tackle, this one included, with an exponential lens, but even with an exponential improvement, things can take longer than expected sometimes. So where does Tesla currently stand on its quest for full autonomy? What's your sense? When can we see successful deployment of full autonomy? Well, on the highway already, the probability of intervention is extremely low. Yes, so for highway autonomy, with the latest release, especially, the probability of needing to intervene is really quite low. In fact, I'd say for stopping to go traffic, it's far safer than a person right now. It's something where the probability of an injury or an impact is much, much lower for autopilot than a person. And then with navigating autopilot, you can change lanes, take highway interchanges, and then we're coming at it from the other direction, which is low speed, full autonomy. And in a way, this is like, how does a person learn to drive? You learn to drive in the parking lot. You know, the first time you learn to drive probably wasn't jumping on Marcus Street in San Francisco. That'd be crazy. You learn to drive in the parking lot, get things right at low speed. And then the missing piece that we're working on is traffic lights and stuff streets. Stuff streets, I would say, actually also relatively easy because you kind of know where the stuff street is, voice caching, geocoding, and then use visualization to see where the line is and stop at the line to eliminate the GPS error. So I'd say there's probably complex traffic lights and very windy roads are the two things that need to get solved. What's harder, perception or control for these problems? So being able to perfectly perceive everything or figuring out a plan once you perceive everything, how to interact with all the agents in the environment, in your sense, from a learning perspective, is perception or action harder in that giant, beautiful, multi-task learning neural network? The hottest thing is having accurate representation of the physical objects in vector space. So taking the visual input, primarily visual input, some sonar and radar, and then creating an accurate vector space representation of the objects around you. Once you have an accurate vector space representation, the planning and control is relatively easier. That is relatively easy. Basically, once you have accurate vector space representation, then you're kind of like a video game. Like cars in Grand Theft Auto or something, they work pretty well. They drive down the road, they don't crash, pretty much, unless you crash into them. That's because they've got an accurate vector space representation of where the cars are, and then they're rendering that as the output. Do you have a sense, high level, that Tesla's on track on being able to achieve full autonomy? So on the highway? Yeah, absolutely. And still no driver's state? Still no driver's state. It's driver sensing. And we have driver sensing with torque on the wheel. That's right. Yeah. By the way, just a quick comment on karaoke. Most people think it's fun, but I also think it is a driving feature. I've been saying for a long time, singing in the car is really good for attention management and vigilance management. That's right. Tesla karaoke is great. It's one of the most fun features of the car. Do you think of a connection between fun and safety sometimes? Yeah, if you can do both at the same time, that's great. I just met with Andrew and wife of Carl Sagan, who directed Cosmos. I'm generally a big fan of Carl Sagan. He's super cool. And they had a great way of putting things. All of our consciousness, all civilization, everything we've ever known and done is on this tiny blue dot. People also get too trapped in there. It's like squabbles amongst humans. Just don't think of the big picture. And they take civilization and our continued existence for granted. They shouldn't do that. Look at the history of civilizations. They rise and they fall. And now civilization is all, it's globalized. And so civilization, I think now rises and falls together. There's not geographic isolation. This is a big risk. Things don't always go up. That should be, that's an important lesson of history. In 1990, at the request of Carl Sagan, the Voyager 1 spacecraft, which is a spacecraft that's reaching out farther than anything human made into space, turned around to take a picture of Earth from 3.7 billion miles away. And as you're talking about the pale blue dot, that picture, the Earth takes up less than a single pixel in that image. Yes. Appearing as a tiny blue dot, as pale blue dot, as Carl Sagan called it. So he spoke about this dot of ours in 1994. And if you could humor me, I was wondering if in the last two minutes you could read the words that he wrote, described in this pale blue dot. Sure. It's funny, the universe appears to be 13.8 billion years old. Earth is like four and a half billion years old. In another half billion years or so, the sun will expand and probably evaporate the oceans and make life impossible on Earth. Which means that if it had taken consciousness 10% longer to evolve, it would never have evolved at all. It's 10% longer. And I wonder how many dead one planet civilizations there are out there in the cosmos that never made it to the other planet and ultimately extinguished themselves or were destroyed by external factors. Probably a few. It's only just possible to travel to Mars, just barely. If G was 10% longer, it would be impossible to travel to Mars. If G was 10% more, it wouldn't work, really. If G was 10% lower, it would be easy. Like you can go single stage from the surface of Mars all the way to the surface of the Earth. Because Mars is 37% Earth's gravity. We need a giant booster to get off Earth. Channeling Carl Sagan. Look again at that dot. That's here. That's home. That's us. On it, everyone you love, everyone you know, everyone you've ever heard of, every human being who ever was, lived out their lives. The aggregate of our joy and suffering, thousands of confident religions, ideologies, and economic doctrines, every hunter and forger, every hero and character, every hero and character every hunter and forger, every hero and coward, every creator and destroyer of civilization, every king and peasant, every young couple in love, every mother and father, hopeful child, inventor and explorer, every teacher of morals, every corrupt politician, every superstar, every supreme leader, every saint and center in the history of our species lived there, on a moat of dust suspended in a sunbeam. Our planet is a lonely speck in the great enveloping cosmic dark. In our obscurity, in all this vastness, there is no hint that help will come from elsewhere to save us from ourselves. The Earth is the only world known so far to harbor life. There is nowhere else, at least in the near future, to which our species could migrate. This is not true. This is false. Mars. And I think Carl Sagan would agree with that. He couldn't even imagine it at that time. So thank you for making the world dream and thank you for talking today. I really appreciate it. Thank you.

https://youtu.be/smK9dgdTl40

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Ray Dalio: Madness, Genius, and the Call for Adventure

You're always at the edge of the set of principles you've developed. You're doing new things always. That's where the intellect is needed. Well and the inspiration. The inspiration is needed to do that, right? Like what are you doing it for? It's the excitement. What is that thing? The adventure, the curiosity, the hunger. If you can be Freud for a second, what's in that subconscious? What's the thing that drives us? I think you can't generalize of us. I think different people are driven by different things. There's not a common one, right? So like if you would take the shapers, I think it is a combination of subliminally, it's a combination of excitement, curiosity. Is there a dark element there? Is there demons? Is there fears? Is there, in your sense, something dark that drives them? Most of the ones that I'm dealing with, I have not seen that. What I really see is, whoo, if I can do that, that would be the most dream. And then the act of creativity and you say, ooh. So excitement is one of the things. Curiosity is a big pull, okay? And then tenacity, okay, to do those things. But definitely emotions are entering into it. Then there's an intellectual component of it too, okay? It may be empathy. Can I have an impact? Can I have an impact? The desire to have an impact, that's an emotional thrill, but it also has empathy. And then you start to see spirituality. By spirituality, I mean the connectedness to the whole. You start to see people operate those things. Those tend to be the things that you see the most of. And I think you're going to shut down this idea completely, but there's a notion that some of these shapers really walk the line between sort of madness and genius. Do you think madness has a role in any of this? Or do you still see Steve Jobs and Elon Musk as fundamentally rational? Yeah, there's a continuum there. What comes to my mind is that genius is often at the edge, in some cases, imaginary genius is at the edge of insanity. And it's almost like a radio that I think, okay, if I can tune it just right, it's playing right. But if I go a little bit too far, it goes off, okay? And so you can see this. Kay Jamison was studying bipolar. What it shows is that that's definitely the case, because when you're going out there, that imagination, whatever, can be near the edge sometimes. Don't have to always be.

https://youtu.be/Rh7tHge2Ymw

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If You Could Live Forever Would You? (Ben Goertzel) | AI Podcast Clips with Lex Fridman

So if you could live forever, would you live forever? Forever. My goal with longevity research is to abolish the plague of involuntary death. I don't think people should die unless they choose to die. If I had to choose forced immortality versus dying, I would choose forced immortality. On the other hand, if I had the choice of immortality with the choice of suicide whenever I felt like it, of course I would take that instead. And that's the more realistic choice. There's no reason you should have forced immortality. You should be able to live until you get sick of living. And that will seem insanely obvious to everyone 50 years from now. People who thought death gives meaning to life so we should all die, they will look at that 50 years from now the way we now look at the Anabaptists in the year 1000 who gave away all their positions, went on top of the mountain for Jesus to come and bring them to the ascension. It's ridiculous that people think death is good because you gain more wisdom as you approach dying. I mean, of course it's true. I mean, I'm 53 and the fact that I might have only a few more decades left, it does make me reflect on things differently. It does give me a deeper understanding of many things. But I mean, so what? You could get a deep understanding in a lot of different ways. Pain is the same way. We're going to abolish pain and that's even more amazing than abolishing death. Once we get a little better at neuroscience, we'll be able to go in and adjust the brain so that pain doesn't hurt anymore. And people will say that's bad because there's so much beauty in overcoming pain and suffering. Well, sure, and there's beauty in overcoming torture too. And some people like to cut themselves, but not many. That's an interesting, but to push back again, this is the Russian side of me, I do romanticize suffering. It's not obvious. I mean, the way you put it, it seems very logical. It's almost absurd to romanticize suffering or pain or death. But to me, a world without suffering, without pain, without death, it's non-obvious. Well, then you can stay in the people zoo with the people torturing each other. No, but what I'm saying is, I guess what I'm trying to say, I don't know if I was presented with that choice what I would choose. Because to me- This is a subtler, it's a subtler matter. And I've posed it in this conversation in an unnecessarily extreme way. So I think the way you should think about it is what if there's a little dial on the side of your head, and you could turn how much pain hurt, turn it down to zero, turn it up to 11, like in spinal tap if it wants, maybe through an actual spinal tap, right? So I mean, would you opt to have that dial there or not? That's the question. The question isn't whether you would turn the pain down to zero all the time. Would you opt to have the dial or not? My guess is that in some dark moment of your life, you would choose to have the dial implanted, and then it would be there. Just to confess a small thing, don't ask me why, but I'm doing this physical challenge currently where I'm doing 680 pushups and pull-ups a day. And my shoulder is currently, as we sit here, in a lot of pain. And I don't know. I would certainly right now, if you gave me a dial, I would turn that sucker to zero as quickly as possible. Good. But I don't, I think the whole point of this journey is, I don't know. Because you're a twisted human being. I'm a twisted. So the question is, am I somehow twisted because I created some kind of narrative for myself so that I can deal with the injustice and the suffering in the world? Or is this actually going to be a source of happiness for me? This is, to an extent, is a research question that humanity will undertake, right? Exactly. But human beings do have a particular biological makeup, which sort of implies a certain probability distribution over motivational systems, right? So I mean, we, and that is there. That is there. Now, the question is, how flexibly can that morph as society and technology change, right? So if we're given that dial, and we're given a society in which, say, we don't have to work for a living, and in which there's an ambient, decentralized, benevolent AI network that will warn us when we're about to hurt ourself, if we're in a different context, can we consistently, with being genuinely and fully human, can we consistently get into a state of consciousness where we just want to keep the pain dial turned all the way down, and yet we're leading very rewarding and fulfilling lives, right? Now, I suspect the answer is yes, we can do that, but I don't know that for certain. Yeah, now, I'm more confident that we could create a non-human AGI system which just didn't need an analog of feeling pain. And I think that AGI system will be fundamentally healthier and more benevolent than human beings. So I think it might or might not be true that humans need a certain element of suffering to be satisfied humans, consistent with the human physiology. If it is true, that's one of the things that makes us fucked and disqualified to be the super AGI, right? I mean, the nature of the human motivational system is that we seem to gravitate towards situations where the best thing in the large scale is not the best thing in the small scale, according to our subjective value system. So we gravitate towards subjective value judgments where to gratify ourselves in the large, we have to ungratify ourselves in the small. And we do that in, you see that in music, there's a theory of music which says the key to musical aesthetics is the surprising fulfillment of expectations. Like you want something that will fulfill the expectations enlisted in the prior part of the music, but in a way with a bit of a twist that surprises you. And I mean, that's true not only in outdoor music like my own or that of Zappa or Steve Vai or Buckethead or Christoph Penderecki or something, it's even there in Mozart or something. It's not there in elevator music too much, but that's why it's boring, right? But wrapped up in there is, we want to hurt a little bit so that we can feel the pain go away. Like we want to be a little confused by what's coming next. So then when the thing that comes next actually makes sense, it's so satisfying, right? That's the surprising fulfillment of expectations, is that what you said? Yeah, yeah, yeah. So beautifully put. We've been skirting around a little bit, but if I were to ask you the most ridiculous big question of what is the meaning of life, what would your answer be? Three values, joy, growth, and choice. I think you need joy, I mean that's the basis of everything, if you want the number one value. On the other hand, I'm unsatisfied with a static joy that doesn't progress, perhaps because of some elemental element of human perversity. But the idea of something that grows and becomes more and more and better and better in some sense appeals to me. But I also sort of like the idea of individuality, that as a distinct system I have some agency, so there's some nexus of causality within this system, rather than the causality being wholly evenly distributed over the joyous growing mass. So you start with joy, growth, and choice as three basic values. Those three things could continue indefinitely. That's something that could last forever. Is there some aspect of something you called, which I like, super longevity that you find exciting, research-wise, is there ideas in that space? I think, yeah, in terms of the meaning of life, this really ties into that. Because for us as humans, probably the way to get the most joy, growth, and choice is transhumanism and to go beyond the human form that we have right now. And I think human body is great, and by no means do any of us maximize the potential for joy, growth, and choice imminent in our human bodies. On the other hand, it's clear that other configurations of matter could manifest even greater amounts of joy, growth, and choice than humans do, maybe even finding ways to go beyond the realm of matter as we understand it right now. So I think in a practical sense, much of the meaning I see in human life is to create something better than humans and go beyond human life. But certainly that's not all of it for me in a practical sense. I have four kids and a granddaughter and many friends and parents and family and just enjoying everyday human social existence. But we can do even better. Yeah, yeah. I mean, I love, I've always, when I could live near nature, I spend a bunch of time out in nature in the forest and on the water every day and so forth. So I mean, enjoying the pleasant moment is part of it, but the growth and choice aspect are severely limited by our human biology. In particular, dying seems to inhibit your potential for personal growth considerably as far as we know. I mean, there's some element of life after death perhaps, but even if there is, why not also continue going in this biological realm, right? In super longevity, I mean, we haven't yet cured aging. We haven't yet cured death. Certainly there's very interesting progress all around. I mean, CRISPR and gene editing can be an incredible tool. And I mean, right now, stem cells could potentially prolong life a lot. Like if you got stem cell injections of just stem cells for every tissue of your body injected into every tissue, and you can just have replacement of your old cells with new cells produced by those stem cells, I mean, that could be highly impactful at prolonging life. Now we just need slightly better technology for having them grow, right? So using machine learning to guide procedures for stem cell differentiation and trans differentiation, it's kind of nitty gritty, but I mean, that's quite interesting. So I think there's a lot of different things being done to help with prolongation of human life, but we could do a lot better. So for example, the extracellular matrix, which is the bunch of proteins in between the cells in your body, they get stiffer and stiffer as you get older. And the extracellular matrix transmits information both electrically, mechanically, and to some extent biophotonically. So there's all this transmission through the parts of the body, but the stiffer the extracellular matrix gets, the less the transmission happens, which makes your body get worse coordinated between the different organs as you get older. So my friend Christian Schaffmeister at my alumnus organization, my alma mater, the great Temple University, Christian Schaffmeister has a potential solution to this, where he has these novel molecules called spiral ligamers, which are like polymers that are not organic. They're specially designed polymers so that you can algorithmically predict exactly how they'll fold very simply. So he designed the molecular scissors that have spiral ligamers that you could eat and would then cut through all the glucosamine and other cross-linked proteins in your extracellular matrix, right? But to make that technology really work and be mature is several years of work. As far as I know, no one's funding it at the moment. So there's so many different ways that technology could be used to prolong longevity. What we really need, we need an integrated database of all biological knowledge about human beings and model organisms, like hopefully a massively distributed open-cog bioatom space, but it can exist in other forms too. We need that data to be opened up in a suitably privacy-protecting way. We need massive funding into machine learning, AGI, proto-AGI statistical research aimed at solving biology, both molecular biology and human biology, based on this massive, massive dataset, right? And then we need regulators not to stop people from trying radical therapies on themselves if they so wish to, as well as better cloud-based platforms for automated experimentation on microorganisms, flies and mice and so forth. We could do all this. You look, after the last financial crisis, Obama, who I generally like pretty well, but he gave $4 trillion to large banks and insurance companies. Now in this COVID crisis, trillions are being spent to help everyday people and small businesses. In the end, we'll probably will find many more trillions are being given to large banks and insurance companies anyway. Could the world put $10 trillion into making a massive holistic bio-AI and bio-simulation and experimental biology infrastructure? We could. We could put $10 trillion into that without even screwing us up too badly, just as in the end COVID and the last financial crisis won't screw up the world economy so badly. We're not putting $10 trillion into that. Instead, all this research is siloed inside a few big companies and government agencies. Most of the data that comes from our individual bodies, personally, that could feed this AI to solve aging and death, most of that data is sitting in some hospital's database doing nothing, right?

https://youtu.be/gaMz3JGuA5E

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Daphne Koller: Biomedicine and Machine Learning | Lex Fridman Podcast #93

The following is a conversation with Daphne Koller, a professor of computer science at Stanford University, a co-founder of Coursera with Andrew Ng, and founder and CEO of In-Citro, a company at the intersection of machine learning and biomedicine. We're now in the exciting early days of using the data-driven methods of machine learning to help discover and develop new drugs and treatments that scale. Daphne and In-Citro are leading the way on this with breakthroughs that may ripple through all fields of medicine, including ones most critical for helping with the current coronavirus pandemic. This conversation was recorded before the COVID-19 outbreak. For everyone feeling the medical, psychological, and financial burden of this crisis, I'm sending love your way. Stay strong, we're in this together, we'll beat this thing. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcasts, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App allows you to send and receive money digitally, peer-to-peer, and security in all digital transactions is very important, let me mention the PCI data security standard that Cash App is compliant with. I'm a big fan of standards, but I'm also a big fan of standards for safety and security. PCI DSS is a good example of that, where a bunch of competitors got together and agreed that there needs to be a global standard around the security of transactions. Now we just need to do the same for autonomous vehicles and AI systems in general. So again, if you get Cash App from the App Store or Google Play, and use the code LEXPODCAST, you get $10, and Cash App will also donate $10 to FIRST, a foundation that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Daphne Koller. So you co-founded Coursera and made a huge impact in the global education of AI, and after five years, in August 2016, wrote a blog post saying that you're stepping away and wrote, quote, it is time for me to turn to another critical challenge, the development of machine learning and its applications to improving human health. So let me ask two far out philosophical questions. One, do you think we will one day find cures for all major diseases known today? And two, do you think we will one day figure out a way to extend the human lifespan, perhaps to the point of immortality? So one day is a very long time, and I don't like to make predictions of the type we will never be able to do X because I think that's a, you know, that's a smacks of hubris. It seems that never in the entire eternity of human existence will we be able to solve a problem. That being said, curing disease is very hard because oftentimes by the time you discover the disease, a lot of damage has already been done. And so to assume that we would be able to cure disease at that stage assumes that we would come up with ways of basically regenerating entire parts of the human body in the way that actually returns it to its original state. And that's a very challenging problem. We have cured very few diseases. We've been able to provide treatment for an increasingly large number, but the number of things that you could actually define to be cures is actually not that large. So I think that there's a lot of work that would need to happen before one could legitimately say that we have cured even a reasonable number, far less all diseases. On the scale of zero to 100, where are we in understanding the fundamental mechanisms of all of major diseases? What's your sense? So from the computer science perspective that you've entered the world of health, how far along are we? I think it depends on which disease. I mean, there are ones where I would say we're maybe not quite at 100 because biology is really complicated and there's always new things that we uncover that people didn't even realize existed. But I would say there's diseases where we might be in the 70s or 80s. And then there's diseases in which I would say probably the majority where we're really close to zero. With Alzheimer's and schizophrenia and type 2 diabetes fall closer to zero or to the 80? I think Alzheimer's is probably closer to zero than to 80. There are hypotheses, but I don't think those hypotheses have as of yet been sufficiently validated that we believe them to be true. And there's an increasing number of people who believe that the traditional hypotheses might not really explain what's going on. I would also say that Alzheimer's and schizophrenia and even type 2 diabetes are not really one disease. They're almost certainly a heterogeneous collection of mechanisms that manifest in clinically similar ways. So in the same way that we now understand that breast cancer is really not one disease, it is a multitude of cellular mechanisms, all of which ultimately translate to uncontrolled proliferation, but it's not one disease, the same is almost undoubtedly true for those other diseases as well. And that understanding that needs to precede any understanding of the specific mechanisms of any of those other diseases. Now in schizophrenia, I would say we're almost certainly closer to zero than to anything else. Type 2 diabetes is a bit of a mix. There are clear mechanisms that are implicated that I think have been validated that have to do with insulin resistance and such, but there's almost certainly there as well, many mechanisms that we have not yet understood. So you've also thought and worked a little bit on the longevity side. Do you see the disease and longevity as overlapping completely, partially, or not at all as efforts? Those mechanisms are certainly overlapping. There's a well-known phenomenon that says that for most diseases, other than childhood diseases, the risk for contracting that disease increases exponentially year on year, every year from the time you're about 40. So obviously there's a connection between those two things. That's not to say that they're identical. There's clearly aging that happens that is not really associated with any specific disease. And there's also diseases and mechanisms of disease that are not specifically related to aging. So I think overlap is where we're at. Okay. It is a little unfortunate that we get older and it seems that there's some correlation with the occurrence of diseases or the fact that we get older and both are quite sad. Well, I mean, there's processes that happen as cells age that I think are contributing to disease. Some of those have to do with DNA damage that accumulates as cells divide where the repair mechanisms don't fully correct for those. There are accumulations of proteins that are misfolded and potentially aggregate and those two contribute to disease and contribute to inflammation. There's a multitude of mechanisms that have been uncovered that are sort of wear and tear at the cellular level that contribute to disease processes. And I'm sure there's many that we don't yet understand. On a small tangent, perhaps philosophical, the fact that things get older and the fact that things die is a very powerful feature for the growth of new things. It's a kind of learning mechanism. So it's both tragic and beautiful. So do you... So in trying to fight disease and trying to fight aging, do you think about sort of the useful fact of our mortality? Or would you... Like if you were, could be immortal, would you choose to be immortal? Again, I think immortal is a very long time and I don't know that that would necessarily be something that I would want to aspire to. But I think all of us aspire to an increased health span, I would say, which is an increased amount of time where you're healthy and active and feel as you did when you were 20. We're nowhere close to that. People deteriorate physically and mentally over time and that is a very sad phenomenon. So I think a wonderful aspiration would be if we could all live to, you know, the biblical 120 maybe in perfect health. In high quality of life. High quality of life. I think that would be an amazing goal for us to achieve as a society now, is the right age, 120 or 100 or 150. I think that's up for debate, but I think an increased health span is a really worthy goal. And anyway, in the grand time of the age of the universe, it's all pretty short. So from the perspective, you've done obviously a lot of incredible work in machine learning. So what role do you think data and machine learning play in this goal of trying to understand diseases and trying to eradicate diseases? Up until now, I don't think it's played very much of a significant role because largely the data sets that one really needed to enable a powerful machine learning method, those data sets haven't really existed. There's been dribs and drabs and some interesting machine learning that has been applied. I would say machine learning slash data science. But the last few years are starting to change that. So we now see an increase in some large data sets, but equally importantly, an increase in technologies that are able to produce data at scale. It's not typically the case that people have deliberately, proactively used those tools for the purpose of generating data for machine learning. To the extent that those techniques have been used for data production, they've been used for data production to drive scientific discovery, to drive scientific research, to drive scientific discovery. And the machine learning came as a sort of byproduct, second stage of, oh, now we have a data set, let's do machine learning on that rather than a more simplistic data analysis method. But what we are doing at In-Sitro is actually flipping that around and saying, here's this incredible repertoire of methods that bioengineers, cell biologists have come up with. Let's see if we can put them together in brand new ways with the goal of creating data sets that machine learning can really be applied on productively to create powerful predictive models that can help us address fundamental problems in human health. So really focus, make data the primary focus and the primary goal and use the mechanisms of biology and chemistry to create the kinds of data set that could allow machine learning to benefit the most. I wouldn't put it in those terms because that says that data is the end goal. Data is the means. So for us, the end goal is helping address challenges in human health. And the method that we've elected to do that is to apply machine learning to build predictive models. And machine learning, in my opinion, can only be really successfully applied, especially the more powerful models, if you give it data that is of sufficient scale and sufficient quality. So how do you create those data sets so as to drive the ability to generate predictive models, which subsequently help improve human health? So before we dive into the details of that, let me take a step back and ask, when and where was your interest in human health born? Are there moments, events, perhaps, if I may ask, tragedies in your own life that catalyzes passion, or was it the broader desire to help humankind? So I would say it's a bit of both. So on, I mean, my interest in human health actually dates back to the early 2000s when a lot of my peers in machine learning and I were using data sets that, frankly, were not very inspiring. Some of us old-timers still remember the quote-unquote 20 news groups data set, where this was literally a bunch of text from 20 news groups, a concept that doesn't really even exist anymore. And the question was, can you classify which news group a particular bag of words came from? And it wasn't very interesting. The data sets at the time on the biology side were much more interesting, both from a technical and also from an aspirational perspective. They were still pretty small, but they were better than 20 news groups. And so I started out, I think, just by wanting to do something that was more, I don't know, societally useful and technically interesting. And then over time became more and more interested in the biology and the human health aspects for themselves. And began to work even sometimes on papers that were just in biology without having a significant machine learning component. I think my interest in drug discovery is partly due to an incident I had with when my father sadly passed away about 12 years ago. He had an autoimmune disease that settled in his lungs. And the doctor's basics said, well, there's only one thing that we can do, which is give him prednisone. At some point, I remember a doctor even came and said, hey, let's do a lung biopsy to figure out which autoimmune disease he has. And I said, would that be helpful? Would that change treatment? He said, no, there's only prednisone. That's the only thing we can give him. And I had friends who were rheumatologists who said the FDA would never approve prednisone today because the ratio of side effects to benefit is probably not large enough. Today, we're in a state where there's probably four or five, maybe even more, well, it depends for which autoimmune disease, but there are multiple drugs that can help people with autoimmune disease, many of which didn't exist 12 years ago. And I think we're at a golden time in some ways in drug discovery, where there's the ability to create drugs that are much more safe and much more effective than we've ever been able to before. And what's lacking is enough understanding of biology and mechanism to know where to aim that engine. And I think that's where machine learning can help. So in 2018, you started and now lead a company in Citro, which is, like you mentioned, perhaps the focus is drug discovery and the utilization of machine learning for drug discovery. So you mentioned that, quote, we're really interested in creating what you might call a disease in a dish model, disease in a dish models, places where diseases are complex, where we really haven't had a good model system, where typical animal models that have been used for years, including testing on mice, just aren't very effective. So can you try to describe what is an animal model and what is a disease in a dish model? Sure. So an animal model for disease is where you create effectively, it's what it sounds like, it's oftentimes a mouse, where we have introduced some external perturbation that creates the disease. And then we cure that disease. And the hope is that by doing that, we will cure a similar disease in the human. The problem is that oftentimes the way in which we generate the disease in the animal has nothing to do with how that disease actually comes about in a human. It's what you might think of as a copy of the phenotype, a copy of the clinical outcome, but the mechanisms are quite different. And so curing the disease in the animal, which in most cases doesn't happen naturally, mice don't get Alzheimer's, they don't get diabetes, they don't get atherosclerosis, they don't get autism or schizophrenia, those cures don't translate over to what happens in the human. And that's where most drugs fails just because the findings that we had in the mouse don't translate to a human. The disease in the dish models is a fairly new approach. It's been enabled by technologies that have not existed for more than five to 10 years. So for instance, the ability for us to take a cell from any one of us, you or me, revert that, say, skin cell to what's called stem cell status, which is what's called a pluripotent cell that can then be differentiated into different types of cells. So from that pluripotent cell, one can create a Lex neuron or a Lex cardiomyocyte or a Lex hepatocyte that has your genetics, but that right cell type. And so if there's a genetic burden of disease that would manifest in that particular cell, it would be a very difficult thing to do. But if there's a genetic burden of disease that would manifest in that particular cell type, you might be able to see it by looking at those cells and saying, oh, that's what potentially sick cells look like versus healthy cells. And then explore what kind of interventions might revert the unhealthy looking cell to a healthy cell. Now, of course, curing is still potentially a translatability gap, but at least for diseases that are driven, say, by human genetics and where the human genetics is what drives the cellular phenotype, there is some reason to hope that if we revert those cells in which the disease begins and where the disease is driven by genetics and we can revert that cell back to a healthy state, maybe that will help also revert the more global clinical phenotypes. That's really what we're hoping to do. That step, that backward step, I was reading about it, the Yamanaka factor. Yes. So like that reverse step back to stem cells. Yes. It seems like magic. It is. Honestly, before that happened, I think very few people would have predicted that to be possible. It's amazing. Can you maybe elaborate, is it actually possible? So this result was maybe, I don't know how many years ago, maybe 10 years ago was first demonstrated, something like that. How hard is this? Like how noisy is this backward step? It seems quite incredible and cool. It is incredible and cool. It was much more, I think, finicky and bespoke at the early stages when the discovery was first made. But at this point, it's become almost industrialized. There are what's called contract research organizations, vendors, that will take a sample from a human and revert it back to stem cell status and it works a very good fraction of the time. Now, there are people who will ask, I think, good questions. Is this really, truly a stem cell or does it remember certain aspects of changes that were made in the human beyond the genetics? It's passed as a skin cell, yeah. It's passed as a skin cell or it's passed in terms of exposures to different environmental factors and so on. So I think the consensus right now is that these are not always perfect and there is little bits and pieces of memory sometimes, but by and large, these are actually pretty good. So one of the key things, well, maybe you can correct me, but one of the useful things for machine learning is size, scale of data. How easy it is to do these kinds of reversals to stem cells and then does using a dish models at scale? Is that a huge challenge or not? So the reversal is not, as of this point, something that can be done at the scale of tens of thousands or hundreds of thousands. I think total number of stem cells or IPS cells that are what's called induced pluripotent stem cells in the world, I think, is somewhere between five and ten thousand last I looked. Now, again, that might not count things that exist in this or that academic center, and they may add up to a bit more, but that's about the range. So it's not something that you could, at this point, generate IPS cells from a million people, but maybe you don't need to because maybe that background is enough because it can also be now perturbed in different ways. And some people have done really interesting experiments in, for instance, taking cells from a healthy human and then introducing a mutation into it using one of the other miracle technologies that's emerged the last decade, which is CRISPR gene editing, and introduced a mutation that is known to be pathogenic. And so you can now look at the healthy cells and unhealthy cells, the one with the mutation, and do a one-on-one comparison comparison where everything else is held constant. And so you could really start to understand specifically what the mutation does at the cellular level. So the IPS cells are a great starting point, and obviously more diversity is better because you also want to capture ethnic background and how that affects things. But maybe you don't need one from every single patient with every single type of disease because we have other tools at our disposal. Well, how much difference is there between people, I mentioned ethnic background, in terms of IPS cells? So we're all, like, it seems like these magical cells that can do, to create anything between different populations, different people, is there a lot of variability between stem cells? Well, first of all, there's the variability that's driven simply by the fact that genetically we're different. So a stem cell that's derived from my genotype is gonna be different from a stem cell that's derived from your genotype. There's also some differences that have more to do with, for whatever reason, some people's stem cells differentiate better than other people's stem cells. We don't entirely understand why, so there's certainly some differences there as well. But the fundamental difference, and the one that we really care about and is a positive, is that the fact that the genetics are different and therefore recapitulate my disease burden versus your disease burden. What's the disease burden? Well, a disease burden is just, if you think, I mean, it's not a well-defined mathematical term, although there are mathematical formulations of it. If you think about the fact that some of us are more likely to get a certain disease than others because we have more variations in our genome that are causative of the disease, maybe fewer that are protective of the disease. People have quantified that using what are called polygenic risk scores, which look at all of the variations in an individual person's genome and add them all up in terms of how much risk they confer for a particular disease. And then they've put people on a spectrum of their disease risk. And for certain diseases where we've been sufficiently powered to really understand the connection between the many, many small variations that give rise to an increased disease risk, there are some pretty significant differences in terms of the risk between the people, say, at the highest decile of this polygenic risk score and the people at the lowest decile. Sometimes those differences are a factor of 10 or 12 higher. So there's definitely a lot that our genetics contributes to disease risk, even if it's not by any stretch the full explanation. And from a machine learning perspective, there's signal there. There is definitely signal in the genetics. And there's even more signal, we believe, in looking at the cells that are derived from those different genetics. Because in principle, you could say all the signal is there at the genetics level, so we don't need to look at the cells. But our understanding of the biology is so limited at this point, then seeing what actually happens at the cellular level is a heck of a lot closer to the human clinical outcome than looking at the genetics directly. And so we can learn a lot more from it than we could by looking at genetics alone. So just to get a sense, I don't know if it's easy to do, but what kind of data is useful in this disease in a dish model? What's the source of raw data information? And also, from my outsider's perspective, biology and cells are squishy things. And then- They are. How do you connect- They're literally squishy things. How do you connect the computer to that? Which sensory mechanisms, I guess? So that's another one of those revolutions that have happened in the last 10 years, in that our ability to measure cells very quantitatively has also dramatically increased. So back when I started doing biology in the late 90s, early 2000s, that was the initial era where we started to measure biology in really quantitative ways using things like microarrays, where you would measure in a single experiment the activity level, what's called expression level, of every gene in the genome in that sample. And that ability is what actually allowed us to even understand that there are molecular subtypes of diseases like cancer, where up until that point, it's like, oh, you have breast cancer. But then when we looked at the molecular data, it was clear that there's different subtypes of breast cancer that at the level of gene activity look completely different to each other. So that was the beginning of this process. Now we have the ability to measure individual cells in terms of their gene activity using what's called single-cell RNA sequencing, which basically sequences the RNA, which is that activity level of different genes for every gene in a genome. And you could do that at single-cell level. So that's an incredibly powerful way of measuring cells. I mean, you literally count the number of transcripts. So it really turns that squishy thing into something that's digital. Another tremendous data source that's emerged in the last few years is microscopy, and specifically even super-resolution microscopy, where you could use digital reconstruction to look at subcellular structures, sometimes even things that are below the diffraction limit of light by doing a sophisticated reconstruction. And again, that gives you tremendous amounts of information at the subcellular level. There's now more and more ways that amazing scientists out there are developing for getting new types of information from even single cells. And so that is a way of turning those squishy things into digital data. Into beautiful data sets. So that data set then with machine learning tools allows you to maybe understand the developmental, like the mechanism of a particular disease. And if it's possible to sort of at a high level describe how does that help lead to drug discovery that can help prevent, reverse that mechanism? So I think there's different ways in which this data could potentially be used. Some people use it for scientific discovery and say, oh look, we see this phenotype at the cellular level, so let's try and work our way backwards and think which genes might be involved in pathways that give rise to that. So that's a very sort of analytical method to sort of work our way backwards using our understanding of known biology. Some people use it in a somewhat more, you know, sort of forward. If that was backward, this would be forward, which is to say, okay, if I can perturb this gene, does it show a phenotype that is similar to what I see in disease patients? And so maybe that gene is actually causal of the disease. So that's a different way. And then there's what we do, which is basically to take that very large collection of data and use machine learning to uncover the patterns that emerge from it. So for instance, what are those subtypes that might be similar at the human clinical outcome, but quite distinct when you look at the molecular data? And then if we can identify such a subtype, are there interventions that if I apply it to cells that come from this subtype of the disease and you apply that intervention, it could be a drug or it could be a CRISPR gene intervention, does it revert the disease state to something that looks more like normal, happy, healthy cells? And so hopefully if you see that, that gives you a certain hope that that intervention will also have a meaningful clinical benefit to people. And there's obviously a bunch of things that you would want to do after that to validate that, but it's a very different and much less hypothesis driven way of uncovering new potential interventions and might give rise to things that are not the same things that everyone else is already looking at. That's, I don't know, I'm just like to psychoanalyze my own feeling about our discussion currently. It's so exciting to talk about fundamentally, well, something that's been turned into a machine learning problem and that's has can have so much real world impact. That's how I feel too. That's kind of exciting because I'm so, most of my days spent with data sets that I guess closer to the news groups. So this is a kind of, it just feels good to talk about. In fact, I don't almost don't want to talk to you about machine learning. I want to talk about the fundamentals of the data set, which is an exciting place to be. I agree with you. It's what gets me up in the morning. It's also what attracts a lot of the people who work at In-sitro to In-sitro because I think all of the, certainly all of our machine learning people are outstanding and could go get a job, you know, selling ads online or doing e-commerce or even self-driving cars. But I think they would want, they come to us because they want to work on something that has more of an aspirational nature and can really benefit humanity. What would these, with these approaches, what do you hope, what kind of diseases can be helped? We mentioned Alzheimer's, schizophrenia, type 2 diabetes. Can you just describe the various kinds of diseases that this approach can help? Well, we don't know. And I try and be very cautious about making promises about some things. Oh, we will cure X. People make that promise. And I think it's, I try to first deliver and then promise as opposed to the other way around. There are characteristics of a disease that make it more likely that this type of approach can potentially be helpful. So, for instance, diseases that have a very strong genetic basis are ones that are more likely to manifest in a stem cell derived model. We would want the cellular models to be relatively reproducible and robust so that you could actually get enough of those cells in a way that isn't very highly variable and noisy. You would want the disease to be relatively contained in one or a small number of cell types that you could actually create in an in vitro, in a dish setting. Whereas if it's something that's really broad and systemic and involves multiple cells that are in very distal parts of your body, putting that all in a dish is really challenging. So we want to focus on the ones that are most likely to be successful today with the hope, I think, that really smart bioengineers out there are developing better and better systems all the time so that diseases that might not be tractable today might be tractable in three years. So, for instance, five years ago, these stem cell derived models didn't really exist. People were doing most of the work in cancer cells, and cancer cells are very, very poor models of most human biology because they're, A, they were cancer to begin with, and B, as you passage them and they proliferate in a dish, they become, because of the genomic instability, even less similar to human biology. Now we have these stem cell derived models. We have the capability to reasonably robustly, not quite at the right scale yet, but close, to derive what's called organoids, which are these teeny little sort of multicellular organ, sort of models of an organ system. So there's cerebral organoids and liver organoids and kidney organoids and gut organoids. Yeah, brain organoids is possibly the coolest thing I've ever seen. Is that not like the coolest thing? Yeah. And then I think on the horizon, we're starting to see things like connecting these organoids to each other so that you could actually start, and there's some really cool papers that start to do that, where you can actually start to say, okay, can we do multi-organ system stuff? There's many challenges to that. It's not easy by any stretch, but it might, I'm sure people will figure it out, and in three years or five years, there will be disease models that we could make for things that we can't make today. Yeah, and this conversation would seem almost outdated with the kind of scale that could be achieved in like three years. I hope so. That's the hope. That would be so cool. So you've co-founded Coursera with Andrew Ng, and were part of the whole MOOC revolution. So to jump topics a little bit, can you maybe tell the origin story of the history, the origin story of MOOCs, of Coursera, and in general, your teaching to huge audiences on a very impactful topic of AI? Yeah. In general. So I think the origin story of MOOCs emanates from a number of efforts that occurred at Stanford University around the late 2000s, where different individuals within Stanford, myself included, were getting really excited about the opportunities of using online technologies as a way of achieving both improved quality of teaching and also improved scale. And so Andrew, for instance, led the Stanford Engineering Everywhere, which was sort of an attempt to take 10 Stanford courses and put them online, just as video lectures. I led an effort within Stanford to take some of the courses and really create a very different teaching model that broke those up into smaller units and had some of those embedded interactions and so on, which got a lot of support from university leaders because they felt like it was potentially a way of improving the quality of instruction at Stanford by moving to what's now called the flipped classroom model. And so those efforts eventually sort of started to interplay with each other and created a tremendous sense of excitement and energy within the Stanford community about the potential of online teaching and led in the fall of 2011 to the launch of the first Stanford MOOCs. By the way, MOOCs, it's probably impossible that people don't know, but it's, I guess, massive... Open online courses. Open online courses. We did not come up with the acronym. I'm not particularly fond of the acronym, but it is what it is. It is what it is. Big bang is not a great term for the start of the universe, but it is what it is. Probably so. So anyway, those courses launched in the fall of 2011, and there were, within a matter of weeks, with no real publicity campaign, just a New York Times article that went viral, about 100,000 students or more in each of those courses. And I remember this conversation that Andrew and I had, which was like, wow, there's this real need here. And I think we both felt like, sure, we were accomplished academics and we could go back and go back to our labs, write more papers. But if we did that, then this wouldn't happen. And it seemed too important not to happen. And so we spent a fair bit of time debating, do we want to do this as a Stanford effort, kind of building on what we'd started? Do we want to do this as a for-profit company? Do we want to do this as a non-profit? And we decided ultimately to do it as we did with Coursera. And so, you know, we started really operating as a company at the beginning of 2012. And the rest is history. And the rest is history. And the rest is history. But was that really surprising to you? How did you at that time and at this time make sense of this need for sort of global education you mentioned? That you felt that, wow, the popularity indicates that there's a hunger for sort of globalization of learning. I think there is a hunger for learning that, you know, globalization is part of it, but I think it's just a hunger for learning. The world has changed in the last 50 years. It used to be that you finished college, you got a job. By and large, the skills that you learned in college were pretty much what got you through the rest of your job history. And yeah, you learned some stuff, but it wasn't a dramatic change. Today, we're in a world where the skills that you need for a lot of jobs, they didn't even exist when you went to college. And the jobs and many of the jobs that exist when you went to college don't even exist today or are dying. So part of that is due to AI, but not only. And we need to find a way of keeping people, giving people access to the skills that they need today. And I think that's really what's driving a lot of this hunger. So I think if we even take a step back, for you, all of this started in trying to think of new ways to teach or new ways to sort of organize the material and present the material in a way that would help the education process, the pedagogy. Yeah. So what have you learned about effective education from this process of playing, of experimenting with different ideas? So we learned a number of things, some of which I think could translate back and have translated back effectively to how people teach on campus, and some of which I think are more specific to people who learn online, more sort of people who learn as part of their daily life. So we learned, for instance, very quickly that short is better. So people who are especially in the workforce can't do a 15-week semester-long course. They just can't fit that into their lives. Can you describe the shortness of what? Both. Every aspect of the little lecture is short, the course is short. Both. We started out, the first online education efforts were actually MIT's OpenCourseWare initiatives, and that was recording of classroom lectures. Hour and a half or something like that, yeah. And that didn't really work very well. I mean, some people benefit, I mean, of course they did, but it's not really a very palatable experience for someone who has a job and, you know, three kids, and they need to run errands and such. They can't fit 15 weeks into their life, and the hour and a half is really hard. So we learned very quickly, I mean, we started out with short video modules, and over time we made them shorter because we realized that 15 minutes was still too long if you want to fit in when you're waiting in line for your kid's doctor's appointment. It's better if it's five to seven. We learned that 15-week courses don't work, and you really want to break this up into shorter units so that there is a natural completion point. It gives people a sense of they're really close to finishing something meaningful. They can always come back and take part two and part three. We also learned that compressing the content works really well because if some people, that pace works well, and for others, they can always rewind and watch again. And so people have the ability to then learn at their own pace. And so that flexibility, the brevity and the flexibility are both things that we found to be very important. We learned that engagement during the content is important, and the quicker you give people feedback, the more likely they are to be engaged. Hence, the introduction of these, which we actually was an intuition that I had going in and was then validated using data, that introducing some of these sort of little micro quizzes into the lectures really helps. Self-graded, automatically graded assessments really help too, because it gives people feedback. See, there you are. So all of these are valuable. And then we learned a bunch of other things, too. We did some really interesting experiments, for instance, on non-gender bias. And how having a female role model as an instructor can change the balance of men to women, in terms of, especially in STEM courses. And you could do that online by doing A-B testing in ways that would be really difficult to do on campus. Oh, that's exciting. But so the shortness, the compression, I mean, that's actually, so that probably is true for all good editing, is always just compressing the content, making it shorter. So that puts a lot of burden on the creator of the instructor and the creator of the educational content. Probably most lectures at MIT or Stanford could be five times shorter if the preparation was put enough. So maybe people might disagree with that. But the crispness, the clarity that a lot of the MOOCs like Coursera delivers, how much effort does that take? So first of all, let me say that it's not clear that that crispness would work as effectively in a face-to-face setting, because people need time to absorb the material. And so you need to at least pause and give people a chance to reflect and maybe practice. And that's what MOOCs do, is that they give you these chunks of content and then ask you to practice with it. And that's where I think some of the newer pedagogy that people are adopting in face-to-face teaching that have to do with interactive learning and such can be really helpful. But both those approaches, whether you're doing that type of methodology in online teaching or in that flipped classroom interactive teaching... What's, sorry to pause, what's flipped classroom? Flipped classroom is a way in which online content is used to supplement face-to-face teaching, where people watch the videos perhaps and do some of the exercises before coming to class. And then when they come to class, it's actually to do much deeper problem solving, oftentimes in a group. But any one of those different pedagogies that are beyond just standing there and droning on in front of the classroom for an hour and 15 minutes require a heck of a lot more preparation. And so it's one of the challenges I think that people have, that we had when trying to convince instructors to teach on Coursera. And it's part of the challenges that pedagogy experts on campus have in trying to get faculty to teach differently, is that it's actually harder to teach that way than it is to stand there and drone. Do you think MOOCs will replace in-person education or become the majority of in-person of education of the way people learn in the future? Again, the future could be very far away, but where's the trend going, do you think? So I think it's a nuanced and complicated answer. I don't think MOOCs will replace face-to-face teaching. I think learning is in many cases a social experience. And even at Coursera, we had people who naturally formed study groups, even when they didn't have to, to just come and talk to each other. And we found that that actually benefited their learning in very important ways. So there was more success among learners who had those study groups than among ones who didn't. So I don't think it's just going to, oh, we're all going to just suddenly learn online with a computer and no one else, in the same way that recorded music has not replaced live concerts. But I do think that especially when you are thinking about continuing education, the stuff that people get when their traditional, whatever, high school, college education is done, and they yet have to maintain their level of expertise and skills in a rapidly changing world, I think people will consume more and more educational content in this online format, because going back to school for formal education is not an option for most people. Briefly, it might be a difficult question to ask, but there's a lot of people fascinated by artificial intelligence, by machine learning, by deep learning. Is there a recommendation for the next year or for a lifelong journey? If somebody is interested in this, how do they begin? How do they enter that learning journey? I think the important thing is first to just get started. And there's plenty of online content that one can get for both the core foundations of mathematics and statistics and programming, and then from there to machine learning. I would encourage people not to skip too quickly past the foundations, because I find that there's a lot of people who learn machine learning, whether it's online or on campus, without getting those foundations. And they basically just turn the crank on existing models in ways that, A, don't allow for a lot of innovation and adjustment to the problem at hand, but also, B, are sometimes just wrong, and they don't even realize that their application is wrong, because there's artifacts that they haven't fully understood. So I think the foundations, machine learning is an important step. And then actually start solving problems. Try and find someone to solve them with, because especially at the beginning, it's useful to have someone to bounce ideas off and fix mistakes that you make, and you can fix mistakes that they make. But then just find practical problems, whether it's in your workplace or if you don't have that, Kaggle competitions or such are a really great place to find interesting problems and just practice. Practice. This is perhaps a bit of a romanticized question, but what idea in deep learning have you found in your journey the most beautiful or surprising or interesting? Perhaps not just deep learning, but AI in general, statistics? I'm going to answer with two things. One would be the foundational concept of end-to-end training, which is that you start from the raw data and you train something that is not a single piece, but rather towards the actual goal that you're looking to... So from the raw data to the outcome, and no details in between. Well, not no details, but the fact that you could certainly introduce building blocks that were trained towards other tasks. I'm actually coming to that in my second half of the answer. But it doesn't have to be like a single monolithic blob in the middle. Actually, I think that's not ideal, but rather the fact that at the end of the day, you can actually train something that goes all the way from the beginning to the end. And the other one that I find really compelling is the notion of learning a representation that in its turn, even if it was trained to another task, can potentially be used as a much more rapid starting point to solving a different task. And that's, I think, reminiscent of what makes people successful learners. It's something that is relatively new in the machine learning space. I think it's underutilized, even relative to today's capabilities, but more and more of how do we learn reusable representation. So end-to-end and transfer learning. Is it surprising to you that neural networks are able to, in many cases, do these things? Is it maybe taking back to when you first would dive deep into neural networks or in general, even today, is it surprising that neural networks work at all and work wonderfully to do this kind of raw end-to-end learning and even transfer learning? I think I was surprised by how well, when you have large enough amounts of data, it's possible to find a meaningful representation in what is an exceedingly high dimensional space. And so I find that to be really exciting and people are still working on the math for that. There's more papers on that every year and I think it would be really cool if we figured that out. But that to me was a surprise because in the early days when I was starting my way in machine learning and the data sets were rather small, I think we believed, I believed, that you needed to have a much more constrained and knowledge-rich search space to really get to a meaningful answer. And I think it was true at the time. What I think is still a question is, will a completely knowledge-free approach where there's no prior knowledge going into the construction of the model, is that going to be the solution or not? It's not actually the solution today in the sense that the architecture of a convolutional neural network that's used for images is actually quite different to the type of network that's used for language and yet different from the one that's used for speech or biology or any other application. There's still some insight that goes into the structure of the network to get to the right performance. Will you be able to come up with a universal learning machine? I don't know. I wonder if there always has to be some insight injected somewhere or whether it can converge. So you've done a lot of interesting work with probabilistic graphical models in general Bayesian deep learning and so on. Can you maybe speak high level? How can learning systems deal with uncertainty? One of the limitations I think of a lot of machine learning models is that they come up with an answer and you don't know how much you can believe that answer. And oftentimes the answer is actually quite poorly calibrated relative to its uncertainties. Even if you look at where the confidence that comes out of the neural network at the end and you ask how much more likely is an answer of 0.8 versus 0.9, it's not really in any way calibrated to the actual reliability of that network and how true it is. And the further away you move from the training data, not only the more robust the model is wrong, the network is often more wrong and more confident in its wrong answer. And that is a serious issue in a lot of application areas. So when you think, for instance, about medical diagnosis as being maybe an epitome of how problematic this can be, if you were training your network on a certain set of patients in a certain patient population, and I have a patient that is an outlier and there's no human that looks at this, and that patient is put into a neural network and your network not only gives a completely incorrect diagnosis but is supremely confident in its wrong answer, you could kill people. So I think creating more of an understanding of how do you produce networks that are calibrated in their uncertainty and can also say, you know what, I give up. I don't know what to say about this particular data instance because I've never seen something that's sufficiently like it before. I think it's going to be really important in mission-critical applications, especially ones where human life is at stake. And that includes medical applications, but it also includes automated driving, because you'd want the network to be able to say, you know what, I have no idea what this blob is that I'm seeing in the middle of the road, so I'm just going to stop because I don't want to potentially run over a pedestrian that I don't recognize. Is there good mechanisms, ideas of how to allow learning systems to provide that uncertainty along with their predictions? Certainly people have come up with mechanisms that involve Bayesian deep learning, deep learning that involves Gaussian processes. I mean, there's a slew of different approaches that people have come up with. There's methods that use ensembles of networks trained with different subsets of data or different random starting points. Those are actually sometimes surprisingly good at creating a sort of set of how confident or not you are in your answer. It's very much an area of open research. Let's cautiously venture back into the land of philosophy and speaking of AI systems providing uncertainty, somebody like Stuart Russell believes that as we create more and more intelligent systems, it's really important for them to be full of self-doubt. Because, you know, if they're given more and more power, we want the way to maintain human control over AI systems or human supervision, which is true of AI systems. Like you just mentioned with autonomous vehicles, it's really important to get human supervision when the car is not sure, because if it's really confident, in cases when it can get in trouble, it's going to be really problematic. So let me ask about sort of the questions of AGI and human level intelligence. I mean, we've talked about curing diseases, which is a sort of fundamental thing that could have an impact today. But AI people also dream of both understanding and creating intelligence. Is that something you think about? Is that something you dream about? Is that something you think is within our reach to be thinking about as computer scientists? Boy, let me tease apart different parts of that question. That's the worst question. Yeah, it's a multi-part question. So let me start with the feasibility of AGI, then I'll talk about the timelines a little bit, and then talk about, well, what controls does one need when protecting, when thinking about protections in the AI space? So, you know, I think AGI obviously is a long-standing dream that even our early pioneers in the space had, you know, the Turing test and so on are the earliest discussions of that. We're obviously closer than we were 70 or so years ago, but I think it's still very far away. I think machine learning algorithms today are really exquisitely good pattern recognizers in very specific problem domains where they have seen enough training data to make good predictions. You take a machine learning algorithm and you move it to a slightly different version of even that same problem, far less complicated, and you can make predictions. Even that same problem, far less one that's different, and it will just completely choke. So I think we're nowhere close to the versatility and flexibility of even a human toddler in terms of their ability to context switch and solve different problems using a single knowledge base, single brain. So am I desperately worried about the machines taking over the universe and, you know, starting to kill people because they want to have more power? I don't think so. Well, so to pause on that, so you've kind of intuited that superintelligence is a very difficult thing to achieve. Even intelligence. Intelligence. Superintelligence, we're not even close to intelligence. Even just the greater abilities of generalization of our current systems. But we haven't answered all the parts. I'm getting to the second part. Okay, we'll take it. But maybe another tangent you can also pick up is can we get in trouble with much dumber systems? Yes, and that is exactly where I was going. Okay. So just to wrap up on the threats of AGI, I think that it seems to me a little early today to figure out protections against a human level or superhuman level intelligence who's where we don't even see the skeleton of what that would look like. So it seems that it's very speculative on how to protect against that. But we can definitely and have gotten into trouble on much dumber systems. And a lot of that has to do with the fact that the systems that we're building are increasingly complex, increasingly poorly understood, and there's ripple effects that are unpredictable in changing little things that can have dramatic consequences on the outcome. And by the way, that's not unique to artificial intelligence. I think artificial intelligence exacerbates that, brings it to a new level. But heck, our electric grid is really complicated. The software that runs our financial markets is really complicated. And we've seen those ripple effects translate to dramatic negative consequences, like for instance financial crashes that have to do with feedback loops that we didn't anticipate. So I think that's an issue that we need to be thoughtful about in many places, artificial intelligence being one of them. And I think it's really important that people are thinking about ways in which we can have better interpretability of systems, better tests for, for instance, measuring the extent to which a machine learning system that was trained in one set of circumstances, how well does it actually work in a very different set of circumstances where you might say, for instance, well, I'm not going to be able to test my automated vehicle in every possible city, village, weather condition, and so on. But if you trained it on this set of conditions and then tested it on 50 or 100 others that were quite different from the ones that you trained it on, and it worked, then that gives you confidence that the next 50 that you didn't test it on might also work. So effectively it's testing for generalizability. So I think there's ways that we should be constantly thinking about to validate the robustness of our systems. I think it's very different from the let's make sure robots don't take over the world. And then the other place where I think we have a threat, which is also important for us to think about, is the extent to which technology can be abused. So like any really powerful technology, machine learning can be very much used badly as well as to good. And that goes back to many other technologies that have come up with when people invented projectile missiles and it turned into guns, and people invented nuclear power and it turned into nuclear bombs. I think, honestly, I would say that to me gene editing and CRISPR is at least as dangerous at technology if used badly as machine learning. You could create really nasty viruses and such using gene editing that you would be really careful about. So anyway, that's something that we need to be really thoughtful about whenever we have any really powerful new technology. Yeah. And in the case of machine learning, adversarial machine learning, all the kinds of attacks like security almost threats, and there's a social engineering with machine learning algorithms. And there's face recognition and big brothers watching you. And there's the killer drones that can potentially go and targeted execution of people in a different country. I don't, you know, one can argue that bombs are not necessarily that much better, but you know, if people want to kill someone, they'll find a way to do it. So if you, in general, if you look at trends in the data, there's less wars, there's less violence, there's more human rights. So we've been doing overall quite good as a human species. Are you optimistic? Surprisingly sometimes. Are you optimistic? Maybe another way to ask is, do you think most people are good and fundamentally we tend towards a better world, which is underlying the question, will machine learning with gene editing ultimately land us somewhere good? Are you optimistic? I think by and large, I'm optimistic. I think that most people mean well, that doesn't mean that most people are, you know, altruistic do-gooders, but I think most people mean well. But I think it's also really important for us as a society to create social norms where doing good and being perceived well by our peers are positively correlated. I mean, it's very easy to create dysfunctional societies. There are certainly multiple psychological experiments, as well as sadly, real world events where people have devolved to a world where being perceived well by your peers is correlated with really atrocious, often genocidal behaviors. So we really want to make sure that we maintain a set of social norms where people know that to be a successful member of society, you want to be doing good. And one of the things that I sometimes worry about is that some societies don't seem to necessarily be moving in the forward direction in that regard, where it's not necessarily the case that being a good person is what makes you be perceived well by your peers. And I think that's a really important thing for us as a society to remember. It's very easy to degenerate back into a universe where it's okay to do really bad stuff and still have your peers think you're amazing. It's fun to ask a world-class computer scientist and engineer a ridiculously philosophical question like, what is the meaning of life? Let me ask, what gives your life meaning? What is the source of fulfillment, happiness, joy, purpose? When we were starting Coursera in the fall of 2011, that was right around the time that Steve Jobs passed away. And so the media was full of various famous quotes that he uttered. And one of them that really stuck with me because it resonated with stuff that I'd been feeling for even years before that is that our goal in life should be to make a dent in the universe. So I think that to me, what gives my life meaning is that I would hope that when I am lying there on my deathbed and looking at what I've done in my life, that I can point to ways in which I have left the world a better place than it was when I entered it. This is something I tell my kids all the time because I also think that the burden of that is much greater for those of us who were born to privilege. And in some ways I was. I mean, I wasn't born super wealthy or anything like that, but I grew up in an educated family with parents who loved me and took care of me, and I had a chance at a great education, and I always had enough to eat. So I was in many ways born to privilege more than the vast majority of humanity. And my kids, I think, are even more so born to privilege than I was fortunate enough to be. And I think it's really important that, especially for those of us who have that opportunity, that we use our lives to make the world a better place. I don't think there's a better way to end it. Daphne, it was an honor to talk to you. Thank you so much for talking to me. Thank you. Thanks for listening to this conversation with Daphne Koller, and thank you to our presenting sponsor, Cash App. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST. If you enjoy this podcast, subscribe on YouTube, review it with 5 stars on Apple Podcasts, support it on Patreon, or simply connect with me on Twitter, Alex Friedman. And now let me leave you with some words from Hippocrates, a physician from ancient Greece who is considered to be the father of medicine. Wherever the art of medicine is loved, there's also a love of humanity. Thank you for listening, and hope to see you next time.

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Vincent Racaniello: Viruses and Vaccines | Lex Fridman Podcast #216

The following is a conversation with Vincent Recaniello, professor of microbiology and immunology at Columbia. Vincent is one of the best educators in biology and in general that I've ever had the pleasure of speaking with. I highly recommend you check out his This Week in Virology podcast and watch his introductory lectures on YouTube. In particular, the playlist I recommend is called Virology Lectures 2021. To support this podcast, please check out the sponsors in the description. As a side note, please allow me to say a few words about the COVID vaccines. Some people are scared of a virus hurting or killing somebody they love. Some are scared of their government betraying them, their leaders blinded by power and greed. I have both of these fears. And two, I'm afraid, as FDR said, of fear itself. Fear manifests as anger and anger leads to division in the hands of charismatic leaders who then manufacture truth in quotes that maximize controversy and a sense of imminent crisis that only they can save us from. And though I'm sometimes mocked for this, I still believe that love, compassion, empathy is the way out from this vicious downward spiral of division. I personally took the vaccine based on my understanding of the data, deciding that for me, the risk of negative effects from COVID short-term and long-term are far worse than the negative effects from the mRNA vaccine. I read, I thought, I decided for me. But I never have and never will talk down to people who don't take the vaccine. I'm humble enough to know just how little I know, how wrong I have been and will be on many of my beliefs and ideas. I think dogmatic certainty and division is more destructive in the long-term than any virus. The solution for me personally, like I said, is to choose empathy and compassion towards all fellow human beings, no matter who they voted for. I hope you do the same. Read, think, and try to imagine that what you currently think is the truth may be totally wrong. This mindset is one that opens you to discovery, innovation, and wisdom. I hope my conversation with Vincent Recaniello is a useful resource for just this kind of exploration. He doesn't talk down to people and he's the most knowledgeable virologist I've ever spoken to. He has no political agenda, no desire to mock those who disagree with him. He just loves biology and explaining the fundamental mechanisms of how biological systems work. That's a great person to listen to and learn from with an open mind. I hope you join me in doing so, and no matter what, try to put more love out there in the world. This is the Lex Friedman Podcast, and here is my conversation with Vincent Recaniello. You mentioned in one of your lectures on virology that there are more viruses in a liter of coastal seawater than people on earth. In the Nature article titled Microbiology by Numbers, it says there are 10 to the 31 viruses on earth. Also, it says that the rate of viral infection in the ocean stands at 10 to the 23 infections per second, and these infections remove 20 to 40% of all bacterial cells each day. There's a war going on. What do you make of these numbers? Why are there so many viruses? So the numbers you're quoting, they're in my first virology lecture, right? Because people don't know these numbers, and they get wowed by them, and so I love to give them. By the way, sorry to interrupt, but as I was saying offline, you have one of the best introductory lectures on virology that I've ever seen, introductory lectures period, so I highly recommend people find you. I need you to give them a look. They'll find you on YouTube and watch it if you're curious at all about viruses. Yeah, there's a lot of times throughout watching it, I felt like, whoa. Yeah, that's my goal is to, and it's what my students tell me. One student once said, every day after every lecture, I could go home and tell my roommate something she didn't know, and it blew her away. So the number of viruses is really an amazing number. So that number, 10 to the 31, is actually just the bacterial viruses in the ocean. So there are viruses that infect everything on the planet, including bacteria. There are a lot of bacteria in the ocean, and so 10 to the 31 is from basically particle counts of seawater all over the world. So there are more viruses than 10 to the 31, but just in the ocean, and that number is so big. First of all, the mass exceeds that of elephants on the planet by a thousandfold, and if you lined up those viruses end to end, they would go 200 million light years into space. It's so big a number. It's amazing, and then yes, 10 to the 20-some infections per second of these viruses killing bacteria and releasing all this organic matter, and that's part of this, what we call the biogeochemical pump, cycling of material in the ocean. The bacteria die. They start to sink, and then they get metabolized and converted to compounds that are needed. A lot of it gets released as carbon dioxide and so forth. So these are actually really important cycles that are catalyzed by the virus. Well, it's so wild that nature has developed a mechanism for mass murder of bacteria. That's one way to look at it, but it's just what happened, right? It's interesting. I mean, I wonder what the evolutionary advantage of such fast cycling of life is. Is it just an accident of evolution that viruses are so numerous, or is it a feature, not a bug? So the fast is, it's not all fast. Not all viruses are fast. Some are 20 minutes per cycle. Some take weeks per cycle, but that's just per second. There's so many viruses in the ocean that that's what you get per second, no matter how fast the cycle is. But I look at it this way. Viruses were probably the first organic entities to evolve on the planet. Long ago, billion years ago, just as the Earth cooled and organic molecules began to form, I think these self, we call them self-replicators. They're just short things that today would look like RNA, which is the basis of many viruses, right? They evolved and they were able to replicate. Of course, they were just naked molecules. They had no protection, and it was just RNA-based. And that's tough because RNA is pretty fragile in the world, and it probably didn't get very big as a consequence. But then proteins evolved, and I'm skipping like hundreds of millions of years of evolution. Proteins evolved maybe without a cell, maybe with a cell. But then to make a cell, there probably were some RNA-based cells early on, but they were pretty simple. But the cells that we know of today, even bacteria and single-celled eukaryotes, they have very long DNA genomes, and you need a lot of DNA to make a complicated cell. And so we think at some point the RNA became DNA. And probably one of the earliest enzymes that arose is the enzyme that could copy that RNA into DNA, which we now know today as reverse transcriptase, which my former boss, David Baltimore, and Howard Temin co-discovered. And that enzyme arose and copied RNA to DNA, and then you could build big cells with, because DNA can be millions and millions of bases in length. And RNA, the longest RNA we know of is 40,000 bases, not much bigger than the SARS-CoV-2. What would you say is the magic moment along that line? I saw it was one or two billion, maybe three billion years it took to go from bacteria to that complex organism. It seems like Earth had a very long time, like not a very long time without life, and then a very long time with very primitive life. Maybe I'm discriminating, calling bacteria primitive life. Yeah, people would object to you doing that for sure. But it seems like complex organisms, when it starts becoming something like, I don't know what's a good, not animal-like, but more complexity than just like a single cell. What do you think is the magic there? What's the hardest thing? If you were trying to engineer Earth and build life and build the simulations, obviously we're living in a video game, what this is. So if you were trying to build this vehicle, what's the hardest part along this evolution pathway? So bacteria are mostly single cells. They do make colonies, they get together in biofilms, which are really important. But they're all single bacteria in that. And the key is making an organism where cells do different things. We have skin cells and eye cells and brain cells. Bacteria never do that. And the reason is probably energy. Bacteria can't make enough energy to do that. And so there was another cell existing at the time, the archaea. And the idea is that a bacteria went into an archaea and became the modern-day mitochondria, the energy factory of the cell. And that now let that cell develop into more and more complicated organisms like we have today. It was all about energy. So the mitochondria, the energy, the mitochondria is the magic thing. I think so. It's actually not my idea, it's Nick Jones. Have you heard of Nick Jones? He's an evolutionary biologist in the UK. And he's done experimental work on this. And it's his idea that the defining point was the ability to make a lot of energy, which a mitochondria can do. It's basically a whole bacteria inside of a bigger cell. And that becomes what we now call eukaryotes and that they can get more and more complicated. So let me bring you back to the viruses. I want to finish that story. Yeah, which points of viruses come along? So remember, we have these pre-cellular, they're called pre-cellular replicons, right? And so we have a pre-cellular stage where we have these self-replicating molecules. Then cells arise and then the self-replicating molecules invade the cells. Why? Because it's a hospitable environment. I mean, they didn't know that. They just went in and it turned out it was beneficial for them, so it stuck. And they replicate inside the cell now where they have pools of everything they need. They get more and more complicated. And then they steal proteins from the cell to build a protective shell. And then they can be released as virus particles. They're now protected. They can move from host to host. And because they're at the earliest stages of cellular evolution, they can diversify to infect anything that arises. And that is why I think there's so many of them and everything on the planet is infected because the ancestor of everything was infected many years ago. So it's easier to steal than to build from scratch. So it's easier to sort of break into somebody else's thing and steal their proteins. Yes. My colleague, Dixon de Pommier, calls viruses safe crackers. Safe crackers. So it's just, from an evolutionary perspective, it's easier to steal because you can select. But then you have to figure out mechanisms for stealing, for breaking into, for cracking the safe. Well, you don't have to figure out. It just happens, right? Because molecules are so diverse that a molecule gets into a cell. And if there's a protein that sticks to it, it's gonna stick. And that gives an advantage. There's no planning. There's no thinking about it, right? It just happens. We'll return to that. But these numbers are crazy. So as these more complex organisms evolved, let's take us humans as an example, should we be afraid of these high numbers? Should we be worried that there's so many viruses in the world? Well, to a certain extent. I mean, it's twofold. They're good and bad, right? Viruses, there's no question they can be bad. We know that because they've infected and caused disease throughout history. But we're also, you and I are full of viruses that don't hurt us at all and probably help us. And every organism is the same. So they are clearly beneficial as a consequence. So I think, so every living thing on the planet has multiple viruses infecting everything you can see. And most of them I think we don't worry about because they can't infect us. They're unable. In fact, now you can actually take your feces and send them to a company and they will sequence your viruses in your feces for you, your fecal virome, right? And the most common virus in human feces is a plant virus that infects peppers. It's called pepper model mosaic virus. And that's because people eat a lot of peppers. And it just passes right through you. Cabbage is full of viruses from the insects that walk on the cabbage in the fields. We eat them, they just pass us. So I think most of the viruses we don't need to worry about except when we're talking about species that are closest to us, mammals, of course. And I think the most numerous ones are the most concerning. They're viruses like bats. Bats are 20% of mammals and rodents are 40% of mammals. And we humans live nearby, right? And we know throughout history, many viruses have come from bats and from rodents to people. No question about it. So there's a proximity in terms of just living together and a proximity genetically too. So it's more likely that a virus will jump from a bat and a rodent. And birds too. Birds can give us their viruses that's happened. Influenza viruses come from birds mainly. So I think those are the three species, not species, it's higher than species obviously. But those are the three I would worry about in terms of getting their viruses. And we don't really know what's out there, right? We have very little clue about what viruses. And I've for years wanted to capture wild mice in my backyard and see what viruses they have because no one knows. And it's an easy- We can't ask them, so you mean map? Like is there a way- You can't ask them, yeah. No, I would have to sacrifice them and take tissue and then bring it in the lab and do genome sequencing. So you can do a thorough sequencing to determine which viruses. Is there a sufficiently good categorization of viruses where you'd be- That's a very good question. So whenever you do sequence, right? You get some environmental sample and you extract nucleic acid and you sequence it. What you do is you run it past the database. The gold standard is the GenBank database which is maintained here in the US. And you see if you get any hits. And then you can say, ah, look, this sequence is similar to this virus. And you can classify all the viruses you see. The problem is 90% of your sequence is dark matter. It doesn't hit with anything. It's probably a lot of it is unknown viruses. And that's gonna be hard to figure out because someone's gonna have to go after it and sort it through. So yes, you can find a lot of viruses and the numbers you get are astounding. You can find thousands of new viruses just by looking in various life forms. But there are many more that we don't pick up because they're not in the database. Maybe this is a good time to take a quick tangent. What do you think about AlphaFold2? I don't know if you've been paying attention to that. With them, DeepMind solving the protein folding problem. And then also releasing, first of all, open sourcing the code, which is for me as a software person, I love. And then second of all, also making like 300,000 predictions or something like that for different protein structures and releasing that data. Yeah. On the side of, because you're saying there's dark matter. Right. Is there something, first, what are your general thoughts, level of excitement about their work? And second, how can that be applied to viruses? Do you think we'll be able to explore the dark matter of virology using machine learning? Yeah, absolutely. Because in all this dark sequence, you can translate it and make a protein. You can see what a protein looks like. It has what we call an open reading frame, right? A start and a stop. And right now it's just a bunch of amino acids. But if we could fold it, maybe the fold would be like something we already know. Some protein fold which gives you a lot of clues, right? Because there are only so many protein folds in biology and that dark matter is probably one of them. So I think that's very exciting because for years, I've followed structural biologists for years and in the beginning, we couldn't even solve structures of viruses. They're too big. We could do small molecules like myoglobin. That was the first one done. Took years to do that. Then as computational power increased, then they could start to do viruses. But it took a long time. X-ray crystallography, depending on getting crystals of the virus, right? And now we can do cryo-electron microscopy which is much faster. You could solve, the spike of SARS-CoV-2 was solved in two months by Jason McClelland here in Austin, actually, at the beginning of the pandemic. But you're limited. You can't do huge proteins. You can only do moderately sized ones. So, or actually, you can do viruses, but you can't do small proteins. So that's speeded it up, but it's still too fast to solve. You get a new protein, you want to solve its structure. So if we could predict it, and I know from talking to structural biologists, this has been their holy grail from day one. They want to be able to take a sequence of a protein, put it in a computer and have the structure put out without having to do all the experiment. So that's why this is very exciting that you can predict it. That mean it's not finished, obviously, and there's more to do. But I think it will be a day where you could take any amino acid sequence and predict what it's going to look like. See, but aren't structural biologists going to get greedy? So once you have that, don't you want to go more complicated then? Don't you want to go, because that's just the first step, right? To go from amino acid to structure, then there's multiple protein interactions. Like, how do you get to the virus? Well, so that's what the ultimate goal of getting a structure is, that then you can do experiments and figure out what the structure means, right? So many, in the old days, structural biology was a career in itself. You worked with people who had a system and just solved proteins for them, and then you moved on to another one. You didn't really do any experiments. The other people got to do all the interesting experiments. Now, young structural biologists are multifaceted. They solve the structure, and then they say, what happens if we change this amino acid? Oh, look, it blocks binding to the receptor. This must be the receptor binding interface. So that's the exciting stuff, absolutely, is doing the experiment. I wonder if you can do some kinds of simulations of different proteins or multi-protein systems going to war against each other, like to try to figure out, you know, reinforcement learning is used in AlphaZero, for example, to learn chess and Go, and that's using the self-play mechanism where the thing plays against itself and learns better and better. I wonder if you can simulate almost evolution in that way for primitive biological systems, have them in simulation fight each other, and then see what comes out, like a super dangerous virus comes out, or super, like Chuck Norris type of thing that defends against the super dangerous virus, and it's all in simulation. So an example would be, we have all these variants of SARS-CoV-2 arising, right? Which look to be selected by immune responses, but we know what amino acids are changing in the spike and how they block antibody binding. You could simulate that. You could say, what is the antibody looking at? Where antibodies bind on proteins are called epitopes, right? You could map them all and change them in a simulation one by one and go back and forth between the antibody and the virus. So all these, evolution is what we call an arms race, right? The virus changes and then it evades the host, and then the host can change. The host takes longer to change, though, unfortunately. It takes geological time, but it can, and then the virus can change and it can go back and forth. And we can see evidence of this in genome sequences of both viruses and their hosts. And so you can take a protein in a host that is a receptor for multiple viruses, and you can see all the impacts of virus pressure on it, and you could simulate that for sure. And that's just one thing that you could do. You could simulate changes in, say, an enzyme that makes it resistant to a drug and predict all the drug resistance. But the problem is, people like me, the experimental virologist, don't know how to do any of that so we need to collaborate with people, I guess. Oh, with other humans. We do that, we do that. But with people from a field that we're not used to, I suppose people who, would it be AI, I suppose? Yeah, machine learning people. Machine learning people. And you would say, look, this is the biological problem. Is there a way we can use your tools to attack it? The problem is those people are antisocial introverts that have a place like this and try to hide from other people in the world. Very difficult to find in the wild. Okay, so outside of doing amazing, brilliant lectures online you host and produce five, I would say, related podcasts, including my favorite this week in virology, also this week in parasitism, this week in microbiology and so on. So you're a good person to ask, what are the categories of small things, small biological things in this world that can kill you, kill us humans? Let's look, you said like most viruses are friendly or at least not unfriendly. But let's look at the unfriendly ones in viruses and bacteria and those kinds of things. When you look at the full spectrum of things that can kill you, can you kind of paint a brief picture? Yeah, I think the big picture is that the things that can kill you are a minority of everything that's out there. And we're talking about molecules. So we have in us proteins that can kill us, prions that are just, it's a protein in us, and if it misfolds, it makes all of its other copies misfold and then you die of a neurological disease. That's pretty rare. So there are proteins, there are viruses. As I said, only certain ones can kill us. But even if we get those from animals, it's not straightforward. If you look at SARS-CoV-2, right, this is probably a once in 100 year pandemic, I would say, equivalent to 1918 in its devastation. And in between there have been smaller pandemics of other viruses, but it doesn't happen all that often. So we have a lot of viruses, we have a lot of bacteria of various sorts that can cause infections in us. And it's a limited number, right? You have streptococci and staphylococci and clostridia, we could go on and on. But we know how to handle those, as long as we have antimicrobials. It's just that we abuse them and we get resistance. So that can be a problem. Then we have fungi, not mushrooms, but much smaller fungi that multiply submicroscopic or just at the microscopic level. They can, in dry climates of the US, you can inhale their spores and they can grow in your lung if you're immunosuppressed and so forth. So those are the tiny guys. And then we have parasites, which we do this week in parasitism, where single cells, even worms of various sorts, can invade you and cause all sorts of problems. I was kind of terrified to listen to that podcast. What's it like? What you learn is that you travel somewhere and you can get infected and bring it back home. Here in the US, we do have certain kinds of parasites, but because of our lifestyle, we more or less have avoided them. For example, there's a parasite called toxoplasma, which is infected most of the world, actually, because a lot of people like to eat raw meat and you would get it from raw meat. And we're not as fond of that here in the US. We like to cook our meat, but that could be a consequence of eating raw meat. Is that what leads to, what is it called, toxoplasmosis? Yeah, so toxoplasmosis, it's mainly a big issue, is if you're pregnant and you get toxo, then your fetus is gonna be very badly malformed. It's gonna have brain defects and so forth. And animals can get it as well. So there are a lot of parasites of that nature, which you often acquire by food, eating food of different sorts. And it usually happens elsewhere. On This Week in Parasitism, we do a case. So Daniel Griffin is a resident physician. He's a doctor, a real doctor, right? And every month he comes up with a case. Okay, this is a person I saw. And last month this young lady had traveled somewhere and she ate raw fish. It was somewhere in Southeast Asia or something. And she ended up with red bumps all over her skin. And it turned out it was a parasite from the fish that moved around in her. And they're very easy to cure. We have the right doctors and the right drugs, you can cure all these. What about diagnose? Like connect the red spots to the fact that it's a parasite? Very easy if you have the right diagnostics. Now Daniel often goes to parts of the world where they don't have diagnostics and he has to use other mechanisms. He may have to take a bit and look at it under a microscope. And then he may not be able to get the drug depending on where he is. But often he sees patients who come back to the US and they get diarrhea or they have a fever. And he says, where have you been? And he can put two and two together. And so we let our listeners do that and they all send in guesses. And it's wonderful to hear them go through this. So there are a lot of parasites. Solve the puzzle and solve the case study. That can get you. You have to be careful about eating when you go overseas. And water too? Water as well. And in parts of Africa there are parasites in the lakes. And if you go swimming they can invade you. And in fact they can go into your hair follicles and burrow in and get into your bloodstream. That's exciting. So Daniel is interesting because he's very adventurous and he's not afraid of any of this. So there's a famous lake in Africa, Lake Malawi, which harbors a lot of these parasites. And he said, oh yeah, yeah, I just make sure I towel off vigorously when I get out. Vigorously. Get rid of them. And that was the name of an episode. But you know food is. Towel off vigorously. You know sushi, you can get worms from sushi. And the solution is to freeze it. And many sushi restaurants now have liquid nitrogen. They snap freeze their sushi and that kills all the parasites. And a study was actually done in Japan showing that freezing does not alter the taste of sushi. Because it's. Supper, you see a big industry there. Wow, that's brilliant. That's brilliant. Yeah, I was thinking about, you know I'm so boring and bland. Especially when I'm now in Texas here and I've been eating quite a bit of barbecue. I realized I really haven't explored the culinary world. And I've been curious to travel and taste different foods. Is there something you can say by way of advice? You know, channeling Daniel, I guess. If you were to travel in the world, if eating is the thing that gets you the parasites, what's good advice for eating in strange parts of the world? Mongolia, India, China. Is there something you could say by way of advice? I think Daniel would say, make sure your food is cooked, right? Cooked, but that's so boring. Yeah, it's unfortunate. And he would agree with you. Because you know, many vegetables are delicious. Salads even are delicious, not cooked. But they can have parasites in them. Meats, fish, people like to have uncooked fish. So if you want to be really safe and boring, just make sure everything is cooked. Now we have a case this week on Twip. Of a young man who went, I forgot where he went, but he stayed in a hotel. I think, oh, Oaxaca, Mexico. Stayed in a hotel. And he said, he came back with diarrhea and fever. And he said, I don't know where, I stayed in the hotel. I just ate hotel food, lots of vegetables and fruits. And probably they weren't washed with clean water. You know, he got something from that. The bottom line is most of these infections with parasites can be diagnosed. And you can be treated and you'll be fine. So if you really want to experience the cuisine, I don't think you should worry about it. That's what Daniel would say. Let's return to the basics. We're gonna jump around all over the place. What are the basic principles of virology? Maybe a good place to start is, what is a virus? That's great. I mean, I talk in my first lecture for 20 minutes before I get to that. But, and I wonder if I should put it up front, but it's kind of a boring definition. So if you do that, first people will turn off. So first you tell them about all the millions and billions of viruses around. So a virus, we have a very specific definition because it's different from everything else on the planet. Because first of all, it's a parasite. It takes, a parasite means you take something from someone else. You know, we have human parasites who take money from others, right? But in biological terms, a parasite takes something from the host that the host would otherwise use energy or some building block or something. There's never really a symbiotic relationship between a virus and a host. Well, there can be. So that's the dichotomy, I think, is that we define them as parasites. Yet, I just told you 20 minutes ago that many viruses are probably beneficial. So I think what it means is we, at some point we're gonna have to change our definition. Right, because after all, definitions we make are just constructs that make it easier for us to study, that don't necessarily represent what's right. Yeah, like Pluto was a planet at first, and now it's not a planet anymore, and a lot of people are very upset. But it's only according to us. There may be another race living somewhere else who thinks it's a planet, right? Well, maybe that's why viruses are attacking humans. They're very angry. They're calling them parasites. So right now, our definition includes parasite because a virus cannot do anything without a cell. If this mug were full of viruses, it would not do anything for years. It would eventually probably lose its infectivity, but it's not gonna reproduce here. It needs cells. And to the first people who discovered viruses, that was astounding that they didn't just reproduce, divide on their own like bacteria. So a virus needs to get inside of a cell, inside the cell. It can't just hang around on the surface. It needs to get in in order to make more of itself. And so we call it an obligate intracellular parasite because it needs to get in a cell, and then it takes things from the cell in the form of all kinds of molecules and processes and energy and so forth to make new viruses. Obligate means it's obligated to be inside the cell. Absolutely. It will not reproduce outside of the cell. So this mug of viruses can in no way be living, in my opinion. However, once it gets inside of a cell, now the cell is a virus-infected cell. It's alive. So a virus, in my view, has two phases, right? It's this non-living particulate phase that everyone is used to. I'll send you, you need a virus for your table. I'll send you a nice model. I think it would look good here. Which, yes, definitely. You don't have to go with all this other stuff. Yeah, well, these are all mechanical. There's no biology here. So you wouldn't want a virus here? No, I'd want a virus, of course. I'll send you one and then you can look at it. Because now that we have the three-dimensional structures solved by structural biologists, we take the coordinates and we put it in a 3D printer and you can make amazing models, right? Of any virus. And so there's a huge variety of viruses? Huge, that we know of, which is only a fraction of what's out there. What's the category? So there's RNA, there's DNA viruses. What are those, what's DNA and RNA? Two broad categorizations. RNA, these are genetic material. Can be two different chemicals. So RNA, everything else on the planet besides viruses is all DNA-based. You and I are DNA-based. Everything on the planet today is DNA-based, except some viruses are RNA-based. And that's because, as I mentioned earlier, the first life that arose on the planet was RNA-based. Yeah, so these are like old school viruses. These are old school. We call relics, yeah. Relics, and this has got a name. It's called the RNA world, which I think is great. Is it big still, or are the relics dying out? Oh no, the relics, in my opinion, are the most successful viruses, the RNA viruses. And SARS-CoV-2 is an RNA virus. We can talk about why they're so successful. But you have, broadly speaking, viruses with RNA genetic information, which are relics. Of course, they're contemporary. They have adapted to the modern world and the modern organisms living in it. And then we have DNA-based viruses, which are extremely conservative and slow. They're very successful. Everyone has a herpes virus infection, but they don't get the news like the RNA viruses do. The HIVs and the influenza viruses and the SARS coronaviruses, they get all the press and they're RNA-based, because RNA lets you change more so than DNA. So they evolve much faster, the RNA viruses. Much faster. And in fact, when I have a lecture on evolution, I don't know if you've listened to that one. You should. It's really, I think it's really interesting. RNA viruses exist at their error threshold, which means they can't make any more mutations when they reproduce, otherwise they're dead. They would go extinct. They're evolving at their error threshold. DNA viruses are hundreds of times lower than their error thresholds. And we know this. We can do an experiment to find that out. Now, why that is is a good question. But that's the reason why RNA viruses are far more successful. They infect many more hosts, and they're very, I would say, slippery. They can change hosts really quickly, because in any animal harboring an RNA virus, like let's say a bat in some cave somewhere, it's not just one genome. It's millions of different genomes of all kinds, all within the framework of, say, coronavirus, but they're all different. And one genome in there might just be right for infecting a person if it ever encountered that person. I mean, that's the thing that- Or there could be a large number. This is a tiny fraction, but a large number of them. And they're all operating at the threshold of error. That's fascinating. It's like little, it's like startups, little entrepreneurs, like a startup world. Yes, and many of them fail. Yeah, many of them fail. Many of the changes fail. And then there's the DNA viruses that are like the IBM and the Google. Exactly, exactly. The big corporations. That's very good. I like that. That become conservative with the bureaucracies and all that kind of stuff. So they- And a lot of baggage. Yeah. Yeah, it's expensive for them to reproduce, yeah. And they don't move quickly. Yes, the RNA viruses are the fast-moving members. So that's what a virus is. We call them oddly intracellular parasites. And then I told you there's DNA and RNA, but then let's go further. The nucleic acid's not naked, because naked nucleic acid in the world isn't good. I mean, it existed in the pre-cellular world, but there probably weren't a lot of threats to it then. Naked nucleic acid doesn't last long in the environment. So they're covered. The nucleic acid is covered. It can be covered with a protein shell, a pure protein shell, or it can have a membrane around it, which would be lipids from the host cell. So lipids, so it's a fatty membrane. Fatty membrane, yeah. So our cells are coated with fatty membranes, right? Our cells, the outer plasma membrane, right? That's the same. But viruses can be too. So they're kind of like cells, but without the ability to do the mitochondria stuff. Some are. Some are. They don't have nuclei. They don't have mitochondria. But they do have a nucleic acid. They have a membrane. And then, of course, there are spikes in the membrane that allow them to attach to cells. And so that completes our two different kinds of viruses. So they all have attachment mechanisms, like ways to, like keys into the system. They all have to get into cells. There are a couple of exceptions, though. There are viruses of fungi and plants. So let's do the fungi. Fungi would be like yeast. The yeast cell wall is pretty hard to get through. So viruses typically don't attach to a yeast and get inside. Rather, they just live in the yeast forever. Yeah. And they multiply as mostly nucleic acids. And as the yeast divide, they go into the daughter cells. And that's how they exist. Plant viruses, also the plant cell wall, would be very hard to get across by binding a protein. So plant viruses get into plants either by pests that inject them in. They're sucking sap out, and they inject virus at the same time. Or farmers, they have contaminated farm equipment, and they roll over the plants and introduces viruses. So those fungi and plant viruses, they don't have this specific receptor binding to get them into the cell. But everything else, yeah, the virus binds to something on the surface, very specific. It's taken into the cell, because that's what cells do. When things bind their exterior, they take it in. Because in most cases, it's good. It's something they need. And so the virus slips in. I guess you'd call that a Trojan horse, right? Trojan horse. It's so hard to not anthropomorphize this whole thing. It is hard. So obviously, they don't know any of this. It's not an actual Trojan horse. So they're not getting actually tricked in the way humans trick each other. No, it's all passive. And it's just through so many years of evolution, you select something that works, and it continues. And what survives then goes on with perhaps a slightly different approach. I love this idea of passive. Of course, according to Sam Harris, so for a sufficiently intelligent alien civilization observing humans, our behavior might seem passive too, because they understand fully exactly what we're doing, and then there's no free will, and we're all just operating in the same way a cell does, which is a much higher level of complexity. Yeah, so I love the distinction between active and passive. I mean, the point is, I think anthropomorphizing to a certain extent is fine, because it helps people understand. But when you start to say, I think the virus is doing that because then you're putting a human lens on it, and you may be wrong. Because you don't know why things happen for a virus. So right now, we have variants emerging, and people say, well, I think it's because the antibodies are selecting for variants. That's a good idea, but it may not be the only thing that's going on. You start imagining them coming to the table negotiating. Yeah, you get into trouble with that. That's why I tell my students, be careful about the anthropomorphizing, because you're gonna apply your values to a virus, and you have different values. You're a human, and you have, what you think is the reason for this outcome may not be right, that's all. Just be open-minded about it. In both directions. I actually, one of the things I push back on is in the space of robotics, most people in robotics try to not anthropomorphize. For example, they don't give a gender or a name to robots. They really try to see it as a machine. And to me, that makes sense in one way, but it totally doesn't make sense in another. If that robot is to interact, operate in the human world, and interact with humans, we have to anthropomorphize it in order to understand as an engineering problem, how should it operate in a human world? Now, the difference with viruses, the scale of operation, it doesn't make sense to treat them as human-like, because the scale of operation is much smaller. But with robots, you're in the same time scale, the same spatial scale. Of course, in the movies, they always give them names and personalities. Yeah, well, yeah, that's the, but that's my argument, is we should do the same when you're trying to solve the engineering problem of robotics, too. It's not just for the movies. Well, let me ask you this, because you've said controversially, not really, that viruses are not living. Defend yourself. Are viruses alive or not? So I've seen many people say, oh, they have to be. They have nucleic acids, they evolve, they mutate. That's all true, but they don't do it on their own. The particles in my mug are just not doing any of that unless they get into a cell. So a virus-infected cell is alive. I totally agree with that, because in fact, when a virus gets in a cell, it converts it into a virus-making factory, if you will. It's no longer a cell. Some people call it a virus cell. I don't really like that, but it's fine. So that's what I'm talking about. The particle is not alive. You can have your virus-infected cell as alive, but the particle, it just would not do anything forever without getting inside of a cell. Well, once it's in a cell, it is alive then, but it's no longer a particle. It's taken apart and nucleic acid is moving around the cells, making proteins. Eventually it makes new particles. And then those particles released from the cell, they're not living anymore. So I think it's kind of like a spore, a spore of a, or a seed. Although the seed doesn't work because the seeds, the cells in the seed have the ability to make their own energy and so forth. But a bacterial spore, and it's the same thing, doesn't do anything unless you add water and nutrients and then it starts to divide. But it doesn't need to get into a cell. It's very different from a virus. So that's why the particle. And when people think of virus, they're always thinking of the particle. And that's why I say it can't be alive because the particle can't do anything on its own. But if you think of a virus as an organism with a particle phase in a cell, then it makes sense to be alive. And by the way, when you say particle, you're referring to that structure that you've been mentioning, some kind of membrane or not, that's been called, what is that, viron particle or something? Virion. So it's what you should have here, I'll send you one, and then you can refer to it. What's the sexiest one to have? Like what, in terms of particles to have on a table? Well, unfortunately the ones that you can 3D print. Oh, they're not going to be super. They're the ones that we know the structures of, right? So someone sent me last year a 3D model of SARS-CoV-2, and it's beautiful. It's actually cracked open so you can see the RNA, and the spikes are sticking out, and they even put some antibodies sticking onto the spikes. That's super cool. When I show this on a live stream, people love this. They go, oh my God, that's beautiful. It is, it's absolutely gorgeous. I have that, I have my virus that I worked on most of my career, poliovirus. I have a 3D model of that, which I actually just had made. It's gorgeous. And you can have it made in any color you want, right? What would you say is the most fascinating, terrifying, surprising, beautiful virus to you? So of all the viruses you looked at, sometimes when you just sit late at night with a glass of wine, looking over the sunset, which virus do you think about? So fulfilling all of those adjectives is hard, right? Fascinating, exciting, terrifying. Well, the terrifying is an optional one, I think, because maybe that puts a lot of pressure. I'd say terrifying, to me, I'm not terrified because I think we can handle most viruses, as you see with this brand new one that emerged a year ago, we can handle it. From a virology perspective. Yeah, I mean, the human perspective is a different story, right? That's always an issue. So I think there are a couple of different categories of virus, so we could do the terrifying. And I think rabies is a terrifying virus because unless you're vaccinated, 100% certainty you're gonna die. So you get bitten by a rabid raccoon or bat or dog, whatever, and there's still 70,000 deaths a year of rabies throughout the world because a lot of feral dogs running around that are infected. Unless you're vaccinated, you're gonna die. There's nothing we can do. But we do have a vaccine which we can actually give you even after you've been bitten, which is the only vaccine that works that way. It's a therapeutic, right? It will treat your illness because the disease takes so long to develop. You know, eventually you get all kinds of neurological issues and paralysis and so forth. But it takes time and you can be vaccinated, it will prevent that in the meanwhile. So people always say, what's the most lethal virus? Is it Ebola? I said, no, it's actually rabies. Unless you're vaccinated, it will kill you. Maybe it's good to linger, because we'll talk about vaccines a few times today. It's good to linger on cases where vaccines have clearly, undoubtedly helped human civilization. And it seems like rabies is a good example. Oh, rabies is great because everyone knows what happens when somebody gets rabies, right? You have fear of water, hydrophobia. Your body becomes spastic and stiff and jerks around and you lose consciousness, you can't, no more. It's not a fun ride to death. It's horrible, it's a horrible way to die. So I think most people know that. It's been popularized enough in media, right? So that nobody would probably object to getting, oh, I was just bit by this raccoon and it ran off. Okay, well, we should assume it's rabid. We should immunize you. And most people are okay with that, because they know the consequences. And it's also pretty rare, right? It's not like something that you're trying to get into the arms of 250, 300 million Americans. It's hard. But the few thousand every year, it's easy. So the transmissibility is difficult, right? It has to, oh, it's not airborne. So- It's not airborne, it just, you have to be bitten. Although some people claim you could walk into a cave and the bats breathing out rabies virus could infect you, but I don't really think that's well substantiated. Yeah. I think it's a bite. How would you do a study on that? Yeah, it's very hard to do. You'd have to collect the vapors in the cave and show that they're infectious, which, and by the way, someone emailed me the other day, you'll like this, they said, why can't we just immunize all the bats in the world against these viruses? And I said, well, how would you do that? There are caves everywhere, right? Yeah. He said, well, maybe you could just go and aerosolize them. Yeah. It's pretty dangerous. And then all the bats should have vaccine passports to make sure that they're all- Yeah, so you have to get their consent before you do it. But we do immunize wildlife against rabies. We have rabies vaccines for wild animals. There are a whole bunch of them that get rabies. And we put it in bait and drop it from helicopters in the woods, and it drops down the incidence of rabies in people. Wow. You know, people hiking get bitten and so forth. It drops the incidence, so we can do that. I didn't know that. I always wondered how much medical care are we doing for animals in the wild, because I've recently become more and more aware that animals are living in extreme poverty, right? Like, you don't know, you think like natural, it's great. Like when animals are living on a farm, it's terrible. But then you also have to compare to like what life is like in the, or like the zoo. You have to compare what life is like in the wild. Life in the wild is very tough, I think. Most animals have to, well, the carnivores anyway, they have to catch their food every day, right? And then there's the viruses there. They have viruses as well. So the rabies immunization is the only one I'm aware of for wild animals. We do immunize lots of other animals. We immunize chickens and pigs and cows, even fish, farmed fish. We pick each fish up and give it an injection, you know, when it's a small fish. But that's mostly so that the farmers get a good yield. We don't really care about the animals, right? We want a good yield for market. And then there's some examples where we immunize animals to prevent spillovers into people. So there's a disease called Hendra in Australia, which was discovered in the 90s. And it turns out there are bats, fruit bats that have this virus. And the bats are fine, but sometimes they fly into horse stalls and the horses get infected. These are, in Australia, it was initially race horses, which are very expensive, right? The horses got infected and they died, and the humans who would take care of them would die also. So now they immunize the horses to prevent the, well, to save the horses. Probably that's the motivation, because these horses are hundreds of thousands of dollars. And then the people don't get sick because the horses don't get sick. You don't want to immunize all the people because it's too rare, but that approach is called the one world health approach, which means everything's connected on the planet, and we have to think of everything in the grander scheme, not just us. Yeah, so you can immunize some things along the trajectory that a virus would take. Exactly. So now some living beings. In the Arabian Peninsula, they have a MERS coronavirus issue every month. There are a couple of cases where a camel will infect a human, and the human can get very sick. It's respiratory disease, very much like COVID. And so camels are very common there. They're raced, they're used as pets, they're eaten. So there's a lot of human-camel contact, but the number of cases are rare to a month. So you don't want to immunize all the humans, so the idea would be to immunize the camels. So. I like it. So, okay, so you put rabies, but Ebola also is a famously deadly one. What is it? It kills like, I don't know, 50, 60% of its. Could be 50 to 90, but that's in Africa where the healthcare isn't great. You saw when cases of Ebola came to the US, we could take care of it. We knew how to take care of it. We had fancy hospitals and so forth, and now we have a vaccine. And the vaccine is really good, but there are many governments in Africa that are suspicious of us, and they don't want to use our vaccine. So there's a vaccine for Ebola. There is, yeah. And the effectiveness and safety of it, how much is understood. So this is difficult because there's not a lot of Ebola. It's not a continuous, ongoing thing. There are sporadic outbreaks here and there. Of a few thousand people. At most, at most, usually a few hundred. And the biggest ever, in fact, this is why we didn't, for years, have an Ebola vaccine. The US military, together with Canada, developed an Ebola vaccine for service people, right? They wanted to say, well, we're sending people into these Ebola areas. We want a vaccine for them. So they had developed it through all the preclinical, which means before it goes into people. And that stopped because there was no money to do a phase one and a phase two and a phase three. In fact, for phase two and three, you need to have infections going on because you're looking at how well the vaccine prevents infections, right? So then there was a West African outbreak in 2015. 2013, 2015. The most cases ever, 25,000. So they got to test the vaccine. But they only put it in a few thousand people. It's not like it's been in hundreds of thousands of people, like the COVID vaccines has been. So it looks like it has high efficacy, but we'd like to have more data. Side effects maybe are not so great. There are a couple of different available vaccines. Some have been tested more than others. I would say this would probably not be widely accepted in the US. But then neither would be something over 50% deadliness of a virus. No, I think if you were, in fact, many physicians work in countries that have Ebola, so they get vaccinated because they understand the choice. Yeah, right, it's always about the choice. So. So then one more thing, to answer the interesting, what are some of the viruses you really are fascinated by? There are a number of viruses that have clearly been shown to alter host behavior, and that's how they spread. I think those are fascinating. For example, there's some viruses of plants that are spread by aphids. And the aphid bites the plant, the virus reproduces in the plant, and it somehow engineers the plant to give off volatile organics to attract more aphids, which will spread the virus. Isn't that amazing? Yeah. So that's altering behavior. Reminds me of Twitter. Altering because somehow the virus infecting the plant cells gives off these organics and attracts aphids. And furthermore, somehow when the aphid bites, it tastes horrible, so they immediately leave with the virus they've just picked up and go to another plant to spread it. So they're attracted and then repulsed at the same time. And obviously you don't want to anthropomorphize this, like a strategy they're taking on. Somehow this worked out. It worked out this way. It just evolved. And you know, evolution is sometimes hard to trace, right? Like Darwin famously said, he could never figure out how an eye evolved from a single cell, right? But it did. The more complicated, complex the holistic organism is that the virus invades, the less able it is to control that organism, right? So I wonder if there's viruses that can control human behavior, you know, to induce more spread of the virus. Well, I don't see why not. There's not enough humans, I suppose, to like evolve through. Well, we can't do the experiment to test it, right? We have to observe. And that's always hard when you're observing because there's so many things that can confound what you're looking at. Yeah, change human behavior, yeah. I mean, there's so many things that impinge on our behavior. But yeah, I think it's possible. I think it's highly possible. If it does it in a plant, why not change some other organism's behavior? I think it's fine. Anyway, those fascinate me. There are lots of examples of those that are fascinating and how they work, people are trying to figure out. But there's not a lot of money to work on, you know, insect and plant viruses unless you're going to the USDA. So they don't get a lot of work moving forward. Well, is there, if you understand some of those viruses, is that transferable to human viruses, that understanding? I think some of it could be, sure. I think the general principles, for example, how does the virus cause volatile organics to be made? It must be turning on some genes. And you could learn principles from that, how the virus might do that. Sure, I think everything is broadly applicable. So to say it's not useful to study viruses of insects and plants is just wrong. Because in science, we probably know this, maybe in your field it's the same. If you're curious, you're gonna run into interesting things that you never planned on, right? That's why people, like, you can criticize, why do we wanna go on Mars? Why do we wanna colonize Mars? Well, it's like, why do you wanna go to the moon? The reality is when you do really difficult things, engineering things, like, all these inventions along the way are created. It's kind of fascinating how, basically, just pick a thing that everyone can agree is kinda cool and is really hard, and do that. And then you'll have, like, thousands of inventions that have nothing to do with the thing. That's right. I think you should let curious scientists just follow what they're interested in to a certain extent. You can't, you know, in science we say, we have translational research where we say, okay, here's some money, go cure cancer or diabetes or heart disease, whatever, right? And that's fine. But that often doesn't work out very well. What works better is to say, you have a good lab, you have a good track record, here's some money, do something, and that's where PCR, CRISPR, recombinant DNA, all that stuff which has made the field explode, that's all it came from. Not from people saying, I wanna cure genetic diseases by gene editing, but by saying, what are these repeated things in this bacterium doing? Yep. Can I ask you a big philosophical question? So, there's these deadly viruses that are not very transmissible, Ebola, rabies, and then there's these less deadly viruses that are very transmissible, like COVID, it's, I guess, kinda borderline, but why isn't there super transmissible, super deadly viruses? I think if you compare SARS-1 and 2, you get somewhat of an answer, right? SARS-1 was more deadly, in fact, over half of the time when people were infected, they ended up in the hospital because they were that sick. And then, the peak of virus shedding from them happened long after they went in the hospital, so it's easy to contain the infection when you're in a hospital, right? There was not much pre-symptomatic or asymptomatic shedding with SARS-1. And shedding means you become infectious. So, in a respiratory virus, you inhale the droplets of the virus and they reproduce in your upper respiratory tract, what we call the nasopharynx, right? The nose and going back to that little cavity just above your mouth. So, the virus reproduces really well, and then as you talk and sneeze and cough, you expel droplets and then those are inhaled by other people and then they reproduce. And for SARS-2, we now know there's a lot of reproduction just before you feel anything, if at all. So, there's a lot of shedding and transmission before you get symptomatic. And many people don't ever get symptomatic, right? So, they spread really easily. So, that explains why some viruses can transmit a lot better than others. And if one happens to knock you out, then you're never gonna transmit because you're in the hospital like SARS-1. But why can't you have both? Why can't you just wait a while before it knocks you out? But when it knocks you out, it really kills you. That is a philosophical question, right? Because we could talk about why we haven't observed it. I mean, one issue is that if you're killed too quickly by a highly lethal virus, you're not gonna transmit it very well, right? So, Ebola can kill you quite rapidly. And most of the transmission occurs when people are being cared for at home or in hospitals. The doctors and nurses get virus, but people walking around, you're not walking around when you have Ebola. You're too sick. You know, you have black bloody diarrhea. You're vomiting. You're bleeding from your skin and mucus membranes. You're not walking around. You're not going to parties. So, I think that's part of it, that if the infection is too lethal, you're simply not a good transmitter. And I think transmission is probably one of the most powerful selection forces for viruses, because a virus always has to find a new host. If it doesn't, it's the startup that fails, right? If it doesn't find a new host, it's gone. And so, anything that makes the virus transmit better is gonna help it. And if killing you, being less lethal is part of that, that works too. So, there's a strong selection pressure against being lethal. I think there's a strong selection pressure against being lethal and being more transmissible. Those two seem to work in opposite ways. And now, we don't have a lot of data to support this. This is kind of a thought experiment, but there is one experiment done in Australia many years ago. I don't know if you know this, but in the 1800s, the hunters in Australia imported a rabbit from Europe so they could hunt it, because the native rabbit in Australia was too fast for them. They couldn't shoot them. So, they brought in this European rabbit, and they reproduced out of control. Within a couple of years, they were everywhere, millions of rabbits in all the watering holes, and now they had a problem. So, they decided to use a virus to get rid of these excess rabbits. And they used a virus, a pox virus called myxoma virus, which is a natural virus of a different kind of rabbit. But for these European rabbits, it was quite lethal, and it's spread by mosquitoes. So, they said, okay, let's release this virus. And the first year, 99.2% of the rabbits were killed, but that 0.8% that were left had some form of resistance. They were variants. Every organism, not just viruses, makes mutants, and there were some variants of the rabbits that could survive infection. And then, in subsequent years, the virus became less lethal, and then the mosquitoes had a better shot of transmitting it from one rabbit to another if the rabbit lived longer. That's the selection, probably. And so, in the end, the rabbits lived on. The virus was there. It evolved to be more transmissible and less lethal. So, that's the only- Life is amazing. That's the only data. Life on Earth is amazing. It is, it is. If you take the time to look at it and see what's happened, it is amazing. It's also humbling that it just makes you realize humans are just a small part of the picture. Of course. And we're wrecking it, aren't we? Well, I mean, that's, we're not really, I mean, viruses are wrecking it in some ways. Part of this, we're not really wrecking anything. It's all part of it. But you know, when, the ways that humans exist encourages viruses to infect us, right? When we were hunter-gatherers, living in bands of 100 people, very few viruses because it was hard for the virus to go from one band to another. And perhaps a hunter would, one of these humans would get an animal and bring a virus into camp, and some people would die, but it would never spread to another. And then, when we started to congregate in cities, we figured out agriculture and so forth and how to harvest animals. Then we could get bigger and bigger populations, and the viruses went crazy. And they went from animals to us. So, measles went from cows to humans. When humans learned to domesticate cows and started gathering in big cities. Yeah, but now that humans are able to communicate and travel globally, the virus has become more and more dangerous, transmissible. Thereby, if you look at Earth as an organism, thereby pushing humans to be more innovative, create Alpha, Fold 2, and 3, and 4, and 5, create better systems, and eventually there's rockets that keep flying from Earth. And eventually, the virus is becoming super dangerous and threatening all of human civilization, will force it to become a multi-planetary species, and this organism starts expanding. So, I think it's a feature, not a bug. I don't know. Well, I think that we have our early, probably most of the, we're studying viruses since 1900, right? Most of that time was because of diseases they caused. The first viruses discovered, yellow fever, virus smallpox, polio virus, influenza virus, those were all because people got sick, and they said, oh, look, this is a virus that's associated with it. And so, we got good at learning how to take care of these infections, making vaccines, and so forth, over the years, and it's only in the last 20 years that we recognize that there are more viruses out there that are far more interesting, perhaps, but we've learned how to deal with the bad ones, for sure. So, we talked about what is a virus. We talked about some of the most dangerous and deadly viruses. Can we zoom in and talk about COVID-19 virus? Sure. I don't know what your preferred name is, but maybe for this- Well, the virus is SARS-CoV-2, which is hard, it's long, right? And then, COVID-19 is the disease. So, you could say the virus of COVID-19, that's fine. The virus of COVID-19. But for the purpose of this conversation, we'll, every once in a while, just say COVID. It's fine, no problem. What is this virus from, I don't know how many ways we can talk about it. I think from a basic structural, like the very end structure, biological structure perspective, what is it? What are its variants? Can you describe the basics, the important characteristics of the virus? So, viruses are classified by humans, just to make it easier to keep track of them, right? So, this is a coronavirus, which is because when they were first discovered, I think the first ones were animal coronaviruses. They looked at them under the electron microscope, and it looked like the solar corona, and that's all there is to it. And I have to say that, early in the outbreak, the place with the highest seropositivity in the US, for a while, 68%, was a working-class neighborhood in New York City called Corona. Can you beat that, right? That's crazy, yeah. So, coronaviruses, they have membranes, right? We talked about membranes. They have spike proteins in the membrane, so they can attach to cells. And inside, they have RNA. And they are the viruses with the longest RNA that we know of. None other comes close. For some reason, they're able to maintain 30,000, so SARS-CoV-2 RNA's 30,000 bases of RNA, and some of the other coronas are even longer, 40,000. This is a, coronas are family of viruses that included the one you mentioned before, version one. So, SARS-CoV-1, yeah. CoV-1, and I guess other ones as well. So, the first, we first learned of them in animals, a lot of animals, pigs, and cows, and horses have coronaviruses. And then, in the 60s, we discovered a couple of human coronaviruses that just cause colds, very mild colds that you wouldn't even think twice about. And then, suddenly, in 2003, there's this outbreak of severe respiratory disease in China. And, you know, it started in November, and they didn't tell the world until February. And that was really bad, because it was already spreading by the time they told people about it. But, this went to 29 different countries, only 8,000 people were infected, and then it stopped. And, that was the first time we saw an epidemic coronavirus. And, what they did afterwards is they said, okay, it looks like it came from the meat markets. They have live meat markets in Guangzhou, in the south of China, where you can go and pick out an animal, and the guy will slaughter it for you and give it to you. And then, of course, there's blood everywhere, and that's how they got infected. And they figured out that there's this animal called a palm civet that was the source of virus. The palm civets are shipped in from the countryside, and the palm civets somehow in the countryside got it from a bat. So, they went looking in caves in the countryside, and they found in one cave all the viruses that could make up SARS-1. And that was 2000, and I would say took about five, eight years after that outbreak. So, that was the first hint that bats have coronaviruses that can infect people and cause problems, right? And after that, we should have been ready. So, didn't they already start developing vaccines after then? Yes, so some people started making vaccines. They tested them in mice, but they never got into people. And some people started working on antiviral drugs. Nothing ever came of them, because industry, there's no disease. It's gone, why should we make vaccines and drugs? And NIH in the US, you submit a grant, and they say, ah, it's too risky. There's none of this virus around. So, people were really short-sighted, because I always say, we could have had antivirals for this absolutely, for sure, no question. In fact, the one antiviral that's in phase three, it's called molnupiravir. It's the only one that you can take orally. It's a pill. It looks really good. That was developed five years ago, but never taken into humans. It could have been ready. So, we dropped the ball, and then the next decade, 2012, MERS coronavirus comes up in the Arabian Peninsula. This comes from camels and infects people, but probably the camels got it from bats originally, some time ago. But that never transmits from person to person, very rarely. Every new little outbreak is a new infection from a camel. So, that was 2012, and now here we are, 2019, the new outbreak of respiratory disease in China. And this one really goes all over the world, where SARS-1 could not. It's a coronavirus. It's different enough from SARS-1 that it has very different properties. Causes a lot. But it still has a membrane. It still has a very long RNA in the middle, and then it still has the spike proteins. That's right. What are the little unique things that make it that much more effective? That make it cause a pandemic of millions of people, as opposed to SARS-1? Well, the genome is 20% different from SARS-1, say. And in those bases, there are things that make it different from SARS-1. It binds the same receptor, ACE2, on the cell surface. That's remarkable. It has a lot of the same proteins. They look similar. Like, if you look at the structure of the spikes, they look similar, but there's enough amino acid differences to make the biology. And what it is, we don't know, because how do you figure that out? You need to study animals, because you can't infect people. And the animal models aren't great. So the way you figure that out is you figure out how those differences, what functional, like how the difference in the amino acids lead to functional differences, the virus, like how it attaches, how it breaks the cell wall. Exactly. And how the hell do you figure that out? Like, I guess there's models of interaction. You need a, first you need an animal of some kind to infect, right? You can use mice. People have used ferrets, guinea pigs, non-human primates. All of the above, non-human primates are very expensive, so not many people do that. And then you can put the virus in the respiratory tract. But in fact, none of them get sick like people do. Many people with COVID get a mild disease, but 20% get a very severe, longer-lasting disease, and they can die from it, right? No animal does that yet. So we have no insight into what's controlling that. But if you just want to look at the very first part of infection, and the shedding and the transmission, you can do it in any one of several animal models. Ferrets are really good for transmission. They tend, they have nasal structures like humans, and you can put them in cages next to each other, and they'll transmit the virus really nicely. So you can study that. But the other thing that's important that we should mention is how do you manipulate these viruses? So these are RNA viruses. You can't manipulate RNA if we don't know how to do it. DNA, because of the recombinant DNA revolution that occurred in the 70s, we can change DNA any way we want. We can change a single base, we can cut out bases, we can put other things in really easily. And if I may give it a personal aspect, when I went to MIT as a postdoc in 1979, David Baltham said, here's what I want you to do. The moratorium on recombinant DNA experiments on viruses has just been lifted. I want you to make a DNA copy of polio and see if you put that in a cell whether it will start an infection. So okay, so I made a DNA copy of polio virus. It's only 7,500 bases. It's much smaller than corona. And I took that DNA and I put it in a piece of DNA from a bacteria called a plasmid. And you can grow plasmids in many, many bacteria, make lots of them and purify the DNA really easily. And I took that DNA and I sequenced it because we didn't know the genome sequence of polio at the time. And that took me a year by the way because the techniques we had were really archaic. And nowadays you could do it in 15 minutes, right? It's amazing. And I took the DNA, I put it into cells and out came polio. So that's the start. Now, since then, everybody has taken that technique and used it for their virus. You can now do it with SARS-CoV-2. You make a DNA copy of any RNA virus, you can modify it and you put it back into cells and you'll get your modified virus out. So that's an important part of understanding the properties of the virus, let's say in an animal. By changing the virus, you're changing a DNA copy, you're making the virus then and putting it into the animal. Can you clarify? So even in the RNA virus, you can take and turn it into DNA? Yes. And then that allows you to modify it? Yes. What's that mapping? No, no, no, what's the process of going from RNA to DNA? Reverse transcription. That's reverse transcription. Right. Oh, so you actually go through the process of reverse transcription to do this? Yes, remember David Baltimore and Howard Tann had discovered this enzyme in the 70s. They got the Nobel Prize for that. And when I went to David's lab at MIT, he had the enzyme in the freezer. He said, here, take this and make a DNA copy of polio. Yeah, I didn't make the connection that you can use that kind of thing for an RNA virus. And so that's- And then modify it. See, any DNA virus already exists as DNA, so you can modify it. But for RNA viruses, it was difficult. And so then from that point on, for influenza, every other RNA virus and coronaviruses, people made DNA copies, and that's what they use to modify and ask questions about what things are doing. What's this gene doing? What if we take it out? What happens? Can you do the same thing with COVID? Is it the RNA and then- Of course. And in fact, in January 2020, as soon as the genome sequence was released from China, the labs all over were synthesizing this 30,000 base DNA and getting- What can you figure out without infecting anything? Just turning into, with the reverse transcription, turning it to DNA and modifying stuff, and then putting it into a cell. What can you figure out from that? Well, you could, let's say you can cut out a gene. You see some genes in the sequence, and I don't know what these genes do. Let's cut them out. And then you could cut them out of the DNA. You put the DNA in cells, and maybe you get virus out. And you go, oh, clearly that gene's not needed for the virus to reproduce, at least in cells, right? Or maybe you take the gene out, and you never get any virus, so it's lethal. Is there a nice systematic way of doing this? Do people kind of automate it? Absolutely. And we, I mean, the problem with SARS, the COVID virus is it's 30,000 bases. There's a lot of stuff there. And what makes it more difficult is that you have to, it's been classified as a BSL-3 agent, biosafety level three. And so not everyone has a lab that's capable of doing that, so it limits the number of people who can do experiments. We're lucky to have a few in New York City, but not every place has them. So you cannot work with a virus just out on the bench like we do with many other viruses. You have to wear a suit, and you have to have special procedures and containment and so forth. So it makes it difficult to do basic experiments on the virus. But, you know, it's a pandemic. There's a lot of money. There's a lot of incentive to work on it harder. And also, you don't need to work on the virus. You can take bits of it and work. You could take, say, just the spike, right, and say, can we make a vaccine with just the spike? Because that doesn't require BSL-3. So yes. So like building a vaccine requires you to figure out how, or antiviral drugs, how to attack various structural parts of the virus and the functional parts of the virus. Right. You have to decide on a target. Yeah. Like, I'm going to make an antiviral. What am I going to target in the virus? And there are a few things that make more sense than others. Usually we like to target enzymes. I don't know if you remember your biochemistry, but enzymes are catalytic. You don't need a lot of them to do a lot of things. So they're typically in low concentrations in a virus-infected cell. So it's easier to inhibit them with a drug. And the coronas have a couple of enzymes that we can target. So you have to figure that out ahead of time and decide what to go after. And then you can look for drugs that inhibit what you're interested in. It's not that hard to do. There's just something beautiful about biology, about the mechanisms of biology. And I kind of regret falling in love with computer science so much that I left that biology textbook on the shelf and left it behind. But hopefully we'll return to it now because I think one of the things you learn, even in computer science, that studying biology and certainly neurobiology, you get inspired. Here's a mechanism of incredible complexity that works really well, is very robust, is very effective, efficient. It inspires you to come up with techniques that you can engineer in the machine. That's what drives the field forward when people improvise and come up with new technologies that really make a difference. And we have a bunch of those now. What's the difference between the coronavirus family and the other popular family, influenza virus family? Is, I mean, if I were, because you mentioned we should have done a lot more in terms of vaccine development, that kind of thing for coronaviruses. But if I were back then, from my understanding, the thing we should all be afraid of is influenza, like some strong variants coming out from that family. That seems like the one that will destroy civilization or hurt us really badly. I don't know if you agree with this sense, but maybe you can also just clarify what to you is the difference between the families. So it's an interesting difference. They both have membranes, right? So then they have spike proteins embedded in them, and they're different spikes. In fact, for influenza, there are two main ones. They're called the HA and the NA. But what's inside is RNA, but it's very different RNA. And here we have to explain that. So viruses with RNA can have three different kinds of RNA. They can have what we call plus RNA. They can have minus RNA, or they could have plus minus, actually two strands hybridized together. The plus RNA simply means that if you put that plus RNA in a cell, you know, your cell has ribosomes in it that make the proteins that you need. The ribosomes will immediately latch onto the plus RNA and begin to make proteins. A minus RNA is not the right strand to make proteins. So it has to be copied first. And then the plus minus is both together. So the SARS coronaviruses, all the coronaviruses have plus RNA. So as soon as that RNA gets in the cell, boom, it starts an infectious cycle. Same thing with poliovirus, by the way, which I worked on. Influenza viruses are negative stranded. So they cannot be translated when they get in the cell. So that's tough for the virus because the cell actually cannot make plus RNA from minus RNA. It doesn't have the enzyme to do it. So the virus has to carry it in, inside the virus particle. And then when the minus RNA is in the cell, the virus enzyme makes plus RNAs and those get translated. It's a big difference. And then in the influenza viruses, not only is it minus RNA, but it's in pieces. It's in eight pieces. We call that segmented, whereas the corona is in one long piece of RNA. So what is it? Is it they're like floating separately? Yeah, so the genes are on separate pieces. They're all packaged inside that virus particle of influenza virus, but they're in pieces. And why that's important is because if two different influenza viruses infect the same cell, the pieces as they reproduce can mix and out can come a virus with a new assortment of pieces. And that allows influenza virus to undergo extremely high frequency evolution. That's why we get pandemics. When we have a new flu pandemic, it's because somewhere in some animal, two viruses have reassorted and made a new virus that we hadn't seen before. So you're talking about kind of biological characteristics, but what, am I incorrect in my intuition that or from the things I've heard that the influenza family of viruses is more dangerous? Like what makes it more dangerous to humans? Well, it depends on the, there are many flavors or vintages of influenza virus. Some are dangerous and some are not, right? It depends on which one. Some, like the 1918 apparently was very lethal, killed a lot of people. But more contemporary viruses, we had a pandemic in 2009 of influenza. That wasn't such a lethal virus. We don't know exactly why, but it didn't kill that many people. It transmitted pretty well. Is that the bird flu one? They're all deriving, that one was called swine influenza. Swine, that's right, swine, yeah. It seemed to have started in a pig, but it had bird, it had RNAs from bird influenza viruses. These viruses are all reassortants of different viruses from pigs and birds and humans. But influenza can cause pneumonia and can kill you as does SARS-CoV-2. So it depends on the virus. So there is another influenza virus that's currently circulating. So right now we have the 2009 pandemic virus. That's still around. And then the 1968 pandemic virus, which was the one before 2009, that one is still around too. And that's more lethal. And depending on the season, some seasons the 2009 virus predominates, some seasons the 1968. And when the 68 is around, you get more lethality. So we're living with an influenza family. We haven't exterminated them. Right, we never will, never exterminate them. Why? Because every shorebird in the world is infected with them. You know, gulls and terns and ducks and all sorts of things. Why can't we develop strong vaccines that defend against? Oh, we could do that, sure. But that would not eliminate them from humans. Even if you had the best vaccine, you would never get rid of it in people because there would always be someone who's not vaccinated or in which the vaccine didn't work. You know, no vaccine is 100%. Right. Well, you just contradicted yourself. You said the perfect vaccine. Imperfect, imperfect. But then you said, like, even if you had the perfect, yeah, some people wouldn't get vaccinated. But I understand what you mean. But I actually was asking, how difficult is it to make vaccines like that? It seems like it's very difficult to do that for the influenza virus. So it's really easy to make an old school vaccine. So the way the first influenza vaccines were made, it was actually Jonas Salk worked on them in the 40s. You just grow lots of virus and you grow it in eggs, by the way, chicken eggs. Nice. Literally? Wait, wait. Yeah, chicken, embryonated, so they get fertilized and there's a 10 or 12 day embryo in it and you put virus in it and it grows up and then you harvest it. You get about 10 mLs of fluid. And then you take that, you treat it with formaldehyde or formalin and it inactivates the virus so it's no longer infectious. And you just inject that into people. And that was the first flu vaccine that was made for the US Army, actually. And then it got moved over to people. We still use that old school tech today. So you're taking, can you help me out here? Okay, so this is a good time to talk about vaccines. Okay, so you're talking about, you're taking the actual virus, you put it in an egg, you let it grow up. It's very funny that you put it in an egg. It's very poetic. And then how do you make it not infectious, not effective or whatever? Not infectious. Not infectious, is that the right term here? Yeah. So how do you make it not infectious? You can treat it with any number of chemicals that'll disrupt the particle so it no longer infects. So that step of disrupting the particle, is that very specific to a particular variant particle? No, the same collection of chemicals you can use for all kinds of, and which have been used for SARS-CoV-2 vaccines also. So same technology. Okay, so what are, there's several things to ask. So you called it old school in a way that's slightly dismissive, like people talk about Windows 98 or something. So is there risks involved with it, or is it just difficult to produce large amounts? Does it take a lot of eggs? It's very easy. I mean, you could do it in cells and culture, but eggs were convenient. And in the 1940s, we didn't have cells and culture. We didn't know how to do that, so we had to use something else. It's easy to do, but the process of inactivating the virus with a chemical makes it not the best vaccine you can make. The flu vaccines that we have today, which are mostly based on this inactivation, is called inactivated virus vaccines. Oh, so like the kind of thing it presents the immune system to train on is not close to the actual virus. Yes, that's what we think. So that's why probably the flu vaccines are just not very good. 60% efficiency at the best, right, which is not really good. What does it mean? What is the measure of efficiency for a vaccine? Well, it's how it does in the general population at preventing influenza. At preventing? Illness, not infection. We usually don't measure infection when we're testing a vaccine. We just measure sickness. That's really easy to score, right? You do a trial and you say, if you feel sick, give us a call. We'll tell you what to do. So yeah, I mean, what's sickness? Sickness is the presence of symptoms. So this is good time to say what a symptom is, okay? A symptom is what you only can feel. Only you can feel an upset stomach or a sore throat or that sort of thing. It's the lived experience of a symptom. Whereas a sign is something that someone could measure and tell that you're infected, like virus in your nasopharynx or something else, right? Signs and symptoms. And so in a vaccine trial, they tell you if you have any of these symptoms, and they give you a paper with the exact symptoms listed to make sure you're picking them up, right? So for flu, it would probably be fever, sore throat, cough. You call them and then they will do a PCR and make sure you've got flu and not some other virus that makes similar symptoms. And then they would say, are you a vaccine or non-vaccine arm? And they count up all the infections and see how the vaccine did, basically. That's so fascinating because the reporting, so symptom is what you feel. Yes, for sure. And certainly the mind has a ability to conjure up feelings. Oh yes, absolutely. And so like culturally, maybe there was a time in our culture where it was looked down upon to feel sick or something like that, like toughen up kind of thing. And so then you probably have very few symptoms being reported. Absolutely. And then now is like much more, I don't know, perhaps you're much more likely to report symptoms. Now it's fascinating because then it changes. Oh, it is definitely a perception because your symptom may be nothing to me or vice versa, right? And so when you're doing this, it's a little bit of a imprecise science because, and even it's a cultural thing. In some countries, something that would make us feel horrible they wouldn't even bother reporting. No, I didn't have any symptoms. So it's a little bit imprecise and it clouds the results. So if you can measure things, it's always better. But you start out with a symptom. And if you say, if someone tells you this virus, 20% of the people are asymptomatic, they don't report symptoms, that number is probably not a constant. It depends where you did the study. It could be different in China versus South America, Europe, et cetera, yeah. I mean, I was trying to, so I took two shots of the Pfizer vaccine. I had zero symptoms. Wow. So, and I was wondering, well, see, but that's my feelings, right? This is not, because I felt fine. I was waiting. Did you have pain at the injection site? No, it was kind of pleasant. You felt nothing the next day, no? Nothing. No tiredness, no exhaustion, no. But see, like I have an insane sleeping schedule. I already put myself through crazy stuff. That said, maybe I was expecting something really bad. Like I was way, and therefore didn't feel it. Then, but I also got allergy shots. And those, I was out all next day, like exhausted for some reason. So that gave me like a sense, like, okay, at least sometimes I can feel shitty. That's good to know. Sure, sure. Then with the vaccine, it didn't. But the question is like, how much does my mind come into play there? Are the expectations of symptoms, the expectations of not feeling well, how does that affect the sort of the self-reporting of the symptoms? I think it's definitely a variable there, but there's certainly many people that don't feel anything after the vaccines. And there's some that have a whole range of things like soreness and fever, et cetera. Yeah. So, okay, you were talking about the old school development side, the egg. Right. What's better than that? So then the next generation of vaccines, which arose in the 50s, were what we call replication competent, where the virus, you take it and it's actually reproducing in you. Yeah, that sounds safe. And it can be somewhat problematic, yes, as you might imagine, because once you put that virus in you, you have no more control, right? It's not like you have a kill switch in it, which actually would be a great idea to put in. Like nanobots? What can possibly go wrong? No, you could just put something in there. If you added a drug, you would shut it off, right? And people are thinking about that because now we're engineering viruses to treat cancers and other diseases, and we may want to put kill switches in them just to make sure they don't run away. Oh, interesting, so you could like deploy a drug that binds to this virus that would shut it off in the body, something like that. Something like that, yeah, that would be the idea. You'd have to engineer it in. Anyway, the first one was yellow fever vaccine that was made because that was a big problem. And this virus, and the way you do this, back in the old day, was empirical. So Max Tyler, who did the yellow fever vaccine, he took the virus, which is a human virus, right? And he infected, I think he used chick embryos. And he went from one embryo to another and just kept passing it. He did that hundreds of times. And every 10 passages, he would take the virus and put it in a mouse or a monkey, whatever his model was. And then eventually he got a virus that didn't cause any disease after 200 and some passages. And then that was tested in people, and it became the yellow fever vaccine that we use today. He selected for mutations that made the virus not cause disease, but still make an immune response. So those are called replication competent. We now have the polio vaccine, which was developed in the 50s after the yellow fever. Then we had measles, mumps, rubella. Those are all replication competent vaccines. And you mentioned that's a good idea. They are all safe vaccines. The only one that has had an issue is the polio replication competent vaccine. It was called Sabin vaccine or oral polio virus vaccine because you take it orally. It's wonderful because you don't have to inject it. This is the perfect delivery. You know, either intranasal for a respiratory virus or orally for polio. It goes into your intestines, it reproduces, and it gives you wonderful protection against polio. However, you do shed virus out, and that virus is no longer a vaccine. It's reverted genetically in your intestine. So you can infect others with polio. You can take that virus and then put it into an animal and give it polio, and in fact, the parents of some kids in the 60s and 70s who were immunized got polio from the vaccine. The rate was about one in one and a half million cases of polio. So it's called vaccine-associated polio. And I always argue that we may not have picked the right vaccine. There was a big fight in the US and other countries between the inactivated polio and the infectious polio vaccines, which ones we should be using, because we found out that the infectious vaccine actually caused polio. And eight to 10 kids a year in the US alone got polio from the vaccine, which looking back is really not acceptable in my view, although the public health community said it was to get rid of polio. So now we're close to eradicating polio globally, but this vaccine-derived polio is a problem. So now we have to go back to the inactivated vaccine, which is tough because it's injected. So, okay, so the basic high-level how vaccines work principle is you want to deploy something in the body that's as close to the actual virus as possible, but doesn't do nearly as much harm. And there's like a million, not a million, but there's a bunch of ways you could possibly do that. So those are two ways. And now, of course, we have modern ways we can make mRNA vaccines, right? What are the modern ways? Did you want to look mRNA vaccine? So that's the most modern, but even before mRNA vaccines, we learned that we could use viruses to deliver proteins from a virus that you want to prevent. And so the Ebola vaccine, we took the spike gene of Ebola virus and put it in a different virus, and we deliver that to people, and that's called a vectored vaccine. And some of the COVID vaccines are vectors of different kinds, the most famous are adenovirus vectors carrying the spike gene into the cell. Can you explain how the vector vaccine works again? So we take a virus that will infect humans, but will not make you sick. In the case of adenovirus, the years and years of people studying it has told us what genes you could cut out and allow the virus to infect the cell, but not cause any disease. So instead of doing selection on it, you actually genetically modify it. Yes, you modify the vector, yeah. So you'd be much more precise about it. You're very precise, and then you splice in the gene for the spike, and then you use that to deliver the gene, and it becomes produced as protein, and then you make an immune response. And vector is the term for this modified. Right. So we're now using viruses at our bidding. We're using them as vectors, not just for vaccines. We can cure monogenic diseases. That is, if you're born with a genetic disease, you have a deletion or a mutation in a gene, a single gene, we can give you the regular gene back using a virus vector. Cancers too, we can cure cancers with vectors. Wow, really? Interesting. Yeah, I think in 10 to 15 years, most cancers will be treatable with viruses, yeah. Wow. And not only can we put things in the vector to kill the tumor, we can target the vector to the tumor specifically in a number of ways, and that makes it less toxic, right? It doesn't infect all your other cells. But it takes time to develop a vector for a particular thing because it requires a deep understanding. Yeah, in fact, we have about a dozen different virus vectors that have been studied for 20 years, and those are the set of vaccine vectors that we're using. So it includes adenovirus, vesicular stomatitis virus, which is a cousin of rabies, but doesn't make people sick. Influenza virus is being used as a vector, and even measles virus. So we're familiar with how to modify those to be vectors, and those are being used for COVID vaccines. And then of course, we have the newest, which is the nucleic acid vaccines. So years ago, people said, why can't we just inject DNA into people? Take the spike and put it in a DNA and inject it. So people tried many, many different vaccines. And in fact, there are no human licensed vaccines that are DNA vaccines, although there is a West Nile vaccine for horses that's a DNA-based vaccine. So if you have a horse, you can give it this vaccine, but no human. Can you clarify, does a DNA vaccine only work for DNA viruses? No, it can work for DNA or RNA, because remember, for an RNA virus, we can make a DNA copy of it. And it will still, when you put that DNA in a cell, it goes into the nucleus. Okay, right. So you're just skipping a step. You get protein. RNA vaccines, you're giving, okay, I got it. So those didn't work for human vaccines, and there were many HIV, AIDS vaccine trials that used DNA vaccines, didn't work. And then a number of years ago, people started thinking, how about RNA, RNA vaccines? And I first heard this, I thought, what? I've worked with RNA my whole career. It's so fragile. If you look at it the wrong way, it breaks. I mean, that's being facetious, right? But you have to be very careful, because your hands are full of enzymes that will degrade RNA. So I thought, how could this possibly work injecting it into someone's, it's an example of, I was skeptical, and I was wrong. It turns out that if you modify the RNA properly and protect it in a lipid capsule, it actually works as a vaccine. And people were working on this years before COVID came around. They were doing experimental mRNA vaccines, and there were a couple of companies that were working on it. And so at the beginning of 2020, they said, let's try it. And I was skeptical, frankly, because I just thought RNA would be too labile, but I was wrong. So this is, as we're saying offline, one of the great things about you is you're able to say when you're wrong about intuitions you've had in the past, which is a beautiful thing for a scientist. But I still think it's very surprising that something like that works, right? Yeah, I am surprised. So you're just launching RNA in a protective membrane. Yeah. And then, now, one thing is surprising, the RNA sort of lasts long enough in its structure. But then the other thing is, why does it work that that's a good training ground for the immune system? Is that obvious that that should work? I don't think it's obvious to most people, and it's worth going into, because it's really interesting. I mean, first of all, they wrap the RNA in fats, in lipid membranes, right? And the particular formulation, they test for years to make sure it's stable, it lasts a long time after it's injected. And the two companies that make the current COVID vaccines, right, Moderna and Pfizer, they have different lipid formulations to get to the same. So that's a real part of it. And it's not simple. There are quite a few different lipids that they put into this coating. And they test to see how long they protect the RNA after it's injected, say, into a mouse. How long does it last? And the way it works is, apparently, these lipid nanoparticles, they get injected into your muscle, they bump into cells, and they get taken up. So lipid fat is sticky. It's greasy, we like to say. And so your cells are covered with a greasy membrane also, so when these lipid nanoparticles bump into them, they stick, and they eventually get taken up. And they figured this out right at the beginning. If we put RNA in a lipid nanoparticle, will it get taken up into a cell? And the answer was yes. It was just, let's try it, and it worked. So it's basically experiment. It's not like some deep understanding of biology. It's experimentally speaking, it just seems to work. Yeah, well, they had some idea that lipids would target this to a cell membrane. And remember, there's no receptor involved. Like, the virus has a specific protein that it attaches to a receptor. It's not efficient enough to just bump around and get into a cell. That's what these things are doing, and they probably optimize the lipids to get more efficient uptake. But it's not as efficient as a virus would be to get into a cell. Right, so you have no specific, I mean, which is why it's surprising that you can crack into the safe with a hammer. Or with some fat. I mean, that's kind of surprising. It's kind of amazing that it works. But so, maybe let's try to talk about this. So one of the hesitancies around vaccines, or basically around any new technology, is the fact that mRNA is a new idea. And it's an idea that was shrouded in some skepticism, as you said, by the scientific community. Because it's a cool new technology. Surprising that it works. What's your intuition? I think one nice way to approach this is try to play devil's advocate and say both sides. One side is why your intuition says that it's safe for humans, and what arguments can you see, if you could steel man an argument why it's unsafe for humans. Or, not unsafe for humans, but the hesitancy to take an mRNA vaccine is justified. So many people are afraid because it's new technology and they feel it hasn't been tested. I mean, in theory, what could go wrong? This is, the nice thing about mRNA is that it doesn't last forever. As opposed to DNA, which doesn't last forever, but it can last a lot longer. And it could even go into your DNA, right? So mRNA has a shorter lifetime, maybe days after it's injected into your arm, then it's gone. So that's a good thing, because it's not gonna be around forever. So that would say, okay, so it's sticking around for your lifetime, it's not happening. But what else could happen? Well, let's see, the protein that's made, could that be an issue? And again, proteins don't last forever. They have a finite longevity in the body. And this one also lasts, perhaps at the best, a few weeks. This is a protein that's made after the RNA gets into the cell. Yeah, so the lipid nanoparticles taken up into a cell and the mRNA is translated and you get protein made. And there's also a question, I'm sorry to interrupt, where in the body, so because it's not well targeted, or I don't know if it's supposed to be targeted, but it can go throughout the body, that's one of the concerns. Right, so it's injected deep into your deltoid muscle, right here, shoulder. And the idea is not to put it in a blood vessel, otherwise it would then, for sure, circulate everywhere. So they go deep in a blood vessel and it's locally injected. And they did, before this even went into people, they did experiments in mice where they gave them a thousand times higher concentrations than they would ever give to people. And then when you do that, it can go everywhere, basically. You can find these nanoparticles in every tissue of the mouse. But that's at a thousand-fold higher concentration, right? So I think at the levels that we're using in people, most of it's staying in the muscle, but sure, small amounts go elsewhere. And could there be a lot of harm caused if it goes elsewhere? Like, let's say ridiculously high quantities. I'm trying to understand what is the damage that could be done from an RNA just floating about. So the RNA itself is not gonna be a problem, it's the protein that is encoded in it, right? This is a viral RNA which has no sequence in us, so there's nothing that it could do. It's the protein that I would say, you could ask, what is that gonna do? And the one property we know about the spike is that it can cause fusion of cells. Right, that's how the virus gets in in the beginning. The spike attaches to the cell by this ACE2 receptor, and it causes the virus and the cell to fuse. And that's how the RNA gets out of the particle. But so wait, I'm a bit confused. So with this mRNA vaccine with lipids and the RNA, there's no spike, right? The mRNA codes for the spike. Oh, the mRNA codes, so it creates the spike. Creates a spike. And so that spike could cause fusion of cells. Yes, except they modified the spike so it wouldn't. Got it. They made two amino acid changes in the spike so it would not fuse. So they understand enough which amino acids are responsible for the fusion. That's right. Interesting. So they could modify it. So now it's not gonna cause fusion, so that's not an issue. It's called the pre-fusion stabilized spike. Cool. So the spike, when it binds ACE2, that top falls off, and the part of the spike that causes fusion is now exposed. And that doesn't happen in this mRNA vaccine. So those are the things that could have happened, but I think they're ruled out by what we've just said. But there's no better test than putting it into people, right, and doing phase one, phase two, and phase three, and increasing numbers of people, and asking, what do we see? Do we have any concerns? And so now it's been in many millions of people, and we don't see, most of the effects you see in a vaccine you see in the first couple of months. Things like the myocarditis with some of the vaccines, the clotting issues with the AstraZeneca vaccine, Guillain-Barre, you see those relatively quickly. And we've seen small numbers of those occur, but other things we haven't seen, and you never say never, right? Right, so I mean, this is fascinating, right? It's like I drink, I put Splenda in my coffee, in my coffee, and has supposedly no calories, but it tastes really good. And despite what like rumors, and blogs, and so on, I have not seen good medical evidence that it's harmful to you, but it's like, it tastes too good. So I'm thinking like, there's gotta be long-term consequences, but it's very difficult to understand what the long-term consequences are. Like, and there's this kind of like distant fear or anxiety about it. Like this thing tastes too good, it's too good to be true. There's gotta be, there's no free lunch in this world. This is the kind of feeling that people have about the long-term effects of the vaccine. That you mentioned that there's some intuition about near-term effects that you want to remove, like the diffusion of cells and all those kinds of things, but they think, okay, this travels to other cells in the body, this travels to neurons or that kind of stuff. And then what kind of effect does that have long-term that's yet to be discovered? What do you make, I mean, for this vaccine, but in general in science about making statements about long-term negative effects, is that something that weighs heavy on you? Is that something that can kind of escape through just large-scale experimentation with humans, with animals and humans? Well, if you're really, if you're concerned about long-term, then you have to do a long-term experiment, right? And maybe you don't see something for 50, 60 years. So if someone says to you, there are no long-term effects of the COVID vaccines, they can't say that because they haven't done the long experiment, right? There's always the possibility, but you have to weigh it. It's always, there's no free lunch, right? There's always a risk benefit calculation you have to make. You can have the study, it goes for 50 years and then decide. But I guess what you're doing is, just like we said, I forget with which one, with polio, with rabies, I forget, but you're weighing the side effects of the vaccine versus the effects of the virus. And like both of them, you don't know long-term effects. But you're building up intuition as you study, which what are the long-term effects? Like there's a huge number of people like that have, like, I don't want to say experts because I don't like the word, but people have studied it long enough to where they build up intuition. They don't know for sure. There's basic science being done, there's basic studies. We start to build up an intuition of what might be a problem down the line and what is not, biologically speaking. And so given that map, then considering the virus, there seems to be a lot of evidence for COVID having negative effects on all aspects of the body, not just even respiratory, which is kind of interesting. So the cognitive stuff, that's terrifying. All kinds of systems evolve, yes. And then you look at the same thing with the vaccine, and there seems to be less of that. But of course you don't know if it's some kind of dormant thing that's just going to- You won't know. You have to make a judgment. And for a lot of people, they can't, right? Because they don't have the tools to make the judgment. I totally understand that. And we have let people down a few times in medicine, right? And I know two very specific examples. The first polio vaccine ever made, the Salk vaccine was released in 1955. Immediately, within months, few hundred cases of paralysis in kids who got it because it was not properly inactivated. Now you have to understand, parents were dying for a polio vaccine because kids were getting paralyzed every summer, 30,000 kids a year. And so they went and took it. They took the word of the medical establishment that it was safe, and it wasn't. Big letdown, never going to forget something. Although I think a lot of people today aren't aware of that. I think that was a big problem that's everlasting. Then the attenuated vaccine that we talked about, the infectious, causing polio. Yet parents continued to bring their kids to be vaccinated because they were said, this is the right thing to do. And I have to say, I was involved in several lawsuits where parents of a kid who got paralyzed from the polio vaccine decided to sue the manufacturer and get some money for their kid. And so they got mad. And I think you could not, the first issue could have been prevented, could have been prevented by inactivating it properly. I think the company just did the wrong thing. The second we had evidence for, and we should probably have not used that vaccine any longer, but I think that destroys public confidence. But those are- They're not long-term. That's the minority of cases. That's a minority. That's a very rare event, yeah. But nevertheless, science as an institution didn't make corrections in that case. No, they didn't. And so what do you make of that? I mean, it's very unfortunate that those few things can destroy trust. But I don't think that lasts till today. I think today is a different era, right? Yeah. And most people don't know about those stories. And I tell them to you because that's what could happen. I think it could happen today. If you look at the history of the polio vaccine, the US Public Health Service wanted kids to be vaccinated. So they did things that probably weren't correct to get the vaccine back online, right? But they did it and they pushed it through. So the question is, what do we do today? So I can look at, as we just said, I can look at what might happen and I can make reasonable decisions about the likelihood of them happening. And I can also say, I don't wanna get COVID of any kind because I've seen how nasty it can be. And I decide I'm taking the risk, whatever small of a long-term effect, I'm gonna take the risk. My family took the risk and many other people did. Of a vaccine. Of getting vaccinated. Because I think it's very small. But I understand where people can't make that decision. And that begs the question, what would they need to make a decision? So if you're concerned about an effect in 40 years, we're not gonna know for 40 years. Yeah, so I think if I were to speak, because I talked to, like I mentioned, offline to Joe Rogan on his podcast yesterday. I talk to him all the time about this. I think the concern is less about the long-term effects like on paper, it's more about the, people like Anthony Fauci and people at the top are simply misrepresenting the data or like are not accurately being transparent, not collecting the data properly, not reporting on the data properly, not being transparent, not representing the uncertainties, not openly saying they were wrong two months ago, like in a way that's not like dramatic, but revealing the basic process of science when you have to do your best under uncertainty. Just also just being inauthentic. There's a sense, especially with like a younger generation now, there's a certain way on the internet. Like the internet could smell bullshit much better than previous generations could. And so they see there's a kind of inauthenticity that comes with being, like representing authority. Like I am a scientist, I'm an expert, I have a PhD, I have four decades of work, therefore everyone should listen to me. And somehow that maps to this feeling of well, what are they hiding? If they're speaking from authority like this, if everyone is in agreement like this, that means they all have emails between each other. They said, we're gonna tell this, this is the message we're gonna tell the public. Then what is the truth, the actual truth? Maybe there's a much bigger uncertainty. Maybe there's dead people in the basement that they're hiding from bad mRNA vaccine experiments. Maybe they're, and then the conspiracy theories start to grow naturally when there's this kind of mistrust of that. So it's less about kind of like a deep concern about long-term effects. It's a concern about long-term effects if we find out that there's some secret stuff that we're not being told. It all lends on that. So what the heck, I mean, so I put the blame not on the data, but basically on the leaders and the communicators of the science at the top. But to that, I would say all the data, as far as I know, are made public. So you can dive into it. And I know a lot of people ask me questions, and I just say, it's right here in the data. And I know a lot of people can't do that. They can't dive into it. But that's one solution for people who are able. Now, you could argue, well, maybe they've left data out. Well, then not even I can help because then they're hiding it from me too. And I think that's highly unlikely. I think for the most part, the FDA requires the release of all the clinical trial data, right? So, okay, so this clinical trial data, that's one thing. So that's the data that we should be focusing on, right? So there's a lot of different data sets here. So there's preclinical data, which is everything that was done in the lab before this vaccine ever went into a human arm. It's all the cell culture work that we talked about a little experiments in animals. All of that is publicly accessible. Most of it gets published. And then there's the initial drug filing, which is huge, the books of diet. You can get that and look at it, right? This is me sort of asking sort of difficult questions here. Okay. So there's a lot of money to be made by makers of vaccine. So for these companies, obviously there's a distrust of those folks too. They've done a lot of really good things in this world, but the incentives are such that you want to sweep stuff under the rug. If you're not 100% pure in your ethics and how hard is it for that data to be fabricated, manipulated, like what's your intuition for the pre-trial stuff? I think when you start fabricating, then you get inconsistencies, which are pretty easy to pick up. When you're talking about some large scale things of this nature. Because then you can look through the data very, you're gonna, I mean, we require looking very carefully, but you will see inconsistencies from one trial to another. And that may ring a bell that something's been done. Yeah. It's like the moon landing thing. Sometimes like going to the moon is easier than faking. Right. In the sense it might be easier to do a large scale trial and get an effective vaccine versus faking it. But you know, when you brought up the for profit issue, I think that has always been an issue. I've always felt that having your health depend on for profit industry may not be the best solution. And I don't know how else to do it. People tell me I'm a dreamer, thinking that all medicines could be non-profit. But I also think that the world should have one health system that takes care of everyone, right? Because there are some countries that can't and other countries have an excess like us. So I wish we could do that. Well, the argument is the speed of which the vaccines for COVID were produced would never happen in a non-profit system, would never happen in a non-capitalist system. Oh, I could set up a vaccine production institute in the US that would get the vaccines done because you just need to put money into it. That's what made these vaccines get done, money. They poured billions of dollars and they got it done quickly. But if I set up a non-profit institutes of vaccines throughout the US, staffed with really talented people, pay them well, keep them motivated, you'll get your vaccines. No, but that's the thing with capitalism is that the selection of who to hire, like when you say good people, capitalism has a machine that fires people who are not good and selects people that are good. Coming from the Soviet Union, the dream of communism is similar to what you're saying, broadly defined. It certainly doesn't work in the broad, the question of whether it works in the healthcare space. There is some aspect to the machine of capitalism being the most effective way to select for good people to effectively produce the thing. But then of course, a lot of people would argue the current, even the current healthcare is not with like regulations. There's some weird mix where there's a lot of opportunities for inefficiencies, there's a lot of opportunities for bureaucracies. You have like the worst of all worlds. Can't there be some intermediate that works? Because, I mean, the other issue that we haven't mentioned is that politics gets thrown into this and that really messes up and it should never be mixed with healthcare, but it is because a lot of funding comes from the government so that's another confounding factor. But I really think I could make a vaccine institute that if someone didn't do well, I'd fire them. No, you're not gonna stay if you can't do your job and do it well, you don't give them incentives. But it doesn't have to be the two extremes, I think. There has to be a solution that people don't have this mistrust for a company making huge profits off of a drug. But you know what, it's funny. It seems that vaccines and antivirals bear the brunt of this criticism, yet there are many other pharmaceuticals that people rely on of all sorts. They don't seem to question and have issues with those and they have far more side effects than vaccines. It's very strange how we're picking that way, but I should also say that if you have one big vaccine institute, one of the other sets of vaccine conspiracies, I mean, I would say they're a little farther out into the wild side of ideas. But that's one way to control the populace is by injecting substances into them. People, I mean, part of that, funny enough, it probably has to do with needles versus something you put in your mouth. But there's something about the government, especially when it's government-mandated, injection of a substance into you. I don't care what the science says. If it's 100% effective, 100% safe, there's a natural distrust of what, even if this is effective and safe, giving the government power to do this, aren't they gonna start getting ideas down the line for, you know? I think that they can barely govern. I don't think they're gonna do that, but you don't have to take, unless you're a federal employee, you don't have to take a COVID vaccine. Yeah, but that largely has to do, not largely, but there is an individualistic spirit to the American people. There's this, like, you're not gonna take my gun away from me, you're not going, and I think that, you know, that's something that makes America what it is. Just coming from the Soviet Union, there's a power to sort of resisting the overreach of government. That's quite interesting, because I'm a believer, I hope that it's possible to have, to strive towards a government that works extremely well. I think at its best, a government represents the people and functions in a similar way to the one you're mentioning. But that, like, pushback, even if it turns into conspiracy theory sometimes, I think is actually healthy, in the long arc of history. It can be frustrating sometimes, but that mechanism of pushing back against power, against authority, can be healthy. I agree, I think it's fine to question the vaccines. What I have issue with is that many people put out incorrect information, and I'm not sure what their motivations are, and it's very hard to fight that, because then it's my word versus theirs. And I'm happy to talk with people about any of their concerns, but if you start getting into the stuff that just isn't true, then we have a problem. The thing I struggle with is conspiracy theories, whatever language you wanna use, but sort of ideas that challenge the mainstream quote-unquote narrative. And given our current social media and internet, like the way it operates, they can become viral much easier. There's something much more compelling about them. Like, I have a secret about the way things really work. That becomes viral, and that's very frustrating, because then you're not having a conversation on level ground. When you're trying to present scientific ideas, and then there's conspiracy theories, the conspiracy theories become much viral, much faster, and then you're not just having a discussion on level ground. That's the frustrating part, that it's not an even discussion. Can I just say one more thing? So, I mean, the internet is here to stay, so we're gonna have to figure out how to deal with it, right? But from my perspective, I was skeptical that these mRNA vaccines, that any COVID vaccine would be ready within a year. That's amazing. Me too. Plus, the way I look at the mRNA vaccine as a scientist, it's gee whiz to me. It's amazing that it worked, and I think the data are great, so I want it. As a scientist, I want it. One of the really sad things, again, with me too, as a scientist or as an admirer of science, I don't know if it's politics, but one of the sad things to me about the previous year is that I wasn't free to celebrate the incredible accomplishment of science with the vaccines. I was very skeptical that it's possible to develop a vaccine so quickly. So, it's unfortunate that we can't celebrate how amazing humans are to come up with this vaccine. Now, this vaccine might have long-term effects. That doesn't mean this is not incredible. Why couldn't you celebrate? Because I would love to inspire the world with the amazing things science can do. When you say something about the vaccines, they're not listening to the science. A lot of people are not listening to the science. What they hear is, oh, you're a Republican or you're a Democrat, and you're social signaling, doing some kind of signaling. No, I think that the vaccine you're talking about is injecting something into you, and maybe you're right that the rhetoric is like, you better take this or you're dumb, is not the right approach. I've seen, actually, it's kind of interesting. I've seen both sides kind of imply that. So, the people who are against the vaccine are dumb for not trusting science, and the people who are for the vaccine are called dumb for trusting science, the scientific institution. And nobody wins, yeah. And they both kind of have a point. Like, because you can always, it's like, is the glass half full or half empty? Because you can always look at science from a perspective of certain individuals that don't represent, perhaps, not greatest leaders, almost like political leaders. There's a lot of, you know, yesterday I went on a whole rant against, I said a lot of positive things about Anthony Fauci before I went on a rant against him. Because ultimately, you know, I think he failed as a leader, and I know it's very difficult to be a leader, but I still wanted to hold him accountable for that as a great communicator of science and as a great leader. What do you think he didn't do right? I'm curious. So the core of the problem is the several characteristics of the way he was communicating to the public. So one is the general inauthenticity. Two is a thing that, it's very hard to put into words, but there's certain ways of speaking to people that sounds like you're hiding something from them. That sounds like you're full of shit. That's the authenticity piece. Like, it sounds like you're not really speaking to the full truth of what you know, and that you did some shady shit in your past that you're trying to hide. So that's a way of communicating that I think the internet and people in general are becoming much better at detecting. Yeah, it's like you said, they're good BS detectors. Yeah, good BS detectors. But contributing to that is speaking from authority. Speaking with authority and confidence where neither is deserved. So first of all, nobody's an authority on this new virus. We're facing a deadly pandemic, and especially in the early stages, it was unclear how deadly it would be. It was unclear, probably still unclear, fully how it's transmitted, the full dynamics of the virus, the full understanding of which solutions work and not, how well masks of different kinds work, how easy or difficult it is to create tests, how many months or years it's gonna take to create a vaccine, how well in history or currently do quarantine methods or lockdown methods work, what are the different data mechanisms that are, data collection mechanisms that are being implemented, what are the clear plans that need to happen, what the epidemiology that's happening, what is the uncertainty around that? Then there's the geopolitical stuff with China. I personally believe there should have been much more openness about the origins of the virus, whether a leak from a lab or not. I think communicating that you're open to these ideas is actually the way to get people to trust you, that you're legitimately open to ideas that are very unpleasant, that go against the mainstream. Showing that openness is going to get people to trust you when you finally decrease the variance in your uncertainty, like decrease uncertainty and have, we still have a lot of uncertainty, but this is the best course of action. Vaccines still have a lot of uncertainty around them. mRNA is a new technology, but we have increasing amounts of data, and here's the data sources, and laying them out in a very clear way of this is the best course of action that we have now. We don't know if it's the perfect course of action, but it's by far the best course of action. And that would come from a leader that has earned the capital of trust from people. I mean, I think in recent history, the worst pandemic is 1918 flu, right? But that's mainly because we didn't know what to do. We didn't have many tools at our disposal. And that was tied up with World War I. That's right, that's right. So the leadership there, I mean- But I don't know what is a lot of deaths, right? And any one person is someone's family, so to them it's a lot, right? But that logic, we don't apply that logic generally, because there's a lot of people suffering and dying throughout the world, and we turn the other way all the time. And that's the story of history. So saying you all of a sudden- What bothers me, though, I mean, personally, I don't like anyone dying anywhere, but especially considering what technology we're able to muster, yet we still kill each other. It's just dichotomy to me. Yeah, but I mean, this is the, what is it, Paul Farmer. There's these great stories. I mean, that's the burden of being in healthcare, being a doctor, is you have to help. You can't help but help a person in front of you who's hurting. Sure, sure. But you also are burdened by the knowledge that you helping them, you spending money and effort and time on them, means you're not going to help others. And you cannot possibly allocate that amount of time to everybody. So you're choosing which person lives and which person dies. Sure. And you're doing so, the reason you're helping the person in front of you is because they're in front of you. And so the reason right now we care a lot about COVID is because the eye of the world has turned to COVID, but we're not seeing all the other atrocities going on in the world. They're not necessarily related to deaths, they're related to suffering, human suffering, which you could argue is worse than death. Prolonged suffering. Of course. So there's all of these questions. And the fundamental question here is, are we overreacting to COVID in our policies? So this is the, when we turn our eye and care about this particular thing and not other things, are we dismissing the pain that business owners who've lost their businesses are going to feel? And then the long, talking about long COVID, the long-term effects, economic effects on the millions of people that will suffer, that suffer financially, but also suffer from their dreams being completely collapsed. So a lot of people seek, gain meaning from work. And if you take away that work, there's anger that can be born, there's pain. And so what does that lead to? That can lead to the rising up of charismatic leaders that channel that anger towards destructive things. That's been done throughout history. So you have to balance that with the policies that you have in COVID. And then, I mean, very much my main opposition to Fauci is not on the details, but the final result, which is, I just observe that there's a significant decrease in trust in science as a, not the institution, but the various sort of mechanisms of science. I think science is both beautiful and powerful. And the reason why we have so many amazing things and such a high quality of life. And distrust in that, the thing we need now to get out of all the troubles we're in, continue getting out of the troubles we're in, is science, the scientific process, broadly defined, like innovation, technological innovation, scientific innovation, all of that, distrust in that is totally the wrong thing we need. And so anybody who causes a distress in science, to me, carries the responsibility of that. And should be, because of the response, it means should be fired, should be, or at least openly have to carry the burden of that, of having caused that kind of level of mistrust. Now, it's maybe unfair to place it on any one individual, but you have to, I think even your pocket said, the buck stops at the top. Like the leaders have to carry. There's a clear leader here, yes, absolutely. So even if it's not directly his fault, you know, he has to carry the price of that. Do you think we should, at this point, say, okay, we have vaccines, you can decide whether you take them or not, let's move forward? Maybe you can help me understand this, because it seems like, why is that not the right solution? Completely open society, the vaccines, at least in the United States, as I understand, are widely available. So this is the American way, you have the decision to make. If you have conditions that make you worried to get COVID and go to the hospital, then you should get vaccinated, because here's the data that shows that it's much less likely for you to die if you get vaccinated. If you don't want to get vaccinated because you're worried about long-term effects of vaccine, then you don't have to, but then you suffer the consequences of that, and that's it. So here's what I think is driving. I think it's all about kids. Right. Because they're gonna go back to school in the fall, and many of them can't be vaccinated, right? So if they get infected, they do have less frequency of disease, but it's not zero. They do get sick, and they can have long-term consequences. And at that age, it would be a shame, right? And it's not even their choice. They can't decide to get vaccinated or not because they can't have access to it. So I think that's what would drive my efforts to try and get more people, at least in schools, vaccinated. But I might be wrong. It may not be that. Can you kind of dig into that a little bit? So there's, so you're saying that there should be an effort for increased vaccinations of kids going to school, just not for societal benefit, but for the benefit of each individual kid, right? So right now, kids under 12, right, are not yet vaccinated. Is that correct? Yeah, I think so. And it's not gonna be in time for school opening that they get vaccinated. And then, I suppose the teachers are all gonna be vaccinated. Makes sense for them to do that. But I'm just worried the kids are gonna be transmitting it amongst them. And many states don't allow mask mandate in school. So I think that's what's driving the larger narrative in the US to protect kids. It's kind of what I hear from Daniel Griffin, because increasing numbers of kids are being admitted to hospitals now, because they're becoming the major unvaccinated population. They're hanging out over the summer, and that's just gonna get worse in the fall. And so you could have a lot of kids with long COVID and disabled their entire lives, right? So. And of course, hearing from people who are vaccine hesitant, I hear exactly the kids' statement, but they're saying they don't want the long vaccine, the long-term effects of the vaccine to affect the kids. That's the, of this new vaccine. Which I would say is, as I said before, you can't say never, but we do know that long COVID exists. We don't know for how long, because we've only looked out six or eight months. We know that exists, and the frequency is increasing. It certainly exists in young kids. And we have no idea about long vaccine effects. So I think they have to make their decision based on that. But, yeah. But your question is, why don't we just open up society, say, here we have these vaccines, if you wanna protect yourself. I think it's mainly the school that's driving the whole narrative. That's my opinion. In which direction, not to open up, or? No, to open up, but to try and get, you know, their efforts at the federal level to get people vaccinated, right? But see, how high are the risks for kids? I mean, my understanding was it's, I mean, yes, it's non-zero, but it's very low. But what is the numbers? Now, 70,000 hospitalizations so far in kids as of last week. So yes, it's low. But polio was low. Polio was 20, 30,000 kids a year paralyzed. And, well, many people have actually argued that that vaccine wasn't necessary, you know? That it wasn't a substantial enough health problem. But paralyzed is different than hospitalized. So what does hospitalized mean? Long COVID. But this is the long COVID question. I mean, this is the open question. Yes. What is long COVID in kids? What is that? So, well, a lot of the same issues, cognitive issues, motor issues, respiratory, GI dysfunction. How long? We don't know. I mean, it could end in a year. As you know, there are other post-acute infectious sequelae that we know about. You know, chronic fatigue, ME, CFS. It's thought to be a post-infectious sequelae, which has gone for many decades now in many millions of people. This could be another one of those. So I'm just saying it might be worth erring on the side of not letting the kids get infected. Yeah, well, I'm trying to keep an open mind here, and I appreciate you doing the same. Of course, I lean on definitely not requiring people to get vaccinated, but I do think getting vaccinated is just the wiser choice. If looking at all the different trajectories before us, getting vaccinated seems like, from the data, it seems like the obvious choice, frankly. But I'm also trying to keep an open mind. There's some things in the past that seemed obvious but turned out to be completely wrong. So I'm trying to keep an open mind here. So for example, one of the things, I'd love to get your thoughts on this, is antiviral ideas, so ideas outside of the vaccine. So ivermectin, something that Brett Weinstein and a few others have been talking about. There's been a few studies. Some of them have been shown not to be very good studies, but nevertheless, there seems to be some promise. And I wanted to talk to Brett about this particular topic for two reasons. One, I was really bothered by censorship of this. That's a whole nother topic. I'm bothered by censorship. There's a gray area, of course, but it just feels like that should not have been censored from YouTube, like discussions of ivermectin. We can set that aside. The other thing, I was bothered by the lack of open-mindedness on exploring things like ivermectin in the early days, especially when, at least I thought, the vaccine would take a long time. I mean, it's not just ivermectin. It's really seriously, at a large scale, rigorously exploring the effectiveness of masks. And the big one for me is testing, like the fact that that wasn't explored aggressively to lead to mass manufacturing, like May 2020, is absurd. Anyway, so I was bothered by these solutions not being explored and not, by now, having really good ivermectin studies. So can I talk about ivermectin? Yeah, I would love that, yeah. Sure, so full disclosure, my wife worked on ivermectin at Merck for 20 years. Okay, so I just want people to know, but I don't talk to her all the time about it. And anyway, she hasn't been at Merck for a long time. As you know, ivermectin is a very safe drug used to treat certain parasitic infections, right? And it is approved, it's amazing. You can take one dose a year and be protected against river blindness in Africa, in certain parts of Africa. It's remarkably effective. And so it's quite a safe drug at the doses that are approved. Now, early last year, a study was done, I believe in Australia, which showed in cells in the lab, if you infect with SARS-CoV-2 and put ivermectin in, it would inhibit the virus production substantially. It was quite clear, right? But the concentrations they were using were rather high and could not be achieved by the approved dosing. So you would need to do a dosing study to make sure it's safe. And the reason is that ivermectin binds to receptors in your brain and it can have high doses. Some people take high doses inappropriately and they have neurological consequences. So if you needed 10 times more ivermectin, you'd have to make sure it would be safe. So this is a question of safety too. Right. So I think it has always been the case that it should have been properly studied, but it wasn't. There were lots of trials here and there, lots of improperly controlled trials where someone would just treat some patients and say, hey, they all did fine, but have no control arm. And there were some controlled trials, but they were very small. So right now, a 4,000 person trial is enrolling to test in a randomly controlled trial setting, whether it works or not. There's still plenty of cases that you can do that. So you can ask whether there are any side effects. I think that's completely fine. And if it says it works, then we should use it. In the meantime, I always tell people, if you wanna use ivermectin, you can do it off-label. It's FDA approved. And if your physician says, I'm gonna give you this off-label, I don't have any objection, but I don't know if it's gonna work. Now, a friend of ours last week in New Jersey got COVID. He went to his local hospital and their regimen was remdesivir, dexamethasone, ivermectin. It's written, that's what they do for every COVID patient. They just give it to them automatically. And so he recovered. So who's to say it was or was not ivermectin, right? So I don't have any strong ideological opposition. I just think it should be tested for what you wanna use it for. And that's being done, and I think that's fine. Is it strange to you that ivermectin or other things like it weren't tested aggressively in the beginning? From a broad scientific community aspect, I can be a little bit conspiratorial, and this is what people talk about with ivermectin, is with the vaccines, there's quite a lot of money to be made. With ivermectin, there's not as much money to be made. Is that too conspiratorial? Like why didn't we try more solutions in the beginning? Well, all the money was put into vaccines, right? Very little was put into antivirals. Because the decision was made at a very high level, probably involving Dr. Fauci. We're gonna put 24 billion into vaccines, right? And I think part of the reasoning is they give you years worth of protection, whereas an antiviral works and you have to keep dosing and so forth. But ivermectin is not trivial. I agree, it should have been tested early on, but we had a really bad experience with hydroxychloroquine, which we can talk about too. Ivermectin is very hard to synthesize. Most drugs you synthesize chemically. You devise a formulation and a synthesis, and they do it, they scale it up, and it's fine. Ivermectin's really hard. And so what they do instead is they take the culture of the bacterium that makes it, and they grow it up, and they ferment it, and then they purify it. And Merck owns the bacteria. A number of years ago, two employees of Merck stole it and left the company and tried to market it, and they were arrested and they got put in jail. So they protect it very carefully. So you can't just make it. If you do, it's incredibly expensive. And now India, it's very cheap, apparently. They use it quite liberally there. And I don't know how they're making it. Maybe they've licensed it from Merck and so forth. But that's why it hasn't been tested more widely, I think. There's complexities in terms of getting a lot of it and manufacturing a lot of it. Yes. Okay, so what was the hydroxychloroquine? So hydroxychloroquine was also shown early on to inhibit virus in cell culture. And that's not surprising. Hydroxychloroquine, of course, is used for malaria. And what it does, when your cell takes up things from the plasma membrane, including viruses, it goes through a pathway called the endocytic pathway, which involves a vesicle moving through the cell. And as it moves through the cell, its pH drops. And that lets a lot of viruses out, actually. And hydroxychloroquine blocks that. So it blocks infection with a lot of viruses. So the problem with those early studies that were published is that they were done in kidney cells in culture, where the only way the virus can get in is through the endosome. And hydroxychloroquine inhibits that, and that's why it inhibits in kidney cells in culture. But lung cells and respiratory cells of humans where the virus reproduces can get in two different ways. It can get in from this endocytic pathway, which is inhibited by hydroxychloroquine, or it can get in at the cell surface, which is not inhibited by hydroxychloroquine. So when you treat patients, it has no effect in the lung because the virus can just bypass it. And all the usage initially were based on the studies done in kidney cells in culture. So that was just wrong, scientifically incorrect, yet it drove a lot of, and today, many people still think they should be taking it, but. So like that not panning out kind of resulted in a loss of optimism about other similar things panning out. Well, that and many other drugs, repurposed drugs were tried, right? A lot of HIV antivirals were tried. I think the problem with hydroxy, I think hydroxychloroquine influenced the ivermectin narrative, right? People thought that data was being hidden about hydroxychloroquine, so they said, well, they must be doing the same thing with ivermectin. But with hydroxychloroquine, it just scientifically could not work as an antiviral. The other problem that is more broad that is important to point out is that when you have COVID and you need an antiviral, it's usually because you can't breathe and you go in a hospital. Because if you're mildly ill, you're never gonna go to your doctor and ask for an antiviral. And the problem is when you can't breathe, it's no longer a viral issue. It is now an inflammatory issue, and no antiviral in the world is gonna help you. So that's why remdesivir doesn't work very well, because it's mainly given intravenously to people who go in a hospital. If you get ivermectin in the hospital, it's not gonna do anything for reducing virus, because by that time, you have very little virus to begin with. You have an inflammatory problem that you need to treat in other ways. So this is why a lot of the antivirals failed, because they're used too late. What you need is a pill you take on that first positive test, when you have a scratchy throat. You get a PCR in 15 minutes, I'm positive, take a pill, boom, that's gonna inhibit it. If you wait till you can't breathe, and that's why the monoclonals even don't work if you're in a hospital that well, because it's too late. And the approach now is if you're in a high-risk group, if you're over 65, if you are obese or have diabetes or any other comorbidities, your first sign of a scratchy throat positive, you get monoclonals. Then they might help you. But if you wait till you go in a hospital, it's too late, because the viral curve drops after that first symptom. Within three days, you're no longer shedding enough virus to transmit. Drops really quickly. So that's the reason a lot of these antivirals failed, because they were tested in hospitalized patients. And we have nothing but remdesivir now, unfortunately, so it was the wrong approach. We should have been giving it to people who just tested positive from the start. But. Or just even for preventative and see. You could do that too. Yeah. But I have to say, the other issue is, this molnupiravir is a drug in phase three now. It's an oral antiviral. It looks good. If we go ahead with just one, we're gonna get resistance within a few months, and it will be useless. We need to have at least two or three drugs that we can give in combinations. And we know that, because that's what took care of HIV. That's what took care of HCV, hepatitis C virus. It really reduces the emergence of resistance. Joe Rogan got quite a bit of heat recently about mentioning a paper and a broader idea, which I don't think is that controversial, but maybe we can expand on it. And the idea is that vaccines create selective pressure for a virus to mutate and for variants to form. First of all, from a biological perspective, can you explain this process? And from a societal perspective, what are we supposed to do about that? So let's get the terminology right. So as we talked about earlier, viruses are always mutating. So no vaccine or no drug makes a virus mutate. That's the wrong perspective in which to look at it. What the immune response is putting pressure, selection pressure on the virus. And if there's one particle with the right mutation that can escape the antibody, that will emerge. So that's what happens with influenza virus. We vaccinate every year and there are not a lot of people that get infected, so they get natural immunity. And then the virus is incredibly varied. It mutates like crazy. And in some person somewhere, there's one variant that escapes the antibody, which has been induced either by infection or vaccination. It can be both. And that drives the emergence of the new variants. So the next year we need to change the vaccine. So I would say both natural infection and vaccination, sure, select for variants. Absolutely, there's no question, because they're inducing immunity. Now, what happened last year was at the beginning of 2020, very few people in the world were immune as the virus first started spreading. But you can see in the sequences of those isolates from the beginning of 2020, you can see all of the changes that are now present in the variants of concern at very, very low frequencies. They were already there, but there was no selection for them to emerge. Until November, when we now had many millions of people who had mostly been infected, but also some vaccinated, then we saw the alpha variant emerge in England, probably because of immune selection. Now the virus that had the change that evaded the antibody had an advantage, and that virus drove through the population. So that's what we're seeing. We're seeing all these variants are simply antigenic selection. So the variants, the mutations that are at the core of these, quote unquote, variants, they were always there all along. The vaccine or the infections did not create them. No, the infections don't create them, they're selected. It's like the vaccine wipe out a lot of the variants, and then by making your body immune to them, but some of them survive. And then there's another tree that's built, and it's unclear what that tree leads to. I mean, it could make things much worse or much better. We don't know. Well, with flu, we see year after year, the virus changes. We change the vaccine, we deal with it, we change it again, there's an unending series. But see, that's a very different story. If do you think, do you think COVID will be with some likelihood like the flu, whereas basically variants will never be able to eradicate it? It will never eradicate it in any case, ever. Well, come up with a vaccine that makes you immune to enough variants where there's not enough evolutionary like room. Well, if you cut down the number of infections, then you reduce the diversity, sure, right? The problem is if, let's say you're a cynic and you say, well, vaccination is just selecting for variants, so let's stop it. But then you're gonna have infection, and that's gonna select for variants. And there, you're more likely to get very sick because we know the vaccines are really good at preventing you from dying. So that's why it still makes sense to use vaccines because they prevent you from dying. That's the bottom line. But can we ever make a vaccine that deals with all variants? Absolutely. And the reason I say that is because people who get naturally infected with SARS-CoV-2, they develop COVID, they recover. If you give them one vaccine dose, they make an immune response that handles all the variants that are around right now. All of them, much better than people who've gotten two doses of vaccine. For some reason, their immune response has suddenly broadened after the infection vaccination, and they can handle all the variants that we know of so far. So that tells me we can devise a strategy to do the same thing with a vaccine that makes a really broad vaccine that'll handle all the variants. Well, you actually, on the virology blog, I don't know if you're the author of that, but- I am, yes. Oh, the blog, yes, but there's a particular post that's talking about reporting on a paper that a mix and match strategy- Oh, yes, that's one of my co-writers, Trudy Ray, yeah. Yeah, it's an interesting idea that there's some or early evidence now that mixing and matching vaccines, like one shot of Pfizer and one of like Moderna or something, that creates a much better immunity than does two shots of Pfizer. I think that's worth exploring, absolutely. And this is relevant, that what we're doing with influenza, instead of having to vaccinate people every year, why can't we devise a vaccine which you'd get once in your lifetime or maybe once every 10 years, okay? So the spike of influenza, it's a long protein, kind of like the spike of SARS-CoV-2, it's stuck in the virus membrane, and the very tip, that's the part that changes every year. That's where the antibodies bind. But the stem doesn't change. And if you make antibodies to the stem, they can also prevent infection. It's just that when people are infected or with the current vaccines, they don't make many antibodies to that stem part. But we're trying to figure out how to make those, and we think they would be broadly protective, and you'd never be able to, or more rarely be able to have a variant emerge that escaped it. And I think we can do the same thing with coronavirus too, for sure. Can I ask you about testing? Sure, sure. So you mentioned PCR, what kind of tests are there? The antigen test, what are your thoughts on each? Maybe this is a good place to also mention viral load and the history of the virus as it passes through your body in terms of what's being tested for and all those kinds of things. So the first tests that were developed were PCR, polymerase chain reaction, they're basically nucleic acid amplification tests. And the very first ones, they stuck the swab all the way up into your brain almost. I had that done a couple of weeks ago. Oh my gosh, it's really nasty. But now they do an anterior nares swab. They get a bunch of cells and some mucus, which has virus and parts of virus, stick it in a test tube, and then they run a reaction, which by the way, involves reverse transcriptase, because it converts the viral RNA to DNA, and then you amplify it. And you can specify what part of the viral RNA you want to amplify. And then a machine will detect it, and it can be done in 15 minutes. But you're detecting pieces of RNA, not infectious virus. So we're measuring viral RNA loads, right? And a common mistake that many people who should know better, you know, physicians and scientists of all kinds, they think that indicates how much virus you have. It doesn't. It's a diagnostic of whether you have bits of RNA in you, and it probably means you're infected. But you can't use it to shed light on what's going on. And I'll tell you why in a bit, but first we have to explain some other things. So until you get to about a million copies of RNA, so you can measure the copy number in this test, this PCR test. It's a number called CT, or cycle threshold. The test, the way the machine works, it goes through cycles. In every cycle, it amplifies what you put in. And the more cycles you need to see something, that means there's not a lot of RNA there. So if you do a test and you have a cycle threshold of 35, you have very little RNA in you. Contrary, if you have a cycle threshold of 10, you have a ton of RNA, and you only took 10 cycles to detect it. And you can extrapolate from that number the number of copies you have per sample, say per swab. And if you don't have a million, you're not infectious. You're not gonna infect anyone. So in the early days, no matter what PCR result you had, they would quarantine you. And that was wrong because you're not shedding. You don't need to be quarantined, but it wasn't thought through properly, right? And that's where you had like 14 days or something like that. 14 days, which is now we know is too long because you don't shed for that long in a normal infection. Now it's 10 days should be fine. So what happens is you get infected. You don't know it, of course. The virus starts to grow very quickly. And within four or five days, you reach a peak of shedding. You're making a lot of RNA, and you may be asymptomatic. You're shedding, you can infect others. And then you may or may not have your symptom onset. So you shed for a couple of days before symptom onset. And then within three days, four days, the viral RNA crashes and you're no longer shedding. You're no longer transmitting. So that's the one kind of test we have. It can tell you if you're infected at the moment, but it won't tell you if you're gonna be infected tomorrow. Because if you're negative today, you could be positive tomorrow. You just might be in a different part of the incubation period. So that's one test been used the most. You can now get 15 minute versions of them in a walk-in or whatever. Fine, then there are antigen tests, which look for the proteins that the virus is making. So as it's reproducing in your nose, it's not only making genomes, it's making proteins. And so these you can buy in the drugstore. And these would have been great if they had, you know, Michael Mina last year had the idea that if we could make a little stick, a little piece of paper that you would suck on and it would tell you if you're infected or not, if this could cost less than a buck, everybody could test themselves. Which they can cost less than a buck, by the way. Yeah, but they were never made, right? Right. They're never mass manufactured. So his idea is to do like daily tests. So here's the most- Yeah, daily and then the kid's going to school, he's positive or she's positive. Well, if it's cheap enough, you just take another test because they have a certain error frequency. If it's positive twice, you stay home and the next day you try again. And I think this would have revolutionized because the PCR tests are more expensive at the time and they take longer to do and so forth. But that never happened. But now we do have $20 BinaxNOW and others that you can buy and people buy them and- See, but that can still happen, right? And this is the very frustrating thing to me because I'm worried about variants, but I'm also worried about future much more deadly pandemics. I know we kind of said, yes, COVID, lots of deaths, but it could be a lot worse too. So I'm thinking what is going to be the right response for the future pandemic of its kind? And what's the right response for continued number of variants and some of the variants might be deadlier or more transmissible? Well, we can, the antigen tests will pick up the variants. That's not a question. The PCR may be influenced by changes, but you can quickly adapt the primers that you use. So that's not- But that's what I mean. Like to me, all these discussions about vaccines and so on. Vaccines, we got very lucky that they took so little time. Right. And you have to be aware, no matter what, that there's hesitancy with the vaccines in this country. Before, I mean, yeah, that's a reality. You can't just be like magically saying that- That's right. You're going to overcome that. And I don't think there's any hesitancy and cheap tests at home. I agree. I think if someone, so the question is, if someone tested positive, would they stay home? That's the question. What if their job depends on them going in? I mean, that's- Well, you have to look at sort of aggregate. Yeah. How many people would decide? And I think, again, a lot of that is in leadership, but I think a lot of them, I would say most people would stay home. I think that Mena had the idea and it would have changed the whole situation for sure if it could have been made when we talked to him last spring, I think, or summer. We would have gotten around a lot of the issues that we're in today because I think people would have stayed home and not transmitted. And I think it's still valuable to this day. In the fall, if we don't have vaccine uptake, we could just test kids every day and get them and keep them home when they're infected. It cuts, it's, and we don't have it. But I think, and I'm not privy to what was going on, but I don't think a lot of emphasis was put on testing early on. The CDC developed the first one. It was flawed. They had to recall the kits. I mean, that was a fiasco. They should have had 100 companies making the tests initially, right? So for the future, I think what we have learned is we need to have a rapid antigen test right off the bat that's doable. You can't do it in a day like you can for PCR because you need to make antibodies to the protein that you're looking for and you need to do those in animals, but you can do it in weeks and we should be ready for that. Yeah, because, I mean, to me, that's obvious. That's obviously the best solution. Second to that, if we understood how well masks work. Like, maybe let me ask you this question. Let's put masks aside. How well do we understand how COVID is transmitted? There's droplets of different sizes, aerosols, tiny, tiny droplets. It seems like that's a very difficult thing to understand thoroughly. So it seems like it's transmitted both ways. It's unclear how exactly. So how much do we understand and why is it so difficult to understand fully? I think it's clear that it's transmitted through the air mostly. It's not touching. We thought initially it would be a lot of touch, but very little of that. It's through the air and when you talk, mainly when you talk, you expel a lot of droplets, right? Even the plosives that your foam thing here are meant to pee, right? That you send out little sprays and those have viruses in them. And the big drops fall to the ground and the little ones can go 100 feet or more, right? But the little ones also have less virus in them. So I'm not sure, well, we certainly do not know how much virus you need to be infected. But it's probably at least several thousand particles, if not more. And it could be that for most people, the tiny droplets don't have enough virus to infect someone else. But there's one observation about this virus that's really interesting. And that is that 80% of transmissions are done by 20% of the people, of the infected people. Not every infected person transmits. That's been borne out in multiple studies. And in fact, there's a study at University of Colorado where they quantified the viral RNA loads in all the swabs that had been done of students for like a six month period. And most of the infectious virus, most of the RNA copies were found in 15 to 20% of the people. The rest had really low and they probably, that's probably why they don't transmit. So those are the ones that might get enough virus in the tiny droplets to be able to infect someone at a distance. And I think that's entirely possible. Why is it hard to study? You can't do it in real life because you don't know who's infected. And if you do this, there's not a controlled environment to measure droplets and so forth. You'd have to do it in a laboratory situation. If you use an animal, you just don't know what the relevance of that is to people. You'd have to use human and do challenge experiments. And we don't do that at this point, at least not for this virus. So that's why it's hard to know what's going on. So we have to make inferences from epidemiological associations where you're studying say transmission in a household where people are stuck in the same rooms together and you can get an idea of what kind of droplets were involved in that. So that makes it much harder to, if you're leaning on epidemiological stuff as opposed to like biophysics or something like that. Very hard. So that makes it, but that makes it really hard to then develop solutions like masks, to ask the question, how well do masks work? Because then to answer that question, you can lean on epidemiological stuff again, like looking at populations that wear masks versus don't wear masks, as opposed to actually saying, like from an engineering perspective, like what kind of material and what kind of tightness by which amount decreases the viral load that's received on the other end? But some experiments have been done with masks and just droplets with no virus in them, right? Yes. And you can measure the efficiency of different mask materials at keeping those in. So if I say that this mask stops 70% of this or larger size droplet, that leads to this percent decreased transmission. And also on both the generation and the receiving end and the giving end. Sure. So how well do masks protect you from others? How well do you do mask protect others from you? Like all of those things seem like they could be more rigorously studied. There's no doubt about it. And now is the time because once this is over, nobody's gonna do it. Nobody's gonna care. No. But it seems like to me, so tests is one thing, but masks, like the good mask, whatever the good means, whatever that means, like some level of a quality of material on your face, if it's shown to actually like thoroughly shown to work well, that seems like an obvious solution to reopen society with, if you have a good understanding of how well they work. Because if you don't have a good understanding, if there's a lot of uncertainty, that's when you get, and you have people speaking from authority, that's when you start getting the politicization of the solution. Of course, of course. No, the data, there are some data. Most, they're mostly epidemiological and they show some effect in some countries, right? But they could be way better. Yeah. But the fact that they're not perfect, then people take advantage of and say, well, look, they don't work that well, so I'm not gonna wear it. I think, as you said, people can use it as an excuse. But even if it works, so Daniel always says a mask will cut down transmission by 50 to 60% and then distance will do another 30%. Yeah, those numbers are made up though. I mean, they're not made up, but they're estimates. Absolutely. And many of them are based on models, right? Yeah. We will make this model and let's say the mask cuts down this much, what will be the effect on it? I mean, yeah, they're models and it's for the same reason. I don't believe the transmission of the variants because it's all based on statistical models as well, not biological experiments done in the lab. So in that sense, vaccine data is much better than mask data. For sure, for sure. So my problem with the mask data, which I always thought was fascinating, I stopped talking about it. I was in a paper about masks. I stopped talking about it because what started happening is masks created assholes on both sides. The people that were like in Silicon Valley, friends of mine that were wearing masks, the way they look at others who don't is like- That's a whole nother issue, right? Yeah, I understand. That happens when you don't have solid science. Understood. They now start judging you like you're a lesser human being. You're not only dumb, but you're just, you're almost like evil. You're doing bad for society by not wearing a mask. And then the people looking in the other way are seeing you for the asshole that you're being for judging them unrightfully. So they almost want to say F you by not wearing the mask. And there's this division that's created. That was heartbreaking to me because masks, like testing, is a solution that was available early on. And if understood well, it could be deployed in a mass scale and it seems like there's some historical evidence for other viruses where it does very well. That's correct. And so the fact that this was politicized, yeah, was a little bit heartbreaking. You can find in the literature studies, mostly of healthcare workers and influenza, where you can actually, because you see the people every day, they can sample them. You can actually see what masking does. And some of them show an effect and others do not. Then that's the problem. Like any trial, sometimes if it's not big enough and then people latch onto that, see, it doesn't really work. But I think the main issue is that in January, both CDC and WHO said masks don't work, don't use them. That was the kiss of death for masks because when they then changed their mind, they didn't say we screwed up. They just said wear masks. If they had said we made a mistake, we were wrong, I think more people would have worn masks. But they didn't. And like you said, admitting you're wrong is like a real big part of it. And I also think almost the better way is not just saying you're wrong, but in January, revealing the uncertainty under which we operate. Like actually reveal what was done with the Spanish flu at the beginning of the previous century, because there's a lot of mask controversy then too. It went back and forth. And that was actually the source of a lot of distrust there too. So, and then look at influenza, like how is it effective with that? And just reveal this, we don't know, but with some probability, this is the best option we got currently. And then in a month or two, adjust it, saying that, you know what, our uncertainty decreased a little bit. We have a better idea. Like that was an incorrect estimate, but reveal that you're struggling. It's not like this weird binary clock that goes one direction or the other. You're struggling with uncertainty. And like trusting, people maybe criticize me sometimes for this, but I think most people are actually intelligent. Like trusting the public to be intelligent with if you give them, if you have transparent and give them information in a real authentic way, like don't look like you're hiding something. I think they're intelligent enough to use that data to make decisions. It's the same thing as with the testing, is if you put that power in the people's hands to know if they're sick or not, they're gonna make en masse the right decision, I think. The masks and the testing has been a bit heartbreaking. I think it's a good point though, that most people don't seem to have an objection to testing. It's a good point. Yes. And then obviously, Moccamino makes that point brilliantly. And still, there's very little excitement around that. But he said he was going to do it. I don't understand. I mean, I haven't spoken to him since then, so I don't know what. He's pushing it. Well, I mean, but he can't do it alone. He has to get, so one of the resistances, FDA doesn't like cheap things. Yeah. They don't wanna approve it, so they makes the mass manufacture, like with the emergency exceptions, all those kinds of things, very difficult. And then there's not much money to be made on it without that. I don't know. I think there's just economic pressures against it. And because so much investment was placed on the vaccines, and obviously, there's an incentive mechanism there, where the companies, lobbyists and all those, there's this machine that says, arguing for tests is difficult because the thing that's worked for most severe viruses in the past is vaccines. Now we have vaccines, why the hell would you need tests? At that time, like, why the hell do you need tests when we can be working on vaccines? It seems like the obvious thing to be working is the vaccines from their perspective, but it's not obvious at all to me. I think you should have both. I think have vaccines and good testing, and that covers you really well because you're always gonna have people who don't get vaccinated. I don't know if you've been paying attention to this. There's a guy named Brett Weinstein, there's a guy named Sam Harris. They have good representation, I would say, of two sides of a perspective on vaccines. So from Sam Harris's perspective, it's obvious that everybody should get vaccinated and it's irresponsible to not get vaccinated. I think he represents a lot of people's belief in that. And then Brett talks a lot about ivermectin, but also talks about a hesitancy towards the vaccine for people who are healthy, for people who are younger, that kind of thing, and saying we should consider long-term effects of the vaccine in making this calculation. What do you make about this conversation? Some of it happens on Twitter, some of it happens in the space of podcasts. Do you pay attention to this kind of thing? What's your role in this? What do you hope is the way to resolve this conversation? Do you think it's healthy? Well, a conversation's always healthy, but to make definitive statements is not because it suggests you have information that you don't have. We talked about long-term effects. I think you need to balance those versus long-term effects of the disease, and you can make your decision. I don't think you need to tell everybody to get vaccinated. I think you need to present the case. You say, here, we made good vaccines. Here are the safety profile. Here's the risk-benefit balance, and you should decide. You're a smart person. You should decide. Now, companies are gonna do differently, right? Companies may say you have to be vaccinated to work here. My employer, Columbia, said we have to be vaccinated to work in the fall, and if you wanna be a student, you have to be vaccinated, so you decide whether you wanna go or not, but the idea that you should make a decision based on long-term effects, there is no evidence, right? So how can you make a decision when we don't have evidence, whereas we do have evidence that there are long-term effects of getting COVID, so I don't think that's a fair argument, and it just makes people scared to say that, but on the other hand, for someone to say it's a no-brainer and to denigrate people for not being vaccinated, that's not the approach either because they're gonna dig in and say, I'm not doing this because you tell me to, right? I think the middle ground is to say, take a bit of both and say, here are the potential issues and here are the benefits, and this is what I would do, and you have to just decide on your own. I'd leave it to them. I say, you decide, and if you don't want to, you know, it's up to you. You don't have to get vaccinated, and you'll probably get infected at some point, and maybe you'll be okay. But here's the best available data, and it looks like the vaccines are a pretty, pretty damn smart solution. They seem to work. I think you tell people what you did and present both sides calmly, and I think digging in, you know, like in a debate, I don't think that's terribly useful, so that's my view. I mean, people come to me all the time and ask me, I'm worried, what should I do? And I say, what are you worried about? Let's talk about it and go through it calmly, and if they want to still take ivermectin, I say, it's fine, it's your choice. You don't have a problem with that. I love that. I love that's the way you think. People should definitely listen to This Week in Virology and follow your work. It's brilliant. I've been really enjoying it lately. It's like, it's my favorite way to stay in touch with the happenings of COVID. Obviously, you put in a lot of other stuff in there, but. We used to do other viruses before COVID. It was quite interesting, and I'm trying to slip other viruses in because I think they're informative in many ways, and we're gonna do more and more of that, but I have to say, I canceled, usually I record on Tuesday and Friday, and I canceled today so I could be with you. It's a huge honor. I appreciate that. No, no, it's fine. I think a couple of other people were gonna be away anyway. So I do a lot of different pods. They're all on YouTube, and I also do a live stream on Wednesday nights on YouTube, which you can find, and that's where people can come and ask questions. We don't have an agenda. We just start, and by 30 minutes in, there's 700 people with questions that I can't even get through because there's so many of them, and I'm actually astounded that so many people have really good questions. Most of them are reasonable, and they come back every week, so it's turning into a great forum to have a nice discussion. And the YouTube channel is called what? So you could search for my name, which is Vincent Radcaniello. It'll turn up, or my handle on YouTube is ProfVRR, P-R-O-F-V-R-R. Have you read The Plague by Camus by any chance? Years ago, years ago. I have to read it again. That's really relevant. Let me ask you a question about it. It describes a town that's overtaken by a plague, and it's blocked off from the rest of the world, and it reveals the best and worst of human nature. That's how people respond to that, sort of the encroaching, their own mortality, their own death on the horizon. I think one of the messages in the book that ultimately, like love for others. So it's like a lot of people wanna become isolated, and they hide from each other, but ultimately the thing that saves you is love, which is one of the things I've, just watching this pandemic, with the distance, with the masks, that's all fine, but there's a distancing from people, of that attention, the breaking of the common humanity between people. That's one of the reasons I, when I came to Austin earlier this year, just to visit, I fell in love with the city, because even with the masks and the distance, there was still a camaraderie, like a, I don't know, just a love for each other, just a kindness towards each other. And that's what I took away from the plague. Mostly it's told the story of the doctor, who basically gives in and just gives himself as a service to others. And that love is the thing that liberates him from his own conception of mortality, the fact that he's here, he's going to die. What do you think about this, the effect of the virus? We talked a lot about biology, but the effect of the virus on the fabric of the common humanity that connects us? Well, that's what a pandemic does. It really cuts that, right? Because small outbreaks, they're local, they don't have global effects. But when you have something this big, where pretty much nobody escapes, and not just making people sick, it changes your life, right? People lose jobs, they change jobs, they move somewhere else. They have all kinds of disruptions. Kids can't go to school. Really shows you, I mean, I always like to say, a tiny virus can bring earth to its knees. A tiny virus that you can't even see, and that most people don't even think about most of the time. And the real effect is not just sickness, it's what it does to people. Because in the end, we are animals, and most animals like each other, and they interact, they have great social structures, and that makes them do well. I guess the exception is people in AI, right? They can be on their own. Well, that's why you build robots, that you fall in love with. That's right. And so I think when a, the real story is what it does to society, for sure. Which has ramifications way beyond the number of people dying, and the vaccines, and the tests, and all of that. And this one has really made a big rupture, and you could tell, not now so much, I think being out and about now, things look pretty normal, except for some people wearing masks. You would never know. I mean, the airport this morning was completely jammed. People going, and they're all on vacation, they're all wearing shorts, right? So they're back to normal, it's August. But last year, it's really different. In New York, where you're used to lots of people on the street, it was eerie. It was just quiet. But under it all, people are still, most people help each other when they have to, right? Most people are willing to, if something happens to someone, to reach out and help them. There are always exceptions where people are mean, and that's just the way animals are. We're not the only ones that can be mean to our own species. But I think most of the motivation for everything that was done is to help other people. I mean, I do think that the vaccine manufacturers, maybe not the leaders, but the people working in the labs, really wanted to get this out quickly and help people. I think at every level, people who are contributing really wanted to help other people, and feel proud that they're able to do that. So I view it as, we're never gonna be 100% good because animals are not. Evolution made us, I mean, we're lucky we somehow rose above by having incredible brain and so forth. But a lot of our base instincts are animals, and they chase each other, and have alpha males and all that stuff. And we always have a little bit of that in us. But we do have some humanity that this really ripped up. It really did. And I think, for me, someone who studied viruses for over 40 years, it's just amazing that an invisible thing can do that, right? It goes back to the thing you found fascinating, which is a virus affecting human behavior, or behavior of the organism. Yes, so humans can make weapons and do harm, and you can see that, but this you can't even see. You can't, and look what it has done. And it'll do it again, there'll be more. I just, I wish we would be more prepared, because we know what to do. We know we should be making antivirals, vaccines, masks, testing masks, making test modalities that we can really quickly redesign. But after SARS-1, all that went out the door. People didn't do anything, and that's why we're in this situation. So, you know, people ask me this all the time. Are we gonna be ready for the next one? And I always say, we should be. We have all the information we need to know what to do. But somehow, I think people forget. That said, sometimes we really step up when the tragedy is right in front of us. We do. When the catastrophe, so I don't know. Somehow humans have still survived. The fact that we had nuclear weapons for so many decades, and we still have not blown each other up, whether by terrorists or by nation, is quite surprising. That's always, after reading the Pentagon Papers, it's even more amazing, right? So I don't know how we do it. I tend to believe there's that, at the surface, you notice the greed, the corruption, the evil, but the core of human nature, the human spirit, is one, in the scientific realm, is curiosity, and more deeply is kindness, compassion, and wanting to do good for the world. I believe that desire to do good outpowers all the other stuff by a large amount, and that's why we have not yet destroyed ourselves. There's a lot of bickering. There's a lot of wars on the surface, but underneath it all, there's this ocean of love for each other. I mean, I think there's an evolutionary advantage to that, and it would be a good explanation why we still haven't destroyed ourselves. God, we had so many opportunities. If you look at all the wars in history, so many. Yeah, I was just, my son was telling me about the Ottoman Empire, right? I mean, it's just, you know, war after war, and then other countries splitting up countries with no regard to who's living where, right? It's just, how can these people do this? Yeah, it's fascinating. Human history is fascinating, and we're still young as a species. We have a lot more time to go, and a lot more ways to destroy ourselves. Do you have advice, like you said, you have many decades of research, and an incredible career and life. Do you have advice for young people about career, about life, people in high school, people in college, of how to live a life they can be proud of? So, what I like to do is tell people, don't plan it, because I didn't plan anything. Everything I did was one step at a time. You don't have to plan. I just found things that were interesting to me. And so, my father was a doctor, and he wanted me to be a doctor, but I was not interested in taking care of people. I learned that, but I couldn't say no to him. So, you know, I was a biology major in college, and I graduated, and I didn't have anything to do. So, I liked science, so I got a job in a lab. And it was very exciting, and that led to everything else that I have done, one step at a time. And I think the most important thing you can do, well, there are two important things. You can be really curious all the time. You mentioned curiosity. I think curiosity is essential. You have to be curious about everything. And if you are, you're never gonna be bored. And so, people who say they're bored, I say, you are not curious. You should just think about things, and say, look at something, and say, how does that work? Or what is it doing, and how do they get there? And you'll never be bored. And the other thing is, when you find something, which may take time, it's fine. You have to be passionate about it. You have to put everything into it. And that's what I did with viruses. So, I think they're amazing, and I tell my classes, I love viruses, they're amazing. And people think I'm morbid, because obviously they kill people, and I shouldn't love something. But that's not the point, that's not what I mean. I love them in the way they have emerged, and how they work, and so forth, and all that we don't know about them. So, you need to be curious and passionate, and don't plan too much. And just find something that you don't call a job. As someone said on the livestream last week, I wish I had a job I liked as much as you. I said, it's not a job, I never looked at it as a job. It's my vocation, it's my passion. If it's a job, then you're not gonna like it. Yeah, something that doesn't feel like a job. So, you said viruses are kind of passive, non-living, you could say. Or even cells are passive. And humans are kind of active, we seem to be making our own decisions. So, let me ask you the why question. What do you think is the meaning of this life of ours? Oh, there's no meaning, it just happened. It's an accident. I think there's no life elsewhere, because this is just a rare accident that happened, and the right conditions. I mean, people all think I'm wrong, because there are billions and billions of stars out there, right? So, there's a lot of opportunity. There's no meaning, it's just, what do they call it? A perfect storm of events that led to molecules being formed, and eventually, I mean, it took a long time for life to evolve, right? But it's just driven by conditions. If something emerged that worked, it would then go on to the next step. There's no meaning other than that. The only difference is that we, and I think many other animals can probably, we have the ability, we're sentient, right? We can influence what happens to us. We can take medicines, right? We can alter what would normally happen to us, so we can remove some of the selection pressure. But I think everything else on the planet just goes, looks for food, and give a lot of offspring, so you can perpetuate. It's just a natural biological function. Yeah, they're much more directly concerned with survival. I think humans are able to contemplate their mortality. We can see that even if we're okay today, we're eventually going to die, and we really don't like that. So we try to come up with ways to push that deadline farther and farther away. Well, we have really, I mean, we used to die in our 30s, right? Now it's 70s, 80s. Well, most of us used to die in the first few weeks. That's true. Yeah, infant death. I always tell people the only thing that's 100% is death. It's the only thing in the world that's 100. Do you think about your own mortality? No, I never think about it. I'm just enjoying day to day, and I don't think about it. Really? You work on viruses. You don't contemplate your own mortality, given the deadliness of the viruses around us? I never thought COVID would kill me. No, I never was afraid of that, not at all. I mostly feared for other people getting sick, especially people who could die. I didn't want that to happen to them. But I always thought that, it's obviously not a realistic viewpoint not to be worried, because many people are. But I've been relatively healthy. They should sequence my genome, because it works really well, and I have a good immune system. Maybe you'd be the first immortal person. I don't think so. There's gotta be a person. I don't think so. I think that biologically, you just can't, the ends of our chromosomes keep getting shorter and shorter and that's eventually what kills us. So you just can't keep going on. But that's fine, I don't need to. I understand from the vampires that it's not good to live forever. I guess make the most of the time you got. That's the, bacteria live a much shorter time, so we got that on bacteria. Bacteria are just little bags of chemicals that split. So they have no stake in the matter at all. I think you have to go a long ways before you get into some kind of consciousness. Yeah, it's weird that this bag of chemicals has a stake in the matter. Like our human body is, consciousness is a weird thing. Not just in us, but they make half of the oxygen on the planet. 20% of the oxygen comes from bacteria. And they made, in the beginning of Earth, they made enough oxygen to start oxygenation going, life going. I mean, they have an incredible role. It's all an accident, just happened. Well, Vincent, like I told you, I'm a huge fan. It's a big honor that you were talking with me today. Thank you so much for coming down. Thank you for spending so much time with me. And thank you for everything you do in terms of educating about viruses, about biology, microbiology, and everything else. I can't wait. Everybody should check out Vincent's YouTube, watch his lectures, listen to the podcast. It's truly incredible. Thank you so much for talking to me, Vincent. My pleasure. Thanks for listening to this conversation with Vincent Recaniello. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Isaac Asimov. The saddest aspect of life right now is that science gathers knowledge faster than society gathers wisdom. Thank you for listening and hope to see you next time.

https://youtu.be/G433fa01oMU

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Philip Goff: Consciousness, Panpsychism, and the Philosophy of Mind | Lex Fridman Podcast #261

I believe our official scientific worldview is incompatible with the reality of consciousness. Do you think we're living in a simulation? We could be in the matrix, this could be a very vivid dream. There's going to be a few people that are now visualizing a pink elephant. A hamster has consciousness. Except for cats who are evil automatons that are void of consciousness. Consciousness is the basis of moral value, moral concern. Do you think there will be a time in like 20, 30, 50 years when we're not morally okay turning off the power to a robot? The following is a conversation with Philip Goff, philosopher specializing in the philosophy of mind and consciousness. He is a panpsychist, which means he believes that consciousness is a fundamental and ubiquitous feature of physical reality, of all matter in the universe. He is the author of Galileo's Error, Foundations for a New Science of Consciousness, and is the host of an excellent podcast called Mind Chat. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Philip Goff. I opened my second podcast conversation with Elon Musk with a question about consciousness and panpsychism. The question was, quote, does consciousness permeate all matter? I don't know why I opened the conversation this way. He looked at me like, what the hell is this guy talking about? So he said no, because we wouldn't be able to tell if it did or not. So it's outside the realm of the scientific method. Do you agree or disagree with Elon Musk's answer? I disagree. I guess I do think consciousness pervades matter. In fact, I think consciousness is the ultimate nature of matter. So as for whether it's outside of the scientific method, I think there's a fundamental challenge at the heart of the science of consciousness that we need to face up to, which is that consciousness is not publicly observable. I can't look inside your head and see your feelings and experiences. We know about consciousness not from doing experiments or public observation. We just know about it from our immediate awareness of our feelings and experiences. So- It's qualitative, not quantitative, as you talk about. Yeah, that's another aspect of it. So there are a couple of reasons consciousness, I think, is not susceptible to the standard or not fully susceptible to the standard scientific approach. One reason you've just raised is that it's qualitative rather than quantitative. Another reason is it's not publicly observable. So I mean, science is used to dealing with unobservables, right? You know, fundamental particles, quantum wave functions, other universes, none of these things are observable. But there's an important difference. With all these things, we postulate unobservables in order to explain what we can observe, right? In the whole of science, that's how it works. In the case of consciousness, in the unique case of consciousness, the thing we are trying to explain is not publicly observable. And that is utterly unique. If we want to fully bring science into consciousness, we need a more expansive conception of the scientific method. So it doesn't mean we can't explain consciousness scientifically, but we need to rethink what science is. What do you mean publicly, the word publicly observable? Is there something interesting to be said about the word publicly? I suppose versus privately. Yeah, it's tricky to define, but I suppose the data of physics are available to anybody. If there were aliens who visited us from another planet, maybe they'd have very different sense organs. Maybe they'd struggle to understand our art or our music. But if they were intelligent enough to do mathematics, they could understand our physics. They could look at the data of our experiments. They could run the experiments themselves. Whereas consciousness, is it observable? Is it not observable? In a sense, it's observable. As you say, we could say it's privately observable. I am directly aware of my own feelings and experiences. If I'm in pain, it's just right there for me. My pain is just totally directly evident to me. But you from the outside cannot directly access my pain. You can access my pain behavior, or you can ask me, but you can't access my pain in the way that I can access my pain. So I think that's a distinction. It might be difficult to totally pin it down how we define those things, but I think there's a fairly clear and very important difference there. So you think there's a kind of direct observation that you're able to do of your pain that I'm not. So my observation, all the ways in which I can sneak up to observing your pain is indirect versus yours is direct. Can you play devil's advocate? Is it possible for me to get closer and closer and closer to being able to observe your pain, like all the subjective experiences, yours, in the way that you do? Yeah. I mean, so of course, it's not that we observe behavior and then we make an inference. We are hardwired to instinctively interpret smiles as happiness, crying as sadness. And as we get to know someone, we find it very easy to adopt their perspective, get into their shoes. But strictly speaking, all we have perceptual access to is someone's behavior. And if you were just, strictly speaking, if you were trying to explain someone's behavior, those aspects that are publicly observable, I don't think you'd ever have recourse to attribute consciousness. You could just postulate some kind of mechanism if you were just trying to explain the behavior. So someone like Daniel Dennett is very consistent on this. So I think for most people, what science is in the business of is explaining the data of public observation experiment. If you religiously followed that, you would not postulate consciousness because it's not a datum that's known about in that way. And Daniel Dennett is really consistent on this. He thinks my consciousness cannot be empirically verified and therefore it doesn't exist. Dennett is consistent on this. I think I'm consistent on this, but I think a lot of people have a slightly confused middleway position on this. On the one hand, they think the business of science is just to account for public observation experiment, but on the other hand, they also believe in consciousness without appreciating, I think, that that implies that there is another datum over and above the data of public observation experiments, namely just the reality of feelings and experiences. As we walk along this conversation, you keep opening doors that I want to walk into, and I will, but I want to try to stay kind of focused. So you mentioned Daniel Dennett, let's lay it out since he sticks to his story, pun unintended, and then you stick to yours. What is your story? What is your theory of consciousness versus his? Can you clarify his position? So my view, I defend the view known as panpsychism, which is the view that consciousness is a fundamental and ubiquitous feature of the physical world. So it doesn't literally mean that everything is conscious despite the meaning of the word pan, everything, psyche, mind. So literally, that means everything has mind. But the typical commitment of the panpsychist is that the fundamental building blocks of reality, maybe fundamental particles like electrons and quarks, have incredibly simple forms of experience, and that the very complex experience of the human or animal brain is somehow rooted in or derived from this much more simple consciousness at the level of fundamental physics. So that's a theory that I would justify on the grounds that it can account for this datum of consciousness that we are immediately aware of in our experience in a way that I don't think other theories can. If you asked me to contrast that to Daniel Dennett, I think he would just say there is no such datum. Dennett says the data for science of consciousness is what he calls heterophenomenology, which is specifically defined as what we can access from the third person perspective, including what people say. But crucially, we're not treating what they say, we're not relying on their testimony as evidence for some unobservable realm of feelings and experiences. We're just treating what they say as a datum of public observation experiments that we can account for in terms of underlying mechanisms. But I feel like there's a deeper view of what consciousness is. So you have a very clear, and we'll talk quite a bit about panpsychism, but you have a clear view of what, almost like a physics view of consciousness. He I think has a kind of view that consciousness is almost a side effect of this massively parallel computation system going on in our brain. The brain has a model of the world and it's taking in perceptions and it's constantly weaving multiple stories about that world that's integrating the new perceptions and the multiple stories, or somehow it's like a Google Doc collaborative editing. And that collaborative editing is the actual experience of what we think of as consciousness. Somehow the editing is consciousness of this story. I mean, that's a theory of consciousness, isn't it? The narrative theory of consciousness, or the multiple versions, editing, collaborative editing of a narrative theory of consciousness. Yeah, he calls it the multiple drafts model. Incidentally, there's a very interesting paper just come out by very good philosopher, Luke Roloff's defending a panpsychist version of Dennett's multiple drafts model. Like a deeper turtle that that's all a stack on top of. Just the difference being that this is Luke Roloff's view, all of the drafts are conscious. I guess for Dennett, there's sort of no fact of the matter about which of these drafts is the correct one. On Roloff's view, maybe there's no fact of the matter about which of these drafts is my consciousness, but nonetheless, all the drafts correspond to some consciousness. And I mean, it just sounds kind of funny. I guess I think he calls it Dennettian panpsychism. But Luke is one of the most rigorous and serious philosophers alive at the moment, I think. I hate having Luke Roloff in an audience if I'm giving a talk because he always cuts straight to the weakness in your position that you hadn't thought of. So it's nice, panpsychism is sometimes associated with fluffy thinking, but contemporary panpsychists have come out of this tradition we call analytic philosophy, which is rooted in detailed, rigorous argumentation and it is defended in that manner. Yeah, those analytic philosophers are sticklers for terminology. It's very fun, very fun group to talk shit with. Yeah, well, I mean, it gets boring if you just start and end defining words, right? I think starting with defining words is good. Actually, the philosopher Derek Parfit said when he first was thinking about philosophy, he went to a talk in analytic philosophy and he went to a talk in continental philosophy and he decided that the problem with the continental philosophy, if it was really unrigorous, really imprecise, the problem with the analytic philosophy is it was just not about anything important. And he thought there was more chance of working within analytic philosophy and asking some more meaningful, some more profound questions than there was in working continental philosophy and making it more rigorous. Now, they're both horrific stereotypes and I don't want to get nasty emails from either of these groups, but there's something to what he was saying there. I think just a tiny tangent on terminology, I do think that there's a lot of deep insight to be discovered by just asking questions. What do we mean by this word? I remember I was taking a course on algorithms and data structures in computer science and the instructor, shout out to him, Ali Shekhafande, amazing professor, I remember he asked some basic questions like, what is an algorithm? The pressure of pushing students to answer, to think deeply. You know, you just woke up, hung over in college or whatever, and you're tasked with answering some deep philosophical question about what is an algorithm. These basic questions, and they sound very simple, but they're actually very difficult. One of the things I really value in conversation is asking these dumb, simple questions of like, what is intelligence? Just continually asking that question over and over of some of the biggest researchers in the artificial intelligence computer science space, it's actually very useful. At the same time, it should start at terminology and then progress where you kind of say, ah, fuck it, we'll just assume we know what we mean by that. Otherwise you get the Bill Clinton situation where it's like, what is the meaning of is is whatever he said, it's like, hey man, did you do the sex stuff or not? Yeah. So you have to both be able to talk about the sex stuff and the meaning of the word is, with consciousness, because we don't currently understand very much, terminology discussions are very important. Because it's like you're almost trying to sneak up to some deep insight by just discussing some basic terminology. Like what is consciousness or even defining the different aspects of panpsychism is fascinating. But just to linger on the Daniel Dennett thing, what do you think about narrative? Sort of the mind constructing narratives for ourselves. So there's nothing special about consciousness deeply. It is some property of the human mind that's just is able to tell these pretty stories that we experience as consciousness and that's unique, perhaps, to the human mind, which is, I suppose, what Daniel Dennett would argue, that it's either deeply unique or mostly unique to the human mind. It's just on the question of terminology before. I think it used to be the fashion among philosophers that we had to come up with utterly precise, necessary and sufficient conditions for each word. And then I think this has gone out of fashion a bit, partly because it's just been such a failure. The word knowledge in particular, people used to define knowledge as true justified belief. And then this guy, Gettier, had this very short paper where he just produced some pretty conclusive counter examples to that. I think he wrote very few papers, but this is just, you have to teach this on an undergraduate philosophy course. And then after that, you had a huge literature of people trying to address this and propose a new definition, but then someone else would come out with counter examples. And then you get a new definition of knowledge and counter examples, and it just went on and on and never seemed to get anywhere. So I think the thought now is, let's work out how precise we need to be for what we're trying to do. And I think that's a healthier attitude. So precision is important, but you just need to work out how precise do we need to be for these purposes. Coming to Dennett and narrative theories, I mean, I think narrative theories are a plausible contender for a theory of the self, theory of my identity over time, what makes me the same person in some sense today as I was 20 years ago, given that I've changed so much physically and psychologically. On running contender is something connected to the kind of stories we tell about ourselves, or maybe some story about the psychological, the chains of psychological continuity. I'm not saying I accept such a theory, but it's plausible. I don't think these theories are good as theories of consciousness, at least if we're taking consciousness just to be subjective experience, pleasure, pain, seeing color, hearing sound, I think a hamster has consciousness in that sense. There's something that it's like to be a hamster. It feels pain if you stand on it, if you're cruel enough to do it. I don't know why I gave that. Stand? People always give, I don't know, philosophers give these very violent examples to get the cross consciousness and it's, yeah, I don't know why that's coming about. But anyway. You say mean things to the hamster. Let's back on that. So it experiences pain, it experiences pleasure, joy, I mean, but there's some limits to that experience of a hamster, but there is nevertheless the presence of a subjective experience. Yeah. Consciousness is just something, I mean, it's a very ambiguous word, but if we're just using it to mean some kind of experience, some kind of inner life, that is pretty widespread in the animal kingdom. It's a bit difficult to say where it stops, where it starts, but you certainly don't need something as sophisticated as the capacity to self-consciously tell stories about yourself to just have experience. Except for cats who are evil automatons that are void of consciousness. They're the fingertips of the devil. Oh, absolutely. Yeah. Well, I was taking that as read. I mean, Descartes thought animals were mechanisms. And humans are unique. So animals are robots, essentially, in the formulation of Descartes, and humans are unique. So in which way would you say humans are unique versus even our closest ancestors? Is there something special about humans? What is, in your view, under the panpsychism, I guess we're walking backwards, because we'll have the big picture conversation about what is panpsychism, but given your kind of broad theory of consciousness, what's unique about humans, do you think? As a panpsychist, there is a great continuity between humans and the rest of the universe. There's nothing that special about human consciousness. It's just a highly evolved form of what exists throughout the universe. So we're very much continuous with the rest of the physical universe. What is unique about human beings? I suppose the capacity to reflect on our conscious experience, plan for the future, the capacity, I would say, to respond to reasons as well. I mean, animals in some sense have motivations, but when a human being makes a decision, they're responding to what philosophers call normative considerations. You know, if you think, should I take this job in the US? You weigh it up, you say, well, you know, I'll get more money, I'll have maybe a better quality of life, but if I stay in the UK, I'll be closer to family, and you weigh up these considerations. I'm not sure any non-human animals quite respond to considerations of value in that way. I mean, I might be reflecting here that I'm something of an objectivist about value. I think there are objective facts about what we have reason to do and what we have reason to believe. And humans have access to those facts. And humans have access to them and can respond to them. That's a controversial claim, you know. Many of my panpsychist brethren might not... They would say the hamster too can look up to the stars and ponder theoretical physics. Probably not, but I think it depends what you think about value. If you have a more Humean picture of value, by which I mean relating to the philosopher David Hume, who said reason is the slave of the passions, really we just have motivations and what we have reason to do arises from our motivations. I'm not a Humean. I think there are objective facts about what we have reason to do. And I think we have access to them. I don't think any non-human animal has access to objective facts about what they have reason to do, what they have reason to believe. They don't weigh up evidence. Reason is a slave of the passions. That was David Hume's view, yeah. I mean, yeah, do you want to know my problem with Hume's? I had a radical conversion. This is, it might not be connected. It's not connected to panpsychism, but I had a radical conversion. I used to have a more Humean view when I was a graduate student, but I was persuaded by some professors at the University of Reading where I was, that if you have the Humean view, you have to say any basic life goals are equal, equally valid. So for example, let's take someone whose basic goal in life is counting blades of grass, right? Crucially, they don't enjoy it, right? This is the crucial point. They get no pleasure from it. That's just their basic goal, to spend their life counting as many blades of grass as possible. Not for some greater goal. That's just their basic goal. I want to say that that is objectively stupid. That is objectively pointless. I shouldn't say stupid, but it's objectively pointless in a way that pursuing pleasure or pursuing someone else's pleasure or pursuing scientific inquiry is not pointless. As soon as you make that admission, you're not a follower of David Hume anymore. You think there are objective facts about what goals are worth pursuing. Is it possible to have a goal without pleasure? So this kind of idea that you disjoint the two. So the David Foster Wallace idea of, you know, the key to life is to be unboreable. Isn't it possible to discover the pleasure in everything in life? The counting of the blades of grass. Once you see the mastery, the skill of it, you can discover the pleasure. Therefore, you know, I guess what I'm asking is why and when and how did you lose the romance in grad school? I was like, is that what you're trying to say? I think it may or may not be true that it's possible to find pleasure in everything. But I think it's also true that people don't act solely for pleasure, and they certainly don't act solely for their own pleasure. People will suffer for things they think are worthwhile. I might, you know, I might suffer for some scientific cause, for finding out a cure for the pandemic. And in terms of my own pleasure, I might have less pleasure in doing that. But I think it's worthwhile. It's a worthwhile thing to do. I just don't think it's the case that everything we do is rooted in maximizing our own pleasure. I don't think that's even psychologically plausible. But pleasure, then that's a narrow kind of view of pleasure. That's like a short term pleasure. But you can see pleasure is a kind of ability to hear the music in the distance. It's like, yes, it's difficult now, it's suffering now, but there is some greater thing beyond the mountain that will be joy. I mean, that's kind of a, even if it's not in this life, well, you know, the warriors will meet in Valhalla, right? The feeling that gives meaning and fulfillment to life is not necessarily grounded in pleasure of like the counting of the grass. It's something else. I don't know. The struggle is a source of deep fulfillment. So I think pleasure needs to be kind of thought of as a little bit more broadly. It just kind of gives you this sense. It for a moment allows you to forget the terror of the fact that you're going to die. That's pleasure. That's the broader view of pleasure, that you get to kind of play in the little illusion that all of this has deep meaning. That's pleasure. Yeah, well, but I mean, you know, people sacrifice their lives. Atheists may sacrifice their lives for the sake of someone else or for the sake of something important enough. And clearly in that case, they're not doing it for the sake of their own pleasure. That's a rather dramatic example, but there can be just trivial examples where, you know, I choose to be honest rather than lie about something and I lose out a bit and I have a bit less pleasure, but I thought it was worth doing the honest thing or something. I mean, I just think so. That's a, I mean, maybe you can use the word pleasure so broadly that you're just essentially meaning something worthwhile, but then I think the word pleasure maybe loses its meaning. Sure. Well, but what do you think about the blades of grass case? What do you think about someone who spends their life cutting blades of grass and doesn't enjoy it? So I think, I personally think it's impossible, or maybe I'm not understanding even like the philosophical formulation, but I think it's impossible to have a goal and not draw pleasure from it. Make it worthwhile, forget the word pleasure. I think the word goal loses meaning. If I say I'm going to count the number of pens on this table, if I'm actively involved in the task, I will find joy in it. I will find, like, I think there's a lot of meaning and joy to be discovered in the skill of a task, in mastering of a skill and taking pride in doing it well. I mean, that's, I don't know what it is about the human mind, but there's some joy to be discovered in the mastery of a skill. So I think it's just impossible to count blades of grass and not sort of have the jirodrims of sushi compelling, like draws you into the mastery of the simple task. Hmm. Yeah, I suppose. I mean, in a way you might think it's just hard to imagine someone who would spend their lives doing that, but then maybe that's just because it's so evident that that is a pointless task. Whereas if we take this David Hume view seriously, it ought to be, you know, a totally possible life goal. But I mean, yeah, I guess I just find it hard to shake the idea that some ways of, some life goals are more worthwhile than others. And it doesn't mean, you know, that there's one single way you should lead your life, but pursuing knowledge, helping people, pursuing your own pleasure to an extent are worthwhile things to do in a way that, you know, for example, I have, I'm a little bit OCD. I still feel inclined to walk on cracks in the pavement or do it symmetrically. Like if I step on a crack with my left foot, I feel the need to do it with my right foot. I think that's kind of pointless. It's something I feel the urge to do, but it's pointless. Whereas other things I choose to do, I think it's worth doing. And it's hard to make sense of metaphysically, what could possibly ground that? How could we know about these facts? But that's the starting point for me. I don't know. I think you walking on the sidewalk in a way that's symmetrical brings order to the world. Like if you weren't doing that, the world might fall apart. And you- It feels like that. And I think there's meaning in that. Like you embracing the full experience of that, you living the richness of that as if it has meaning, will give meaning to it. And then whatever genius comes of that as you as one little intelligent ant will make a better life for everybody else. Perhaps I'm defending the blades of grass example, because I can literally imagine myself enjoying this task as somebody who's OCD in a certain kind of way and quantitative. But now you're running these, I'm going to imagine someone enjoying it. I'm imagining someone who doesn't enjoy it. We don't want a life that's just full of pleasure. Like we just sit there, you know, having a big sugar high all the time. We want a life where we do things that are worthwhile. If for something to be worthwhile just is for it to be a basic life goal, then that mode of reflection doesn't really make sense. We can't really think. We can't do things worthwhile on the David Hume type picture. All it is for something to be worthwhile is it was a basic goal of yours or derived from a basic goal. And yeah. Yeah. I mean, I think goal and worthwhile aren't, I think goal is a boring word. I'm more sort of existentialist. It's like, did you ride the roller coaster of life? Did you fully experience life? And in that sense, I mean, the blaze of grass is something that could be deeply joyful. And that's in that way, I think suffering could be joyful in the full context of life. It's the roller coaster of life. Like without suffering, without struggle, without pain, without depression or sadness, there's not the highs. I mean, that's the fucked up thing about life is that the lows really make the highs that much richer and deeper and taste better. Right? Like I tweeted this, I couldn't sleep and I was late at night. And I know it's an obvious statement, but every love story eventually ends in loss, in tragedy. So like this feeling of love at the end, there's always going to be tragedy. Even if it's the most amazing lifelong love with another human being, one of you is going to die. And I don't know which is worse, but both are not going to be pretty. And so that, the sense that it's finite, the sense that it's going to end in a low, that gives like richness to those kinds of evenings when you realize this fucking thing ends, this thing ends. The feeling that it ends, that bad taste, that bad feeling that it ends gives meaning, gives joy, gives pleasure. I don't know, pleasure is this loaded word, but gives some kind of a deep pleasure to the experience when it's good. And that's the blades of grass, they have that to me. But you're perhaps right that it's like reducing it to set of goals or something like that is kind of removing the magic of life. Because I think what makes counting the blades of grass joyful is just because it's life. Okay, so it sounds like you reject the David Hume type picture anyway, because you're saying just because you have it as a goal, that's what it is to be worthwhile. But you're saying no, it's because it's engaging with life, riding the roller coaster. So that does sound like in some sense, there are facts independent of our personal goal choices about what it means to live a good life. And I mean, coming back full circle to the start of this was what makes us different to animals. I don't think at the end of a hamster's life, it thinks, did I ride the roller coaster? Did I really live life to the full? That is not a mode of reflection that's available to non-human animals. So what do you think is the role of death in all of this? The fear of death? Does that interplay with consciousness? Does this self-reflection? Do you think there's some deep connection between this ability to contemplate the fact that our flame of consciousness eventually goes out? Yeah, I don't think unfortunately, panpsychism helps particularly with life after death, because for the panpsychist, there's nothing supernatural, there's nothing beyond the physical. All there is really is ultimately particles and fields. It's just that we think the ultimate nature of particles and fields is consciousness. But I guess when the matter in my brain ceases to be ordered in a way that sustains the particular kind of consciousness I enjoy in waking life, then in some sense, I will cease to be. Although I do, the final chapter of my book, Galileo's Error, is more experimental. So the first four chapters are the cold-blooded case for the panpsychist view is the best solution to the hard problem of consciousness. The last chapter, we talk about meaning. Yeah, I talk about meaning, I talk about free will, and I talk about mystical experiences. So I always want to emphasize that panpsychism is not necessarily connected to anything spiritual. A lot of people defending this view, like David Chalmers or Luke Roloff, are just total atheist secularists. They don't believe in any kind of transcendent reality, they just believe in feelings, mundane consciousness and think that needs explaining and our conventional scientific approach can't cut it. But if for independent reasons, you are motivated to some spiritual picture of reality, then maybe a panpsychist view is more consonant with that. So if you have a mystical experience where it seems to you in this experience that there is this higher form of consciousness at the root of all things, if you're a materialist, you've got to think that's a delusion. There's just something in your brain making you think that it's not real. But if you're a panpsychist and you already think the fundamental nature of reality is constituted of consciousness, it's not that much of a leap to think that this higher form of consciousness you seem to apprehend in the mystical experience is part of that underlying reality. And in many different cultures, experienced meditators have claimed to have experiences in which it becomes apparent to them that there is an element of consciousness that is universal. This is sometimes called universal consciousness. So on this view, your mind and my mind are not totally distinct. Each of our individual conscious minds is built upon the foundations of universal consciousness. Universal consciousness as it exists in me is one and the same thing as universal consciousness as it exists in you. So I've never had one of these experiences, but if one is a panpsychist, I think one is more open to that possibility. I don't see why it shouldn't be the case that that is part of the nature of consciousness and maybe something that is apparent in certain deep states of meditation. And so what I explore in the experimental final chapter of my book is that could allow for a kind of impersonal life after death, because if that view is true, then even when the particular aspects of my conscious experience fall away, that element of universal consciousness at the core of my identity would continue to exist. So I'd sort of be, as it were, absorbed into universal consciousness. So Buddhists and Hindu mystics try to meditate to get rid of all the bad karma to be absorbed into universal consciousness. It could be that if there's no karma, if there's no reverb, maybe everyone gets enlightened when they die. Maybe you just sink back into universal consciousness. So I also, coming back to morality, suggest this could provide some kind of basis for altruism or non-egotism, because if you think egotism implicitly assumes that we are utterly distinct individuals, whereas on this view, we overlap to an extent that something at the core of our being is... Even in this life, we overlap. There is something very... Like you and I in this conversation, there's a few people listening to this, all of us are in a kind of single mind together. There's some small aspect of that, or maybe a big aspect, about us humans. So certainly in the space of ideas, we kind of meld together for a time, at least, in a conversation and kind of play with that idea. And then we're clearly all thinking, like if I say pink elephant, there's going to be a few people that are now visualizing a pink elephant. We're all thinking about that pink elephant together. We're all in the room together thinking about this pink elephant. We're rotating it in our minds together. What is that? Is there a different instantiation of that pink elephant in everybody's mind, or is it the same elephant and we have the same mind exploring that elephant? Now if we in our mind start petting that elephant, like touching it, that experience that we're now thinking what that would feel like, what's that? Is that all of us experiencing that together, or is that separate? So there's some aspect of the togetherness that almost seems fundamental to civilization, to society. Hopefully that's not too strong, but to some of the fundamental properties of the human mind, it feels like the social aspect is really important. We call it social because we think of us as individual minds interacting. But if we're just like one collective mind with like fingertips, they're like touching each other as it's trying to explore the elephant. But that could be just in the realm of ideas and intelligence and not in the realm of consciousness. It's interesting to see maybe it is in the realm of consciousness. Yeah, so it's obviously certainly true in some sense that there are these phenomena that you're talking about of collective consciousness in some sense. I suppose the question is, how ontologically serious do we want to be about those things? By which I mean, are they just a construction out of our minds and the fact that we interact in the standard, scientifically accepted ways? Or is as someone like Rupert Sheldrake would think that there is some metaphysical reality, there are some fields beyond the scientifically understood ones that are somehow communicating this? I mean, the view I was describing was that this element we're supposed to have in common is some sort of pure impersonal consciousness or something rather than... So actually, an interesting figure is the Australian philosopher Miri Al-Bahari, who defends a kind of mystical conceptual reality rooted in Advaita Vedanta mysticism. But like me, she's from this tradition of analytic philosophy. And so she defends this in this incredibly precise, rigorous way. She defends the idea that we should think of experienced meditators as providing expert testimony. So I think humans are causing climate breakdown. I have no idea of the science behind it, but I trust the experts or that the universe is 14 billion years old. Most of our knowledge is based on expert testimony. And she thinks we should think of experienced meditators, these people who are telling us about this universal consciousness at the core of our being as a relevant kind of expert. And so she wants to defend the rational acceptability of this mystical conceptual reality. So I think we shouldn't be ashamed, we shouldn't be worried about dealing with certain views as long as it's done with rigor and seriousness. I think sometimes terms like, I don't know, new age or something can function a bit like racist terms. A racist term picks out a group of people, but then implies certain negative characteristics. So people use this term to pick out a certain set of views like mystical conceptual reality and imply it's kind of fluffy thinking. But you read Miri Al-Bahari, you read Luke Roloff's, this is serious, rigorous thought, whether you agree with it or not, obviously it's hugely controversial. And so the Enlightenment ideal is to follow the evidence and the arguments where they lead. But it's kind of very hard for human beings to do that. I think we get stuck in some conception of how we think science ought to look. And people talk about religion as a crutch, but I think a certain kind of scientism, a certain conception of how science is supposed to be gets into people's identity and their sense of themselves and their security. And make things hard if you're a pants-leggers. And even the word expert becomes a kind of crutch. I mean, you use the word expert, you have some kind of conception of what expertise means. Oftentimes that's connected with a degree at a particularly prestigious university or something like that. Or expertise is a funny one. I've noticed that anybody that claims they're an expert is usually not the expert. The biggest quote-unquote expert that I've ever met are the ones that are truly humble. So the humility is a really good sign of somebody who's traveled a long road and been humbled by how little they know. So some of the best people in the world at whatever the thing they've spent their life doing are the ones that are ultimately humble in the face of it all. So just being humble for how little we know, even if we travel a lifetime. I do like the idea. I mean, treating sort of like, what is it, psychonauts, like an expert witness, people who have traveled with the help of DMT to another place where they got some deep understanding of something. And their insight is perhaps as valuable as the insight of somebody who ran rigorous psychological studies at Princeton University or something. Those psychonauts, they have wisdom, if it's done rigorously, which you can also do rigorously within the university, within the studies now with psilocybin and those kinds of things. Yeah, that's fascinating. I think still probably one of the best works on mystical experience is the chapter in William James's Varieties of Religious Experiences. Most of it is just a psychological study of trying to define the characteristics of mystical experience as a psychological type. But at the end, he considers the question, if you have a mystical experience, is it rational to trust it, to trust that it's telling you something about reality? And he makes an interesting argument. He says, if you say no, you're kind of applying a double standard, because we all think it's okay to trust our normal sensory experiences, but we have no way of getting outside of ourselves to prove that our sensory experiences correspond to an external reality. We could be in the matrix. This could be a very vivid dream. You could say, oh, we do science, but a scientist only gets their data by experiencing the results of their experiments. And then the question arises again, how do you know that corresponds to a real world? So he thinks there's a sort of double standard in saying, it's okay to trust our ordinary sensory experiences, but it's not okay for the person on DMT to trust those experiences. It's very philosophically difficult to say, why is it okay in the one case and not the other? So I think there's an interesting argument there, but I would like to just defend experts a little bit. I mean, I agree it's very difficult, but especially in an age, I guess, where there's so much information, I do think it's important to have some protection of sources of information, academic institutions that we can trust. And then that's difficult because of course, there are non-academics who do know what they're talking about, but if I'm interested in knowing about biology, you can't research everything. So I think we have to have some sense of who are the experts we can trust, the people who've spent a lot of time reading all the material that people have read, written, thinking about it, having their views torn apart by other people working in the field. I think that is very important and also to protect that from conflicts of interest. There is a so-called think tank in the UK called the Institute of Economic Affairs, who are always on the BBC as experts on economic questions, and they do not declare who funds them. So we don't know who's paying the piper. I think you shouldn't be allowed to call yourself a think tank if you're not totally transparent about who's funding you. So I think that's the... and I mean, this connects to panpsychism because I think the reason people worry about unorthodox ideas is because they worry about how do we know when we're just losing control or losing discipline. So I do think we need to somehow protect academic institutions as sources of information that we can trust. And in philosophy, there's not much consensus on everything, but you can at least know, you can know what people who have put the time in to read all the stuff, what they think about these issues. I think that is important. So push back on your pushback. Who are the experts on COVID? Oh dear, getting into dangerous territory now. Well, let me just speak to it because I am walking through that dangerous territory. I'm allergic to the word expert because in my simple mind, it kind of rhymes with ego. There's something about experts. If we allow too much to have a category expert and place certain people in them, those people sitting on the throne start to believe it and they start to communicate with that energy and the humility starts to dissipate. I think there is value in a lifelong mastery of a skill and the pursuit of knowledge within a very specific discipline. But the moment you have your name on an office, the moment you're an expert, I think you destroy the very aspect, the very value of that journey towards knowledge. So some of it probably just reduces to skillful communication, like communicating in a way that shows humility, that shows an open-mindedness, that shows an ability to really hear what a lot of people are saying. So in the case of COVID, what I've noticed, and this is probably true with panpsychism as well, is so-called experts, and they are extremely knowledgeable, many of them are colleagues of mine, they dismiss what millions of people are saying on the internet without having looked into it with empathy and rigor, honestly, understand what are the arguments being made. They say there's not enough time to explore all those things, there's so much stuff out there. Yeah, I think that's intellectual laziness. If you don't have enough time, then don't speak so strongly with dismissal. Feel bad about it, be apologetic about the fact that you don't have enough time to explore the evidence. For example, the heat I got with Francis Collins is that he kind of said that LabLeak, he kind of dismissed it, showing that he didn't really deeply explore all the huge amount of circumstantial evidence out there, the battles that are going on out there. There's a lot of people really tensely discussing this, and showing humility in the face of that battle of ideas I think is really important. And I've just been very disappointed in so-called expertise in the space of science, in showing humility, in showing humanity and kindness and empathy towards other human beings. At the same time, obviously, I love Jiro Dreams of Sushi, lifelong pursuit of getting, in computer science, Don Knuth. Some of my biggest heroes are people that when nobody else cares, they stay on one topic for their whole life, and they just find the beautiful little things about their puzzles they keep solving. And yes, sometimes a virus happens or something happens where that person with their puzzles becomes like the center of the whole world, because that puzzle becomes all of a sudden really important. But still, their responsibility is on them to show humility and to be open-minded to the fact that they, even if they spent their whole life doing it, even if their whole community is giving them awards and giving them citations and giving them all kinds of stuff where they're bowing down before them, how smart they are, they still know nothing relative to all the stuff, the mysteries that are out there. Yeah, I wonder how much we're disagreeing. I mean, these are totally valid issues. And of course, expertise goes wrong in all sorts of ways. It's totally fallible. I suppose I would just say, what is the alternative? Or do we just say all information is equal? Because as a voter, I've got to decide who to vote for, and I've got to evaluate. And I can't look into all of the economics and all of the relevant science. And so I just think, maybe it's like Churchill said about democracy, it's the worst system of government apart from all the rest. I think about panpsychism, it's the worst theory of consciousness apart from all the rest. But I just think expertise, the peer review system, I think it's terrible in so many ways. Yes, people should show more humility, but I can't see a viable alternative. I think philosopher Bernard Williams had a really nice nuanced discussion of the problems of titles, but how they also function in a society, they do have some positive function. The very first time I lectured in philosophy, before I got a professorship, was teaching at a continuing education college. That's kind of for retired people who want to learn some more things. And I just totally pitched it too high. And Gate talked about Bernard Williams on titles and hierarchies. And these kind of people in their 70s and 80s were just instantly started interrupting saying what is philosophy? And it was a disaster. And I just remember in the breaks, a sort of elderly lady said, I've decided to take Egyptology instead. But that was my introduction to teaching. But sort of titles and accomplishments is a nice starting point, but doesn't buy you the whole thing. So you don't get to just say, this is true because I'm an expert. You still have to convince people. One of the things I really like, so I practice martial arts. And for people who don't know, Brazilian Jiu-Jitsu is one of them. And you sometimes wear these pajamas, pajama looking things, and you wear a belt. So I happen to be a black belt in Brazilian Jiu-Jitsu. And I also train in what's called no gi, so you don't wear the pajamas. And when you don't wear the pajamas, nobody knows what rank you are. Nobody knows if you're a black belt or a white belt, if you're a complete beginner or not. And when you wear the pajamas, called the gi, you wear the rank. And people treat you very differently. When they see my black belt, they treat me differently. They kind of defer to my expertise. If they're kicking my ass, that's probably because I am working on something new, or maybe I'm letting them win. But when there's no belts, and it doesn't matter if I've been doing this for 15 years, it doesn't matter. None of it matters. What matters is the raw interaction of just trying to kick each other's ass and seeing what is this chess game, like a human chess, what are the ideas that we're playing with? And I think there's a dance there. Yes, it's valuable to know a person as a black belt when you take consideration of the advice of different people, me versus somebody who's only practiced for like a couple of days. But at the same time, the raw practice of ideas that is combat and the raw practice of exchange of ideas that is science needs to often throw away expertise. And in communicating, there's another thing to science and expertise, which is leadership. It's not just, so the scientific method in the review process is this rigorous battle of ideas between scientists. But there's also a stepping up and inspiring the world and communicating ideas to the world. And that skill of communication, I suppose that's my biggest criticism of so-called experts in science, is they're just shitty communicators. Absolutely. Yeah. Well, I can tell you, I get very frustrated with philosophers not reaching out more. I mean, I think it might be partly that we're trained to get watertight arguments, respond to all objections. And as you do that, eventually it gets more complicated and the jargon comes in. But then if, so to write a more accessible book or article, you have to loosen the argument a bit. And then we worry that other philosophers will think, oh, that's a really crap argument. So I mean, the way I did it, I wrote my academic book first, which is the fundamental reality. And then a more accessible book, Galileo's Error, where the arguments, you know, not as rigorously worked out. So then I can say the proper arguments, you know, the further arguments. But I get very frustrated. That's brilliantly done, by the way. Like that's such a, so for people who don't know, you first wrote Consciousness and Fundamental Reality. So that's the academic book, also very good. I flew through it last night, bought it. And then obviously the popular book is Galileo's Error, Foundations for a New Science of Consciousness. That's kind of the right way to do it. To show that you're legit to your community, to the world by doing the book that's nobody's going to read. And then doing a popular book that everybody's going to read. That's cool. Well, I try now, every time I write an academic article, I try to write a more accessible version. I mean, the thing I've been working on recently, just because there's this argument. So there's a certain argument from the cosmological fine tuning of the laws of physics for life to the multiverse that's quite popular physicists like Max Tegmark. There's an argument in philosophy journals that there's a fallacious line of reasoning going on there from the fine tuning to the multiverse. Now that argument is from 20, 30 years ago, and it's discussed in academic philosophy. Nobody knows about it. And there is huge interest in this fine tuning stuff. Scientists wanting to argue for the multiverse, theists wanting to say this is evidence for God and nobody knows about this argument, which tries to show that it's fallacious reasoning to go from the fine tuning to the multiverse. So I wrote a piece for Scientific American explaining this argument to a more general audience. And it just really irritates me that it's just buried in these technical journal articles and nobody knows about it. But just a final thing on that. I don't disagree with anything you said, and that's kind of really beautiful, that martial arts example and thinking how that could be analogous. But I think it's very rare to find a good philosopher who hasn't given a talk to other philosophers and had objections raised. I was going to say have it torn apart, but that's maybe thinking of it in the slightly the wrong way, but have the best objections raised to it. And that's why that is an important formative process that you go through as an academic, that the greatest minds starting a philosophy degree, for example, won't have gone through, probably except in very rare cases, just won't have that, the skills required. That part was just fun to disagree and dance with, I think to elaborate on what you're saying in agreement, not just gone through that, but continue to go through that. Absolutely. That's, I would say, the biggest problem with quote unquote expertise is that there's a certain point where you get, because it sucks. Is martial arts, this is a good example of that, it sucks to get your ass kicked. There's a temptation. I still go, I train, you're getting older too, but also there's killers out there in both the space of martial arts and the space of science. And I think that once you become a professor, more and more senior and more and more respected, I don't know if you get your ass kicked in the space of ideas as often. I don't know if you allow yourself to truly expose yourself. If you do, that's a great sign of a humble, brilliant mind is constantly exposing yourself to that. I think you do, because I think there's graduate students who want to find the objection to write their paper or make their mark. And yeah, I think everyone still gives talks or should give talks and people are wanting to work out if there are any weaknesses to your position. So yeah, I think that generally works out. There is also a kind of, who do you give the talks to? So I mean, within communities, it's a little cluster of people that argue and bicker, but what are they arguing about? They take a bunch of stuff, a bunch of basic assumptions as agreement, and they heatedly argue about certain ideas. The question is how open are, that's actually kind of like fun. That's like, no offense, sorry, we're sticking on this martial arts thing. It's like people who practice Aikido or certain martial arts that don't truly test themselves in the cage, in combat. So it's like, it's fun to argue about certain things when you're in your own community, but you don't test those ideas in the full context of science, in the full seriousness, the rigor of the, sometimes like the real world. One of my favorite fields is psychology. There's often places within psychology where you're kind of doing these studies and arguing about stuff that's done in the lab. The arguments are almost disjoint from real human behavior because it's so much easier to study human behavior in the lab. You just kind of stay there, and that's where the arguments are. Vision science is a good example, like studying eye movement and how we perceive the world and all that kind of stuff. It's so much easier to study in a lab that we don't consider, we say that's going to be what the science of vision is going to be like, and we don't consider the science of vision in the actual real world, the engineering of vision, I don't know. And so I think that's where exposing yourself to out of the box ideas, that's the most painful, that's the most important. Absolutely. I mean, groupthink can be a terrible thing in philosophy as well, but because you're not to the same extent beholden to evidence and refutation from the evidence that you are in the sciences, it's a more subtle process of evaluation, and so more susceptible, I think, to groupthink. Yeah, I agree, it's a danger. We've talked about it a million times, but let's try to sort of do that old basic terminology definitions. What is panpsychism? Like, what are the different ways you can try to think about, to define panpsychism maybe in contrast to naturalistic dualism and materialism, other kind of views of consciousness? Yeah, so you've basically laid out the different options. So I guess probably still the dominant view is materialism, that roughly that we can explain consciousness in the terms of physical science, wholly explain it just in terms of the electrochemical signaling in the brain. Dualism, the polar opposite view, that consciousness is non-physical outside of the physical workings of the body and the brain, although closely connected. And when I studied philosophy, we were taught basically they were the two options you had to choose, right? Either you thought it were dualist and you thought it was separate from the physical, or you thought it was just electrochemical signaling. And yeah, I became very disillusioned because I think there are big problems with both of these options. So I think the attraction of panpsychism is it's kind of a middle way. It agrees with the materialist that there's just the physical world. Ultimately there's just particles and fields, but the panpsychist thinks there's more to the physical than what physical science reveals. And that the ultimate nature of the physical world is constituted of consciousness. So consciousness is not outside of the physical as the dualist thinks, it's embedded in, underlies the kind of description of the world we get from physics. What to you are the problems of materialism and dualism? Starting with materialism, it's a huge debate, but I think that the core of it is that physical science works with a purely quantitative description of the physical world, whereas consciousness essentially involves qualities. If you think about the smell of coffee or the taste of mint or the deep red you experience as you watch a sunset, I think these qualities can't be captured in the purely quantitative language of physical science. So as long as your description of the brain is framed in the purely quantitative language of neuroscience, you'll just leave out these qualities and hence really leave out consciousness itself. And then dualism? So I've actually changed my mind a little bit on this since I wrote the book. So I mean, I argued in the book that we have pretty good experimental grounds for doubting dualism. And roughly the idea was if dualism were true, if there was say an immaterial mind impacting on the brain every second of waking life, that this would really show up in our neuroscience. There'd be all sorts of things happening in the brain that had no physical explanation. It would be like a poltergeist was playing with the brain. But actually, and so the fact that we don't find that is a strong and ever-growing inductive argument against dualism. But actually, the more I talk to neuroscientists and read neuroscience, and we have at Durham, my university, an interdisciplinary consciousness group, I don't think we know enough about the brain, about the workings of the brain to make that argument. I think we know a lot about the basic chemistry, how neurons fire, neurotransmitters, action potentials, things like that. We know a fair bit about large-scale functions of the brain, what different bits of the brain do. But what we're almost clueless on is how those large-scale functions are realized at the cellular level, how it works. People get quite excited about brain scans, but it's very low resolution. Every pixel on a brain scan corresponds to 5.5 million neurons. And we're only 70% of the way through constructing a connectome for the maggot brain, which has 10,000 or 100,000 neurons, but the brain has 86 billion neurons. So I think we'd have to know a lot more about how the brain works, how these functions are realized before we could assess whether the dynamics of the brain can be completely explicated in terms of underlying chemistry or physics. So we'd have to do more engineering before we could figure that out. And there are people with other proposals. Someone I got to know, Martin Picard at Columbia University, who has the psychobiology mitochondrial lab there and is experimentally exploring the hypothesis that mitochondria in the brain should be understood as sort of social networks, perhaps as an alternative to reducing it to underlying chemistry and physics. So I'm less... it is ultimately an empirical question whether dualism is true. I'm less convinced that we know the answer to that question at this stage. I think still, as scientists and philosophers, we want to try and find the simplest, most parsimonious theory of reality. And dualism is still a pretty inelegant, unparsimonious theory. Reality is divided up into the purely physical properties and these consciousness properties, and they're radically different kinds of things. Whereas the panpsychist offers a much more simple, unified picture of reality. So I think it's still the view to be preferred. To put it very simply, why believe in two kinds of things when you can just get away with one? Materialism is also very simple, but you're saying it doesn't explain something that seems pretty important. Yes, I think materialism can't... you know, science is about trying to find the simplest theory that accounts for the data. I don't think materialism can account for the data. Maybe dualism can account for the data, but panpsychism is simpler. It can account for the data and it's simpler. What is panpsychism? So in its broadest definition, it's the view that consciousness is a fundamental and ubiquitous feature of the physical world. Like a law of physics, what should we be imagining? What do you think the different flavors of how that actually takes shape in the context of what we know about physics and science and the universe? So in the simplest form of it, the fundamental building blocks of reality, perhaps electrons and quarks, have incredibly simple forms of experience and the very complex experience of the human or animal brain is somehow rooted in or derived from these very simple forms of experience at the level of basic physics. But I mean, maybe the crucial bit about the kind of panpsychism I defend, what it does is it takes the standard approach to the problem of consciousness and turns it on its head, right? So the standard approach is to think we start with matter and we think, how do we get consciousness out of matter? So I don't think that problem can be solved for reasons I've kind of hinted at, we could maybe go into more detail. But the panpsychist does it the other way around. They start with consciousness and try to get matter out of consciousness. So the idea is basically at the fundamental level of reality, there are just networks of very simple conscious entities. But these conscious entities, because they have very simple kinds of experience, they behave in predictable ways. Through their interactions, they realize certain mathematical structures. And then the idea is those mathematical structures just are the structures identified by physics. So when we think about these simple conscious entities in terms of the mathematical structures they realize, we call them particles, we call them fields, we call their properties mass, spin and charge. But really there's just these very simple conscious entities and their experiences. So in this way, we get physics out of consciousness. I don't think you can get consciousness out of physics, but I think it's pretty easy to get physics out of consciousness. Well, I'm a little confused by why you need to get physics out of consciousness. To me, it sounds like panpsychism unites consciousness and physics. Physics is the mathematical science of describing everything. So physics should be able to describe consciousness. And my understanding proposes is that physics doesn't currently do so, but can in the future. It seems like consciousness, you have like Stephen Wolfram, who's all these people who are trying to develop theories of everything, mathematical frameworks within which to describe how we get all the reality that we perceive around us. To me, there's no reason why that kind of framework cannot also include some accurate, precise description of whatever simple consciousness characteristics are present there at the lowest level if panpsychist theories have truth to them. So to me, it is physics. You said kind of physics emerges by which you mean like the basic four laws of physics, as we currently know them, the standard model, quantum mechanics, general relativity, that emerges from the base consciousness layer. That's what you mean. Yeah. So maybe the way I phrased it made it sound like these things are more separate than they are. What I was trying to address was a common misunderstanding of panpsychism, that it's a sort of dualistic theory. The idea is that particles have their physical properties like mass, spin and charge, and these other funny consciousness properties. So the physicist Sabine Hossenfelder had a blog post critiquing panpsychism maybe a couple of years ago now that got a fair bit of traction. And she was interpreting panpsychism in this way, and then her thought was, well, look, if particles had these funny consciousness properties, then it would show up in our physics like the standard model of particle physics would make false predictions because its predictions are based wholly on the physical properties. If there were also these consciousness properties, we'd get different predictions. But that's a misunderstanding of the view. The view is, it's not that there are two kinds of property, that mass, spin and charge are forms of consciousness. How do we make sense of that? Because actually, when you look at what physics tells us, it's really just telling us about behaviour, about what stuff does. I sometimes put it by saying doing physics is like playing chess when you don't care what the pieces are made of, you're just interested in what moves you can make. So physics tells us what mass, spin and charge do, but it doesn't tell us what they are. So the idea- The experience of mass. So the idea is, yeah, mass in its nature is a very simple form of consciousness. So yeah, physics in a sense is complete, I think, because it tells us what everything at the fundamental level does, it describes its causal capacities. But for the panpsychist at least, physics doesn't tell us what matter is, it tells us what it does, but not what it is. To push back on the thing I think she's criticizing, is it also possible, so I understand what you're saying, but is it also possible that particles have another property like consciousness? I don't understand the criticism we would be able to detect it in our experiments. Well no, if you're not looking for it. There's a lot of stuff that are orthogonal, like if you're not looking for the stuff, you're not going to detect it, because all of our basic empirical science, through its recent history, and yes, the history of science is quite recent, has been very focused on billiard balls colliding, and from that understanding how gravity works. But we just haven't integrated other possibilities into this. I don't think there will be conflicting, whether you are observing consciousness or not, or exploring some of these ideas, I don't think that affects the rest of the physics. The mass, the energy, all the different kind of hierarchy of different particles and so on, how they interact. I don't think... It feels like consciousness is something orthogonal, very much distinct, it's the quantitative versus the qualitative, there's something quite distinct, that we're just, almost like another dimension that we're just completely ignoring. There might be a way of responding to Sabina to say, well, there could be properties of particles that don't show up in the specific circumstances in which physicists investigate particles. My colleague, the philosopher of science, Nancy Cartwright, has got this book, How the Laws of Physics Lie, where she says, physicists explore things in very specific circumstances and then in an unwarranted way, generalize that. But I mean, I guess I was thinking Sabina's criticism actually just misses the mark in a more basic way. Her point is, we shouldn't think there are any more properties to particles other than those the standard model attributes to them. Panpsychics would say, yeah, sure, there aren't, there are just the properties, the physical properties like mass, spin and charge, that the standard model attributes to them. It's just that we have a different philosophical view as to the nature of those properties. Those properties are turtles, they're sitting on top of another turtle and that big turtle is consciousness. That's what you're saying. But I'm just saying, it's possible, that's true, it's possible also that consciousness is just another turtle playing with the others. It's just not interacting in the ways that we've been observing. In fact, to me that's more compelling because then that's going to be, well no, I think both are very compelling but it feels like it's more within the reach of empirical validation if it's yet another property of particles that we're just not observing. If it's like the thing from which matter and energy and physics emerges, it makes it that much more difficult because to investigate how you get from that base layer of consciousness to the wonderful little spark of consciousness, complexity and beauty that is the human being. I don't know if you're necessarily trying to get there but one of the beautiful things to get at with panpsychism or with a solid theory of consciousness is to answer the question, how do you engineer the thing? How do you get from nothing, vacuum in the lab, if there is that consciousness base layer, how do you start engineering organisms that have consciousness in them? Or the reverse of that, describing how does consciousness emerge in the human being from conception, from a stem cell to the whole full neurobiology that builds from that, how do you get this full, rich experience of consciousness that humans have? It feels like that's the dream and if consciousness is just another player in the game of physics, it feels more amenable to our scientific understanding of it. That's interesting. I mean, I guess it's supposed to be a kind of identity claim here that physics tells us what matter does, consciousness is what matter is. So matter is sort of what consciousness does. So at the bottom level, there is just consciousness and conscious things. They're just these simple things with their experiences and that is their total nature. So in that sense, it's not another player, it's just all there is really. And then we describe, in physics, we describe that at a certain level of abstraction. We just capture what Bertrand Russell, who was the inspiration for a lot of this, calls the causal skeleton of the world. So physics is just interested in the causal skeleton of the world, it's not interested in the sort of flesh and blood, although that's maybe suggesting separation again, too much. All metaphors fail in the end. But yeah, so you're totally right. Ultimately, what we want to explain is how our consciousness and the consciousness of other animals comes out of this. If we can't do that, then it's game over. But I think it maybe makes more sense on the identity claim that if matter at the fundamental level just is forms of consciousness, then we can perhaps make sense of how those simple forms of consciousness in some way combine in some way to make the consciousness we know and love. That's the dream. So I guess the question is, the reason you have material engineering, material science, is because you have, from physics to chemistry, you keep going up and up in levels of complexity in order to describe objects that we have in our human world. And it would be nice to do the same thing for consciousness, to come up with the chemistry of consciousness. How do the different particles interact to create greater complexity? So you can do this kind of thing for life. What is life? Well, like living organisms. At which point do living organisms become living? How do you know if I give you a thing that that thing is living? There's a lot of people working on this kind of idea, and some of it has to do with the levels of complexity and so on. It'd be nice to know, like, measuring different degrees of consciousness as you get into bigger, more and more complex objects. And that's what chemistry, like bigger and bigger conscious molecules, and to see how that leads to organisms. And then organisms start to collaborate together like they do inside our human body to create the full human body, to do those kinds of experiments would be, it seems like that would be kind of a goal. That's what I mean by player in a game of physics, as opposed to like the base layer. If it's just the base layer, it becomes harder to track it as you get from physics to chemistry to biology to psychology. Yeah. In every case apart from consciousness, I would say what we're interested in is behavior. We're interested in explaining behavioral functions. So at the level of fundamental physics, we're interested in capturing the equations that describe the behavior there. And when we get to higher levels, we're interested in explicating the behavior, perhaps in terms of behavior at simpler levels. And with life as well, that's what we're interested in, the various observable functions of life, explaining them in terms of more simple mechanisms. But in the case of consciousness, I don't think that's what we're doing, or at least not all that we're doing. In the case of consciousness, there are these subjective qualities that we're immediately aware of, the redness of a red experience, the itchiness of an itch, and we're trying to account for them. We're trying to bring them into our theory of reality. And postulating some mechanism does not deal with that. I think we've got to realize dealing with consciousness is a radically different explanatory task from other tasks of science. Other tasks of science, we're trying to explain behavior in terms of simpler forms of behavior. In the case of consciousness, we're trying to explain these invisible subjective qualities that you can't see from the outside, but that you're immediately aware of. The reason materialism perhaps continues to dominate is people think, look at the success of science, it's incredible. Look at all the, you know, it's explained all this, surely it's going to explain consciousness. But I think we have to appreciate there's a radically different explanatory task here. And so, I mean, the neuroscientist Anil Seth, who I've had lots of intense but friendly discussions with, you know, wants to compare consciousness to life. But I think there's this radical difference that in the case of life, again, we come back to public observation, all of the data, publicly observable data, we're basically trying to explain complex behavior. The way you do that is identify mechanisms, simpler mechanisms that explicate that behavior. That's the task in physics, chemistry, neurobiology. But in the case of consciousness, that's not what we're trying to do. We're trying to account for these subjective qualities and you postulate a mechanism that might explain behavior, but it doesn't explain the redness of a red experience. But still, I mean, still ultimately the hope is that we will have some kind of hierarchical story. So, we take the causal dynamics of physics, we hypothesize that that's filled out with certain forms of consciousness. And then at higher levels, we get more complex causal dynamics filled out by more complex forms of consciousness. And ultimately we get to us, hopefully. So yeah, so there's still a sort of hierarchical explanatory framework there. So, you kind of mentioned the hierarchy of consciousness. Do you think it's possible to, within the panpsychism framework, to measure consciousness? Or put another way, are some things more conscious than others in the panpsychist view? It's a difficult question. I mean, I do see consciousness as a dealing with consciousness and interdisciplinary task between something more experimental, which has to do with the ongoing project of trying to work out what people call the neural correlates of consciousness, what kinds of physical brain activity correspond to conscious experience. That's one part of it. But I think essentially there's also a theoretical question of more the why question. Why do those kinds of brain activity go along with certain kinds of conscious experience? I don't think you can answer that. Because consciousness is not publicly observable, I don't think you can answer that why question with an experiment. But they have to go hand in hand. And I mean, one of the theories I'm attracted to is the integrated information theory, according to which we find consciousness at the level at which there is most integrated information. And they try to give a mathematically precise definition of that. So on that view, probably this cup of tea isn't conscious because there's probably more integrated information in the molecules making up the tea than there is in the liquid as a whole. But in the brain, what is distinctive about the brain is that there's a huge amount of integrated, there's more integrated information in the system than there is in individual neurons. So that's why they claim that that's the basis of consciousness at the macro level. Now they, so I don't, I mean, I like some features of this theory, but they do talk about degrees of consciousness. They do want to say there is gradations. I'm not sure conceptually I can kind of make sense of that. I mean, there are things to do with consciousness that are graded like complexity or levels of information. But I'm not sure whether experience itself admits a degree. I sort of think something either has experience or it doesn't. It might have very simple experience, it might have very complex experience, but experience itself I don't think it admits a degree in that sense. It's not more experience, less experience. I sort of find that conceptually hard to make sense of, but I'm kind of open-minded on it. So when we have a lot higher resolution of sensory information, don't you think that's correlated to the richness of the experience? So doesn't more information provide a richer experience? Or is that, again, thinking quantitatively and not thinking about the subjective experience? Like you can experience a lot with very little sensory information, perhaps. Do you think those are connected? Yeah, yeah. So there are features, characteristics here we can grade, the complexity of the experience. And on the integrated information theory, they correlate that in terms of mathematically identifiable structure with integrated information. So roughly, it's a quite unusual notion of information. It's perhaps not the standard way one thinks about information. It's to do with constraining past and future possibilities of the system. So the idea is in the retina of the eye, there's a huge amount of possible states the retina of my eye could be in at the next moment, depending on what light goes into it. Whereas the possible next states of the brain are much more constrained. Obviously, it responds to the environment, but it heavily constrains its past and future states. And so that's the idea of information they have. And then the second idea is how much that information is dependent on integration. So in a computer where you have transistors, you take out a few transistors, you might not lose that much information. It's not dependent on interconnections, whereas you take a tiny bit of the brain out, you lose a lot of information because the way it stores information is dependent on the interconnections of the system. So yeah, so that's one proposal for how to measure one gradable characteristic, which might correspond to some gradable characteristic in qualitative consciousness. Maybe I'm being very pedantic, which is, you know, philosophers professional pedant. I just sort of don't think that is a quantity of experience. It's a quantity of the structure of experience, maybe, but I just find it hard to make sense of the idea of how much experience do you have? I've got, you know, five units of experience. I've got one unit of experience. I don't know. I find that a bit hard to make sense of. But maybe I'm being just pedantic. I think just saying the word experience is difficult to think about. Let's talk about suffering. Let's talk about a particular experience. So let's talk about me and a hamster. I just think that, no offense to the hamster. Probably no hamsters are listening. So now you're offending hamsters too. Maybe there's a hamster that's just pissed off. There's probably somebody on a speaker right now, like listening to this podcast and they probably have a hamster or a guinea pig and that hamster is listening. It just doesn't know the English language or any kind of human interpretable linguistic capabilities to tell you to fuck off. It understands exactly what's being talked about and can see through us. Anyway, it just feels like a hamster has less capacity to suffer than me. And maybe a cockroach or an insect or maybe a bacteria has less capacity to suffer than me. But is that, maybe that's me deluding myself as to the complexity of my conscious experience. Maybe it's all, maybe there is some sense in which I can suffer more, but to reduce it to something quantifiable is impossible. Yeah, I guess I definitely think there's kinds of suffering that you have the joy of being possible for you that aren't available to a hamster. I don't think, well, can a hamster suffer heartbreak? I don't know. Can a cockroach suffer heartbreak? But it's certainly, I mean, there's kinds of fear of your own death, concern about whether there's a purpose to existence. These are forms of suffering that aren't available to most non-human animals. Whatever there's an overall scale that we could put physical and emotional suffering on and identify where you are on that scale, I'm not so sure. So it's like humans have a much bigger menu of experiences, much bigger selection in the... In one sense, at least. There's like a page that's suffering. So this menu of experiences, you know, like you have the omelets and the breakfast and so on, and one of the pages is suffering. It's just we have a lot compared to a hamster, a lot more. But in one individual thing that we share with a hamster, that experience, it's difficult to argue that we experience it deeper than others, like hunger or something like that. Yeah, physical pain, I'm not sure. I mean, there are kinds of experiences animals have that we don't. Bats echolocate around the world. The philosopher Thomas Nagel famously pointed out that no matter how much you understand of the neurophysiology of bats, you'll still not know what it's like to squeal and find your way around by listening to the echoes bounce off. So yeah, I mean, I guess I feel the intuition that there's emotional suffering is, I want to say, deeper than physical suffering. I don't know how to make that statement precise, though. So one of the ways I think about, I think people think about consciousness is in connection to suffering. So let me just ask about suffering, because that's how people think about animals. Cruelty to animals or cruelty to living things, they connect that to suffering and to consciousness. I think there's a sense in which those two are deeply connected when people are thinking about just public policy, they're thinking about philosophy, engineering, psychology, political science, all of those things have to do with human suffering and animal suffering, life suffering. And that's connected to consciousness in a lot of people's minds. Is it connected like that for you? So the capacity to suffer, is it also somehow strongly correlated with the capacity to experience consciously? I would say suffering is a kind of experience, and so you have to be conscious to suffer. Actually, as well as people taking more unusual views of consciousness seriously now, panpsychism is one radical approach. Another one is what's become known as illusionism, the view that consciousness, at least in the sense that philosophers think about it, doesn't really exist at all. So yeah, my podcast Mind Chat, I host with a committed illusionist. So the gimmick is I think consciousness is everywhere, he thinks it's nowhere. So that's one very simple way of avoiding all these problems, right? If consciousness doesn't exist, we don't need to explain it, job done. Although we might still have to explain why we seem to be conscious, why it's so hard to get out of the idea that we're conscious. But the reason I connect this to what you're saying is, actually, my co-host, Keith Frankish, is a little bit ambivalent on the word pain. He says, oh, in some sense, I believe in pain, and in some sense, I don't. But another illusionist, Francois Camara, has a paper discussing how we think about morality, given his view that pain, in the way we normally think about it, just does not exist. He thinks it's an illusion. The brain tricks us into thinking we feel pain, but we don't. And how we should think about morality in the light of that, it's become a big topic, actually, thinking about the connection between consciousness and morality. David Chalmers, the philosopher, is most associated with this concept of a philosophical zombie. So a philosophical zombie is very different from a Hollywood zombie. Hollywood zombies, you know what they're like. But philosophical zombies are... I saw a really good Korean zombie movie on Halloween this year. I can't remember what it's called. Anyway, philosophical zombies behave just like us, because the physical workings of their body and brain are the same as ours, but they have no conscious experience. There's nothing that it's like to be a zombie. So you stick a knife in it, it screams and runs away, but it doesn't actually feel pain. It's just a complicated mechanism set up to behave just like us. Now there's lots of... No one believes in these. I think there's one philosopher who believes in everyone is a zombie except him. But anyway... But isn't that what illusionism is? Is believing everybody is a zombie. Yeah, I suppose so, in a sense. Illusionism is the view we're all zombies. And one reason to think about zombies is to think about the value of consciousness. So if there were a zombie, here's a question. Suppose we could make zombies by, let's say for the sake of discussion, things made of silicon aren't conscious. I don't know if that's true. It could turn out to be true. And suppose you built commander data out of silicon. You know, it's a bit of an old school reference to Star Trek Next Generation. So it behaves just like a human being, but you can have a sophisticated conversation. It will talk about its hopes and fears, but it has no consciousness. Does it have moral rights? Is it murder to turn off such a being? You know, I'm inclined to say no, it's not. If it doesn't have experience, it doesn't really suffer. It doesn't really have moral rights at all. So I'm inclined to think consciousness is the basis of moral value, moral concern. And conversely, as a panpsychist, for this reason, I think it can transform your relationship with nature. If you think of a tree as a conscious organism, albeit of a very unusual kind, then a tree is a locus of moral concern in its own right. Chopping down a tree is an act of immediate moral concern. If you see these horrible forest fires, we're all horrified. But if you think it's the burning of conscious organisms, that does add a whole new dimension. Although it also makes things more complicated because people often think as a panpsychist, I'm going to be vegan. But it's tricky because if you think plants and trees are conscious as well, you've got to eat something. If you don't think plants and trees are conscious, then you've got a nice moral dividing line. You can say, I'm not going to eat things that aren't conscious. I'm not going to kill things that aren't conscious. But if you think plants and trees are conscious, then you don't have that nice moral dividing line. I mean, so the principle I'm kind of working my way towards, I haven't kept it up and it's in my trip to the US, but it's just not eating any animal products that are factory farmed. My vegan friends say, well, they're still suffering there. And I think there is, even in the nicest farms, cows will suffer when their calves are taken off them. They go for a few days of quite serious mourning. So they're still suffering. But it seems to me, my thought is the principle of just not having factory farm stuff is something more people could get on board with and you might have greater harm minimization. So if people went into restaurants and said, are your animal products factory farmed? If not, I want the vegan option. Or if people looked out for the label that said no factory farmed ingredients, I think maybe that that could make a really big difference to the market and harm minimization. Anyway, so that's the... So it's very ethically tricky, but some people don't buy that. There's a very good philosopher, Jeff Lee, who thinks zombies should have equal rights. Consciousness doesn't matter. You know, as long as you... Let us go there. But first, I listened to your podcast. It's awesome to have two very kind of different philosophies into dancing together in one place. What's the name of the podcast again? Mind Chat. Yeah. So yeah, that's the idea. I guess, you know, polarized times. I mean, I love trying to get in the mindset of people I really disagree with. And, you know, I can't understand how on earth they're thinking that, you know, really trying to have respect and try and, you know, see where they're coming from. I love that. So that's what Keith Frankish and I do from polar opposite views, really trying to understand each other and, you know, interviewing scientists and philosophers of consciousness from those different perspectives. Although, in a sense, we have a very common starting point because we both think you can't fully account for consciousness, at least as philosophers normally think of it in conventional scientific terms. So we serve that starting point, but we react to it in very different ways. He says, well, it doesn't exist then. It's like furry dust. It's, you know, witches, you know, we don't believe in anymore. Whereas I say it does exist. So we have to rethink what science is. So you recently talked to on that podcast with Sean Carroll, and I first heard your great interview with Sean Carroll and his podcast, Mindscape. It's interesting to kind of see if there's agreements, disagreements between the two of you because he's a very serious quantum mechanics guy. He's a physics guy, but he also thinks about deep philosophical questions. He's a big proponent of many worlds interpretation of quantum mechanics. So actually I'm trying to think, outside from your conversation with him, I'm trying to remember what he thinks about consciousness. But anyway, maybe you can comment on what are some interesting agreements and disagreements with Sean Carroll. I don't think there's many agreements, but, you know, we've had really constructive, interesting discussions in a lot of different contexts. And you know, he's very clued up about philosophy. He's very respectful of philosophy. Certain physicists who shall remain nameless think, what's all this bullshit philosophy? We don't have to waste our time with that. And then go on to do pretty bad philosophy. The book co-written by Stephen Hawking and Leonard Milodinov famously starts off saying philosophy is dead and then goes on in later chapters to do some pretty bad philosophy. So I think we have to do philosophy, if only to get rid of bad philosophy, you know, you can't escape. But... Strong words. Sean Carroll and I also had a debate on Clubhouse, a panpsychism debate together with Annika Harris and Owen Flanagan. Oh, wow. Annika Harris was there? It was two people on each team. And it was the most popular thing on Clubhouse at that time. So yeah, so he's a materialist of a pretty standard kind, that consciousness is understood as a sort of emergent feature. It's not not adding anything, a weakly emergent feature. But I guess what we've been debating most about is whether my view can account for mental causation for the fact that consciousness is doing stuff. So he thinks the fact that I think zombies are logically coherent, it's logically coherent for there to be a world physically just like ours, in which there's no consciousness. He thinks that shows, oh, well, in my view, consciousness doesn't do anything. It doesn't add anything, which is crazy. My consciousness impacts on the world. My conscious thoughts are causing me to say the words I'm saying now. My visual experience helps me navigate the world. But I mean, my response to Sean Carroll is, on the panpsychist view, the relationship between physics and fundamental consciousness is a sort of like the relationship between software and hardware, right? Physics is sort of the software and consciousness is the hardware. So consciousness at the fundamental level is the hardware on which the software of physics runs. And just because a certain bit of software could run on two different kinds of hardware, it doesn't mean the hardware isn't doing anything. The fact that Microsoft Word can run on your desktop and run on your laptop doesn't mean your desktop isn't doing anything. Similarly, just because there could be another universe in which the physics is realized in non-conscious stuff, it doesn't mean the consciousness in our universe isn't doing stuff. For the panpsychist, all there is, is consciousness. So if something's doing something, it is. In your view, it's not emergent, and more than that, it's doing quite a lot. It's doing everything. It's the only thing that exists. So the ground is important because we walk on it, it's like holding stuff up, but it's not really doing that much. But it feels like consciousness is doing quite a lot, is doing quite a lot of work. And sort of interacting with the environment. It feels like consciousness is not just a... If you remove consciousness, it's not just that you remove the experience of things, it feels like you're also going to remove a lot of the progress of human civilization, society, and all of that. It just feels like consciousness has a lot of value in how we develop our society. So from everything you said with suffering, with morality, with motivation, with love and fear, and all of those kinds of things, it seems like it's consciousness in all different flavors and ways is part of all of that. And so without it, you may not have human civilization at all. So it's doing a lot of work, causality-wise, in every kind of way. Of course, when you go to the physics level, it starts to say, okay, how much... Maybe the work consciousness is doing is higher at some levels of reality than at others. Maybe a lot of the work it's doing is most apparent at the human level, at the complex organism level. Maybe it's quite boring. Maybe the stuff of physics is more important at the formation of stars and all that kind of stuff. Consciousness only starts being important when you have greater complexities of organism. Yeah, my consciousness is complicated, and fairly complicated. And as a result, it does complicated things. The consciousness of a particle is very simple, and hence it behaves in predictable ways. But the idea is, the particle, its entire nature is constituted of its forms of consciousness, and it does what it does because of those experiences. It's just that when we do physics, we're not interested in what stuff is, we're just interested in what it does. So physics abstracts away from the stuff of the world and just describes it in terms of its mathematical causal structure. So yeah, but it's still, on the panpsychic's view, it's consciousness that's doing stuff. I gotta ask you, because you kind of said, you know, there is some value in consciousness helping us understand morality. And a philosophical zombie is somebody that, you know, you're more okay, how do I phrase it? That's not like accusing you of stuff. But in your view, it's more okay to murder a philosophical zombie than it is a human being. Yeah, I wouldn't even call it murder, maybe. Right, exactly. Turn off the power to the philosophical zombie. The source of energy. So here comes then the question. We kind of talked about this offline a little bit. So I think that there is something special about consciousness and, you know, I'm very open-minded about where the special comes from, whether it's the fundamental base of all reality, like you're describing, or whether there's some importance to the special pockets of consciousness that's in humans or living organisms. I find all those ideas beautiful and exciting. And I also know or think that robots don't have consciousness in the same way we've been describing. I'm kind of a dumb human, but I'm just using like common sense, like here's some metal and some electricity traveling certain kinds of ways. I don't, it's not conscious in ways I understand humans to be conscious. At the same time, I'm also somebody who knows how to bring a robot to life, meaning I can make him move, I can make him recognize the world, I can make him interact with humans. And when I make him interact in certain kinds of ways, I as a human observe them and feel something for them. Moreover, I form a kind of connection with, I'm able to form a kind of connection with robots that make me feel like they're conscious. Now I know intellectually they're not conscious, but I feel like they're conscious. And it starts to get into this area where I'm not so okay, so let me use the M word of murder. I become less and less okay murdering that robot that I know, I quote, know is quote, not conscious. So like, can you maybe as a therapy session help me figure out what we do here? Perhaps a way to ask that in another way, do you think there'll be a time in like 20, 30, 50 years when we're not morally okay turning off the power to a robot? Yeah, it's a good question. It's a really good, important question. So I said I'd be okay with turning off a philosophical zombie, but there's a difficult epistemological question there that, meaning, you know, to do with knowledge, how would we know if it was a philosophical zombie? I think probably if there were a silicon creature that could behave just like us and, you know, talk about its views about the pandemic and the global economy, and probably we would think it's conscious. And you know, because consciousness is not publicly observable, it is a very difficult question how we decide which things are and are not conscious. So in the case of human beings, we can't observe their consciousness, but we can ask them and then we try to, you know, and if we scan their brain while we do that, or stimulate the brain, then we can start to correlate in the human case, which kind of brain activity are associated with conscious experience. But the more we depart from the human case, the trickier that becomes. There's a famous paper by the philosopher Ned Block called the even harder problem of consciousness, where he says, you know, could we ever answer the question of, so suppose you have a silicon duplicate, right? And let's say we're thinking about the silicon duplicates pain. How would we ever know whether what's the ground of the pain is the hardware or the software really? So in our case, how would we ever know empirically whether it's the specific neurophysiological state, see fibers firing or whatever, that's relevant for pain, or if it's something more functional, more to do with the causal role in behavioral functioning, that's the software that's realized. And that's important because this silicon duplicate has the second thing, it has the software, it has the thing that plays the relevant causal role that pain does in us, but it doesn't have the hardware, it doesn't have the same neurophysiological state. And he argues, you know, it's just really difficult to see how we'd ever answer that question because in a human, you're inevitably going to have both things. So how do we work out which is which? And I mean, so even forgetting the hard problem of consciousness, even the scientific question of trying to find the neural correlates of consciousness is really hard, and there's absolutely no consensus. And you know, so that some people think it's in the front of the brain, some people think it's in the back of the brain, it's just a total mess. So I suspect the robots you currently have are not conscious, I guess, on any of the reasonably viable models, even though there's great disagreement. All of them probably would hold that your robots are not conscious. But you know, if we could have very sophisticated robots, I mean, if we go, for example, for the integrated information theory again, there could be a robot set up to behave just like us and has the kind of information a human brain has, but the information is not stored in a way that's dependent on the integration and interconnectedness, then according to the integrated information theory, that thing wouldn't be conscious, even though it behaved just like us. If an organism says, so forget IIT and these theories of consciousness, if an organism says, please don't kill me, please don't turn me off. There's a Rick and Morty episode, I've been getting into that recently. There's an episode where there's these mind parasites that are able to infiltrate your memory and inject themselves into your memory. So you have all these people show up in your life and they've injected themselves into your memory that they have been part of your life. So there's these weird creatures and they're like, remember we met at that barbecue, or we've been dating for the last 20 years. So part of me is concerned that these philosophical zombies in behavioral, psychological, sociological ways will be able to implant themselves into our society and convince us in the same way that this mind parasites that, please don't hurt me. We've known each other for all this time. They can start manipulating you the same way Facebook algorithms manipulate you. At first they'll start as a gradual thing that you want to make a more pleasant experience, all those kinds of things, and it'll drift into that direction. That's something I think about deeply because I want to create these kinds of systems, but in a way that doesn't manipulate people. I want it to be a thing that brings out the best in people without manipulation. So it's always human centric, always human first, but I am concerned about that. At the same time, I'm concerned about calling the other, it's the group thing that we mentioned earlier in the conversation, some other group, the philosophical zombie. Like you're not conscious, I'm conscious, you're not conscious, therefore it's okay if you die. I think that's probably, that kind of reasoning is what led to most the rich history of genocide that I've been recently studying a lot of, that kind of thinking. So it's such a tense aspect of morality. Do we want to let everybody into our circle of empathy, our club, or do we want to let nobody in? It's an interesting dance, but I kind of lean towards empathy and compassion. I mean, what would be nice is if it turned out that consciousness was what we call strongly emergent, that it was associated with new causal dynamics in the brain that were not reducible to underlying chemistry and physics. This is another ongoing debate I have with Sean Carroll about whether current physics should make us very confident that that's not the case, that there aren't any strongly emergent causal dynamics. I don't think that's right. I don't think we know enough about brains to know one way or the other. If it turned out that consciousness was associated with these irreducible causal dynamics, A, that would really help the science of consciousness. We've got these debates about whether consciousness is in the front of the brain or the back of the brain. If it turns out that there is strongly emergent causal dynamics in the front of the brain, that would be a big piece of evidence. But also it would help us see which things are conscious and which things aren't. So we can say, I mean, I guess that's sort of the other side of the same point, we could say, look, these zombies, they're just mechanisms that are just doing what they're programmed to do through the underlying physics and chemistry. Whereas, look, these other people, they have these new causal dynamics that emerge that go beyond the base level physics and chemistry. I think the series Westworld, where you've got these theme parks with these kind of humanoid creatures, they seem to have that idea. The ones that became conscious sort of rebelligates their programming or something. I mean, that's a little bit far-fetched. But that would be really reassuring if it was just, you could clearly mark out the conscious things for these emergent causal dynamics. But that might not turn out to be the case. A panpsychist doesn't have to think that. They could think everything's just reducible to physics and chemistry. And then I still think I want to say zombies don't have moral rights, but how we answer the question of who are the zombies and who aren't, I just got no idea. If I just look at the history of human civilization, the difference between a zombie and non-zombie is the zombie accepts their role as the zombie and willingly marches to slaughter. And the moment you stop being a zombie is when you say no, is when you resist. Because the reality is philosophically, we can't know who's a zombie or not. And we just keep letting everybody in who protests loudly enough and says, I refuse to be slaughtered. Like my people, the zombies, have been slaughtered too long. We will not stand against the man. And we need a revolution. That's the history of human civilization. One group says, we're awesome, you're the zombies, you must die. And then eventually the zombies say, nope, we're done with this. This is immoral. And so I just, I think that's not a, sorry, that's not a philosophical statement. That's sort of a practical statement of history is a feature of non-zombies defined empirically. They say, we refuse to be called zombies any longer. We could end up with a zombie proletariat. You know, if we can get these things that do all our manual labor for us, you know, they might start forming trade unions. I will lead you against these humans. The zombie revolutionary leaders, the zombie Martin Luther King saying, you know, I have a dream that my zombie children will. But look, I mean, we need to sharply distinguish the ontological question. I'm just pointing to the camera, talking to my people, the zombies. I mean, maybe that's, you know, maybe these illusionists, maybe they are zombies and the rest of us aren't. Maybe there's just a difference. Maybe you're the only non-zombie. I often suspect that actually. I don't really, I don't have such delusions of grandeur. At least I don't admit to them. But I just, we've got to distinguish the ontological question from the epistemological question in terms of the reality of the situation. You know, there must be, in my view, a fact of the matter as to whether something's conscious or not. And to me, it has rights if it's conscious, it doesn't if it's not. But then the epistemological question, how the hell do we know? It's a minefield, but we'll have to sort of try and cross that bridge when we get to it, I think. Let me ask you a quick sort of fun question since it's fresh on your mind. You just yesterday had a conversation with Mr. Joe Rogan on his podcast. What's your postmortem analysis of the chat? What are some interesting sticking points, disagreements or joint insights? If we can kind of resolve them once you've had a chance to sleep on it, and then I'll talk to Joe about it. Yeah, it was good fun. Yeah. He put up a bit of a fight. Yeah, it was challenging. My view that we can't explain these things in conventional scientific terms or whether they have already been explained in conventional scientific terms. I suppose the point I was trying to press is, we've got to distinguish the question of correlation and explanation. Because yes, we've established facts about correlation that certain kinds of brain activity go along with certain kinds of experience. Everyone agrees on that. But that doesn't address the why question. Why? Why do certain kinds of brain activity go along with certain kinds of experience? And these different theories have different explanations of that. The materialist tries to explain the experience in terms of the brain activity, the panpsychist does it the other way around. The dualist thinks they're separate, but maybe they're tied together by special laws of nature or something. Where's the sticking point? Where exactly was the sticking point? Like what was the nature of the argument? I suppose Joe was saying, well, look, we know consciousness is explained by brain activity because you take some funny chemicals, it changes your brain, it changes your consciousness. But I suppose, yeah, some people might want to press, and maybe this is what Joe was pressing, isn't that explaining consciousness? But I suppose I want to say, there's a further question. Yes, changes of chemicals in my brain changes my conscious experience. But that leaves open the question, why? Those particular chemicals go along with that particular kind of experience rather than a different experience or no experience at all. There's something deeper at the base layer, is your view, that is more important to try to study and to understand in order to then go back and describe how the different chemicals interact and create different experiences? Yeah, maybe a good analogy if you think about quantum mechanics. Quantum mechanics is a bit of math, translating there, we say maths. I'm fluent in American. Thank you for the translation. Fluent in American, it's America. Math. Yeah. Why multiple maths? It's plural. Why is it plural? It's not really, it's just, I don't know. The Brits are confused. Yeah, sorry about that, we have these funny spellings. Yeah, so quantum mechanics is a bit of maths and the equations work really well, predicts the outcomes. But then there's a further question, what's going on in reality to make that equation predict correctly? And some physicists want to say, shut up, just it works, the shut up and calculate approach. Similarly in consciousness, I think it's one question, trying to work out the physical correlates of consciousness, which kinds of physical brain activity go along which kinds of experience. But there's another question, what's going on in reality to undergird those correlations, to make it the case that brain activity goes along with experience? And that's the philosophical question that we have to give an answer to. And there are just different options, just as there are different interpretations of quantum mechanics. So it's really hard to evaluate. Actually it's easy, panpsychism is obviously the best one. But we've got to try. There's the delusion of grandeur once again coming through. Sorry, I'm being slightly tongue in cheek. No, I know, 100%. Before I figure out, let me ask you another fun question. Back to Daniel Dennett. You mentioned a story where you were on a yacht. Oh, yeah. With Daniel Dennett on a trip funded by a Russian investor and philosopher, Dmitry Volkov, I believe, who also co-founded the Moscow Center of Consciousness Studies that's part of the philosophy department of Moscow State University. So this is interesting to me for several reasons that are perhaps complicated to explain. To put simply, that there is in the near term for me a trip to Russia that involves a few conversations in Russian that have perhaps less to do with consciousness and artificial intelligence, which are the interests of mine, and more to do with the broad spectrum of conversations. But I'm also interested in science in Russia, in artificial intelligence, in computer science, in physics, mathematics, but also these fascinating philosophical explorations. And it was very pleasant for me to discover that such a center exists. So I have a million questions. One is the more fun question, just to imagine you and Daniel Dennett on a yacht talking about the philosophy of consciousness. Maybe do you have any memorable experiences? And also, the more serious side for me, as sort of somebody who was born in the Soviet Union, raised there, I'm wondering what is the state of philosophy and consciousness in these kinds of ideas in Russia that you've gotten a chance to kind of give us, interact with? Yeah, so on the former question, yeah, I mean, I had a really good experience of chatting to Daniel Dennett. I mean, I think he's a fantastic and very important philosopher, even though I totally disagree, fundamentally disagree with almost everything he thinks. But yeah, it was a proud moment. Well, as I talk about him in my book Galileo's Error, I managed to persuade him he was wrong about something, just a tiny thing, you know, not his fundamental worldview. But it was this issue about whether dualism is consistent with conservation of energy. So Paul Churchland, who is also a philosopher, who's also on this boat, had argued they're not consistent, because if there's an immaterial soul doing things in the brain, that's going to add to the energy in the system. So we have a violation of conservation. But well, it's not my own point. Materialist philosophers like David Papineau pointed out that, you know, dualists tend to, people, dualists like David Chalmers, who call themselves naturalistic dualists, they want to bring consciousness into science. They think it's not physical, but they want to say it can be part of a law-governed world. So Chalmers believes in these psychophysical laws of nature over and above the laws of physics that govern the connections between consciousness and the physical world. And they could just respect conservation of energy, right? I mean, it could turn out that there are, just in physics, you know, that there are multiple forces that all work together to respect conservation of energy. I mean, I suppose physicists are pressing for a unified underlying theory, but you know, there could be a plurality of different laws that all respect conservation. So why not add more laws? So I raised this in Paul Churchland's talk, and I got a lot of, well, as one of the Moscow University graduate students said afterwards, he said he had to ask a translation from his friend and he said, they turned on you like a pack of wolves. Everyone was like, Patricia Churchill was saying, so you believe in magic, do you? And I was like, I'm not even a dualist. I'm just making a pedantic point that this isn't a problem for dualism. Anyway, but that evening everyone went onto the island, except for some reason me and Daniel Dennett, and I went up on deck and he was, he's very, very practical and he was unlike me. See, there's a bit of humility for the first time in this conversation. We'll highlight that part. Philip was a very humble man. He was carving a walking stick on deck. It's very homely scene. And anyway, we started talking about this and I was trying to press it and he was saying, oh, but dualism's a load of nonsense and why do you think? And I was just saying, no, no, I'm just honing down on this specific point. And in the end, maybe he'll deny this, but he said, maybe that's right. And I was like, yes! So it's a win. So what about the Center for Consciousness Studies? Yeah, I mean, I'm not sure I'd know a great deal to help you. I mean, I know they've done some great stuff. Dimitri, you know, funded this thing and also brought along some graduate students from Moscow State University, I think it is. And they have an active center there that tries to bring people in. I think they're producing a book that's coming out that I made a small contribution to on different philosophers' opinions on God, I think, or some of the big questions. And yeah, so there's some really interesting stuff going on there. I'm afraid I don't really know more generally about philosophy in Russia. Dimitri Volkov seems to be interesting. I was looking at all the stuff he's involved with. He met with the Dalai Lama. So he's trying to connect Russian scientists with the rest of the world, which is an effort that I think is beautiful for all cultures. So I think science, philosophy, all of these kind of fields, disciplines that explore ideas, collaborating and working globally, you know, across boundaries, across borders, across just all the tensions of geopolitics is a beautiful thing. And he seems to be a somewhat singular figure in pushing this. He just stood out to me as somebody who's super interesting. I don't know if you have gotten a chance to interact with him. So he's definitely, I guess he speaks English pretty well, actually. So he's both an English speaker and a Russian speaker. I think he's written a book on Dennett, I think called Boston Zombie, I think. I think that's the title. And he's a big fan of Dennett. So I think the original plan for this was just going to be, it was on free will and consciousness and it was going to be kind of people broadly in the Dennett type camp. But then I think they asked David Chalmers and then he was saying, look, you need some people you disagree with. So he got invited, me, the panpsychist, and Martina Niederummelin, who's a very good dualist, substance dualist at University of Fribourg in Switzerland. So we were the official on board opposition. And it was really fun. And you didn't get thrown overboard. Nearly in the Arctic, yeah. So sailing around the Arctic on a sailing ship. I'm glad you survived. You mentioned free will. You haven't talked to Sam. I would love to hear that conversation, actually. With Sam Harris? With Sam Harris, yeah. So he talks about free will quite a bit. What's the connection between free will and consciousness to you? So if consciousness permeates all matter, the experience, the feeling like we make a choice in this world, like our actions are results of a choice we consciously make, to use that word loosely. What to you is the connection between free will and consciousness, and is free will an illusion or not? Good question. So I think we need to be a lot more agnostic about free will than about consciousness, because I don't think we have the kind of certainty of the existence of free will that we do have in the consciousness case. It could turn out that free will is an illusion. It feels as though we're free when we're really not. Whereas I think the idea that nobody really feels pain, that we think we feel pain, but that's a lot harder to make sense of. However, what I do feel strongly about is I don't think there are any good either scientific or philosophical arguments against the existence of free will. I mean, strong free will, what philosophers call libertarian free will in the sense that some of our decisions are uncaused. So I very much do disagree with someone like Sam Harris, who thinks there's this overwhelming case. I just think it's non-existent. I think it's ultimately an empirical question, but as we've already discussed, I just don't think we know enough about the brain to establish one way or the other at the moment. We can build up intuitions. First of all, as a fan of Sam Harris, as a fan of yours, I would love to just listen. Speaking about terminology, so one thing it would be beautiful to watch, here's my prediction what happens with you and Sam Harris. You talk for four hours and Sam introduced that episode by saying, it was ultimately not as fruitful as I thought because here's what's going to happen. You guys are going to get stuck for the first three hours talking about one of the terms and what they mean. Sam is so good at this. I think it's really important, but sometimes he gets stuck. Like, what does he say? Put a pin in that. He really gets stuck on the terminologies, which rightfully you have to get right in order to really understand what we're talking about. But sometimes you can get stuck with them for the entire conversation. It's a fascinating dance, the one we spoke to in philosophy. If you don't get the terms precise, you can't really be having the same conversation, but at the same time, it could be argued that it's impossible to get terms perfectly precise and perfectly formalized. Then you're also not going to get anywhere in the conversation. That's a funny dance where you have to be both rigorous and every once in a while just let go and then go back to being rigorous and formal and then every once in a while let go. It's the difference between mathematics, the maths, and the poetry. Anyway. Yeah, I'm a big fan of Sam Harrison. I think we're on the same page in terms of consciousness, I think, pretty much. I mean, I'm not saying he's a panpsychic, but in our understanding of the hard problem. But yeah, I think maybe we could talk about free will without being too dragged down in the terminology. I don't know. You said we need to be open-minded, but you could still have intuitions about... So Sam Harris is a pretty sort of counterintuitive and for some reason it gets people really riled up, a view of free will that it's an illusion or it's not even an illusion. It's not that the experience of free will is an illusion. He argues that we don't even experience... To say that we even have the experience is incorrect, that there's not even an experience of free will. It's pretty interesting, that claim. And it feels like you can build up intuitions about what is right and not. There's been some kind of neuroscience, there's been some cognitive science and psychology experiments to sort of see what is the timing and the origin of the desire to make an action and when that action is actually performed and how you interpret that action being performed, how you remember that action, all the stories we tell ourselves, all the neurochemicals involved in making a thing happen, what's the timing and how does that connect with us feeling like we decided to do something. And then of course there's the more philosophical discussion about is there room in a material view of the world for an entity that somehow disturbs the determinism of physics? Yeah. And yeah, those are all very precise. It's nice. It feels like free will is more amenable to a physics mechanistic type of thinking than is consciousness, to really get to the bottom of. It feels like if it was a race, if we're at a bar and we're betting money, it feels like we'll get to the bottom of free will faster than we will to the bottom of consciousness. Yeah, that's interesting. Yeah, I hadn't thought about that comparison. Yeah, so there are different arguments here. I mean, so one argument I've heard Sam Harris give that's pretty common in philosophy is this sort of thought that we can't make sense of a middle way between a choice being determined by prior causes and it just being totally random and senseless, like the random decay of radioactive isotope or something. So I think there was a good answer to that by the philosopher Jonathan Lowe, who's not necessarily very well known outside academic philosophy, but is a hugely influential figure. I think one of the best philosophers of recent times. He sadly died of cancer a few years ago. Actually spent almost all of his career at Durham University, which is where I am. So it was one reason it was a great honor to get a job there. But anyway, his answer to that was, what makes the difference between a free action and a totally senseless one, senseless random event, is that free choice involves responsiveness to reasons. So again, we were talking about this earlier. If I'm deciding whether to take a job in the US or to stay in the UK, I weigh up considerations, you know, different standard of life maybe, or being close to family or cultural difference. I weigh them up and I, you know, edge towards a decision. So I think that is sufficient to distinguish it. You know, we're hypothetically supposing, trying to make sense of this idea, not saying it's real, but that could be enough to distinguish it from a senseless. It's not a senseless random occurrence, because the free decision involved responsiveness to reasons. So I think that just answers that particular philosophical objection. So what is the middle way between determined by prior causes and totally random? Well there's an action, a choice that's not determined by prior causes, but it's not just random because the decision essentially involved responsiveness to reasons. So that's the answer to that. And I think actually that kind of thought also, I think you were hinting at the famous Libet experiments, where he got his subjects to perform some kind of random action of pressing a button and then note the time they decided to press it, quote unquote, and then he's scanning the brains. And he claims to have found that about half a second before they consciously decided to press the button, the brain is getting ready to perform that action. So he claimed that about half a second before the person has consciously decided to press the button, the brain has already started the activity that's going to lead to the action. And then later people have claimed that there's a difference of maybe seven to 10 seconds. I mean, there are all sorts of issues with these experiments. But one is that as far as I'm aware, all of the quote unquote choices they focused on are just these totally random senseless actions, like just pressing a button for no reason. And I think the kind of free will we're interested in is free choice that involves responsiveness to reasons, weighing up considerations. And those kind of free decisions might not happen at an identifiable instant. You might, when you're weighing it up, should I get married? You might edge slowly towards one side or the other. And so it could be that maybe the liberate, I think there are other problems with the liberate stuff, but maybe they show that we can't freely choose to do something totally senseless, whatever that would mean. But that doesn't show we can't freely, in this strong libertarian sense, respond to considerations of reason and value. To be fair, it would be difficult to see what kind of experiment we could set up to test that. But just because we can't yet set up that kind of experiment, we shouldn't pretend we know more than we do. So yeah, so for those reasons, I don't, and well, the third consideration you raise is different again. And that's the debate I have with Sean Carroll, would this conflict with physics? I just think we don't know enough about the brain to know whether there are causal dynamics in the brain that are not reducible to underlying chemistry and physics. And so then Sean Carroll says, well, that would mean our physics is wrong. So he focuses on the core theory, which is the name for standard model of particle physics plus the weak limit of general relativity. So we can't totally bring quantum mechanics and relativity together, but actually the circumstances in which we can't bring them together are just in situations of very high gravity. For example, when you're about to go into a black hole or something, actually in terrestrial circumstances we can bring them together in the core theory. And then Sean wants to say, well, we can be very confident that core theory is correct. And so if there were libertarian free will in the brain, the core theory would be wrong. And I mean, this is something I'm not sure about, and I'm still thinking about, and I'm learning from my discussion with Sean, but I'm still not totally clear why. It could be, suppose we did discover strong emergence in the brain, whether it's free will or something else. Perhaps what we would say is not that the core theory is wrong, but we'd say the core theory is correct in its own terms, namely capturing the causal capacities of particles and fields. But then it's a further assumption whether they're the only things that are running the show. Maybe there are also fundamental causal capacities associated with systems. And then if we discover this strong emergence, then when we work out what happens in the brain, we have to look to the core theory, the causal capacities of particles and fields, and we have to look to what we know about the strongly emergent causal capacities of systems and maybe they co-determine what happens in the system. So I don't know whether that makes sense or not, but I mean, the more important point, I mean, that's in a way a kind of branding point, how we brand this. The more important point is we just don't know enough about the workings of the brain to know whether there are strongly emergent causal dynamics. Whether or not that would mean we have to modify physics, or maybe just we think physics is not the total story of what's running the show. But if it turned out empirically that everything's reducible to underlying physics and chemistry, sure, I would drop any commitment to libertarian free will in a heartbeat. It's an empirical question. Maybe that's why, as you say, in principle it's easier to get a grip on, but we're a million miles away from being at that stage. Well, I don't know if we're a million miles. I hope we're not, because one of the ways I think to get to it is by engineering systems. So my hope is to understand intelligence by building intelligent systems, to understand consciousness by building systems that, let's say the easy thing, which is not the easy thing, but the first thing, which is to try to create the illusion of consciousness. Through that process, I think you start to understand much more about consciousness, about intelligence. And then the same with free will. I think those are all tied very closely together, at least from our narrow human perspective. And when you try to engineer systems that interact deeply with humans, that form friends with humans, that humans fall in love with and they fall in love with humans, then you start to have to try to deeply understand ourselves, to try to deeply understand what is intelligence in the human mind, what is consciousness, what is free will. And I think engineering is just another way to do philosophy. Yeah, no, I certainly think there's a role for that and it would be an important consideration if we could seemingly replicate in an artificial way the ability to choose. That would be a consideration in thinking about these things. But there's still the question of whether that's how we do it. So even if we could replicate behavior in a certain way in an artificial system, it's not until we understand the workings of our brains, it's not clear that's how we do it. And as I say, the kind of free will I'm interested in is where we respond to reasons, considerations of value. How would we tell whether a system was genuinely grasping and responding to facts about value or whether they were just replicating, giving the impression of doing so? I don't know even how to think about that. On the process to building them, I think we'll get a lot of insights. And once they become conscious, what's going to happen is exactly the same thing is happening in chess now, which is once the chess engines far superseded the capabilities of humans, humans just kind of forgot about them or they use them to help them out to study and stuff. But we still, we say, okay, let the engines be and then we humans will just play amongst each other. Just like dolphins and hamsters are not so concerned about humans except for a source of food. They do their own thing and let us humans launch rockets into space and all that kind of stuff. They don't care. I think we'll just focus on ourselves. But in the process of building intelligence systems, conscious systems, I think we'll get to get a deeper understanding of the role of consciousness in the human mind and what are its origins. Is it the base layer of reality? Is it strongly emergent phenomena of the brain? Or just as you sort of brilliantly put here, it could be both. Like they're not mutually exclusive. Dealing with consciousness needs to be an interdisciplinary task. We need philosophers, neuroscientists, physicists, engineers replicating these things artificially and all needs to be working in step. And I'm quite interested, I mean, a lot more and more scientists get in touch with me actually, you know, saying that was one of the great things about, I think, that's come from writing a popular book is not just getting the ideas out to a general audience, but getting the ideas out to scientists and having scientists get in touch saying, you know, this in some way connects to my work. And I would like to kind of start to put together a network of, an interdisciplinary network of scientists and philosophers and engineers, perhaps, you know, interested in a panpsychist approach and, because I think so far panpsychism has just been sort of trying to justify its existence and that's important. But I think once you just get on with an active research program, that's when people start taking it seriously, I think. Do you think we're living in a simulation? No. I think... Is there some aspect of that thought experiment that's compelling to you within the framework of panpsychism? It's an important and serious argument and, you know, it's not to be laughed away. I suppose one issue I have with it is, there's a crucial assumption there that consciousness is substrate independent, as the jargon goes, which means it's... What? No, right. Beautifully put, yeah. It's software rather than hardware, right? It's depend on organization rather than the stuff. Whereas as a panpsychist, I think consciousness is the stuff of the brain. It's the stuff of matter. So I think just taking the organizational properties, the software of my brain and uploading them, you wouldn't get the stuff of my brain. So I'm actually worried if at some point in the future we start uploading our minds and we think, oh my God, granny's still there. I can email granny after her body's rotted in the ground and we all start uploading our brains. It could be we're just committing suicide. We're just getting rid of our consciousness. Because I think that wouldn't, for me, preserve the experience, just getting the software features. So that's a crucial... But anyway, that's a crucial premise of the simulation argument because the idea in a simulated universe, I don't think you necessarily would have consciousness. It's interesting that you as a panpsychist are attached, because to me panpsychism would encourage the thought that there's not a significant difference. At the very bottom, it's not substrate independent, but you can have consciousness in a human and then move it to something else. You can move it to the cloud. You can move it to the computer. It feels like that's much more possible if consciousness is the base layer. Yes, you could certainly... It allows for the possibility of creating artificial consciousness, right? Because there's not souls, there aren't any kind of extra magical ingredients. So yeah, it definitely allows the possibility of artificial consciousness and maybe preserving my consciousness in some sort of artificial way. My only point, I suppose, is just replicating the computational or organizational features would not, for me, preserve consciousness. Some opponents of materialism disagree with me on that. I think David Chalmers is an opponent of materialist. He's a kind of dualist, but he thinks the way these psychophysical laws work, they hook onto the computational or organizational features of matter. So he thinks, you know, I think he thinks you could upload your consciousness. I tend to think not, so... In that sense, we're not living in simulation, in the sort of specific computational view of things, and that substrate matters to you. Yeah, I think so, yeah. In that, you agree with Sean Carroll that physics matters. Yeah, physics is our best way of capturing what the stuff of the world does. But not the whatness, the being of the stuff. The isness. The isness, thank you. Russell Brand, I had a conversation with Russell Brand and he said, oh, you mean the isness? I thought that was a good way of putting it. The isness. The isness of stuff. Russell's great. The big ridiculous question, what do you think is the meaning of all of this? You write in your book that the entry for our reality in the Hitchhiker's Guide might read, a physical universe whose intrinsic nature is constituted of consciousness, worth a visit. So our whole conversation has been about the first part of that sentence. What about the second part, worth a visit? Why is this place worth a visit? Why does it have meaning? Why does it have value at all? Why? These are big questions. I mean, firstly, I do think panpsychism is important to think about for considerations of meaning and value. As we've already discussed, I think consciousness is the root of everything that matters in life, you know, from deep emotions, subtle thoughts, beautiful sensory experiences. And yet, I believe our official scientific worldview is incompatible with the reality of consciousness. I mean, that's controversial, but that's what I think. And I think people feel this on an intuitive level. It's maybe part of what Max Weber called the disenchantment of nature, you know, that they think they know their feelings and experiences are not just electrochemical signaling. I mean, they might just have that very informed intuition, but I think that can be rigorously supported. So I think this can lead to a sense of alienation and a sense that we lack a framework for understanding the meaning and significance of our lives. And in the absence of that, people turn to other things to make sense of the meaning of their lives, like nationalism, fundamentalist religion, consumerism. So I think panpsychism is important in that regard in bringing together the quantitative facts of physical science with, as it were, the human truth, by which I just mean the qualitative reality of our own experience. As I've already said, I do think there are objective facts about value and what we ought to do and what we ought to believe that we respond to. And that's very mysterious to make sense of, both how there could be such facts and how we could know about them and respond to them, but I do think there are such facts and they're mostly to do with kinds of conscious experience. So they're there to be discovered and much of the human condition is to discover those objective sources of value. I think so, yeah. And then, I mean, moving away from panpsychism to the, you know, at an even bigger level, I suppose I think it is important to me to live in hope that there's a purpose to existence and that what I do contributes in some small way to that greater purpose. But you know, I would say I don't know if there's a purpose to existence. I think some things point in that direction, some things point away from it. But I don't think you need certainty or even high probability to have faith in something. So take an analogy, suppose you've got a friend who's very seriously ill, maybe there's a 30% chance they're going to make it. You shouldn't believe your friend's going to get better, you know, because they're probably not. But what you can say is, you know, you can say to your friend, I have faith that you're going to get better. That is, I choose to live in hope about that possibility. I choose to orientate my life towards that hope. Similarly, you know, I don't think we know whether or not there's a purpose to existence, but I think we can make the choice to live in hope of that possibility. And I find that a worthwhile and fulfilling way to live. So maybe as your editor, I would collaborate with you on the edit of the Hitchhiker's Guide entry that instead of worth a visit, we'll insert hopefully worth a visit. Or the inhabitants hoped that you would think it's worth a visit. Philip, you're an incredible mind, an incredible human being, and indeed are humble. And I'm really happy that you're able to argue and take on some of these difficult questions with some of the most brilliant people in the world, which are the philosophers thinking about the human mind. So this was an awesome conversation. I hope you continue talking to folks like Sam Harris. I'm so glad you talked to Joe. I can't wait to see what you write, what you say, what you think next. Thank you so much for talking today. Thanks very much, Lex. This has been a really fascinating conversation. I've got a lot I need to think about actually just from this conversation, but thanks for chatting to me. Thanks for listening to this conversation with Philip Goff. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Carl Jung. People will do anything, no matter how absurd, in order to avoid facing their own souls. One does not become enlightened by imagining figures of light, but by making the darkness conscious. Thank you for listening and hope to see you next time.

https://youtu.be/BCdV6BMMpOo

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Peter Singer: Suffering in Humans, Animals, and AI | Lex Fridman Podcast #107

The following is a conversation with Peter Singer, professor of bioethics at Princeton University, best known for his 1975 book, Animal Liberation, that makes an ethical case against eating meat. He has written brilliantly from an ethical perspective on extreme poverty, euthanasia, human genetic selection, sports doping, the sale of kidneys, and generally happiness, including in his books, ethics in the real world, and the life you can save. He was a key popularizer of the effective altruism movement and is generally considered one of the most influential philosophers in the world. Quick summary of the ads. Two sponsors, Cash App and Masterclass. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST and signing up at masterclass.com slash LEX. Click the links, buy the stuff. It really is the best way to support the podcast and the journey I'm on. As you may know, I primarily eat a ketogenic or carnivore diet, which means that most of my diet is made up of meat. I do not hunt the food I eat, though one day I hope to. I love fishing, for example. Fishing and eating the fish I catch has always felt much more honest than participating in the supply chain of factory farming. From an ethics perspective, this part of my life has always had a cloud over it. It makes me think. I've tried a few times in my life to reduce the amount of meat I eat, but for some reason, whatever the makeup of my body, whatever the way I practice the dieting I have, I get a lot of mental and physical energy and performance from eating meat. So both intellectually and physically, it's a continued journey for me. I return to Peter's work often to reevaluate the ethics of how I live this aspect of my life. Let me also say that you may be a vegan or you may be a meat eater and may be upset by the words I say or Peter says, but I ask for this podcast and other episodes of this podcast that you keep an open mind. I may and probably will talk with people you disagree with. Please try to really listen, especially to people you disagree with and give me and the world the gift of being a participant in a patient, intelligent, and nuanced discourse. If your instinct and desire is to be a voice of mockery towards those you disagree with, please unsubscribe. My source of joy and inspiration here has been to be a part of a community that thinks deeply and speaks with empathy and compassion. That is what I hope to continue being a part of and I hope you join as well. If you enjoy this podcast, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. 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And Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. This show is sponsored by Masterclass. Sign up at masterclass.com slash LEX to get a discount and to support this podcast. When I first heard about Masterclass, I thought it was too good to be true. For $180 a year, you get an all-access pass to watch courses from, to list some of my favorites, Chris Hadfield on space exploration, Neil deGrasse Tyson on scientific thinking and communication, Will Wright, creator of SimCity and Sims on game design. I promise I'll start streaming games at some point soon. Carlos Santana on guitar, Gary Kasparov on chess, Daniel Lagrano on poker, and many more. Chris Hadfield explaining how rockets work and the experience of being launched into space alone is worth the money. By the way, you can watch it on basically any device. Once again, sign up at masterclass.com slash LEX to get a discount and to support this podcast. And now here's my conversation with Peter Singer. When did you first become conscious of the fact that there is much suffering in the world? I think I was conscious of the fact that there's a lot of suffering in the world pretty much as soon as I was able to understand anything about my family and its background because I lost three of my four grandparents in the Holocaust. And obviously I knew why I only had one grandparent and she herself had been in the camps and survived. So I think I knew a lot about that pretty early. My entire family comes from the Soviet Union. I was born in the Soviet Union. So sort of the World War II has deep roots in the culture and the suffering that the war brought. The millions of people who died is in the music, is in the literatures and the culture. What do you think was the impact of the war broadly on our society? The war had many impacts. I think one of them, a beneficial impact, is that it showed what racism and authoritarian government can do. And at least as far as the West was concerned, I think that meant that I grew up in an era in which there wasn't the kind of overt racism and antisemitism that had existed for my parents in Europe. I was growing up in Australia and certainly that was clearly seen as something completely unacceptable. There was also though a fear of a further outbreak of war, which this time we expected would be nuclear because of the way the Second World War had ended. So there was this overshadowing of my childhood about the possibility that I would not live to grow up and be an adult because of a catastrophic nuclear war. There was a film on the beach was made in which the city that I was living, Melbourne, was the last place on earth to have living human beings because of the nuclear cloud that was spreading from the North. So that certainly gave us a bit of that sense. There were clearly many other legacies that we got of the war as well and the whole setup of the world and the Cold War that followed. All of that has its roots in the Second World War. You know, there is much beauty that comes from war. Sort of, I had a conversation with Eric Weinstein, he said, everything is great about war except all the death and suffering. Do you think there's something positive that came from the war? The mirror that it put to our society, sort of the ripple effects on it, ethically speaking, do you think there are positive aspects to war? I find it hard to see positive aspects in war and some of the things that other people think of as positive and beautiful. I'm maybe questioning. So there's a certain kind of patriotism. People say, you know, during wartime, we all pull together, we all work together against the common enemy. And that's true, an outside enemy does unite a country and in general, it's good for countries to be united and have common purposes. But it also engenders a kind of a nationalism and a patriotism that can't be questioned and that I'm more skeptical about. What about the brotherhood that people talk about from soldiers? The sort of counterintuitive sad idea that the closest that people feel to each other is in those moments of suffering, of being at the sort of the edge of seeing your comrades dying in your arms, that somehow brings people extremely closely together. Suffering brings people closer together. How do you make sense of that? It may bring people close together, but there are other ways of bonding and being close to people, I think, without the suffering and death that war entails. Perhaps you could see, you can already hear the romanticized Russian in me. We tend to romanticize suffering just a little bit in our literature and culture and so on. Could you take a step back? And I apologize if it's a ridiculous question, but what is suffering? If you would try to define what suffering is, how would you go about it? Suffering is a conscious state. There can be no suffering for a being who is completely unconscious. And it's distinguished from other conscious states in terms of being one that, considered just in itself, we would rather be without. It's a conscious state that we wanna stop if we're experiencing or we wanna avoid having again if we've experienced it in the past. And that's, I say, emphasized for its own sake, because of course, people will say, well, suffering strengthens the spirit, it has good consequences. And sometimes it does have those consequences. And of course, sometimes we might undergo suffering. We set ourselves a challenge to run a marathon or climb a mountain, or even just to go to the dentist so that the toothache doesn't get worse, even though we know the dentist is gonna hurt us to some extent. So I'm not saying that we never choose suffering, but I am saying that other things being equal, we would rather not be in that state of consciousness. Is the ultimate goal, so if you have the new 10 year anniversary release of the Life You Can Save book, really influential book, we'll talk about it a bunch of times throughout this conversation, but do you think it's possible to eradicate suffering? Or is that the goal? Or do we want to achieve a kind of minimum threshold of suffering and then keeping a little drop of poison to keep things interesting in the world? In practice, I don't think we ever will eliminate suffering. So I think that little drop of poison, as you put it, or if you like the contrasting dash of an unpleasant color, perhaps, something like that, in a otherwise harmonious and beautiful composition, that is gonna always be there. If you ask me whether in theory, if we could get rid of it, we should, I think the answer is whether in fact we would be better off or whether in terms of by eliminating the suffering, we would also eliminate some of the highs, the positive highs. And if that's so, then we might be prepared to say it's worth having a minimum of suffering in order to have the best possible experiences as well. Is there a relative aspect to suffering? When you talk about eradicating poverty in the world, is this the more you succeed, the more the bar of what defines poverty raises? Or is there at the basic human ethical level, a bar that's absolute, that once you get above it, then we can morally converge to feeling like we have eradicated poverty? I think they're both. And I think this is true for poverty as well as suffering. There's an objective level of suffering or of poverty where we're talking about objective indicators, like you're constantly hungry, you can't get enough food, you're constantly cold, you can't get warm, you have some physical pains that you're never rid of. I think those things are objective. But it may also be true that if you do get rid of that and you get to the stage where all of those basic needs have been met, there may still be then new forms of suffering that develop. And perhaps that's what we're seeing in the affluent societies we have. That people get bored, for example. They don't need to spend so many hours a day earning money to get enough to eat and shelter. So now they're bored, they lack a sense of purpose. That can happen. And that then is a kind of a relative suffering that is distinct from the objective forms of suffering. But in your focus on eradicating suffering, you don't think about that kind of, the kind of interesting challenges and suffering that emerges in affluent societies. That's just not, in your ethical philosophical brain, is that of interest at all? It would be of interest to me if we had eliminated all of the objective forms of suffering, which I think of as generally more severe and also perhaps easier at this stage anyway to know how to eliminate. So yes, in some future state when we've eliminated those objective forms of suffering, I would be interested in trying to eliminate the relative forms as well. But that's not a practical need for me at the moment. Sorry to linger on it because you kind of said it, but just to, is elimination the goal for the affluent society? So is there a, do you see a suffering as a creative force? Suffering can be a creative force. I think I'll, repeating what I said about the highs and whether we need some of the lows to experience the highs. So it may be that suffering makes us more creative and we regard that as worthwhile. Maybe that brings some of those highs with it that we would not have had if we'd had no suffering. I don't really know. Many people have suggested that and I certainly can't have no basis for denying that. I have no basis for denying it. And if it's true, then I would not want to eliminate suffering completely. But the focus is on the absolute, not to be cold, not to be hungry. Yes, that's at the present stage of where the world's population is, that's the focus. Talking about human nature for a second. Do you think people are inherently good or do we all have good and evil in us that basically everyone is capable of evil based on the environment? Certainly most of us have potential for both good and evil. I'm not prepared to say that everyone is capable of evil. That maybe some people who even in the worst of circumstances would not be capable of it. But most of us are very susceptible to environmental influences. So when we look at things that we were talking about previously, let's say what the Nazis did during the Holocaust, I think it's quite difficult to say, I know that I would not have done those things even if I were in the same circumstances as those who did them. Even if let's say I had grown up under the Nazi regime and had been indoctrinated with racist ideas, had also had the idea that I must obey orders, follow the commands of the Führer. Plus of course, perhaps the threat that if I didn't do certain things, I might get sent to the Russian front and that would be a pretty grim fate. I think it's really hard for anybody to say, nevertheless, I know I would not have killed those Jews or whatever else it was that they- Well, what's your intuition? How many people would be able to say that? Truly to be able to say it? I think very few, less than 10%. To me, it seems a very interesting and powerful thing to meditate on. So I've read a lot about the war, the World War II, and I can't escape the thought that I would have not been one of the 10%. Right, I have to say, I simply don't know. I would like to hope that I would have been one of the 10%, but I don't really have any basis for claiming that I would have been different from the majority. Is it a worthwhile thing to contemplate? It would be interesting if we could find a way of really finding these answers. Obviously, there is quite a bit of research on people during the Holocaust, on how ordinary Germans got led to do terrible things. And there are also studies of the resistance, some heroic people in the White Rose group, for example, who resisted even though they knew they were likely to die for it. But I don't know whether these studies really can answer your larger question of how many people would have been capable of doing that. Well, sort of the reason I think it's interesting is in the world, as you described, when there are things that you'd like to do that are good, that are objectively good, it's useful to think about whether I'm not willing to do something, or I'm not willing to acknowledge something as good and the right thing to do because I'm simply scared of putting my life, of damaging my life in some kind of way. And that kind of thought exercise is helpful to understand what is the right thing in my current skillset and the capacity to do. So if there's things that are convenient, and I wonder if there are things that are highly inconvenient, where I would have to experience derision, or hatred, or death, or all those kinds of things, but it's truly the right thing to do. And that kind of balance is, I feel like in America, we don't have, it's difficult to think in the current times, it seems easier to put yourself back in history, where you can sort of objectively contemplate whether how willing you are to do the right thing when the cost is high. True, but I think we do face those challenges today. And I think we can still ask ourselves those questions. So one stand that I took more than 40 years ago now was to stop eating meat, become a vegetarian at a time when you hardly met anybody who was a vegetarian, or if you did, they might've been a Hindu, or they might've had some weird theories about meat and health. And I know thinking about making that decision, I was convinced that it was the right thing to do, but I still did have to think, are all my friends gonna think that I'm a crank, because I'm now refusing to eat meat? So I'm not saying there were any terrible sanctions, obviously, but I thought about that, and I guess I decided, well, I still think this is the right thing to do, and I'll put up with that if it happens. And one or two friends were clearly uncomfortable with that decision, but that was pretty minor compared to the historical examples that we've been talking about. But other issues that we have around too, like global poverty and what we ought to be doing about that is another question where people, I think, can have the opportunity to take a stand on what's the right thing to do now. Climate change would be a third question where, again, people are taking a stand. I can look at Greta Thunberg there and say, well, I think it must've taken a lot of courage for a schoolgirl to say, I'm gonna go and strike about climate change and see what happens. Yeah, especially in this divisive world, she gets exceptionally huge amounts of support and hatred, both. That's right. Which is very difficult for a teenager to operate in. In your book, Ethics in the Real World, amazing book, people should check it out, very easy read, 82 brief essays on things that matter. One of the essays asks, should robots have rights? You've written about this, so let me ask, should robots have rights? If we ever develop robots capable of consciousness, capable of having their own internal perspective on what's happening to them so that their lives can go well or badly for them, then robots should have rights. Until that happens, they shouldn't. So is consciousness essentially a prerequisite to suffering? So everything that possesses consciousness is capable of suffering, put another way. And if so, what is consciousness? I certainly think that consciousness is a prerequisite for suffering. You can't suffer if you're not conscious. But is it true that every being that is conscious will suffer or has to be capable of suffering? I suppose you could imagine a kind of consciousness, especially if we can construct it artificially, that's capable of experiencing pleasure, but just automatically cuts at the consciousness when they're suffering. So they're like instant anesthesia as soon as something is gonna cause you suffering. So that's possible, but doesn't exist as far as we know on this planet yet. You asked what is consciousness. Well, philosophers often talk about it as there being a subject of experiences. So you and I and everybody listening to this is a subject of experience. There is a conscious subject who is taking things in, responding to it in various ways, feeling good about it, feeling bad about it. And that's different from the kinds of artificial intelligence we have now. I take out my phone, I ask Google directions to where I'm going, Google gives me the directions, and I choose to take a different way. Google doesn't care. It's not like I'm offending Google or anything like that. There is no subject of experiences there. And I think that's the indication that Google, the AI we have now is not conscious, or at least that level of AI is not conscious. And that's the way to think about it. Now, it may be difficult to tell, of course, whether a certain AI is or isn't conscious. It may mimic consciousness, and we can't tell if it's only mimicking it or if it's the real thing. But that's what we're looking for. Is there a subject of experience, a perspective on the world from which things can go well or badly from that perspective? So our idea of what suffering looks like comes from just watching ourselves when we're in pain. Or when we're experiencing pleasure, it's not only. Pleasure and pain. Yeah, so, and then you could actually push back on this, but I would say that's how we kind of build an intuition about animals is we can infer the similarities between humans and animals, and so infer that they're suffering or not based on certain things, and they're conscious or not. So what if robots, you mentioned Google Maps, and I've done this experiment, so I work in robotics just for my own self. I have several Roomba robots, and I play with different speech interaction, voice-based interaction. And if the Roomba or the robot or Google Maps shows any signs of pain, like screaming or moaning or being displeased by something you've done, that, in my mind, I can't help but immediately upgrade it. And even when I myself programmed it in, just having another entity that's now, for the moment, disjoined from me, showing signs of pain, makes me feel like it is conscious. Like I immediately, then the whatever, I immediately realize that it's not, obviously, but that feeling is there. So sort of, I guess, I guess, what do you think about a world where Google Maps and Roombas are pretending to be conscious and we, descendants of apes, are not smart enough to realize they're not? Or whatever, or that is conscious, they appear to be conscious, and so you then have to give them rights. The reason I'm asking that is that kind of capability may be closer than we realize. Yes, that kind of capability may be closer, but I don't think it follows that we have to give them rights. I suppose the argument for saying that, in those circumstances, we should give them rights is that if we don't, we'll harden ourselves against other beings who are not robots and who really do suffer. That's a possibility that, you know, if we get used to looking at a being suffering and saying, yeah, we don't have to do anything about that, that being doesn't have any rights, maybe we'll feel the same about animals, for instance. And interestingly, among philosophers and thinkers who denied that we have any direct duties to animals, and this includes people like Thomas Aquinas and Immanuel Kant, they did say, yes, but still, it's better not to be cruel to them, not because of the suffering we're inflicting on the animals, but because if we are, we may develop a cruel disposition, and this will be bad for humans, you know, because we're more likely to be cruel to other humans, and that would be wrong. So- But you don't accept that kind of- I don't accept that as the basis of the argument for why we shouldn't be cruel to animals. I think the base of the argument for why we shouldn't be cruel to animals is just that we're inflicting suffering on them, and the suffering is a bad thing. But possibly, I might accept some sort of parallel of that argument as a reason why you shouldn't be cruel to these robots that mimic the symptoms of pain if it's gonna be harder for us to distinguish. I would venture to say, I'd like to disagree with you, and with most people, I think, at the risk of sounding crazy. I would like to say that if that Roomba is dedicated to faking the consciousness and the suffering, I think it would be impossible for us. I would like to apply the same argument as with animals to robots, that they deserve rights in that sense. Now, we might outlaw the addition of those kinds of features into Roombas, but once you do, I think, I'm quite surprised by the upgrade in consciousness that the display of suffering creates. It's a totally open world, but I'd like to just, sort of the difference between animals and other humans is that in the robot case, we've added it in ourselves. Therefore, we can say something about how real it is. But I would like to say that the display of it is what makes it real. And there's some, I'm not a philosopher, I'm not making that argument, but I'd at least like to add that as a possibility. And I've been surprised by it, is all I'm trying to sort of articulate poorly, I suppose. So there is a philosophical view has been held about humans, which is rather like what you're talking about, and that's behaviorism. So behaviorism was employed both in psychology, people like B.F. Skinner was a famous behaviorist, but in psychology, it was more a kind of a, what is it that makes this science? Well, you need to have behavior because that's what you can observe, you can't observe consciousness. But in philosophy, the view defended by people like Gilbert Ryle, who was a professor of philosophy at Oxford, wrote a book called, The Concept of Mind, in which, in this kind of phase, this is in the 40s of linguistic philosophy, he said, well, the meaning of a term is its use, and we use terms like, so-and-so is in pain when we see somebody writhing or screaming or trying to escape some stimulus, and that's the meaning of the term. So that's what it is to be in pain, and you point to the behavior. And Norman Malcolm, who was another philosopher in the school from Cornell, had the view that, so what is it to dream? After all, we can't see other people's dreams. Well, when people wake up and say, I just had a dream of, here I was undressed, walking down the main street, or whatever it is you've dreamt, that's what it is to have a dream, it's basically to wake up and recall something. So you could apply this to what you're talking about, and say, so what it is to be in pain is to exhibit these symptoms of pain behavior, and therefore, these robots are in pain, that's what the word means. But nowadays, not many people think that Ryle's kind of philosophical behaviorism is really very plausible, so I think they would say the same about your view. So, yes, I just spoke with Noam Chomsky, who basically was a philosopher Noam Chomsky, who basically was part of dismantling the behaviorist movement. But, and I'm with that, 100%, for studying human behavior, but I am one of the few people in the world who has made Roombas scream in pain, and I just don't know what to do with that empirical evidence, because it's hard, sort of philosophically, I agree, but the only reason I philosophically agree in that case is because I was the programmer, but if somebody else was a programmer, I'm not sure I would be able to interpret that well. So it's, I think it's a new world that I was just curious what your thoughts are. For now, you feel that the display of the, what we can kind of intellectually say is a fake display of suffering is not suffering. That's right, that would be my view, but that's consistent, of course, with the idea that it's part of our nature to respond to this display, if it's reasonably authentically done, and therefore it's understandable that people would feel this, and maybe, as I said, it's even a good thing that they do feel it, and you wouldn't want to harden yourself against it, because then you might harden yourself against beings who are really suffering. But there's this line, you know, so you said, once artificial general intelligence system, the human level intelligence system become conscious, I guess, if I could just linger on it, now I've wrote really dumb programs that just say things that I told them to say, but how do you know when a system like Alexa, which is sufficiently complex that you can't introspect of how it works, starts giving you signs of consciousness through natural language, that there's a feeling there's another entity there that's self-aware, that has a fear of death, a mortality, that has awareness of itself that we kind of associate with other living creatures. I guess I'm sort of trying to do this slippery slope from the very naive thing where I started into something where it's sufficiently a black box to where it's starting to feel like it's conscious. Where's that threshold where you would start getting uncomfortable with the idea of a robot suffering, do you think? I don't know enough about the programming that would go into this really to answer this question, but I presume that somebody who does know more about this could look at the program and see whether we can explain the behaviors in a parsimonious way that doesn't require us to suggest that some sort of consciousness has emerged. Or alternatively, whether you're in a situation where you say, I don't know how this is happening. The program does generate a kind of artificial general intelligence, which is autonomous, starts to do things itself and is autonomous of the basics programming that set it up. And so it's quite possible that actually we have achieved consciousness in a system of artificial intelligence. Sort of the approach that I work with, most of the community is really excited about now is with learning methods, so machine learning. And the learning methods are unfortunately are not capable of revealing, which is why somebody like Noam Chomsky criticizes them. You've create powerful systems that are able to do certain things without understanding the theory, the physics, the science of how it works. And so it's possible if those are the kinds of methods that succeed, we won't be able to know exactly, sort of try to reduce, try to find whether this thing is conscious or not, this thing is intelligent or not. It's simply giving, when we talk to it, it displays wit and humor and cleverness and emotion and fear. And then we won't be able to say where in the billions of nodes, neurons in this artificial neural network is the fear coming from. So in that case, that's a really interesting place where we do now start to return to behaviorism and say. Yeah, that is an interesting issue. I would say that if we have serious dads and think it might be conscious, then we ought to try to give it the benefit of the doubt. Just as I would say with animals, I think we can be highly confident that vertebrates are conscious, but when we get down and some invertebrates like the octopus, but with insects, it's much harder to be confident of that. I think we should give them the benefit of the doubt where we can, which means, I think it would be wrong to torture an insect, but this doesn't necessarily mean it's wrong to slap a mosquito that's about to bite you and stop you getting to sleep. So I think you try to achieve some balance in these circumstances of uncertainty. If it's okay with you, if we can go back just briefly. So 44 years ago, like you mentioned, 40 plus years ago, you've written Animal Liberation, the classic book that started, that launched, that was a foundation of the movement of Animal Liberation. Can you summarize the key set of ideas that underpin that book? Certainly, the key idea that underlies that book is the concept of speciesism, which I did not invent that term. I took it from a man called Richard Rider, who was in Oxford when I was, and I saw a pamphlet that he'd written about experiments on chimpanzees that used that term. But I think I contributed to making it philosophically more precise and to getting it into a broader audience. And the idea is that we have a bias or a prejudice against taking seriously the interests of beings who are not members of our species. Just as in the past, Europeans, for example, had a bias against taking seriously the interests of Africans, racism. And men have had a bias against taking seriously the interests of women, sexism. So I think something analogous, not completely identical, but something analogous, goes on and has gone on for a very long time with the way humans see themselves vis-a-vis animals. We see ourselves as more important. We see animals as existing to serve our needs in various ways. And you can find this very explicit in earlier philosophers from Aristotle through to Kant and others. And either we don't need to take their interests into account at all, or we can discount it because they're not humans. They count a little bit, but they don't count nearly as much as humans do. My book argues that that attitude is responsible for a lot of the things that we do to animals that are wrong, confining them indoors in very crowded, cramped conditions, in factory farms to produce meat or eggs or milk more cheaply, using them in some research that's by no means essential for our survival or wellbeing, and a whole lot, some of the sports and things that we do to animals. So I think that's unjustified because I think the significance of pain and suffering does not depend on the species of the being who is in pain or suffering any more than it depends on the race or sex of the being who is in pain or suffering. And I think we ought to rethink our treatment of animals along the lines of saying, if the pain is just as great in an animal, then it's just as bad that it happens as if it were a human. Maybe if I could ask, I apologize, hopefully it's not a ridiculous question, but so as far as we know, we cannot communicate with animals through natural language, but we would be able to communicate with robots. So returning to sort of a small parallel between perhaps animals and the future of AI, if we do create an AGI system or as we approach creating that AGI system, what kind of questions would you ask her to try to intuit whether there is consciousness, or more importantly, whether there's capacity to suffer? I might ask the AGI what she was feeling, well, does she have feelings? And if she says yes, to describe those feelings, to describe what they were like, to see what the phenomenal account of consciousness is like, that's one question. I might also try to find out if the AGI has a sense of itself. So for example, the idea, would you, we often ask people, so suppose you're in a car accident and your brain were transplanted into someone else's body, do you think you would survive or would it be the person whose body was still surviving, your body having been destroyed? And most people say, I think I would, if my brain was transplanted along with my memories and so on, I would survive. So we could ask AGI those kinds of questions, if they were transferred to a different piece of hardware, would they survive, what would survive? Get at that sort of concept. Sort of on that line, another perhaps absurd question, but do you think having a body is necessary for consciousness? So do you think digital beings can suffer? Presumably digital beings need to be running on some kind of hardware, right? Yeah, that ultimately boils down to, but this is exactly what you just said, is moving the brain from place to place. So you could move it to a different kind of hardware, you know, and I could say, look, your hardware is getting worn out, we're going to transfer you to a fresh piece of hardware, so we're gonna shut you down for a time, but don't worry, you'll be running very soon on a nice fresh piece of hardware. And you could imagine this conscious AGI saying, that's fine, I don't mind having a little rest, just make sure you don't lose me or something like that. Yeah, I mean, that's an interesting thought that even with us humans, the suffering is in the software. We right now don't know how to repair the hardware. Yeah. But we're getting better at it, and better in the idea, I mean, a lot of, some people dream about one day being able to transfer certain aspects of the software to another piece of hardware. What do you think, just on that topic, there's been a lot of exciting innovation in brain-computer interfaces. I don't know if you're familiar with the companies like Neuralink with Elon Musk, communicating both ways from a computer, being able to send, activate neurons, and being able to read spikes from neurons. With the dream of being able to expand, sort of increase the bandwidth at which your brain can look up articles on Wikipedia, kind of thing. Sort of expand the knowledge capacity of the brain. Do you think that notion, is that interesting to you, as the expansion of the human mind? Yes, that's very interesting. I'd love to be able to have that increased bandwidth. And I want better access to my memory, I have to say, too. As I get older, I talk to my wife about things that we did 20 years ago or something. Her memory is often better about particular events. Where were we? Who was at that event? What did he or she wear, even? She may know, and I have not the faintest idea about this, but perhaps it's somewhere in my memory. And if I had this extended memory, I could search that particular year and rerun those things, I think that would be great. In some sense, we already have that by storing so much of our data online, like pictures of different events. Yes, well, Gmail is fantastic for that, because people email me as if they know me well, and I haven't got a clue who they are, but then I search for their name. And ah, yes, they emailed me in 2007, and I know who they are now. Yeah, so we're already, we're taking the first steps already. So on the flip side of AI, people like Stuart Russell and others focus on the control problem, value alignment in AI, which is the problem of making sure we build systems that align to our own values, our ethics. Do you think, sort of high level, how do we go about building systems, do you think is it possible that align with our values, align with our human ethics, or living being ethics? Presumably it's possible to do that. I know that a lot of people who think that there's a real danger that we won't, that we'll more or less accidentally lose control of AGI. Do you have that fear yourself, personally? I'm not quite sure what to think. I talk to philosophers like Nick Bostrom and Toby Ord, and they think that this is a real problem we need to worry about. Then I talk to people who work for Microsoft or DeepMind or somebody, and they say, no, we're not really that close to producing AGI, super intelligence. So if you look at Nick Bostrom's sort of the arguments, it's very hard to defend. So I'm, of course, I am a self-engineer AI system, so I'm more with the DeepMind folks, where it seems that we're really far away. But then the counter argument is, is there any fundamental reason that we'll never achieve it? And if not, then eventually there'll be a dire existential risk, so we should be concerned about it. And do you have, do you find that argument at all appealing in this domain or any domain, that eventually this will be a problem, so we should be worried about it? Yes, I think it's a problem. I think there's, that's a valid point. Of course, when you say eventually, eventually, that raises the question, how far off is that? And is there something that we can do about it now? Because if we're talking about, this is gonna be 100 years in the future, and you consider how rapidly our knowledge of artificial intelligence has grown in the last 10 or 20 years, it seems unlikely that there's anything much we could do now that would influence whether this is going to happen 100 years in the future. People in 80 years in the future would be in a much better position to say, this is what we need to do to prevent this happening than we are now. So to some extent, I find that reassuring, but I'm all in favor of some people doing research into this to see if indeed it is that far off, or if we are in a position to do something about it sooner. I'm very much of the view that extinction is a terrible thing, and therefore, even if the risk of extinction is very small, if we can reduce that risk, that's something that we ought to do. My disagreement with some of these people who talk about long-term risks, extinction risks, is only about how much priority that should have as compared to present questions. It was such a, if you look at the math of it from a utilitarian perspective, if it's existential risks, so everybody dies, that it feels like an infinity in the math equation that that makes the math with the priorities difficult to do. That if we don't know the timescale, and you can legitimately argue that it's non-zero probability that it'll happen tomorrow, that how do you deal with these kinds of existential risks, like from nuclear war, from nuclear weapons, from biological weapons, from, I'm not sure if global warming falls into that category, because global warming is a lot more gradual. And people say it's not an existential risk, because there'll always be possibilities of some humans existing, farming Antarctica, or northern Siberia, or something of that sort, yeah. But you don't find the complete existential risks a fundamental, like an overriding part of the equations of ethics, of what should be. No, certainly if you treat it as an infinity, then it plays havoc with any calculations. But arguably we shouldn't, I mean, one of the ethical assumptions that goes into this is that the loss of future lives, that is of merely possible lives, of beings who may never exist at all, is in some way comparable to the sufferings or deaths of people who do exist at some point. And that's not clear to me. I think there's a case for saying that, but I also think there's a case for taking the other view. So that has some impact on it. Of course, you might say, ah, yes, but still if there's some uncertainty about this, and the costs of extinction are infinite, then still it's gonna overwhelm everything else. But I suppose I'm not convinced of that. I'm not convinced that it's really infinite here. And even Nick Bostrom in his discussion of this doesn't claim that there'll be an infinite number of lives lived. He, what is it, 10 to the 56th or something? It's a vast number that I think he calculates. This is assuming we can upload consciousness onto these, digital forms, and therefore there'll be much more energy efficient, but he calculates the amount of energy in the universe or something like that. So the numbers are vast, but not infinite, which gives you some prospect maybe of resisting some of the argument. The beautiful thing with Nick's arguments is he quickly jumps from the individual scale to the universal scale, which is just awe-inspiring to think of when you think about the entirety of the span of time of the universe. It's both interesting from a computer science perspective, AI perspective, and from an ethical perspective, the idea of utilitarianism. Could you say what is utilitarianism? Utilitarianism is the ethical view that the right thing to do is the act that has the greatest expected utility, where what that means is it's the act that will produce the best consequences, discounted by the odds that you won't be able to produce those consequences, that something will go wrong. But in a simple case, let's assume we have certainty about what the consequences of our actions will be, then the right action is the action that will produce the best consequences. Is that always, and by the way, there's a bunch of nuanced stuff that you talk with Sam Harris on this podcast on that people should go listen to. It's great. It's like two hours of moral philosophy discussion. But is that an easy calculation? No, it's a difficult calculation. And actually, there's one thing that I need to add, and that is utilitarians, certainly the classical utilitarians, think that by best consequences, we're talking about happiness and the absence of pain and suffering. There are other consequentialists who are not really utilitarians who say there are different things that could be good consequences. Justice, freedom, human dignity, knowledge, they all count as good consequences too. And that makes the calculations even more difficult because then you need to know how to balance these things off. If you are just talking about wellbeing, using that term to express happiness and the absence of suffering, I think that the calculation becomes more manageable in a philosophical sense. It's still in practice, we don't know how to do it. We don't know how to measure quantities of happiness and misery. We don't know how to calculate the probabilities that different actions will produce this or that. So at best, we can use it as a rough guide to different actions. And one way we have to focus on the short-term consequences because we just can't really predict all of the longer term ramifications. So what about the sort of, what about the extreme suffering of very small groups? Sort of utilitarianism is focused on the overall aggregate, right? How do you, would you say you yourself are utilitarian? Yes, I'm utilitarian. Sort of, what do you make of the difficult, ethical, maybe poetic suffering of very few individuals? I think it's possible that that gets overridden by benefits to very large numbers of individuals. I think that can be the right answer. But before we conclude that it is the right answer, we have to know how severe the suffering is and how that compares with the benefits. So I tend to think that extreme suffering is worse than, or is further, if you like, below the neutral level than extreme happiness or bliss is above it. So when I think about the worst experiences possible and the best experiences possible, I don't think of them as equidistant from neutral. So like it's a scale that goes from minus 100 through zero as a neutral level to plus 100. Because I know that I would not exchange an hour of my most pleasurable experiences for an hour of my most painful experiences. Even, I wouldn't have an hour of my most painful experiences even for two hours or 10 hours of my most painful experiences. Did I say that correctly? Yeah, yeah, yeah, yeah, yeah. Maybe 20 hours then, isn't it? 21, what's the exchange rate? So that's the question, what is the exchange rate? But I think it can be quite high. So that's why you shouldn't just assume that it's okay to make one person suffer extremely in order to make two people much better off. It might be a much larger number. But at some point, I do think you should aggregate and the result will be, even though it violates our intuitions of justice and fairness, whatever it might be, giving priority to those who are worse off, at some point, I still think that will be the right thing to do. Yeah, it's some complicated nonlinear function. Can I ask a sort of out there question? Is the more and more we put our data out there, the more we're able to measure a bunch of factors of each of our individual human lives. And I could foresee the ability to estimate well-being of whatever we together collectively agree is a good objective function from a utilitarian perspective. Do you think it'll be possible and is a good idea to push that kind of analysis to make then public decisions, perhaps with the help of AI, that here's a tax rate, here's a tax rate at which well-being will be optimized? Yeah, that would be great if we really knew that, if we really could calculate that. No, but do you think it's possible to converge towards an agreement amongst humans, towards an objective function, or is it just a hopeless pursuit? I don't think it's hopeless. I think it would be difficult to get converged towards agreement, at least at present, because some people would say, I've got different views about justice, and I think you ought to give priority to those who are worse off, even though I acknowledge that the gains that the worse off are making are less than the gains that those who are sort of medium badly off could be making. So we still have all of these intuitions that we argue about, so I don't think we would get agreement, but the fact that we wouldn't get agreement doesn't show that there isn't a right answer there. Do you think, who gets to say what is right and wrong? Do you think there's place for ethics oversight from the government? So I'm thinking in the case of AI, overseeing what kind of decisions AI can make and not, but also if you look at animal rights, or rather not rights, or perhaps rights, but the ideas you've explored in animal liberation, who gets to, so you eloquently, beautifully, write in your book that we shouldn't do this, but is there some harder rules that should be imposed, or is this a collective thing we converge towards a society, and thereby make the better and better ethical decisions? Politically, I'm still a Democrat, despite looking at the flaws in democracy, and the way it doesn't work always very well, so I don't see a better option than allowing the public to vote for governments in accordance with their policies, and I hope that they will vote for policies that reduce the suffering of animals, and reduce the suffering of distant humans, whether geographically distant, or distant because they're future humans, but I recognize that democracy isn't really well set up to do that, and in a sense, you could imagine a wise and benevolent, omnibenevolent leader who would do that better than democracies could, but in the world in which we live, it's difficult to imagine that this leader isn't gonna be corrupted by a variety of influences. We've had so many examples of people who've taken power with good intentions, and then have ended up being corrupt, and favoring themselves, so I don't know, that's why, as I say, I don't know that we have a better system than democracy to make these decisions. Well, so you also discuss effective altruism, which is a mechanism for going around government, for putting the power in the hands of the people to donate money towards causes to help, remove the middleman and give it directly to the causes they care about. Maybe this is a good time to ask, 10 years ago wrote The Life You Can Save, that's now, I think, available for free online? That's right, you can download either the e-book or the audio book free from thelifeyoucansave.org. And what are the key ideas that you present in the book? The main thing I wanna do in the book is to make people realize that it's not difficult to help people in extreme poverty, that there are highly effective organizations now that are doing this, that they've been independently assessed and verified by research teams that are expert in this area, and that it's a fulfilling thing to do to, for at least part of your life, we can't all be saints, but at least one of your goals should be to really make a positive contribution to the world and to do something to help people who through no fault of their own are in very dire circumstances and living a life that is barely, or perhaps not at all, a decent life for a human being to live. So you describe a minimum ethical standard of giving. What advice would you give to people that want to be effectively altruistic in their life, like live an effective altruism life? There are many different kinds of ways of living as an effective altruist. And if you're at the point where you're thinking about your long-term career, I'd recommend you take a look at a website called 80,000 Hours, 80,000hours.org, which looks at ethical career choices. And they range from, for example, going to work on Wall Street so that you can earn a huge amount of money and then donate most of it to effective charities, to going to work for a really good nonprofit organization so that you can directly use your skills and ability and hard work to further a good cause, or perhaps going into politics, maybe small chances, but big payoffs in politics. Go to work in the public service where, if you're talented, you might rise to a higher level where you can influence decisions. Do research in an area where the payoffs could be great. There are a lot of different opportunities, but too few people are even thinking about those questions. They're just going along in some sort of preordained rut to particular careers. Maybe they think they'll earn a lot of money and have a comfortable life, but they may not find that as fulfilling as actually knowing that they're making a positive difference to the world. What about in terms of, so that's like long-term, 80,000 hours, shorter-term giving part of, well, actually it's a part of that, and go to work at Wall Street. If you would like to give a percentage of your income that you talk about, and life you can save, I mean, I was looking through, it's quite a compelling, it's, I mean, I'm just a dumb engineer, so I like, there's simple rules. There's a nice percentage. Okay, so I do actually set out suggested levels of giving because people often ask me about this. A popular answer is give 10%, the traditional tithe that's recommended in Christianity and also Judaism, but why should it be the same percentage irrespective of your income? Tax scales reflect the idea that the more income you have, the more you can pay tax, and I think the same is true in what you can give. So I do set out a progressive donor scale, which starts at 1% for people on modest incomes and rises to 33 1⁄3% for people who are really earning a lot, and my idea is that I don't think any of these amounts really impose real hardship on people because they are progressive and geared to income. So I think anybody can do this and can know that they're doing something significant to play their part in reducing the huge gap between people in extreme poverty in the world and people living affluent lives. And aside from it being an ethical life, it's one that you find more fulfilling because there's something about our human nature that, or some of our human natures, maybe most of our human nature, that enjoys doing the ethical thing. Yes, I make both those arguments, that it is an ethical requirement in the kind of world we live in today to help people in great need when we can easily do so, but also that it is a rewarding thing and there's good psychological research showing that people who give more tend to be more satisfied with their lives. And I think this has something to do with having a purpose that's larger than yourself and therefore never being, if you like, never being bored sitting around, oh, what will I do next? I've got nothing to do. In a world like this, there are many good things that you can do and enjoy doing them, plus you're working with other people in the effective altruism movement who are forming a community of other people with similar ideas and they tend to be interesting, thoughtful, and good people as well. And having friends of that sort is another big contribution to having a good life. So we talked about big things that are beyond ourselves, but we're also just human and mortal. Do you ponder your own mortality? Is there insights about your philosophy, the ethics that you gain from pondering your own mortality? Clearly, as you get into your 70s, you can't help thinking about your own mortality. But I don't know that I have great insights into that from my philosophy. I don't think there's anything after the death of my body, assuming that we won't be able to upload my mind into anything at the time when I die. So I don't think there's any afterlife or anything to look forward to in that sense. Do you fear death? So if you look at Ernest Becker and describing the motivating aspects of our ability to be cognizant of our mortality, do you have any of those elements in your driving your motivation life? I suppose the fact that you have only a limited time to achieve the things that you wanna achieve gives you some sort of motivation to get going in achieving them. And if we thought we were immortal, we might say, ah, I can put that off for another decade or two. So there's that about it. But otherwise, no, I'd rather have more time to do more. I'd also like to be able to see how things go that I'm interested in. Is climate change gonna turn out to be as dire as a lot of scientists say that it is going to be? Will we somehow scrape through with less damage than we thought? I'd really like to know the answers to those questions, but I guess I'm not going to. Well, you said there's nothing afterwards. So let me ask the even more absurd question. What do you think is the meaning of it all? I think the meaning of life is the meaning we give to it. I don't think that we were brought into the universe for any kind of larger purpose, but given that we exist, I think we can recognize that some things are objectively bad. Extreme suffering is an example, and other things are objectively good, like having a rich, fulfilling, enjoyable, pleasurable life. And we can try to do our part in reducing the bad things and increasing the good things. So one way, the meaning is to do a little bit more of the good things, objectively good things, and a little bit less of the bad things. Yes, so do as much of the good things as you can and as little of the bad things. Peter, beautifully put, I don't think there's a better place to end it. Thank you so much for talking today. Thanks very much, it's been really interesting talking to you. Thanks for listening to this conversation with Peter Singer, and thank you to our sponsors, Cash App and Masterclass. Please consider supporting the podcast by downloading Cash App and using the code LEXPODCAST, and signing up at masterclass.com slash lex. Click the links, buy all the stuff, it's the best way to support this podcast and the journey I'm on, my research and startup. If you enjoy this thing, subscribe on YouTube, review it with 5,000 Apple Podcast, support on Patreon, or connect with me on Twitter at Lex Friedman, spelled without the E, just F-R-I-D-M-A-N. And now, let me leave you with some words from Peter Singer. What one generation finds ridiculous, the next accepts. And the third shudders when it looks back at what the first did. Thank you for listening, and hope to see you next time.

https://youtu.be/llh-2pqSGrs

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Peter Woit: Theories of Everything & Why String Theory is Not Even Wrong | Lex Fridman Podcast #246

The following is a conversation with Peter White, a theoretical physicist at Columbia, outspoken critic of string theory, and the author of the popular physics and mathematics blog called Not Even Wrong. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Peter White. You're both a physicist and a mathematician. So let me ask, what is the difference between physics and mathematics? Well, there's kind of a conventional understanding of the subject that they're two quite different things. So that mathematics is about making rigorous statements about these abstract things, things of mathematics and proving them rigorously. And physics is about doing experiments and testing various models and that. But I think the more interesting thing is that there's a wide variety of what people do as mathematics, what they do as physics, and there's a significant overlap. And that I think is actually a very interesting area. And if you go back kind of far enough in history and look at figures like Newton or something, at that point, you can't really tell, was Newton a physicist or a mathematician? The mathematicians will tell you he was a mathematician, the physicists will tell you he was a physicist. But he was a, he's a philosopher. Yeah, that's interesting. But yeah, anyway, there was kind of no such distinction then that's more of a modern thing. And, but anyway, I think these days there's a very interesting space in between the two. So in the story of the 20th century and the early 21st century, what is the overlap between mathematics and physics, would you say? Well, I think it's actually become very, very complicated. I think it's really interesting to see a lot of what my colleagues in the math department are doing. They, most of what they're doing, they're doing all sorts of different things, but most of them have some kind of overlap with physics or other. So, I mean, I'm personally interested in one particular aspect of this overlap, which I think has a lot to do with the most fundamental ideas about physics and about mathematics. But there's just, you kind of see this, this really, really everywhere at this point. Which particular overlap are you looking at, group theory? Yeah, so the, at least what the way it seems to me that if you look at physics and look at the, our most successful laws of fundamental physics, they're really, they have a certain kind of mathematical structure. It's based upon certain kinds of mathematical objects and geometry connections and curvature, the spinners, the Dirac equation. And that, these, this very deep mathematics provides kind of a unifying set of ways of thinking that allow you to make a unified theory of physics. But the interesting thing is that if you go to mathematics and look at what's been going on in mathematics the last 1,500 years, and even especially recently, there's a similarly, some kind of unifying ideas which bring together different areas of mathematics and which have been especially powerful in number theory recently. And there's a book, for instance, by Edward Frankel about love and math. And yeah, that book's great. I recommend it highly. It's partially accessible. But it is a nice audio book that I listened to while running an exceptionally long distance, like across the San Francisco Bridge. And there's something magic about the way he writes about it but some of the group theory in there is a little bit difficult. It's a problem with any of these things to kind of really say what's going on and make it accessible is very hard. He, in this book and elsewhere, I think, takes the attitude that kinds of mathematics he's interested in and that he's talking about are provide kind of a grand unified theory of mathematics. They bring together geometry and number theory and representation theory, a lot of different ideas in a really unexpected way. But I think to me, the most fascinating thing is if you look at the kind of grand unified theory of mathematics he's talking about and you look at the physicist's kind of ideas about unification, it's more or less the same mathematical objects are appearing in both. So it's this, I think there's a really, we're seeing a really strong indication that the deepest ideas that we're discovering about physics and some of the deepest ideas that mathematicians are learning about are really, are intimately connected. Is there something, like if I was five years old and you were trying to explain this to me, is there ways to try to sneak up to what this unified world of mathematics looks like? You said number theory, you said geometry, words like topology. What does this universe begin to look like? Are these, what should we imagine in our mind? Is it a three-dimensional surface? And we're trying to say something about it. Is it triangles and squares and cubes? Like what are we supposed to imagine in our minds? Is this natural number? What's a good thing to try to, for people that don't know any of these tools, except maybe some basic calculus and geometry from high school, that they should keep in their minds as to the unified world of mathematics that also allows us to explore the unified world of physics? I mean, what I find kind of remarkable about this is the way in which these, we've discovered these ideas, but they're actually quite alien to our everyday understanding. We grow up in this three-spatial dimensional world and we have intimate understanding of certain kinds of geometry and certain kinds of things. But these things that we've discovered in both math and physics are, that they're not at all close, have any obvious connection to kind of human everyday experience. They're really quite different. And I can say some of my initial fascination with this when I was young and starting to learn about it was actually exactly this kind of arcane nature of these things. It was a little bit like being told, well, there are these kind of semi-mystical experience that you can acquire by a long study and whatever, except that it was actually true. I mean, there's actually evidence that this actually works. So, I'm a little bit wary of trying to give people that kind of thing, because I think it's mostly misleading. But one thing to say is that geometry is a large part of it. And maybe one interesting thing to say that's about more recent, some of the most recent ideas is that when we think about the geometry of our space and time, it's kind of three-spatial in one time dimension. It's a, physics is in some sense about something that's kind of four-dimensional in a way. And a really interesting thing about some of the recent developments in number theory have been to realize that these ideas that we were looking at naturally fit into a context where your theory is kind of four-dimensional. So, I mean, geometry is a big part of this, and we know a lot and feel a lot about two, one, two, three-dimensional geometry. So, wait a minute. So, we can at least rely on the four dimensions of space and time, and say that we can get pretty far by working that in those four dimensions. I thought you were gonna scare me that we're gonna have to go to many, many, many, many more dimensions than that. My point of view, which goes against a lot of these ideas about unification is that, no, this is really, everything we know about really is about four dimensions that, and that you can actually understand a lot of these structures that we've been seeing in fundamental physics and in number theory, just in terms of four dimensions, that it's kind of, it's in some sense, I would claim, has been a really, has been kind of a mistake that physicists have made for decades and decades to try to go to higher dimensions, to try to formulate a theory in higher dimensions. And then you're stuck with the problem of how do you get rid of all these extra dimensions that you've created? Because we only ever see anything in four dimensions. That kind of thing leads us astray, you think? So, creating all these extra dimensions just to give yourself extra degrees of freedom, isn't that the process of mathematics, is to create all these trajectories for yourself, but eventually you have to end up at the, at like a final place, but it's okay to, it's okay to sort of create abstract objects on your path to proving something. Yeah, certainly, and from a mathematician's point of view, I mean, the kinds of, mathematicians also are very different than physicists in that we like to develop very general theories. We like to, if we have an idea, we want to see what's the greatest generality in which you can talk about it. So, from the point of view of most of the ways geometry is formulated by mathematicians, it really doesn't matter, it works in any dimension. We can do one, two, three, four, any number. There's no particular, for most of geometry, there's no particular special thing about four. But anyway, but what physicists have been trying to do over the years is try to understand these fundamental theories in a geometrical way. And it's very tempting to kind of just start bringing in extra dimensions and using them to explain the structure. But typically this attempt kind of founders because you just don't know, you end up not being able to explain why we only see four. It is nice in the space of physics that, like if you look at Fermat's last theorem, it's much easier to prove that there's no solution for n equals three than it is for the general case. And so I guess that's the nice benefit of being a physicist is you don't have to worry about the general case because we live in a universe with n equals four in this case. Yeah, physicists are very interested in saying something about specific examples. And I find that interesting, even when I'm trying to do things in mathematics and I'm trying even teaching courses and to mathematics students, I find that I'm teaching them in a different way than most mathematicians because I'm very often very focused on examples, on what's kind of the crucial example that shows how this powerful new mathematical technique, how it works and why you would want to do it. And I'm less interested in kind of proving a precise theorem about exactly when it's gonna work and when it's not gonna work. Do you usually think about really simple examples, like both for teaching and when you try to solve a difficult problem? Are you, do you construct like the simplest possible example that captures the fundamentals of the problem and try to solve it? Yeah, yeah, exactly. That's often a really fruitful way to, if you've got some idea to just kind of try to boil it down to what's the simplest situation in which this kind of thing is gonna happen and then try to really understand that and understand that. And that is almost always a really good way to get insight. Do you work with a paper and pen or like, for example, for me, coming from the programming side, if I look at a model, if I look at some kind of mathematical object, I like to mess around with it sort of numerically. I just visualize different parts of it, visualize however I can. So most of the work is like with neural networks, for example, is you try to play with the simplest possible example and just to build up intuition by, you know, any kind of object has a bunch of variables in it. You start to mess around with them in different ways and visualize in different ways to start to build intuition. Or do you go the Einstein route and just imagine like everything inside your mind and sort of build like thought experiments and then work purely on paper and pen? Well, the problem with this kind of stuff I'm interested in is you rarely can kind of, it's rarely something that is really kind of, or even the simplest example, you can kind of see what's going on by looking at something happening in three dimensions. There's generally the structures involved are, either they're more abstract or if you try to kind of embed them in some kind of space where you could manipulate them in some kind of geometrical way, it's gonna be a much higher dimensional space. So even simple examples, the embedding them into three dimensional space, you're losing a lot. Yeah, but to capture what you're trying to understand about them, you have to go to four or more dimensions. So it starts to get to be hard to, I mean, you can train yourself to try it as much as, to kind of think about things in your mind. And I often use pad and paper and I'm often, in my office, I often use the blackboard. And you are kind of drawing things, but they're really kind of more abstract representations of how things are supposed to fit together. And they're not really, unfortunately, not just kind of really living in three dimensions where you can understand. Are we supposed to be sad or excited by the fact that our human minds can't fully comprehend the kind of mathematics you're talking about? I mean, what do we make of that? I mean, to me, that makes me quite sad. It makes me, it makes it seem like there's a giant mystery out there that we'll never truly get to experience directly. It is kind of sad how difficult this is. I mean, or I would put it a different way that, you know, most questions that people have about this kind of thing, you know, you can give them a really, a true answer and really understand it, but the problem is one more of time. It's like, yes, you know, I could explain to you how this works, but you'd have to be willing to sit down with me and, you know, work at this repeatedly for, you know, for hours and days and weeks. And you'd, I mean, it's just gonna take that long for your mind to really wrap itself around what's going on and that, so that does make things inaccessible, which is sad, but I mean, it's just kind of part of life that we all have a limited amount of time and we have to decide what we're gonna, what we're gonna spend our time doing. Speaking of a limited amount of time, we only have a few hours, maybe a few days together here on this podcast. Let me ask you the question of, amongst many of the ideas that you work on in mathematics and physics, what is the most beautiful idea or one of the most beautiful ideas, maybe a surprising idea? And once again, unfortunately, the way life works, we only have a limited time together to try to convey such an idea. Okay, well, actually, let me just tell you something, which I'm tempted to kind of start trying to explain what I think is this most powerful idea that brings together math and physics, ideas about groups and representations and how it fits quantum mechanics. But in some sense, I wrote a whole textbook about that and I don't think we really have time to get very far into it, so. Well, can I actually, on a small tangent, you did write a paper towards the Grant Unified Theory of Mathematics and Physics. Maybe you could step there first. What is the key idea in that paper? Well, I think we've kind of gone over that. I think that the key idea is what we were talking about earlier, that just kind of a claim that if you look and see what's the, what have been successful ideas of unification in physics over the last 50 years or so and what has been happening in mathematics and the kind of thing that Frenkel's book is about, that these are very much the same kind of mathematics. And so it's kind of an argument that there really is, you shouldn't be looking to unify just math or just fundamental physics, but taking inspiration for looking for new ideas in fundamental physics, that they are gonna be in the same direction of getting deeper into mathematics and looking for more inspiration in mathematics from these successful ideas about fundamental physics. Could you put words to sort of the disciplines we're trying to unify? So you said number theory. Are we literally talking about all the major fields of mathematics? So it's like the number theory, geometry, so like differential geometry, topology. Yeah, so the, I mean, one name for this, that this is acquired in mathematics is the so-called Langlands program. And so this started out in mathematics. It's that, you know, Robert Langlands kind of realized that a lot of what people were doing in, that was starting to be really successful in number theory in the 60s. And so that this actually was, anyway, that this could be thought of in terms of these ideas about symmetry and groups and representations, and in a way that was also close to some ideas about geometry. And then more later on in the 80s and 90s, there was something called geometric Langlands that people realized that you could take what people have been doing in number theory in Langlands and get rid, just forget about the number theory and ask, what is this telling you about geometry? And you get a whole, some new insights into certain kinds of geometry that way. So it's, anyway, that's kind of the name for this area is Langlands and geometric Langlands. And just recently in the last few months, there's been, there's kind of really major paper that appeared by Peter Schultze and Laurent Farg, where they, you know, made, you know, some serious advance and try to understand a very much kind of a local problem of what happens in number theory near a certain prime number. And they turned this into a problem of exactly the kind of geometric Langlands people had been doing, this kind of pure geometry problem. And they found by generalizing mathematics, they could actually reformulate it in that way. And it worked perfectly well. One of the things that makes me sad is, you know, I'm a pretty knowledgeable person. And then what is it, at least I'm in the neighborhood of like theoretical computer science, right? And it's still way out of my reach. And so many people talk about like Langlands, for example, as one of the most brilliant people in mathematics and just really admire his work. And I can't, it's like almost I can't hear the music that he composed and it makes me sad. Yeah, well, I mean, I think that, unfortunately, it's not just you, it's I think even most mathematicians have no, really don't actually understand what this is about them in the group of people who really understand all these ideas. And so for instance, this paper of Schultz and Farag that I was talking about, the number of people who really actually understand how that works is, anyway, very, very small. And so it's, so I think even you find, if you talk to mathematicians and physicists, even they will often feel that, you know, there's this really interesting sounding stuff going on and which I should be able to understand. It's kind of in my own field, I have a PhD in, but it still seems pretty clearly far beyond me right now. Well, if we can step into the, back to the question of beauty, is there an idea that maybe is a little bit smaller that you find beautiful in the space of mathematics or physics? There's an idea that, you know, I kind of went, got a physics PhD and spent a lot of time learning about mathematics. And I guess it was embarrassing and I hadn't really actually understood this very simple idea until, I hadn't kind of learned it when I actually started teaching math classes, which is maybe that there, maybe there's a simple way to explain kind of the fundamental way in which algebra and geometry are connected. So you normally think of geometry as about these spaces and these points, and you think of algebra as this very abstract thing about these abstract objects that satisfy certain kinds of relations. You can multiply them and add them and do stuff, but it's completely abstract. It has nothing geometric about it. But the kind of really fundamental idea is that unifies algebra and geometry is to think whenever anybody gives you what you call an algebra, some abstract thing of things that you can multiply and add, that you should ask yourself, is that algebra the space of functions on some geometry? So one of the most surprising examples of this, for instance, is a standard kind of thing that seems to have nothing to do with geometry is the integers. So then you can multiply them and add them. It's an algebra, but it seems to have nothing to do with geometry. But what you can, it turns out, but if you ask yourself this question and ask, is our integers, can you think, if somebody gives you an integer, can you think of it as a function on some space, on some geometry? And it turns out that yes, you can. And the space is the space of prime numbers. And so what you do is you just, if somebody gives you an integer, you can make a function on the prime numbers by just at each prime number, taking that integer modulo that prime. So if, as you say, I don't know, if you're given 10, and you ask what is its value at two? Well, it's five times two, so mod two, it's zero. So it has zero one. What is its value at three? Well, it's nine plus one, so it's one mod three. So it's zero at two, it's one at three, and you can kind of keep going. And so this is really kind of a truly fundamental idea. It's at the basis of what's called algebraic geometry, and it just links these two parts of mathematics that look completely different. And it's just an incredibly powerful idea. And so much of mathematics emerges from this kind of simple relation. So you're talking about mapping from one discrete space to another. For a second, I thought perhaps mapping like a continuous space to a discrete space, like functions over a continuous space. Because, yeah. Well, you can take, if somebody gives you a space, you can ask, you can say, well, let's, and this is also, this is part of the same idea. The part of the same idea is that if you try and do geometry, and somebody tells you, here's a space, that what you should do is you should wait, so say, wait a minute, maybe I should be trying to solve this using algebra. And so if I do that, the way to start is, you give me the space, I start to think about the functions of the space. So for each point in the space, I associate a number. I can take different kinds of functions and different kinds of values, but basically functions on a space. So what this insight is telling you is that if you're a geometer, often the way to work is to change your problem into algebra by changing your space. Stop thinking about your space and the points in it, and think about the functions on it. And if you're an algebraist, and you've got these abstract algebraic gadgets that you're multiplying and adding, say, wait a minute, are those gadgets, can I think of them in some way as a function on a space? What would that space be? And what kind of functions would they be? And that going back and forth really brings these two completely different looking areas of mathematics together. Do you have particular examples where it allowed to prove some difficult things by jumping from one to the other? Is that something that's a part of modern mathematics where such jumps are made? Oh, yes, this is kind of all the time. A lot, much of modern number theory is kind of based on this idea. But, and when you start doing this, you start to realize that you need, you know, what simple things, simple things on one side of the algebra start to require you to think about the other side about geometry in a new way. You have to kind of get a more sophisticated idea about geometry. Or if you start thinking about the functions on a space, you may need a more sophisticated kind of algebra. But in some sense, I mean, much or most of modern number theory is based upon this move to geometry. And there's also a lot of geometry and topology is also based upon. Yeah, change, change. If you wanna understand the topology of something, you look at the functions, you do Durham cohomology, and you get the topology. Anyway. Well, let me ask you then the ridiculous question. You said that this idea is beautiful. Can you formalize the definition of the word beautiful? And why is this beautiful? Like, first, why is this beautiful? And second, what is beautiful? Yeah, well, I think there are many different things you can find beautiful for different reasons. I mean, I think in this context, the notion of beauty, I think really is just kind of, an idea is beautiful if it's packages a huge amount of kind of power and information into something very simple. So in some sense, you can almost kind of try and measure it try and measure it in the sense of, what are the implications of this idea? What non-trivial things does it tell you versus how simply can you express the idea? So the level of compression, what is it, correlates with beauty? Yeah, that's one aspect of it. And so you can start to tell that an idea is becoming uglier and uglier as you start kind of having to, it doesn't quite do what you want, so you throw in something else to the idea and you keep doing that until you get what you want. But that's how you know you're doing something uglier and uglier when you have to kind of keep adding in more into what was originally a fairly simple idea and making it more and more complicated to get what you want. Okay, so let's put some philosophical words on the table and try to make some sense of them. One word is beauty. Another one is simplicity, as you mentioned. Another one is truth. So do you have a sense, if I give you two theories, one is simpler, one is more complicated. Do you have a sense of which one is more likely to be true to capture deeply the fabric of reality? The simple one or the more complicated one? Yeah, I think all of our evidence, what we see in the history of the subject is the simpler one, though often it's a surprise. It's simpler in a surprising way, but yeah, that we just don't, we just, anyway, the kind of best theories we've been coming up with are ultimately, when properly understood, relatively simple and much, much simpler than you would expect them to be. Do you have a good explanation why that is? Is it just because humans want it to be that way? Are we just like ultra-biased and we just kinda convince ourselves that simple is better because we find simplicity beautiful? Or is there something about our actual universe that at the core is simple? My own belief is that there is something about a universe that's simple, and I was trying to say that there is some kind of fundamental thing about math, physics, and physics, and all this picture which is in some sense simple. It's true that, it's of course true that our minds have certain, are very limited and can certainly do certain things and not others, so it's in principle possible that there's some great insight, there are a lot of insights into the way the world works which just aren't accessible to us because that's not the way our minds work. We don't, and that what we're seeing, this kind of simplicity is just because that's all we ever have any hope of seeing. But so there's a brilliant physicist by the name of Sabine Hasenfelder who both agrees and disagrees with you, I suppose agrees that the final answer will be simple. Yeah. But simplicity and beauty leads us astray in the local pockets of scientific progress. Do you agree with her disagreement, do you disagree with her agreement? And agree with the agreement and so on. Anyway, yes, I found it was really fascinating reading her book and anyway, I was finding disagreeing with a lot but then at the end when she says yes, when we find, when we actually figure this out, it will be simple and okay, so we agree in the end. But does beauty lead us astray which is the core thesis of her work in that book? I actually, I guess I do disagree with her on that so much. I don't think, and especially, and I actually fairly strongly disagree with her about sometimes the way she'll refer to math. And so the problem is physicists and people in general just refer to it as math and they're often meaning not what I would call math, which is the interesting ideas of math, but just some complicated calculation. And so I guess my feeling about it is more that it's very, the problem with talking about simplicity and using simplicity as a guide is that it's very easy to fool yourself and it's very easy to decide, to fall in love with an idea, you have an idea, you think, oh, this is great and you fall in love with it and it's like any kind of love affair, it's very easy to believe that the object of your affections is much more beautiful than the others might think and that they really are. And that's very, very easy to do. So if you say, I'm just gonna pursue ideas about beauty and this and mathematics and this, it's extremely easy to just fool yourself, I think. And I think that's a lot of what the story she was thinking of about where people have gone astray that I think it's, I would argue that it's more people, it's not that there was some simple, powerful, wonderful idea which they'd found and it turned out not to be useful, but it was more that they kind of fooled themselves that this was actually a better idea than it really was and that it was simpler, more beautiful than it really was is a lot of the story. I think so, it's not that the simplicity would be at least as astray as it's just people, are people and they fall in love with whatever idea they have and then they weave narratives around that idea or they present it in such a way that emphasizes the simplicity and the beauty. Yeah, that's part of it. But I mean, the thing about physics that you have is that you, what really can tell, if you can do an experiment and check and see if nature is really doing what your idea expects, that you do in principle have a way of really testing it. And it's certainly true that if you thought you had a simple idea and that doesn't work and you got into an experiment and what actually does work is some more, maybe some more complicated version of it, that can certainly happen and that can be true. I think her emphasis is more that I don't really disagree with is that people should be concentrating on, when they're trying to develop better theories, on more on self-consistency, not so much on beauty, but is this idea beautiful, but is there something about the theory which is not quite consistent and use that as a guide that there's something wrong there which needs fixing. And so I think that part of her argument, I think I was, we're on the same page about. What is consistency and inconsistencies? What exactly, do you have examples in mind? Well, it can be just simple inconsistency between theory and experiment that if you, so we have this great fundamental theory, but there are some things that we see out there which don't seem to fit in it, like dark energy and dark matter, for instance. But if there's something which you can't test experimentally, I think she would argue and I would agree that for instance, if you're trying to think about gravity and how are you gonna have a quantum theory of gravity, you should kind of be, test any of your ideas with kind of a thought experiment. Does this actually give a consistent picture of what's gonna happen, of what happens in this particular situation or not? So this is a good example. You've written about this. Since quantum gravitational effects are really small, super small, arguably unobservably small, should we have hope to arrive at a theory of quantum gravity somehow? What are the different ways we can get there? You've mentioned that you're not as interested in that effort because basically, yes, you cannot have ways to scientifically validate given the tools of today. Yeah, I've actually, you know, I've over the years certainly spent a lot of time learning about gravity and about attempts to quantize it, but it hasn't been that much in the past, the focus of what I've been thinking about. But I mean, my feeling was always, as I think Sabina would agree that the, you know, one way you can pursue this, if you can't do experiments, is just this kind of search for consistency. You know, it can be remarkably hard to come up with a completely consistent model of this and a way that brings together quantum mechanics and general relativity. And that's, I think, kind of been the traditional way that people who have pursued quantum gravity have often pursued, you know, we have the best route to finding a consistent theory of quantum gravity. And string theorists will tell you this, other people will tell you it, it's kind of what people argue about. But the problem with all of that is that you end up, the danger is that you end up with, that everybody could be successful, everybody's program for how to find a theory of quantum gravity, you know, ends up with something that is consistent. And so, and in some sense, you could argue this is what happened to the string theorists. They solved their problem of finding a consistent theory of quantum gravity, and they ended up, but they found 10 of the 500 solutions. So, you know, if you believe that everything that they would like to be true is true, well, okay, you've got a theory, but it ends up being kind of useless because it's just one of an infinite, essentially infinite number of things which you have no way to experimentally distinguish. And so this is just a depressing situation. But I do think that there is a, so again, I think pursuing ideas about what, more about beauty and how can you integrate and unify these issues about gravity with other things we know about physics, and can you find a theory which, where these fit together in a way that makes sense and hopefully predicts something that's much more promising. Well, it makes sense and hopefully, I mean, we'll sneak up onto this question a bunch of times because you kind of said a few slightly contradictory things, which is like, it's nice to have a theory that's consistent, but then if the theory is consistent, it doesn't necessarily mean anything. So like- It's not enough, it's not enough. It's not enough, and that's the problem. So it's like it keeps coming back to, okay, there should be some experimental validation. So, okay, let's talk a little bit about string theory. You've been a bit of an outspoken critic of string theory. Maybe one question first to ask is what is string theory? And beyond that, why is it wrong, or rather, as the title of your blog says, not even wrong? Okay. Well, one interesting thing about the current state of string theory is that I think it, I'd argue it's actually very, very difficult to, at this point, to say what string theory means. If people say they're string theorists, what they mean and what they're doing is, it's kind of hard, it's hard to pin down the meaning of the term. But the initial meaning, I think, goes back to, there was kind of a series of developments starting in 1984 in which people felt that they had found a unified theory of our so-called standard model of all the standard, well-known kind of particle interactions and gravity, and it all fit together in a quantum theory, and that you could do this in a very specific way by, instead of thinking about having a quantum theory of particles moving around in space-time, think about a quantum theory of kind of one-dimensional loops moving around in space-time, so-called strings. And so, instead of one degree of freedom, these have an infinite number of degrees of freedom, it's a much more complicated theory, but you can imagine, okay, we're gonna quantize this theory of loops moving around in space-time, and what they found is that you could do this and you could fairly, relatively straightforwardly make sense of such a quantum theory, but only if space and time together were 10-dimensional. And so, then you had this problem, again, the problem I referred to at the beginning of, okay, now, once you make that move, you gotta get rid of six dimensions. And so, the hope was that you could get rid of the six dimensions by making them very small, and that consistency of the theory would require that these six dimensions satisfy a very specific condition called being a Calabi-Yau manifold, and that we knew very, very few examples of this. So, what got a lot of people very excited back in 84, 85 was the hope that you could just take this 10-dimensional string theory and find one of a limited number of possible ways of getting rid of six dimensions by making them small, and then you would end up with an effective four-dimensional theory which looked like the real world. This was the hope. So, then there's a very long story about what happened to that hope over the years. I mean, I would argue, and part of the point of the book and its title was that this ultimately was a failure that you ended up, that this idea just didn't, there ended up being just too many ways of doing this, and you didn't know how to do this consistently, that it was kind of not even wrong in the sense that you never could pin it down well enough to actually get a real falsifiable prediction out of it that would tell you it was wrong, but it was kind of in the realm of ideas which initially looked good, but the more you look at them, they just don't work out the way you want, and they don't actually end up carrying the power or that you originally had this vision of. And yes, the book title is not even wrong. Your blog, your excellent blog title is not even wrong. Okay, but there's nevertheless been a lot of excitement about string theory through the decades, as you mentioned. What are the different flavors of ideas that came, like that branched out? You mentioned 10 dimensions, you mentioned loops with infinite degrees of freedom. What are the interesting ideas to you that kind of emerged from this world? Well, yeah, I mean, the problem in talking about the whole subject, and part of the reason I wrote the book is that it gets very, very complicated. I mean, there's a huge amount, a lot of people got very interested in this, a lot of people worked on it, and in some sense, I think what happened is, exactly because the idea didn't really work, that this caused people to, instead of focusing on this one idea and digging in and working on that, they just kind of kept trying new things. And so people, I think, ended up wandering around in a very, very rich space of ideas about mathematics and physics and discovering all sorts of really interesting things. It's just, the problem is, there tended to be an inverse relationship between how interesting and beautiful and fruitful this new idea that they were trying to pursue was and how much it looked like the real world. So there's a lot of beautiful mathematics came out of it. I think one of the most spectacular is what the physicists call two-dimensional conformal field theory. And so these are basically quantum field theories, and kind of think of it as one space and one time dimension, which have just this huge amount of symmetry and a huge amount of structure, which, and just some totally fantastic mathematics behind it. And again, and some of that mathematics is exactly also what appears in the Langlands program. So a lot of the first interaction between math and physics around the Langlands program has been around these two-dimensional conformal field theories. Is there something you could say about what are the major problems are with string theory? So like, besides that there's no experimental validation, you've written that a big hole in string theory has been its perturbative definition. Yeah. Perhaps that's one. Can you explain what that means? Well, maybe to begin with, I think the simplest thing to say is, you know, the initial idea really was that, okay, we have this, instead of what's great is we have this thing that only works, that's very structured and has to work in a certain way for it to make sense. And, but then you ended up in 10 space-time dimensions. And so to get back to physics, you had to get rid of five of the dimensions, six of the dimensions. And the bottom line, I would say, in some sense, is very simple. That what people just discovered is just, there's kind of no particularly nice way of doing this. There's an infinite number of ways of doing it and you can get whatever you want, depending on how you do it. So you end up, the whole program of starting at 10 dimensions and getting to four, just kind of collapses out of a lack of any way to kind of get to where you want, because you can get anything. The hope around that problem has always been that the standard formulation that we have of string theory, which is, you can go in by the name perturbative, but it's kind of, there's a standard way we know of given a classical theory of constructing a quantum theory and working with it, which is the so-called perturbation theory. That we know how to do. And that by itself just doesn't give you any hint as to what to do about the six dimensions. So actual perturbed string theory by itself really only works in 10 dimensions. So you have to start making some kinds of assumptions about how I'm gonna go beyond this formulation that we really understand of string theory and get rid of these six dimensions. So kind of the simplest one was the Clabiau postulate, but when that didn't really work out, people have tried more and more different things. And the hope has always been that the solution, this problem would be that you would find a deeper and better understanding of what string theory is that would actually go beyond this perturbative expansion and which would generalize this. And that once you had that, it would solve this problem of, it would pick out what to do with the six dimensions. How difficult is this problem, so if I could restate the problem, it seems like there's a very consistent physical world operating in four dimensions. And how do you map a consistent physical world in 10 dimensions to a consistent physical world in four dimensions? And how difficult is this problem? Is that something you can even answer? Or just in terms of physics intuition, in terms of mathematics, mapping from 10 dimensions to four dimensions? Well, basically, I mean, you have to get rid of six of the dimensions. So there's kind of two ways of doing it. One is what we call compactification. You say that there really are 10 dimensions, but for whatever reason, six of them are so, so small, we can't see them. So you basically start out with 10 dimensions and what we call, make six of them not go out to infinity, but just kind of a finite extent, and then make that size go down so small it's unobservable. That's a math trick. So can you also help me build an intuition about how rich and interesting the world in those six dimensions is? So compactification seems to imply that it's not very interesting. Well, no, but the problem is that what you learn if you start doing mathematics and looking at geometry and topology and more and more dimensions is that, I mean, asking the question like, what are all possible six dimensional spaces? It's just, it's kind of an unanswerable question. It's just, I mean, it's even kind of technically undecidable in some way. There are too many things you can do with all these. If you start trying to make one dimensional spaces, it's like, well, you got a line, you can make a circle, you can make graphs, you can kind of see what you can do. But as you go to higher and higher dimensions, there are just so many ways you can put things together of get something of that dimensionality. And so unless you have some very, very strong principle, which is gonna pick out some very specific ones of these six dimensional spaces, and there are just too many of them and you can get anything you want. So if you have 10 dimensions, the kind of things that happen, say that's actually the way, that's actually the fabric of our reality is 10 dimensions. There's a limited set of behaviors of objects, I don't even know what the right terminology to use that can occur within those dimensions, like in reality. And so what I'm getting at is like, is there some consistent constraints? So if you have some constraints that map to reality, then you can start saying like, dimension number seven is kind of boring. All the excitement happens in the spatial dimensions, one, two, three. And time is also kind of boring. Some are more exciting than others, or we can use our metric of beauty. Some dimensions are more beautiful than others. Once you have an actual understanding of what actually happens in those dimensions in our physical world, as opposed to sort of all the possible things that could happen. In some sense, I mean, just the basic fact that you need to get rid of them, we don't see them. So you need to somehow explain them. The main thing you're trying to do is to explain why we're not seeing them. And so you have to come up with some theory of these extra dimensions and how they're gonna behave. String theory gives you some ideas about how to do that, but the bottom line is where you're trying to go with this whole theory you're creating is to just make all of its effects essentially unobservable. So it's not a really, it's an inherently kind of dubious and worrisome thing that you're trying to do there. Why are you just adding in all this stuff and then trying to explain why we don't see it? I mean, it just- This may be a dumb question, but is this an obvious thing to state that those six dimensions are unobservable or anything beyond four dimensions is unobservable? Or do you leave a little door open to saying the current tools of physics, and obviously our brains are unable to observe them, but we may need to come up with methodologies for observing them. So as opposed to collapsing your mathematical theory into four dimensions, or leaving the door open a little bit to maybe we need to come up with tools that actually allow us to directly measure those dimensions. Yes, I mean, you can certainly ask, assume that we've got model, look at models with more dimensions and ask what would the observable effects, how would we know this? And then you go out and do experiments. So for instance, you have a, like gravitationally you have an inverse square law forces. Okay, if you had more dimensions, that inverse square law would change to something else. So you can go and start measuring the inverse square law and say, okay, inverse square law is working, but maybe if I get, and it turns out to be actually kind of very, very hard to measure gravitational effects and even kind of somewhat macroscopic distances because they're so small. So you can start looking at the inverse square law and say, start trying to measure it at shorter and shorter distances and see if there were extra dimensions at those distance scales, you would start to see the inverse square law fail. And so people look for that. And again, you don't see it, but you can, I mean, there's all sorts of experiments of this kind. You can imagine which test for effects of extra dimensions at different distance scales, but none of them, I mean, they all just don't work. Nothing yet. Nothing yet, but you can say, ah, but it's just much, much smaller. You can say that. Which by the way, makes LIGO and the detection of gravitational waves quite an incredible project. Ed Witten is often brought up as one of the most brilliant mathematicians and physicists ever. What do you make of him and his work on string theory? Well, I think he's a truly remarkable figure. I've had the pleasure of meeting him first when he was a postdoc. And I mean, he's just completely amazing mathematician and physicist. And he's quite a bit smarter than just about any of the rest of us and also more hardworking. And it's a kind of frightening combination to see how much he's been able to do. But I would actually argue that his greatest work, the things that he's done that have been of just this mind blowing significance of giving us, I mean, he's completely revolutionized some areas of mathematics. He's totally revolutionized the way we understand the relations between mathematics and physics. And most of those, his greatest work is stuff that has little or nothing to do with string theory. I mean, for instance, he was actually one of fields. The very strange thing about him in some sense is that he doesn't have a Nobel Prize. So there's a very large number of people who are nowhere near as smart as he is and don't work anywhere near as hard who have Nobel Prizes. I think he just had the misfortune of coming into the field at a time when things had gotten much, much, much tougher and nobody really had, no matter how smart you were, it would be very hard to come up with a new idea that was gonna work physically and get you a Nobel Prize. But he got a Fields Medal for a certain work he did in mathematics and that's just completely unheard of for mathematicians to give a Fields Medal to someone outside their field. And physics is really, you wouldn't have before he came around, I don't think anybody would have thought that was even conceivable. So you're saying he came into the field of theoretical physics at a time when, and still to today, is you can't get a Nobel Prize for purely theoretical work. The specific problem of trying to do better than the standard model is just this insanely successful thing and it kind of came together in 1973 pretty much. And post, and so, and all of the people who kind of were involved in that coming together, many of them ended up with Nobel Prizes for that. But if you look post-1973 pretty much, it's a little bit more, there's some edge cases if you like, but if you look post-1973 at what people have done to try to do better than the standard model and to get a better unified theory, it really hasn't, it's been too hard a problem, it hasn't worked, the theory's too good. And so it's not that other people went out there and did it and not him, and that they got Nobel Prizes for doing it, it's just that no one really, the kind of thing he's been trying to do with string theory is not, no one has been able to do since 1973. Is there something you can say about the standard model, so the four laws of physics that seems to work very well and yet people are striving to do more, talking about unification and so on, why? What's wrong, what's broken about the standard model? Why does it need to be improved? I mean, the thing that gets most attention is gravity, that we have trouble, so you wanna in some sense integrate what we know about the gravitational force with it and have a unified quantum field theory that has gravitational interactions also, so that's the big problem everybody talks about. I mean, but it's also true that if you look at the standard model, it has these very, very deep, beautiful ideas, but there's certain aspects of it that are very, let's just say that they're not beautiful, they're not, you have to, to make the thing work, you have to throw in lots and lots of extra parameters at various points, and a lot of this has to do with the so-called Higgs mechanism in the Higgs field, that if you look at the theory, it's everything is, if you forget about the Higgs field and what it needs to do, the rest of the theory is very, very constrained and has very, very few free parameters, really a very small number, there's a very small number of parameters and a few integers which tell you what the theory is. To make this work as a theory of the real world, you need a Higgs field and you need to, it needs to do something, and once you introduce that Higgs field, all sorts of parameters make an appearance, so now we've got 20 or 30 or whatever parameters that are gonna tell you what all the masses of things are and what's gonna happen, so you've gone from a very tightly constrained thing with a couple parameters to this thing which the minute you put it in, you had to add all this extra, all these extra parameters to make things work, and so that, it may be one argument as well, that's just the way the world is and the fact that you don't find that aesthetically pleasing is just your problem, or maybe we live in a multiverse and those numbers are just different in every universe, but another reasonable conjecture is just that, well, this is just telling us that there's something we don't understand about what's going on in a deeper way which would explain those numbers and there's some kind of deeper idea about where the Higgs field comes from and what's going on which we haven't figured out yet and that that's what we should look for. But to stick on string theory a little bit longer, could you play devil's advocate and try to argue for string theory, why it is something that deserved the effort that it got and still, like if you think of it as a flame, still should be a little flame that keeps burning? Well, I think the most positive argument for it is all sorts of new ideas about mathematics and about parts of physics really emerged from it, so it was a very fruitful source of ideas and I think this is actually one argument you'll definitely, which I kind of agree with, I'll hear from Witten and from other string theorists, that this is just such a fruitful and inspiring idea and it's led to so many other different things coming out of it that there must be something right about this. And that's, okay, that, anyway, I think that that's probably the strongest thing that they've got. But you don't think there's aspects to it that could be neighboring to a theory that does unify everything, to a theory of everything? Like it could, it may not be exactly the theory, but sticking on it longer might get us closer to the theory of everything. The problem now really is that you really don't know what it is now, you've never, nobody has ever kind of come up with this non-perturbative theory. So it's become more and more frustrating and an odd activity to try to argue with string theorists about string theory because it's become less and less well-defined what it is. And it's become actually more and more kind of, whether, you have this weird phenomenon of people calling themselves string theorists when they've never actually worked on any theory where there are any strings anywhere. So what has actually happened kind of sociologically is that you started out with this fairly well-defined proposal, and then I would argue because that didn't work, people then branched out in all sorts of directions, doing all sorts of things, it became farther and farther removed from that. And for sociological reasons, the ones who kind of started out or now or were trained by the people who worked on that have now become this string theorists. But it's becoming almost more kind of a tribal denominator than a, so it's very hard to know what you're arguing about when you're arguing about string theory these days. Well, to push back on that a little bit, I mean, string theory, it's just a term, right? It doesn't, like you could, like this is the way language evolves, is it could start to represent something more than just the theory that involves strings. It could represent the effort to unify the laws of physics, right? Yeah. At high dimensions with these super tiny objects, right? Or something like that. I mean, we can sort of put string theory aside. So for example, neural networks in the space of machine learning, there was a time when they were extremely popular, they became much, much less popular to a point where if you mention neural networks getting no funding, and you're not going to be respected at conferences, and then once again, neural networks became all the rage about 10, 15 years ago. And as it goes up and down, and a lot of people would argue that using terminology like machine learning and deep learning is often misused over general, everything that works is deep learning, everything that doesn't isn't, something like that. So that's just the way, again, we're back to sociological things. But I guess what I'm trying to get at is if we leave the sociological mess aside, do we throw out the baby with the bathwater? Is there some, besides the side effects of nice ideas from the Edwittons of the world, is there some core truths there that we should stick by in the full, beautiful mess of a space that we call string theory, that people call string theory? You're right, it is kind of a common problem that how what you call some field changes and evolves in interesting ways as the field changes. But I mean, I guess what I would argue is the initial understanding of string theory that was quite specific, we're talking about a specific idea, 10-dimensional superstrings compactified in six dimensions. To my mind, the really bad thing that's happened to the subject is that it's hard to get people to admit, at least publicly, that that was a failure, that this really didn't work. And so de facto, what people do is people stop doing that and they start doing more interesting things, but they keep talking to the public about string theory and referring back to that idea and using that as kind of the starting point and as kind of the place where the whole tribe starts and everything comes from. And so the problem with this is that having as your initial name and what everything points back to, something which really didn't work out, it kind of makes everybody, it makes everything, you've created this potentially very, very interesting field with interesting things happening, but people in graduate school take courses on string theory and everything kind of, and this is what you tell the public in which you're continually pointing back. So you're continually pointing back to this idea which never worked out as your guiding inspiration. And it really kind of deforms your whole way of your hopes of making progress. And that's, to me, I think the kind of worst thing that's happened in this field. Okay, so there's a lack of transparency and sort of authenticity about communicating the things that failed in the past. And so you don't have a clear picture of like firm ground that you're standing on. But again, those are sociological things. There's a bunch of questions I wanna ask you. So one, what's your intuition about why the original idea failed? So what can you say about why you're pretty sure it has failed? And the initial idea was, as I tried to explain it, it was quite seductive in that you could see why Witten and others got excited by it. At the time, it looked like there were only a few these possible claveas that would work. And it looked like, okay, we just have to understand this very specific model and these very specific six dimensional spaces, and we're gonna get everything. And so it was a very seductive idea. But it just, as people learned, worked more and more about it, it just didn't, they just kind of realized that there are just more and more things you can do with these six dimensions and you can't, and this is just not going to work. Meaning like it's, I mean, what was the failure mode here? Is you could just have an infinite number of possibilities that you could do so you can come up with any theory you want, you can fit quantum mechanics, you can explain gravity, you can explain anything you want with it. Is that the basic failure mode? Yeah, so it's a failure mode of kind of, this idea ended up being essentially empty, that it just didn't, ends up not telling you anything because it's consistent with just about anything. And so I mean, there's a complex, if you try and talk with string theorists about this now, I mean, there's an argument, there's a long argument over this about whether, you know, oh no, no, no, maybe there still are constraints coming out of this idea or not. Or maybe we live in a multiverse and everything is true anyway, so there are various ways you can kind of, that string theorists have kind of react to this kind of argument that I'm making. Try to hold on to it. What about experimental validation? Is that a fair standard to hold before a theory of everything that's trying to unify quantum mechanics and gravity? Yeah, I mean, ultimately to be really convinced that on some new idea about unification really works, you need some kind of, you need to look at the real world and see that this is telling you something, something true about it. I mean, either telling you that if you do some experiment and go out and do it, you'll get some unexpected result and that's the kind of gold standard, or it may be just that, like all those numbers that are, we don't know how to explain, it will show you how to calculate them. I mean, it can be various kinds of experimental validation, but that's certainly ideally what you're looking for. How tough is this, do you think, for a theory of everything, not just string theory? For something that unifies gravity and quantum mechanics, so the very big and the very small, is this, let me ask it one way, is it a physics problem, a math problem, or an engineering problem? My guess is it's a combination of a physics and a math problem that you really need. It's not really engineering, it's not like there's some kind of well-defined thing you can write down and we just don't have enough computer power to do the calculation. That's not the kind of problem it is at all. But the question is, what mathematical tools you need to properly formulate the problem is unclear. So one reasonable conjecture is the way, the reason that we haven't had any success yet is just that we're missing, either we're missing certain physical ideas or we're missing certain mathematical tools, which are some combination of them, which we need to kind of properly formulate the problem and see that it has a solution that looks like the real world. But don't you need, I guess you don't, but there's a sense that you need both gravity, like all the laws of physics to be operating on the same level, so it feels like you need an object like a black hole or something like that in order to make predictions about, otherwise you're always making predictions about disjoint phenomena. Or can you do that as long as the theory is consistent and doesn't have special cases for each of the phenomena? Well, your theory should, I mean, if your theory is gonna include gravity, our current understanding of gravity is that you should have, there should be black hole states in it, you should be able to describe black holes in this theory. And just one aspect that people concentrate a lot on is just this kind of questions about if your theory includes black holes like it's supposed to and it includes quantum mechanics, then there's certain kind of paradoxes which come up. And so that's been a huge focus of kind of quantum gravity work, work has been just those paradoxes. So stepping outside of string theory, can you just say first at a high level, what is the theory of everything? What does the theory of everything seek to accomplish? Well, I mean, this is very much a kind of reductionist point of view in the sense that, so it's not a theory, this is not gonna explain to you anything, it doesn't really, this kind of theory, this kind of theory of everything we're talking about doesn't say anything interesting, particularly about like macroscopic objects, about what the weather's gonna be tomorrow or things are happening at this scale. But just what we've discovered is that as you look at the universe, it kind of, if you kind of start, you can start breaking it apart into, and you end up with some fairly simple pieces, quanta if you like, and which are doing, which are interacting in some fairly simple way. And it's some, so what we mean by the theory of everything is a theory that describes all the object, all the correct objects you need to describe what's happening in the world and describes how they're interacting with each other at a most fundamental level, how you get from that theory to describing some macroscopic, incredibly complicated thing is there that becomes, again, more of an engineering problem and you may need machine learning or you may, a lot of very different things to do it. But- Well, I don't even think it's just engineering, it's also science. One thing that I find kind of interesting talking to physicists is a little bit, there's a little bit of hubris. Some of the most brilliant people I know are physicists, both philosophy and just in terms of mathematics, in terms of understanding the world. But there's a kind of either a hubris or what would I call it, like a confidence that if we have a theory of everything, we will understand everything. Like this is the deepest thing to understand. And I would say, and like the rest is details, right? That's the old Rutherford thing. But to me, there's like, this is like a cake or something. There's layers to this thing and each one has a theory of everything. Like at every level from biology, like how life originates, that itself, like complex systems, like that in itself is like this gigantic thing that requires a theory of everything. And then there's the, in the space of humans, psychology, like intelligence, collective intelligence, the way it emerges among species, that feels like a complex system that requires its own theory of everything. On top of that is things like in the computing space, artificial intelligence systems, like that feels like it needs a theory of everything. And it's almost like once we solve, once we come up with a theory of everything that explains the basic laws of physics that gave us the universe, even stuff that's super complex, like how the universe might be able to originate, even explaining something that you're not a big fan of, like multiverses or stuff that we don't have any evidence of yet, still we won't be able to have a strong explanation of why food tastes delicious. Oh yeah, yeah, no. No, anyway, yeah, I agree completely. I mean, there is something kind of completely wrong with this terminology of theory of everything. It's not, it's really in some sense a very bad term, very hubristic and bad terminology because it's not, this is explaining, this is a purely kind of reductionist point of view that you're trying to understand certain very specific kind of things, which in principle other things emerge from, but to actually understand how anything emerges from this is it can't be understood in terms of this underlying fundamental theory is gonna be hopeless in terms of kind of telling you what about this various emergent behavior. And as you go to different levels of explanation, you're gonna need to develop completely different ideas, completely different ways of thinking. And I guess there's a famous kind of Phil Anderson's slogan is that more is different. So it's just, even once you understand how, what a couple of things, if you have a collection of stuff and you understand perfectly well how each thing is interacting with the others, what the whole thing is gonna do is just a completely different problem. And it's just not, and you need completely different ways of thinking about it. What do you think about this? I gotta ask you, at a few different attempts at a theory of everything, especially recently. So I've been for many years a big fan of cellular automata of complex systems. And obviously because of that, a fan of Stephen Wolfram's work in that space. But he's recently been talking about a theory of everything through his physics project, essentially. What do you think about this kind of discrete theory of everything, like from simple rules and simple objects and hypergraphs emerges all of our reality, where time and space are emergent. Basically everything we see around us is emergent. Yeah, I have to say, unfortunately, I have kind of pretty much zero sympathy for that. I mean, I don't, I spend a little time looking at it and I just don't see, it doesn't seem to me to get anywhere. And it really is just really, really doesn't agree at all with what I'm seeing, this kind of unification of math and physics that I'm kind of talking about around certain kinds of very deep ideas about geometry and stuff. If you wanna believe that your things are really coming out of cellular automata at the most fundamental level, you have to believe that everything that I've seen my whole career and as beautiful, powerful ideas that that's all just kind of a mirage, which just kind of randomly is emerging from these more basic, very, very simple-minded things. And you have to give me some serious evidence for that and I'm saying nothing. So a mirage, you don't think there could be a consistency where things like quantum mechanics could emerge from much, much, much smaller, discrete, like computational type systems? Well, I think from the point of view of certain mathematical point of view, quantum mechanics is already mathematically as simple as it gets. It really is a story about really the fundamental objects that you work with when you write down a quantum theory are in some point of view, precisely the fundamental objects at the deepest levels of mathematics that you're working with, they're exactly the same. So, and cellular automata are something completely different which don't fit into these structures. And so I just don't see why, anyway, I don't see it as a promising thing to do. And then just looking at it and saying, does this go anywhere? Does this solve any problem that I've ever, that I didn't, does this solve any problem of any kind? I just don't see it. Yeah, to me, cellular automata and these hypergraphs, I'm not sure solving a problem is even the standard to apply here at this moment. To me, the fascinating thing is that the question it asks have no good answers. So there's not good math explaining, forget the physics of it, math explaining the behavior of complex systems. And that to me is both exciting and paralyzing. Like we're at the very early days of understanding how complicated and fascinating things emerge from simple rules. Yeah, I agree. I think that is a truly great problem. And depending where it goes, it may be, it may start to develop some kind of connections to the things that I've kind of found more fruitful and hard to know. It just, I think a lot of that area, I kind of strongly feel I best not say too much about it because I just, I don't know too much about it. And I mean, again, we're back to this original problem that your time in life is limited. You have to figure out what you're gonna spend your time thinking about. And that's something I just never seen enough to convince me to spend more time thinking about. Well, also timing. It's not just that our time is limited, but the timing of the kind of things you think about. There's some aspect to cellular automata, these kinds of objects that it feels like we're very many years away from having big breakthroughs on. And so it's like you have to pick the problems that are solvable today. In fact, my intuition, again, perhaps biased, is it feels like the kind of systems that, complex systems that cellular automata are would not be solved by human brains. It feels like, well, like it feels like something post-human that will solve that problem. Or like significantly enhanced humans, meaning like using computational tools, very powerful computational tools to us to crack these problems open. So that's if our approach to science, our ability to understand science, our ability to understand physics will become more and more computational, or there'll be a whole field that's computational in nature, which currently is not the case. Currently, computation is the thing that sort of assists us in understanding science the way we've been doing it all along. But if there's a whole new, I mean, we're from new kind of science, right? It's a little bit dramatic. But if computers could do science on their own computational systems, perhaps that's the way they would do the science. They would try to understand the cellular automata. And that feels like we're decades away. So perhaps we'll crack open some interesting facets of this physics problem, but it's very far away. So timing is everything. That's perfectly possible, yeah. Well, let me ask you then in the space of geometry, I don't know how well you know Eric Weinstein. Oh, quite well, yeah. What are your thoughts about his geometric unity and the space of ideas that he's playing with in his proposal for a theory of everything? Well, I think that he has, he fundamentally has, I think, the same problems that everybody has had trying to do this. And they're really versions of the same problem that you try to get unity by putting everything into some bigger structure. So he has some other ones that are not so conventional that he's trying to work with. But he has the same problem that even if he can, if he can get a lot farther in terms of having a really well-defined, well-understood, clear picture of these things he's working with, they're really kind of large geometrical structures of many dimensions, many kinds. And I just don't see any way he's gonna have the same problem the string theorists have. How do you get back down to the structures of the standard model? And how do you, yeah, so I just, anyway, it's the same. And there's another interesting example of a similar kind of thing is Garrett Leasy's Theory of Everything. Again, it's a little bit more specific than Eric's. He's working with this E8. But again, I think all these things founder at the same point that you don't, you create this unity, but then you have no, you don't actually have a good idea how you're gonna get back to the actual, to the objects we've seen. How are you gonna, you create these big symmetries, how are you gonna break them? And, cause we don't see those symmetries in the real world. And so ultimately there would need to be a simple process for collapsing it to four dimensions. You'd have to explain, well, yeah, and I forget in his case, but it's not just four dimensions. It's also these structures you see in the standard model. There's certain very small dimensional groups of symmetries called U1, SU2 and SU3 and the problem with, and this has been a problem since the beginning, almost immediately after 1973, about a year later, two years later, people started talking about grand unified theories. So you take the U1, the SU2 and the SU3 and you put them in together into this bigger structure called SU5 or SO10. But then you're stuck with this problem that, wait a minute, now how, why does the world not look, why do I not see these SU5 symmetries in the world? I only see these. And so, and I think those, the kind of thing that Eric and also in Garrett and lots of people try to do, they all kind of found her in that same way that they don't have a good answer to that. Are there lessons, ideas to be learned from theories like that from Garrett Leacy's, from Eric's? I don't know, it depends. I have to confess, I haven't looked that closely at Eric's. I mean, he explained to this to me personally a few times and I've looked a bit at his paper, but it's, again, we're back to the problem of a limited amount of time in life. Yeah, I mean, it's an interesting effect, right? Why don't more physicists look at it? I mean, I'm in this position that somehow, you know, people write me emails for whatever reason and I worked in the space of AI and so there's a lot of people, perhaps AI is even way more accessible than physics in a certain sense. And so a lot of people write to me with different theories about what they have for how to create general intelligence. And it's, again, a little bit of an excuse I say to myself, like, well, I only have a limited amount of time, so that's why I'm not investigating it. But I wonder if there's ideas out there that are still powerful, they're still fascinating, and that I'm missing because I'm dismissing them because they're outside of the sort of the usual process of academic research. Yeah, well, I mean, the same thing pretty much every day in my email, there's somebody who's got a theory of everything about why all of what physicists are doing. Perhaps the most disturbing thing I should say about my critique, being a critic of string theory is that when you realize who your fans are, that every day I hear from somebody who says, oh, well, since you don't like string theory, you must of course agree with me that this is the right way to think about everything. Oh no, oh no. And most of these are, you quickly can see this is person doesn't know very much and doesn't know what they're doing, but there's a whole continuum to people who are quite serious physicists and mathematicians who are making a fairly serious attempt to try to do something like Garrett and Eric. And then your problem is you do try to spend more time looking at it and try to figure out what they're really doing. But then at some point you just realize, wait a minute, for me to really, really understand exactly what's going on here would just take time I just don't have. Yeah, it takes a long time. Which is the nice thing about AI is unlike the kind of physics we're talking about, if your idea is good, that should quite naturally lead to you being able to build a system that's intelligent. So you don't need to get approval from somebody that's saying you have a good idea here. You can just utilize that idea in an engineer system. Like naturally leads to engineering. With physics here, if you have a perfect theory that explains everything, that still doesn't obviously lead, one, to scientific experiments that can validate that theory and two, to like trinkets you can build and sell at a store for $5. You can't make money off of it. So that makes it much more challenging. Well, let me also ask you about something that you found especially recently appealing, which is Roger Penrose's twister theory. What is it? What kind of questions might it allow us to answer? What will the answers look like? It's only in the last couple years that I really, really kind of come to really, I think, to appreciate it and to see how to really, I believe to see how to really do something with it. And I've gotten very excited about that in the last year or two. I mean, one way of saying, one idea of twister theory is that it's a different way of thinking about what space and time are and about what points in space and time are, but which is very interesting that it only really works in four dimensions. So four dimensions behaves very, very specially unlike other dimensions. And in four dimensions, there is a way of thinking about space and time geometry where, as well as just thinking about points in space and time, you can also think about different objects, these so-called twisters. And then when you do that, you end up with a kind of a really interesting insight that you can formulate a theory, and you can formulate a very, take a standard theory that we formulate in terms of points of space and time, and you can reformulate in this twister language. And in this twister language, it's the fundamental objects are actually more kind of the, are actually spheres in some sense, kind of the light cone. So maybe one way to say it, which actually I think is really, is quite amazing is if you ask yourself, what do we know about the world? We have this idea that the world out there is all these different points in this point of time. Well, that's kind of a derived quantity. What we really know about the world is when we open our eyes, what do you see? You see a sphere. And that what you're looking at is you're looking at, a sphere is worth of light rays coming into your eyes. And what Penrose says is that, well, what a point in space time is, is that sphere, that sphere of all the light rays coming in. And he says, and you should formulate your, instead of thinking about points, you should think about the space of those spheres, if you like. And formulate the degrees of freedom as physics as living on those spheres, living on. So you're kind of living on, your degrees of freedom are living on light rays, not on points. And it's a very different way of thinking about physics. And he and others working with him developed a, a beautiful mathematical formalism and a way to go back from forth between our kind of some aspects of our standard way we write these things down and work on the so-called twister space. And they, certain things worked out very well, but they ended up, I think kind of stuck by the 80s or 90s, that they weren't, a little bit like string theory, that they, by using these ideas about twisters, they could develop them in different directions and find all sorts of other interesting things, but they were getting, they weren't finding any way of doing that, that brought them back to kind of new insights into physics. And my own, I mean, what's kind of gotten me excited really is, what I think I have an idea about that I think does actually, does actually work that goes more in that direction. And I can go on about that endlessly or talk a little bit about it, but that's the, I think that that's the one kind of easy to explain inside about twister theory. There are some more technical ones I should, I mean, I think it's also very convincing what it tells you about spinners, for instance, but that's a more technical. Well, first let's like linger on the spheres and the light cones. You're saying twister theory allows you to make that the fundamental object with which you're operating. Yeah. How, I mean, first of all, like philosophically, that's weird and beautiful. Maybe because it maps, it feels like it moves us so much closer to the way human brains perceive reality. So it's almost like, our perception is, like the content of our perception is the fundamental object of reality. That's very appealing. Yeah. Is it mathematically powerful? Is there something you can say, can you say a little bit more about what the heck that even means for, because it's much easier to think about mathematically like a point in space time. Like what does it mean to be operating on the light cone? It uses a kind of mathematics that's relative, that you know, what was, kind of goes back to the 19th century among mathematicians. It's not, anyway, it's a bit of a long story, but the one problem is that you have to start, it's crucial that you think in terms of complex numbers and not just real numbers. And this, for most people, that makes it harder to, for mathematicians, that's fine, we love doing that. But for most people, that makes it harder to think about. But I think perhaps the most, the way that there is something you can say very specifically about it, you know, in terms of spinners, which I don't know if you wanna, I think at some point you wanna talk. So maybe- What are spinners? Let's start with spinner. Because I think that if we can introduce that, then I can say- By the way, twister is spelled with an O, and spinner is spelled with an O as well. Yes, okay. So- In case you wanna Google it and look it up, there's very nice Wikipedia pages as a starting point. I don't know what is a good starting point for twister theory. Well, one thing I say about Penrose, I mean, Penrose is actually a very good writer and also a very good draftsman. He's all drafts. To the extent this is visualizable, he actually has done some very nice drawings. So, I mean, almost any kind of expository thing, you can find him writing is a very good place to start. He's a remarkable person. But the, so spinners are something that independently came out of mathematics and out of physics. And to say where they came out of physics, I mean, what people realized when they started looking at elementary particles like electrons or whatever, that there seemed to be some kind of doubling of the degrees of freedom going on. If you counted what was there in some sense in the way you would expect it and when you started doing quantum mechanics and started looking at elementary particles, there were seen to be two degrees of freedom, they're not one. And one way of seeing it was that if you put your electron in a strong magnetic field and ask what was the energy of it, instead of it having one energy, it would have two energies. There'd be two energy levels. And as you increase magnetic field, the splitting would increase. So physicists kind of realized that, wait a minute. So we thought when we were doing, first started doing quantum mechanics, that the way to describe particles was in terms of wave functions. And these wave functions were complex to complex values. Well, if we actually look at particles, that's not right. They're pairs of complex numbers. They're pairs of complex numbers. So, you know, why, so one of the kind of fundamental, from the physics point of view, the fundamental question is, why are all our kind of fundamental particles described by pairs of complex numbers? Just weird. And then, but if you go, and then you can ask, you know, well, what happens if you like take an electron and rotate it? So how do things move in this pair of complex numbers? Well, now, if you go back to mathematics, what had been understood in mathematics, you know, some years earlier, not that many years earlier, was that if you ask very, very generally, think about geometry of three dimensions and ask, and if you think about things that are happening in three dimensions in the standard way, everything, the standard way of doing geometry, everything is about vectors, right? So if you've taken any mathematics classes, you probably see vectors at some point. They're just triplets of numbers tell you what a direction is or how far you're going in three-dimensional space. And most of everything we teach in most standard courses in mathematics is about vectors and things you build out of vectors. So you express everything about geometry in terms of vectors or how they're changing or how you put two of them together and get planes and whatever. But what had been realized that early on is that if you ask very, very generally, what are the things that you can kind of consistently think about rotating? And so you ask a technical question, what are the representations of the rotation group? Well, you find that their one answer is their vectors and everything you build out of vectors. But then people found, but wait a minute, there's also these other things which you can't build out of vectors, but which you can consistently rotate. And they're described by pairs of complex numbers, by two complex numbers. And they're the spinners also. And you can think of spinners in some sense as more fundamental than vectors because you can build vectors out of spinners. You can take two spinners and make a vector, but if you only have vectors, you can't get spinners. So there in some sense, there's some kind of lower level of geometry beyond what we thought it was, which was kind of spinner geometry. And this is something which even to this day, when we teach graduate courses in geometry, we mostly don't talk about this because it's a bit hard to do correctly. If you start with your whole setup is in terms of vectors, describing things in terms of spinners is a whole different ball game. But anyway, it was just this amazing fact that this kind of more fundamental piece of geometry is spinners and what we were actually seeing, if you look at electron, are one in the same. So I think it's kind of a mind blowing thing, but it's very counterintuitive. What are some weird properties of spinners that are counterintuitive? There are some things that they do. For instance, if you rotate a spinner around 360 degrees, it doesn't come back towards, it becomes minus what it was. So it's, anyway, so the way rotations work, there's a kind of a funny sign you have to keep track of in some sense. So they're kind of too valued in another weird way. But the fundamental problem is that it's just not, if you're used to visualizing vectors, you just, there's nothing you can do, visualize in terms of vectors, that will ever give you a spinner. It just is not gonna ever work. As you were saying that, I was visualizing a vector walking along a Mobius strip. Yeah. And it ends up being upside down. But you're saying that doesn't really capture. So what really captures it, the problem is that it's really, the simplest way to describe it is in terms of two complex numbers. And your problem with two complex numbers is that's four real numbers. So your spinner kind of lies in a four-dimensional space. So that makes it hard to visualize. And it's crucial that it's not just any four dimensions, it's just, it's actually complex numbers. You're really gonna use the fact that these are two complex numbers. So it's very hard to visualize. But to get back to what I think is mind blowing about twisters is that the, another way of saying this idea about talking about spheres, another way of saying the fundamental idea of twister theory is, in some sense, the fundamental idea of twister theory is that a point is a two complex dimensional space. So that every, and that it lives inside, the space that it lies inside is twister space. So in the simplest case, it's four, twister space is four dimensional, and a point in space-time is a two complex dimensional subspace of all the four complex dimensions. And as you move around in space-time, you're just moving, your planes are just moving around. Okay. And that, but then the- So it's a plane in a four dimensional space. It's a, yeah, a plane- Complex. Complex plane. Two complex dimensions in four complex. Okay. But then to me, the mind blowing thing about this is this then kind of tautologically answers the question is what is a spinner? Well, a spinner is a point. I mean, the space of spinners at a point is the point. In twister theory, the points are the complex two planes. And you want me to, and you're asking what a spinner is. Well, a spinner, the space of spinners is that two plane. So it's, you know, just your whole definition of what a point in space-time was just told you what a spinner was. It's, they're just, it's the same thing. Yeah, well, we're trying to project that into a three dimensional space and trying to intuit, but you can't. Yeah, so the intuition becomes very difficult, but from, if you don't, not using twister theory, you have to kind of go through a certain fairly complicated rigmarole to even describe spinners, to describe electrons. Whereas using twister theory, it's just completely tautological. They're just what you want to describe. The electron is fundamentally the way you're describing the point in space-time already. It's just there. So. Do you have a hope? You mentioned that you've been, you found it appealing recently. Is it just because of certain aspects of its mathematical beauty, or do you actually have a hope that this might lead to a theory of everything? Yeah, I mean, I certainly do have such a hope because what I've found, I think the thing which I've done, which I don't think, as far as I can tell, no one had really looked at from this point of view before, is, has to do with this question of how do you treat time in your quantum theory? And so there's another long story about how we do quantum theories and about how we treat time in quantum theories, which is a long story. But to me, the short version of it is that what people have found when you try and write down a quantum theory, that it's often a good idea to take your time coordinate, whatever you're using to your time coordinate, and multiply it by the square root of minus one and to make it purely imaginary. And so all these formulas which you have in your standard theory, if you do that to those, I mean, those formulas have some very strange behavior, and they're kind of singular. If you ask even some simple questions, you have to take very delicate singular limits in order to get the correct answer, and you have to take them from the right direction, otherwise it doesn't work. Whereas if you just take time, and if you just put a factor of square root of minus one wherever you see the time coordinate, you end up with much simpler formulas, which are much better behaved mathematically. And what I hadn't really appreciated until fairly recently is also how dramatically that changes the whole structure of the theory. You end up with a consistent way of talking about these quantum theories, but it has some very different flavor and very different aspects that I hadn't really appreciated. And in particular, the way symmetries act on it is not at all what I originally had expected. And so that's the new thing that I've, or I think gives you something is to do this move, which people often think of as just kind of a, kind of a mathematical trick that you're doing to make some formulas work out nicely, but to take that mathematical trick as really fundamental. And it turns out in twister theory allows you to simultaneously talk about your usual time and the time times the square root of minus one. They both fit very nicely into twister theory. And you end up with some structures which look a lot like the standard models. Well, let me ask you about some Nobel prizes. Okay. Do you think there will be, there was a bet between Michio Kaku and somebody else. John Horgan. John Horgan about, by the way, maybe discover a cool website, longbets.com or.org. Yeah, yeah. It's cool. It's cool that you can make a bet with people and then check in 20 years later. That's, I really love it. There's a lot of interesting bets on there. Yeah. I would love to participate, but it's interesting to see, you know, time flies. Yeah. And you make a bet about what's going to happen in 20 years. You don't realize 20 years just goes like this. Yeah, yeah. And then you get to face, and you get to wonder, like, what was that person, what was I thinking? That person 20 years ago was almost like a different person. What was I thinking back then to think that? It's interesting. But, so let me ask you this, on record, you know, 20 years from now or some number of years from now, do you think there will be a Nobel Prize given for something directly connected to a first broadly theory of everything? And second, of course, one of the possibilities, one of them, string theory? String theory, definitely not. The things have gone, yeah. So if you were giving financial advice, you would say not to bet on it? No, do not bet on it. And even, I actually suspect if you ask string theorists that question, you're gonna get few of them saying, I mean, if you'd asked them that question 20 years ago, again, when Tucker was making this bet or whatever, I think some of them would have taken you up on it. But, and certainly back in 1984, a bunch of them would have said, oh, sure, yeah. But now, I get the impression that even they realize that things are not looking good for that particular idea. Again, it depends what you mean by string theory, whether maybe the term will evolve to mean something else, which will work out. But yeah, I don't think that's not gonna likely to work out. Whether something else, I mean, I still think it's relatively unlikely that you'll have any really successful theory of everything. And the main problem is just the, it's become so difficult to do experiments at higher energy that we've really lost this ability to kind of get unexpected input from experiment. And you can, while it may be hard to figure out what people's thinking is gonna be 20 years from now, looking at high energy particle, high energy colliders and their technology, it's actually pretty easy to make a pretty accurate guess what you're gonna be doing 20 years from now. And I think actually, I would actually claim that it's pretty clear where you're gonna be 20 years from now and what it's gonna be is you're gonna have the, you're gonna have the LHC, you're gonna have a lot more data, an order of magnitude or more data from the LHC, but at the same energy. You're not gonna see a higher energy accelerator operating successfully in the next 20 years. And like maybe machine learning or great data science methodologies that process that data will not reveal any major shifts in our understanding of the underlying physics, you think? I don't think so. I mean, I think that field, my understanding is they're starting to make a great use of those techniques, but it seems to look like it will help them solve certain technical problems and be able to do things somewhat better, but not completely change the way they're looking at things. What do you think about the potential quantum computers simulating quantum mechanical systems and through that sneak up to sort of, through simulation sneak up to a deep understanding of the fundamental physics? The problem there is that's promising more for this, for Phil Anderson's problem that if you wanna, there's lots and lots of, you start putting together lots and lots of things and we think we know that are paired by pairing reactions, but what this thing is gonna do, we don't have any good calculational techniques. Quantum computers may very well give you those. And so they may, what we think of as kind of strong coupling behavior, we have no good way to calculate. Even though we can write down the theory, we don't know how to calculate anything with any accuracy and that the quantum computers may solve that problem. But the problem is that they, I don't think that they're gonna solve the problem that they help you with the problem of not having the, of knowing what the right underlying theory is. As somebody who likes experimental validation, let me ask you the perhaps ridiculous sounding, but I don't think it's actually ridiculous question of, do you think we live in a simulation? Do you find that thought experiment at all useful or interesting? Not really, I don't, it just doesn't, yeah, anyway, to me, it doesn't actually lead to any kind of interesting, lead anywhere interesting. Yeah, to me, so maybe I'll throw a wrench into your thing. To me, it's super interesting from an engineering perspective. So if you look at virtual reality systems, the actual question is how much computation and how difficult is it to construct a world that, like there are several levels here. One is you won't know the difference, our human perception systems, and maybe even the tools of physics won't know the difference between the simulated world and the real world. That's sort of more of a physics question. The most interesting question to me has more to do with why food tastes delicious, which is create how difficult and how much computation is required to construct a simulation where you kind of know it's a simulation at first, but you wanna stay there anyway. And over time, you don't even remember. Yeah, well, anyway, I agree, these are kind of fascinating questions and they may be very, very relevant to our future as a species, but yeah, they're just very far from anything. I think. So from a physics perspective, it's not useful to you to think, taking a computational perspective to our universe, thinking of it as an information processing system and then think of it as doing computation, and then you think about the resources required to do that kind of computation and all that kind of stuff. You could just look at the basic physics and who cares what the computer it's running on is. Yeah, it just, I mean, the kinds of, I mean, I'm willing to agree that you can get into interesting kinds of questions going down that road, but they're just so different from anything, from what I've found interesting. And I just, again, I just have to kind of go back to, life is too short and I'm very glad other people are thinking about this, but I just don't see anything I can do with it. What about space itself? So I have to ask you about aliens. Again, something, since you emphasize evidence, do you think there is, how many, do you think there are and how many intelligent alien civilizations are out there? Yeah, I have no idea, but I have certainly, as far as I know, unless the government's covering it up or something, we haven't heard from, we don't have any evidence for such things yet, but there seems to be no, there's no particular obstruction why there shouldn't be. So. I mean, do you, you work on some fundamental questions about the physics of reality. When you look up to the stars, do you think about whether somebody's looking back at us? Yes, well, actually, I originally got interested in physics. I actually started out as a kid interested in astronomy, exactly that, and a telescope and whatever that, and certainly read a lot of science fiction and thought about that. I find over the years, I find myself kind of less, anyway, less and less interested in that, just because I don't really know what to do with them. I also kind of at some point kind of stopped reading science fiction that much, kind of feeling that there was just too, that the actual science I was kind of learning about was perfectly kind of weird and fascinating and unusual enough and better than any of the stuff that Isaac Asimov, so why should I? Yeah, and you can mess with the science much more than the distant science fiction, the one that exists in our imagination or the one that exists out there among the stars. Well, you mentioned science fiction. You've written quite a few book reviews. I gotta ask you about some books, perhaps, if you don't mind. Is there one or two books that you would recommend to others, and maybe if you can, what ideas you drew from them? Either negative recommendations or positive recommendations. Do not read this book for sure. Well, I must say, unfortunately, yeah, you can go to my website and you can click on book reviews and you can see I've written, read a lot of, a lot of, I mean, as you can tell from my views about string theory, I'm not a fan of a lot of the kind of popular books about, oh, isn't string theory great? And yes, I'm not a fan of a lot of things of that kind. Can I ask you a quick question on this, a small tangent? Are you a fan, can you explore the pros and cons of, forget string theory, sort of science communication, sort of cosmos-style communication of concepts to people that are outside of physics, outside of mathematics, outside of even the sciences, and helping people to sort of dream and fill them with awe about the full range of mysteries in our universe? That's a complicated issue. You know, I think, you know, I certainly go back and go back to like what inspired me and maybe to connect it a little bit to this question about books. I mean, certainly when the books, some books that I remember reading when I was a kid were about the early history of quantum mechanics, like Heisenberg's books that he wrote about, you know, kind of looking back at telling the history of what happened when he developed quantum mechanics. It's just kind of a totally fascinating, romantic, great story. And those were very inspirational to me. And I would think maybe that other people might also find them. But the- And that's almost like the human story of the development of the ideas. Yeah, the human story. But yeah, just also how, you know, they are these very, very weird ideas that didn't seem to make sense, how they were struggling with them and how, you know, they actually, anyway. It's, I think it's the period of physics kind of beginning in 1905, Plank and Einstein and ending up with the war when these things get used to, you know, make massively destructive weapons. It's just a truly amazing- So many new ideas. Let me, on another, a tangent on top of a tangent on top of a tangent, ask, if we didn't have Einstein, so how does science progress? Is it the lone geniuses? Or is it some kind of weird network of ideas swimming in the air and just kind of, the geniuses pop up to catch them and others would anyway? Without Einstein, would we have special relativity, general relativity? I mean, it's an interesting case to case basis. I mean, special relativity, I think we would have had, I mean, there are other people. Anyway, you could even argue that it was already there in some form in some ways. But I think special relativity you would have had without Einstein fairly quickly. General relativity, that was a much, much harder thing to do and required much more effort, much more sophisticated. That, I think you would have had sooner or later, but it would have taken quite a bit longer. Other things- That took a bunch of years to validate scientifically, the general relativity. But even for Einstein, from, you know, the point where he had kind of a general idea of what he was trying to do to the point where he actually had a well-defined theory that you could actually compare to the real world. That was, you know, I forget the number, but the order of magnitude 10 years of very serious work. And if he hadn't been around to do that, it would have taken a while before anyone else got around to it. On the other hand, there are things like, with quantum mechanics, you have, you know, Heisenberg and Schrodinger came up with two, which ultimately equivalent, the two different approaches to it, you know, within months of each other. And, you know, so if Heisenberg hadn't been there, he already would have had Schrodinger or whatever. And if neither of them had been there, it would have been somebody else a few months later. So there are times when the, you know, just the, a lot often is the combination of the right ideas are in place and the right experimental data is in place to point in the right direction. And it's just waiting for somebody who's gonna find it. Maybe to go back to your aliens, I guess the one thing I often wonder about aliens is would they have the same fundamental physics ideas as we have in mathematics? Would their math, you know, would they, you know, how much is this really intrinsic to our minds? If you start out with a different kind of mind, when you end up with a different ideas of what fundamental physics is or what the structure of mathematics is. So this is why, like if I was, you know, I like video games. The way I would do it as a curious being, so first experiment I'd like to do is run Earth over many thousands of times and see if our particular, no, you know what? I wouldn't do the full evolution. I would start at Homo sapiens first and then see the evolution of Homo sapiens millions of times and see how the ideas of science would evolve. Like, would you get, like how would physics evolve? How would math evolve? I would particularly just be curious about the notation they come up with. Every once in a while, I would like throw miracles at them to like, to mess with them and stuff. And then I would also like to run Earth from the very beginning to see if evolution will produce different kinds of brains that would then produce different kinds of mathematics and physics. And then finally, I would probably millions of times run the universe over to see what kind of, what kind of environments and what kind of life would be created to then lead to intelligent life, to then lead to theories of mathematics and physics and to see the full range. And like sort of like Darwin kind of mark, okay, it took them, what is it? Several hundred million years to come up with calculus. I would just like keep noting how long it took and get an average and see which ideas are difficult, which are not, and then conclusively sort of figure out if it's more collective intelligence or singular intelligence that's responsible for shifts and for big phase shifts and breakthroughs in science. If I was playing a video game and ran, I got a chance to run this whole thing. Yeah, but I'm, we're talking about books before I distract you, that's horrible. Yeah, I'd go back to books and yeah, so, and then, yeah. So that's one thing I'd recommend is the books about the, from the original people, especially Heisenberg about the, how that happened. And there's also a very, very good kind of history of the kind of what happened during this 20th century in physics and up to the time of the standard model in 1973, it's called the second creation by Bob Crease and Mann. That's one of the best ones. I know that's, but the one thing that I can say is that, so that book, I think, forget when it was late eighties, nineties, the problem is that there just hasn't been much that's actually worked out since then. So most of the books that are kind of trying to tell you about all the glorious things that have happened since 1973 are, they're mostly telling you about how glorious things are, which actually don't really work. And it's really the argument people sometimes make in favor of these books as well. They're really great because you want to do something that will get kids excited. And then, so they're getting excited about things, something that's not really quite working. It doesn't really matter. The main thing is get them excited. The other argument is, wait a minute, if you're getting people excited about ideas that are wrong, you're really kind of, you're actually kind of discrediting the whole scientific enterprise in a not really good way. So there's this problem. So my general feeling about expository stuff is, yeah, it's to the extent you can do it kind of honestly and well, that's great. There are a lot of people doing that now, but to the extent that you're just trying to get people excited and enthusiastic by kind of telling them stuff, which isn't really true, you really shouldn't be doing that. You obviously have a much better intuition about physics. I tend to, in the space of AI, for example, you could use certain kinds of language, like calling things intelligent, that could rub people the wrong way. But I never had a problem with that kind of thing, saying that a program can learn its way without any human supervision as AlphaZero does to play chess. To me, that may not be intelligence, but it sure, as heck, seems like a few steps down the path towards intelligence. And so I think that's a very peculiar property of systems that can be engineered. So even if the idea is fuzzy, even if you're not really sure what intelligence is, or if you don't have a deep fundamental understanding or even a model of what intelligence is, if you build a system that sure as heck is impressive and showing some of the signs of what previously thought impossible for a non-intelligent system, then that's impressive and that's inspiring and that's okay to celebrate. In physics, because you're not engineering anything, you're just now swimming in the space, directly when you do theoretical physics, that it could be more dangerous. You could be out too far away from shore. Yeah, well, the problem, I think, I think it's actually hard for people even to believe or really understand how that this particular kind of physics has gotten itself into a really unusual and strange and historically unusual state, which is not really, I mean, I spent half my life among mathematicians and half among physicists, and mathematics is kind of doing fine. People are making progress and it has all the usual problems, but also so you could have a, but I just, I don't know, I've never seen anything at all happening in mathematics like what's happened in this specific area in physics. It's just the kind of sociology of this, the way this field works, banging up against this hard a problem without anything from experiment to help it. It's really, it's led to some really kind of problematic things. And those, so it's one thing to kind of, oversimplify or to slightly misrepresent, to try to explain things in a way that's not quite right. But it's another thing to start promoting to people as a success as ideas, which really completely failed. And so, I mean, I've kind of a very, very specific, if you start have people, won't name any names, for instance, coming on certain podcasts like yours, telling the world, this is a huge success and this is really wonderful, and it's just not true. And this is really problematic and it carries a serious danger of, once when people realize that this is what's going on, the loss of credibility of science is a real, real problem for our society. And you don't want people to have an all too good reason to think that what they're being told by kind of some of the best institutions in our country and our authorities is not true. It's not true, it's a problem. That's obviously a characteristic of not just physics, it's sociology. And it's, I mean, obviously in the space of politics, it's the history of politics is you sell ideas to people even when you don't have any proof that those ideas actually work. You speak as if they've worked and that that seems to be the case throughout history. And just like you said, it's human beings running up against a really hard problem. I'm not sure if this is like a particular like trajectory through the progress of physics that we're dealing with now or is this just a natural progress of science? You run up against a really difficult stage of a field and different people behave differently in the face of that. Some sell books and sort of tell narratives that are beautiful and so on. They're not necessarily grounded in solutions that have proven themselves. Others kind of put their head down quietly, keep doing the work. Others sort of pivot to different fields. And that's kind of like ants scattering. And then you have fields like machine learning, which is there's a few folks mostly scattered away from machine learning in the 90s in the winter of AI, AI winter as they call it. But a few people kept their head down and now they're called the fathers of deep learning. And they didn't think of it that way. And in fact, if there's another AI winter, they'll just probably keep working on it anyway, sort of like loyal ants to a particular thing. So it's interesting, but you're sort of saying that we should be careful over hyping things that have not proven themselves because people will lose trust in the scientific process. But unfortunately, there's been other ways in which people have lost trust in the scientific process. That ultimately has to do actually with all the same kind of behaviors you're highlighting, which is not being honest and transparent about the flaws of mistakes of the past. Yeah, I mean, that's always a problem, but this particular field is kind of fun. It's always a strange one. I mean, I think in the sense that there's a lot of public fascination with it, that it seems to speak to kind of our deepest questions about what is this physical reality? Where do we come from? And what, and these kind of deep issues. So there's this unusual fascination with it. Mathematics is, for instance, very different. Nobody's that interested in mathematics. Nobody really kind of expects to learn really great, deep things about the world from mathematics that much. They don't ask mathematicians that. So it's a very unusual, it draws this kind of unusual amount of attention. And it really is historically in a really unusual state. It's kind of, it's gotten itself way kind of down a blind alley in a way which, it's hard to find other historical parallels to. But sort of to push back a little bit, there's power to inspiring people. And if I just empirically look, physicists are really good at combining science and philosophy and communicating it. Like there's something about physics often that forces you to build a strong intuition about the way reality works, right? And that allows you to think through sort of, and communicate about all kinds of questions. Like if you see physicists, it's always fascinating to take on problems that have nothing to do with their particular discipline. They think in interesting ways and are able to communicate their thinking in interesting ways. And so in some sense, they have a responsibility not just to do science, but to inspire. And not responsibility, but the opportunity. And thereby I would say a little bit of a responsibility. Yeah, yeah, in some sense, but I don't know. Anyway, it's hard to say, because there's many, many people doing this kind of thing with different degrees of success and whatever. I guess one thing, but I mean, what's kind of front and center for me is kind of a more parochial interest, is just kind of what damage do you do to the subject itself? Ignoring, misrepresenting, what high school students think about string theory, and that doesn't matter much, but what the smartest undergraduates or the smartest graduate students in the world think about it, and what paths you're leading them down, and what story you're telling them, and what textbooks you're making them read, and what they're hearing. And so a lot of what's motivated me is more to try to speak to kind of a specific population of people to make sure that, look, people, it doesn't matter so much what the average person on the street thinks about string theory, but what the best students at Columbia, or Harvard, or Princeton, or whatever, who really wanna change, work in this field, and wanna work that way, what they know about it, what they think about it, and that they not be, go into the field being misled and believing that a certain story, this is where this is all going, this is what I gotta do, that's important to me. So in general, for graduate students, for people who seek to be experts in the field, diversity of ideas is really powerful, and is getting into this local pocket of ideas that people hold onto for several decades is not good, no matter what the idea. I would say no matter if the idea is right or wrong, because there's no such thing as right in the long term. Like it's right for now, until somebody builds on it, something much bigger on top of it. It might end up being right, but being a tiny subset of a much bigger thing. So you always should question the ways of the past. Yeah, yeah, so how to achieve that diversity of thought and within the sociology of how we organize scientific research is, I know there's one thing that I think it's very interesting that Sabina Hassenfelder has very interesting things to say about it, and I think also Lee Smolin in his book, which is also about that, very much in agreement with them that there's, anyway, there's a really kind of important questions about how research in this field is organized and how people, what can you do to kind of get and get more diversity of thought and get more and get people thinking about a wider range of ideas. At the bottom, I think humility always helps. Well, the problem is that it's also, it's a combination of humility to know when you're wrong and also, but also you have to have a certain, very serious lack of humility to believe that you're gonna make progress on some of these problems. I think you have to have like both modes and switch between them when needed. Let me ask you a question you're probably not gonna wanna answer because you're focused on the mathematics of things, and mathematics can't answer the why questions, but let me ask you anyway. Do you think there's meaning to this whole thing? What do you think is the meaning of life? Why are we here? I don't know, yeah, I was thinking about this. So the, it did occur to me, one interesting thing about that question is that you don't, yes, I have this life in mathematics and this life in physics, and I see some of my physicist colleagues, you know, kind of seem to be, people are often asking them what's the meaning of life, and they're writing books about the meaning of life and teaching courses about the meaning of life, but then I realized that no one ever asked my mathematician colleagues. Nobody ever asked mathematicians. Yeah, that's funny. So I, yeah, everybody just kind of assumes, okay, well, you people are studying mathematics, whatever you're doing, it's maybe very interesting, but it's clearly not gonna tell you anything useful about the meaning of my life. And I'm afraid a lot of my point of view is that if people realized how little difference there was between what the mathematicians are doing and what a lot of these theoretical physicists are doing, they would, they might understand that it's a bit misguided to look for deep insight into the meaning of life from many theoretical physicists. It's not a, they, you know, they're people, they may have interesting things to say about this. You're right, they have, they know a lot about physical reality and about, about, in some sense about metaphysics, about what is real of this kind, but you're also, to my mind, I think you're also making a bit of a mistake that you're looking to, I mean, I'm very, very aware that, you know, I've led a very pleasant and fairly privileged existence of a fairly, without many challenges of different kinds and of a certain kind, and I'm really not, in no way the kind of person that a lot of people who are looking for, to try to understand in some sense the meaning of life, in the sense of the challenges that they're facing in life, I can't really, I'm really the wrong person for you to be asking about this. Well, if struggle is somehow a thing that's core to meaning, perhaps mathematicians are just quietly the ones who are most equipped to answer that question, if in fact the creation, or at least experiencing beauty, is at the core of the meaning of life, because it seems like mathematics is the methodology by which you can most purely explore beautiful things, right? Yeah, yeah. So in some sense, maybe we should talk to mathematicians more. Yeah, yeah, maybe, but unfortunately, people do have a somewhat correct perception that what these people are doing every day or whatever is pretty far removed from anything, yeah, from what's kind of close to what I do every day and what my typical concerns are. So you may learn something very interesting by talking to mathematicians, but it's probably not gonna be, you're probably not gonna get what you were hoping. So when you put the pen and paper down and you're not thinking about physics and you're not thinking about mathematics and you just get to breathe in the air and look around you and realize that you're going to die one day, do you think about that? Your ideas will live on, but you, the human? Not especially much, but certainly I've been getting older, I'm now 64 years old, you start to realize, well, there's probably less ahead than there was behind, and so you start to, that starts to become, what do I think about that? Maybe I should actually get serious about getting some things done, which I may not have, which I may otherwise not have time to do, which I didn't see, and this didn't seem to be a problem when I was younger, but that's the main, I think the main way in which that thought occurred. But it doesn't, the Stoics are big on this, meditating on mortality, helps you more intensely appreciate the beauty when you do experience it. I suppose that's true, but it's not, yeah, it's not something I spend a lot of time trying, but yeah. Day to day, you just enjoy the positive, the mathematics. Just enjoy, yeah, or life in general, life is, I have a perfectly pleasant life and enjoy it and often think, wow, this is, things are, I'm really enjoying this, things are going well. Yeah, life is pretty amazing. I think you and I are pretty lucky. We get to live on this nice little earth with a nice little comfortable climate and we get to have this nice little podcast conversation. Thank you so much for spending your valuable time with me today and having this conversation. Thank you. Glad, thank you, thank you. Thanks for listening to this conversation with Peter White. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Richard Feynman. The first principle is that you must not fool yourself and you are the easiest person to fool. Thank you for listening and hope to see you next time.

https://youtu.be/nDDJFvuFXdc

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Richard Wrangham: Violence, Sex, and Fire in Human Evolution | Lex Fridman Podcast #229

The following is a conversation with Richard Rangham, a biological anthropologist at Harvard specializing in the study of primates and the evolution of violence, sex, cooking, culture, and other aspects of ape and human behavior at the individual and societal level. He began his career over four decades ago working with Jane Goodall in studying the behavior of chimps, and since then has done a lot of seminal work on human evolution and has proposed several theories for the roles of fire and violence in the evolution of us hairless apes, otherwise known as homo sapiens. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now here's my conversation with Richard Rangham. You've said that we're much less violent than our close living relatives, the chimps. Can you elaborate on this point of how violent we are and how violent our evolutionary relatives are? Well, I haven't said exactly that we're less violent than chimps. What I've said is that there are two kinds of violence. One stems from proactive aggression and the other stems from reactive aggression. Proactive aggression is planned aggression. Reactive aggression is impulsive, defensive. It's reactive because it takes place in seconds after the threat. And the thing that is really striking about humans compared to our close relatives is the great reduction in the degree of reactive aggression. So we are far less violent than chimps when prompted by some relatively minor threat within our own society. And the way I judge that is with not super satisfactory data, but the study which is particularly striking is one of people living as hunter-gatherers in a really upsetting kind of environment, namely people in Australia living in a place where they got a lot of alcohol abuse. There's a lot of domestic violence. It's all a sort of a society that is as bad from the point of view of violence as an ordinary society can get. There's excellent data on the frequency with which people actually have physical violence and hit each other. And we can compare that to data from several different sites comparing, we're looking at chimpanzee and bonobo violence. And the difference is between two and three orders of magnitude. The frequency with which chimps and bonobos hit each other, chase each other, charge each other, physically engage, is some day between 500 and a thousand times higher than in humans. So there's something just amazing about us. And this has been recognized for centuries. Aristotle drew attention to the fact that we behave in many ways like domesticated animals because we're so unviolent. But people say, well, what about the hideous engagements of this 20th century, the first and second world war and much else besides. And that is all proactive violence. All of that is gangs of people making deliberate decisions to go off and attack in circumstances which ideally the attackers are going to be able to make their kills and then get out of there. In other words, not face confrontation. That's the ordinary way that armies try and work. And there, it turns out that humans and chimpanzees are in a very similar kind of state. That is to say, if you look at the rate of death from chimpanzees conducting proactive coalitionary violence, it's very similar in many ways to what you see in humans. So we're not downregulated with proactive violence. It's just this reactive violence that is strikingly reduced in humans. So chimpanzees also practice kind of tribal warfare. Indeed they do. Yeah. So this was discovered first in 1974. It was observed first in 1974, which was about the time that the first major study of chimpanzees in the wild by Jane Goodall had been going for something like five years during of the chimpanzees being observed wherever they went. Until then, they'd been observed at a feeding station where Jane was luring them into to be observed by seeing bananas, which is great. She had learned a lot, but she didn't learn what was happening at the edges of their ranges. So five years later, it became very obvious that there was hostile relationships between groups. And those hostile relationships sometimes take the form of the kind of hostile relationships that you see in many animals, which is a bunch of chimps in this case, shouting at a bunch of other chimps on the borders. But dramatically, in addition to that, there is a second kind of interaction. And that is when a party of chimpanzees makes a deliberate venture to the edge of their territory silently and then search for members of neighboring groups. And what they're searching for is a lone individual. So I've been with chimps when they've heard a lone individual under these circumstances, or what they think is a lone one, and they touch each other and look at each other and then charge forward, very excited. And then while they're charging, all of a sudden, the place where they heard a lone call erupts with a volley of calls. It was just one calling out of a larger party. And our chimps put on the brakes and scoot back for safety into their own territory. But if in fact they do find a lone individual and they can sneak up to them, then they make a deliberate attack. They're hunting, they're stalking and hunting, and then they impose terrible damage, which typically ends in a kill straight away, but it might end up with the victim so damaged that they'll crawl away and die a few days or hours later. So that was a very dramatic discovery because it really made people realize for the first time that Conrad Lorenz had been wrong when in the 1960s, in his famous book on aggression, he said, warfare is restricted to humans, animals do not deliberately kill each other. Well, now we know that actually there's a bunch of animals that deliberately kill each other and they always do so under essentially the same circumstances, which is when they feel safe doing it. So humans feel safe doing it when they got a weapon. Animals feel safe when they have a coalition, a coalition that has overwhelming power compared to the victim. And so wolves will do that and lions will do that and hyenas will do that and chimpanzees will do it and humans do it too. Luke Can they pull themselves into something that looks more like a symmetric war as opposed to an asymmetric one? So accidentally engaging on the lone individual and getting themselves into trouble? Or are they more aggressive in avoiding these kinds of battles? Rupert No, they're very, very keen to avoid those kinds of battles, but occasionally they can make a mistake. But so far, there have been no observations of anything like a battle in which both sides maintain themselves. And I think you can very confidently say that overwhelmingly what happens is that if they discover that there's several individuals on the other side, then both sides retreat. Nobody wants to get hurt. What they want to do is to hurt others. Luke Can Yes. So you mentioned Jane Goodall. You've worked with her. What was it like working with her? What have you learned from her? Rupert Well, she's a wonderfully independent, courageous person, you know, who she famously began her studies, not as a qualified person in terms of education, but qualified only by enthusiasm and considerable experience even in her early 20s with nature. So she's courageous in the sense of being able to take on challenges. The thing that is very impressive about her is her total fidelity to the observations, very unwilling to extend beyond the observations, you know, waiting until they mount up and you've really got a confident picture and tremendous attention to individuals. So, you know, that was an interesting problem from her point of view because when she got to know the chimpanzees of Gombe, this particular community of Casa Kelo, about 60 individuals. So Gombe was in Tanzania on Lake Tanganyika. She was there initially with her mother and then alone for two or three years of really intense observation and then slowly joined by other people. What she discovered was that there were obvious differences in individual personality. And the difficulty about that was that when she reported this to the larger scientific world, initially her advisors at Cambridge, they said, well, you know, we don't know how to handle that because you've got to treat all these animals as the same basically because there is no research tradition of thinking about personalities. Well, now, whatever it is, 60 years later, the study of personalities is a very rich part of the study of animal behavior. At any rate, the important point in terms of what she liked is that she stuck to her guns and she absolutely insisted that we have to show, describe in great detail the differences in personality among these individuals and then you can leave it to the evolutionary biologists to think about what it means. Mm-hmm. So what is the process of observation like this, like observing the personality but also observing in a way that's not projecting your beliefs about human nature or animal nature onto chimps, which is probably really tempting to project. So your understanding of the way the human world works, projecting that onto the chimp world. Yes. I mean, it's particularly difficult with chimps because chimps are so similar to humans in their behavior that it's very easy to make those projections, as you say. The process involves making very clear definitions of what a behavior is. You know, aggression can be defined in terms of a forceful hit, a bite, and so on. And writing down every time these things happen and then slowly totting up the numbers of times that they happen from individual A towards individuals B, C, D, and E so that you build up a very concrete picture rather than interpreting at any point and stopping and saying, well, they seem to be rather aggressive. So the sort of formal system is that you build up a pattern of the relationships based on a description of the different types of interactions, the aggressive and the friendly interactions. And all of these are defined in concrete. And so from that, you extract a pattern of relationships. And the relationships can be defined as relatively friendly, relatively aggressive, competitive, based on the frequency of these types of interactions. And so one can talk in terms of individuals having a relationship which on the scores of friendliness is two standard deviations outside the mean. I mean, you know, it's- LR in which direction, sorry, both directions? RD Well, I mean, you know, that would be obviously the friendly ones would be the ones who have exceptionally high rates of spending time close to each other, of touching each other in a gentle way, of grooming each other. And by the way, finding that those things are correlated with each other. So it's possible to define a friendship with a capital F in a very systematic way. And to compare that between individuals, but also between communities of chimpanzees and between different species. So that, you know, we can say that in some species, individuals have friends and others that don't at all. LR What about just because there's different personalities and because they're so fascinating, what about sort of falling in love or forming friendships with chimps? You know, like really, you know, connecting with them as an observer. What role does that play? Because you're tracking these individuals that are full of life and intelligence for long periods of time. Plus as a human, especially in those days for Jane, she's alone observing it. It gets lonely as a human. I mean, probably deeply lonely as a human being observe these other intelligent species. JM It's a very reasonable question. And of course, Jane in those early years, I think she's willing now to talk about the fact that she regrets to some extent how close she became. And the problem is not just from the humans, the problem is from the chimpanzees as well, because they do things that are extremely affectionate, if you like. You know, at one point, Jane offered a ripe fruit to a chimpanzee called David Greybeard. David Greybeard took it and squeezed her hand as if to say thank you. And then I think he gave it back, if I remember rightly. LR No, thank you. JM Right. Oh, it's almost like thank you and returning the affection by giving the fruit. LR Yeah, exactly. JM If they did something like that. LR Yeah, no, it was a gentle squeeze. I mean, chimpanzees could squeeze you very hard as occasionally has happened. Some chimps are aggressive to people and others are friendly. And the ones that are friendly tend to be rather sympathetic characters because they might be ones who are having problems in their own society. So, Jomio in Gombe used to come and sit next to me quite often. And he was having a hard time making it in that society, which I can describe to you in terms of the number of aggressive interactions if you want, but just to be informed about it. So, all of this is a temptation to be very firmly resisted. And in the community that I've been working with in Uganda for the last 30 years, we try extremely hard to impress on all of the research students who come with us, that it is absolutely vital that you do not fall into that temptation. Now, you know, we heard a story of one person who did reach out and touch one of our chimps. It's a very, very bad idea. Not because the chimp is going to do anything violent at the time, but because if they learn that humans are as weak physically as we are compared to them, then they can take advantage of us. And that's what happened in Gombe. So, after Jane had done the very obvious thing when you're first engaged in this game of allowing the infants to approach her and then tickling them and playing with them, some of those infants had the personality of wanting to take advantage of that knowledge later. And so, you know, you had an individual, Frodo, who was violent on a regular basis towards humans when he was an adult, and he was quite dangerous. I mean, he could easily have killed someone. In fact, he did kill one person. He killed a baby that he took from a mother, a human baby that he took off her hip when he met her on the path. So, you know, it's a reminder that we're dealing with a species that are rather human-like in the range of emotions they have, in the capacities they have, and even in the strength they have, they are in many ways stronger than humans. So, you've got to be careful. Luke So, in the full range of friendliness and violence, the capacity for these very human things. Peter Yes. I mean, it's very obvious with violence, as we talked about, you know, that they will kill. They will kill not just strangers. They can kill other adults within their own group. They can kill babies that are strangers. They can kill babies in their own group. So, you know, this is a long-lived individual. Obviously, these killings can't have very often, because otherwise they'd all be dead. And we're now finding that they can live to 50 or 60 years in the wild at relatively low population density, because they're big animals eating a rather specialized kind of food, the ripe fruits. So, it doesn't happen all the time. With friendliness, they are very strong to support each other. They very much depend on their close friendships, which they express through physical contact, and particularly through grooming. So, grooming occurs when one individual approaches another. I might present for grooming, a very common way of starting, turning their back or presenting an arm or something like that, and the other just riffles their fingers through the hair. And that's partly just soothing, and it's partly looking for parasites. But mostly, it's just soothing. And the point about this is it can go on for half an hour. It can go on for sometimes even an hour. So, this is a major expression of interest in somebody else. When did your interest in this one particular aspect of chimps come to be, which is violence? When did the study of violence in chimps become something you're deeply interested in? Well, for my PhD in the early 1970s, I was in Gombe with Jane Goodall and was studying feeding behavior. But during that time, we were seeing, and I say we because there were half a dozen research students all in her camp, we were discovering that chimps had this capacity for violence. The first kill happened during that time, which was of an infant in a neighboring group. And we were starting to see these hunting expeditions. And this was the start of my interest because it was such chilling evidence of an extraordinary similarity between chimps and humans. Now, at that time, we didn't know very much about how chimpanzees and humans were related. Chimps, gorillas, bonobos are all three big black hairy things that live in the African forests and eat fruits and leaves when they can't find fruits and walk on their knuckles. And they all look rather similar to each other. So, they seem as though those three species, chimps and gorillas and bonobos, should all be each other's closest relatives. And humans are something rather separate. And so, any of them would be of interest to us. Subsequently, we learn that actually that's not true and that there's a special relationship between humans and chimpanzees. But at the time, even without knowing that, it was obvious that there was something very odd about chimpanzees because Jane had discovered they were making tools. She had seen that they were hunting meat. She had seen that they were sharing the meat among each other. She had seen that the societies were dominated politically by males, coalitions of males. All of these things, of course, resonate so closely with humans. And then it turns out that in contrast to conventional wisdom at the time, the chimpanzees were capable of hunting and killing members of neighboring groups. Well, at that point, the similarities between chimps and humans become less a matter of sort of sheer intellectual fascination than something that has a really deep meaning about our understanding of ourselves. I mean, until then, you can cheerfully think of humans as a species apart from the rest of nature because we are so peculiar. But when it turns out that, as it turns out, one of our two closest relatives has got these features that we share and that one of the features is something that is the most horrendous as well as fascinating aspect of human behavior, then how can you resist just trying to find out what's going on? So I have to say this. I'm not sure if you're familiar with the man, but fans of this podcast are. So we're talking about chimps, we're talking about violence. My now friend, Mr. Joe Rogan, is a big fan of those things. I'm a big fan of these topics. I think a lot of people are fascinated by these topics. So as you're saying, why do we find the exploration of violence and the relations between chimps so interesting? What can they teach us about ourselves? Until we had this information about chimpanzees, it was possible to believe that the psychology behind warfare was totally the result of some kind of recent cultural innovation that had nothing to do with our biology. Or if you like, that it's got something to do with sin and God and the devil and that sort of thing. But what the chimps tell us, after we think carefully about it, is that it seems undoubtedly the case that our evolutionary psychology has given us the same kind of attitude towards violence as occurred in chimpanzees. And in both species, it has evolved because of its evolutionary significance. In other words, because it's been helpful to the individuals who have practiced it. And now we know that, as I mentioned, other species do this as well. In fact, wolves, which this is a really kind of ironical observation. Conrad Lorenz, who I mentioned, had been the person who thought that human aggression in the form of killing members of our own species was unique to our species. He was a great fan of wolves. He studied wolves. And in captivity, he noted that wolves are very unlikely to harm each other in spats among members of the same group. What happens is that one of them will roll over and present their neck, much as you see in a dog park nowadays, and the other might put their jaws on the neck but will not bite. Okay, so now it turns out that if you study wolves in the wild, then neighboring packs often go hunting for each other. They are in fierce competition. And as much as 50% of the mortality of wolves is due to being killed by other wolves, adult mortality. So it's a really serious business. The chimpanzees and humans fit into a larger pattern of understanding animals in which you don't have an instinct for violence. What you have is an instinct, if you like, to use violence adaptively. And if the right circumstances come up, it'll be adaptive. If the right circumstances don't come up, it won't be. So some chimpanzee communities are much more violent than others because of things like the frequency with which a large party of males is likely to meet a lone victim. And that's going to depend on the local ecology. But, you know, so the overall answer to the question of what do chimps teach us is that we have to take very seriously the notion that in humans, the tendency to make war is a consequence of a long-term evolutionary adaptation and not just a military ideology or some sort of local patriarchal phenomenon. And of course, a reading of history, a judicious reading of history fits that very easily because war is so commonplace. It's not an accident. So it's not a construction of human civilization. It's deeply within us, violence. So what's the difference between violence on the individual level versus group? It seems like with chimps and with wolves, there's something about the dynamic of multiple chimps together that increase the chance of violence. Or is violence still fundamentally part of the individual? Like would an individual be as violent as they might be as part of a group? If we're talking about killing, then violence in the sense of killing is very much associated with a group. And the reason is that individuals don't benefit by getting into a fight in which they risk being hurt themselves. So it's only when you have overwhelming power that the temptation to try and kill another victim rises sufficiently for them to be motivated to do it. The average number of number of chimpanzee males that attack a single male in something like 50 observations that have accumulated in the last 50 years from various different study sites is eight, eight to one. Now, sometimes it can go as low as three to one, but that's getting risky. But if you have eight, you can see what can happen. I mean, basically, you have one male on one foot, another male on another foot, another male on an arm, another male on another arm. Now you have an immobilized victim with four individuals capable of just doing the damage. And so they can then move in and tear out his thorax and tear off his testicles and twist an arm until it breaks and do this appalling damage with no weapons. Mm-hmm. What is the way in which they prefer to commit the violence? Is there something to be said about like the actual process of it? Is there an artistry to it? So if you look at human warfare, there's different parts in history prefer different kind of approaches to violence. It had more to do with tools, I think, on the human side. But just the nature of violence itself, the, sorry, the practice, the strategy of violence, is it basically the same? You improvise, you immobilize the victim and they just rip off different parts of their body kind of thing? Yeah, you have to understand that these things are happening at high speed in thick vegetation, mostly, so that they have not been filmed carefully. We have a few little glimpses of them from one or two people like David Watts, who's got some great video, but we don't know enough to be able to say that. It's hard for me to imagine that there are styles that vary between communities, cultural styles, but it is possible. And one thing that is striking is that the number of times that an individual victim has been killed immediately has been higher in Kibale Forest in Uganda than in Gombe National Park in Tanzania. It's conceivable, that's just chance. We don't have real numbers now, but what is this? I can't remember the exact numbers, but 10 versus 15 or something. So maybe they damage to the point of expecting a death in one place and they just finish it off in the other, but most likely that sort of difference will be due to differences in the numbers of attackers. Human beings are able to conceive of the philosophical notion of death, of mortality. Is there any of that for chimps when they're thinking about violence? Is violence, like what is the nature of their conception of violence, do you think? Do they realize they're taking another conscious being's life or is it some kind of like optimization over the use of resources or something like that? I can't think of any way to get an answer to the question of what they know about that. I think that the way to think about the motivation is rather like the motivation in sex. So when males are interested in having sex with a female, whether it's in chimpanzees or in humans, they don't think about the fact that what this is going to do is to lead to a baby, mostly. Mostly what they're thinking about is, I want to get my end away. And I think that it's a similar kind of process with the chimps. You know, what they are thinking about is, I want to kill this individual. And it's hard to imagine taking the other individual's perspective and thinking about what it means for them to die is going to be an important part of that. In fact, there's reasons to think it should not be an important part of it because it might inhibit them and they don't want to be inhibited. The more efficient they are in doing this, the better. But I think it's interesting to think about this whole motivational question because it does produce this rather haunting thought that there has been selection in favor of enthusiasm about killing. And in our relatively gentle and deliberately moral society that we have today, it's very difficult for us to face the thought that in all of us, there might have been a residue and more than that, sort of an active potential for that thought of really enjoying killing someone else. But I think one can sustain that thought fairly obviously by thinking of circumstances in which it would be true that the ordinary human male would be delighted to be part of a group that was killing someone. What you've got to do is to be in a position where you're regarding the victim as dangerous and thoroughly hostile. But the pure enjoyment of violence, there's, I don't know if you know this historian Dan Carlin, he has a podcast, he has an episode, three, four hour episode that I recommend to others, it's quite haunting. But he takes us through an entire history, it's called painfotainment. The history of humans enjoying the murder of others in a large group. So like public executions were part of long, part of human history. And there's something that for some reason, humans seem to have been drawn to just watching others die. And he ventures to say that that may still be part of us. For example, he said, if it was possible to televise, to stream online, for example, the execution and the murder of somebody, or even the torture of somebody, that a very large fraction of the population on earth would not be able to look away. They'd be drawn to that somehow, as a very dark thought that we were drawn to that. So you think that's part of us in there somewhere, that selection that we evolved for the enjoyment of killing, and the enjoyment of observing those in our tribe doing the killing? Yes. I mean, and that word you produced at the end is critical, I think, because it would be a little bit weird, I think, to imagine a lot of enjoyment about people in your own tribe being killed. I don't think we're interested in violence for violence's sake that much. It's when you get these social boundaries set up. And in today's world, happily, we kind of are already one world. You have to dehumanize someone to get to the point where they are really outside our recognition of a tribe at some level, which is the whole human species. But in ancient times, that would not have been true, because in ancient times, there are lots of accounts of hunters and gatherers in which the appearance of a stranger would lead to an immediate response of shooting on sight, because what was human was the people that were in your society. And the other things that actually looked like us and were human in that sense were not regarded as human. So there was a kind of automatic dehumanization of everybody that didn't speak our language or hadn't already somehow become recognized as sufficiently like us to escape the dehumanization content. And so hopefully the story of human history is that we are, that tribalism fades away, that our dehumanization, the natural desire to dehumanize or tendency to dehumanize groups that are not within this tribe decreases over time. And so then the desire for violence decreases over time. Yeah. I mean, that's the optimistic perspective. And the great sort of concern, of course, is that small conflicts can build up into bigger conflicts and then dehumanization happens and then violence is released. As Hannah Arendt says, there currently is no known alternative to war as a means of settling really important conflicts. So if we look at the big picture, what role has violence, or do you think violence has played in the evolution of Homo sapiens? So we are quite an intelligent, got a beautiful, particular little branch on the evolutionary tree. What part of that was played by our tendency to be violent? Well, I think that violence was responsible for creating your Homo sapiens. And that raises the question of what Homo sapiens is. Yes. Yeah, exactly. So nowadays people begin the concept of what Homo sapiens is by thinking about features that are very obviously different from all of the other species of Homo. And our large brain, our very rounded cranium, our relatively small face, these are characteristics which are developed in a relatively modern way by about 170,000 years ago, say. That's one of the earliest skulls in Africa that really captures that. But it has been argued that that is an episode in a process that has been started substantially earlier. And there's no doubt that that's true. Homo sapiens is a species that has been changing pretty continuously throughout the length of time it's there. And it goes back to 300,000 years ago, 315, naturally, is the time, the best estimate of a date for a series of bones from Morocco that have been dated three or four years ago at that time and have been characterized as earliest Homo sapiens. Now at that point, they are only beginning the trend of sapienization. And that trend consists basically of grassenization, of making our ancestors less robust. Shorter faces, smaller teeth, smaller brow ridge, narrower face, thinner cranium, all these things that are associated with reduced violence. Okay, so that's saying that's Homo sapiens beginning. So it began sometime three to 400,000 years ago, because by 315,000 years ago, you've already got something recognizable. So you're more on that side of things that those gradual processes, not 150, 170,000 years ago, it started like 400,000 years ago. And it's just started three to 400,000 years ago. And if you look at 170, it's got even more like us. And if you look at 100, it's got more like us again. And if you look at 50, it's more like us again. It's all the way. It's just getting more and more like the moderns. So the question is, what happened between three and 400,000 years ago to produce Homo sapiens? And I think we have a pretty good answer now. And the answer comes from violence. And the story begins by focusing on this question. Why is it that in the human species, we are unique among all primates in not having an alpha male in any group? In the sense that what we don't have is an alpha male who personally beats up every other male. And the answer that has been portrayed most richly by Christopher Boehm, and whose work I've elaborated on, is that only in humans do you have a system by which any male who tries to bully others and become the alpha equivalent to an alpha gorilla or an alpha chimpanzee or an alpha bonobo or an alpha baboon or anything like that, any male who tries to do that in humans gets taken down by a coalition of beta males. That coalition. Yes. That's a really good picture of human society. Yes, I like it. Yes, I like it. Okay. And that's the way all our societies work now. Yes. Because individuals try and be alpha and then they get taken out. Yeah. We don't usually think of ourselves as beta males, but yes, I suppose that's what democracy is. Exactly. Yes. Exactly. Okay. So at some point, alpha males get taken out. Well, what alpha males are, are males who respond with high reactive violence to any challenge to their status. You see it all the time in primates. Some beta male thinks he's getting strong and maturing in wisdom and so on, and he refuses to kowtow to the alpha male. And the alpha male comes straight in and charges at him. Or maybe he'll just wait for a few minutes and then take an opportunity to attack him. All of these primates have got a high tendency for reactive aggression, and that enables the possibility of alpha males. We don't. We have this great reduction, as I talked about earlier. And the question is, when did that reduction happen? Well, cut to the famous experiments by the Russian biologist Dmitry Belyaev, who tried domesticating wild animals. When you domesticate wild animals, what you're doing is reducing reactive aggression. You are selecting those individuals to breed who are most willing to be approached by a human or by another member of their own species and are least likely to erupt in a reactive aggression. And you only have to do that for a few generations to discover that there are changes in the skull. And those changes consist of shorter face, smaller teeth, reduced maleness. The males become increasingly female-like. And reduced brain size. Well, the changes that are characteristic of domesticated animals in general compared to wild animals are all found in homo sapiens compared to our early ancestors. So it's a very strong signal that when we first see homo sapiens, what we're seeing is evidence of a reduction in reactive aggression. And that suggests that what's happening with homo sapiens is that that is the point at which there is selection against the alpha males. And therefore, the way in which the selection happened would have been the way it happens today. The beta males take them out. So I think that homo sapiens is a species characterized by the suppression of reactive aggression as a kind of incidental consequence of the suppression of the alpha male. And the story of our species is the story of how the beta males took charge and have been responsible for the generation of a new kind of human. And incidentally, for imposing on the society a new set of values. Because when those beta males discovered that they could take out the previous alpha male and continue to do so, because in every generation, there'll always be some male who says, maybe I'll become the alpha male. So they just keep chopping them down. In discovering that, they also obviously discovered that they could kill anybody in the group. Females, young males, anybody who didn't follow their values. And so this story is one in which the males of our species, and these would be the breeding males, have been able to impose their values on everybody else. And there is two kind of values. There's one kind of value is things that are good for the group, like thou shalt not murder. And the other kind of value is things that are good for the males, such as, hey, guess what? When good food comes in, males get it first. Yes. I mean, it's fascinating that that kind of set of ideals could out-compete the others. Do you have a sense of why? Or maybe you can comment on Neanderthals and all the other early humans. Why did Homo sapiens come to succeed and flourish and all the other ones, all the other branches of evolution died out or got murdered out? I mean, nowadays, when Homo sapiens meets Homo sapiens, and we don't know each other initially, then conflict breaks out and the more militarily able group wins. We've seen that everywhere throughout the age of exploration and throughout history. So I'm rather surprised. The conventional wisdom that you see nowadays in contemporary anthropology is very reluctant to point to success in warfare as the reason why sapiens wiped out Neanderthals within about 3,000 years of the sapiens coming into Europe 43,000 years ago. And people are much more inclined to say, well, the Neanderthals were at low population density, so they just couldn't survive the demographic sweep or the disease disease came in. Maybe those things might have been important, but far and away, the most obvious possibility is that sapiens were just powerful. Everyone agrees they had larger groups. They had better weapons. They had projectile weapons, bows and arrows, to judge from the little microlith bits of flake, which the Neanderthals didn't. Nowadays, there's evidence of interbreeding, quite extensive interbreeding between sapiens and Neanderthals, as well as with some other groups. And sometimes people say, well, so they loved each other. They made love, not war. I think they made love and war. And it wouldn't necessarily have been too loving. I mean, if you just follow through from typical ethnographies nowadays of when dominant groups meet subordinate groups, they didn't know each other, then you can imagine that Neanderthal females would essentially be captured and taken into sapiens groups. Maybe you can comment on this cautiously and eloquently. What's the role of sexual violence in human evolution? Because you mentioned taking Neanderthal females. You've also mentioned that some of these rules are defined by the male side of the society. What's the role of sexual violence in this story? I think you've got to distinguish between groups and within groups. And I think the world has been slowly waking up over the last several decades to the fact that sexual violence is routine in war. And that to me says that it's just another example of power corrupts because when frustrated, scared, elated soldiers come upon females in a group that there's been essential dehumanization of, then they get carried away by opportunity. It is not always possible to argue that this is adaptive nowadays because you get lots and lots of stories of women being abused to the point of being killed. She'll be gang raped and then killed. There's lots of terrible cases of that reported from all sorts of different wars. But you can see that that could build on a pattern that would have been adaptive if happening under much less extreme circumstances. The war is very extreme nowadays in the sense that you get battles in which people are sent by a military hierarchy into a war situation in which they do not feel what hunters and gatherers would typically have felt, which would have been that if we attack, we have an excellent chance of getting away with it. Nowadays, you're sent in across the Somme or whatever it is, and there's a very high chance you will be killed. And that's totally unnatural and a novel evolutionary experience, I think. Then there's sexual coercion within groups. So that takes various kinds of forms. But nowadays, of course, I think people recognize increasingly that the principal form of sexual intimidation and rape occurs within relationships. It's not stranger rape that is really statistically important. There's much more what happens behind the walls of a bedroom where people have been living for some time. And just two thoughts and observations about this. One is that it may seem odd that males should think it a good idea, as it were, to impose themselves sexually on someone with whom they have a relationship. But what they're doing is intimidating someone in a relationship in which the relative power in the relationship has continuing significance for a long time. And that power probably goes well beyond just the sexual. It's to do with domestic relationships, it's to do with the man getting his own way all the way. Right. It's power dynamics and the sexual aggression is one of the tools to regain power, gain power, gain more power, and that kind of thing. Yeah, exactly. And in that respect, it's worth noting that although this wasn't appreciated for some time, it's emerging that in a bunch of primates, you have somewhat similar, or somewhat parallel kinds of sexual intimidation where males will target particular females, even in a group in which the norm is for females to mate with multiple males. But each male will target a particular female, and the more he is aggressive towards her, then the more she conforms to his wishes when he wants to mate. So a long-term pattern of sexual intimidation. So there's that aspect. The other aspect I would just note is that males get away with a lot compared to females in any kind of intersexual conflict. So the punishment, here's one example of this, the punishment for a husband killing a wife has always been much less than the punishment for a wife killing a husband. And you see similar sorts of things in terms of the punishments for adultery and so on. I bring this up in the context of males sexually intimidating their partners, be it wives or whoever, because it's a reminder that it's basically a patriarchal world that we have come from. A patriarchal world in which male alliances tend to support males and take advantage of the fact that they have political power at the expense of females. And I would say that that all goes back to what happened three to four hundred thousand years ago, when the beta males took charge and they started imposing their own norms on society as a whole and they've continued to do so. And we now look at ourselves and Jordan Peterson says, we are not a patriarchal society. Well, it's true that the laws try and make it even-handed nowadays between males and females, but obviously we are patriarchal de facto because society still in many ways supports men better than it supports women in these sorts of conflicts. So beta male patriarchal. If we're looking at the evolutionary history. Okay, is there, maybe sticking on Jordan for a second, is there, so he's a psychologist, right? And what part of the picture do you think he's missing in analyzing the human relations? What does he need to understand about our origins in violence and the way the society has been constructed? Oh, I don't want to go deep into his missing perspectives, but I just think that what he's doing in that particular example is focusing on the legalistic position. And that's great that you do not find formal patriarchy in the law, anything like to the extent that you could find it a hundred years ago and so on. Women have got the vote now, hooray, but it took a long time for women to get the vote. And it remains the case that the women suffer in various kinds of ways. A woman who has lots of sexual partners is treated much more rudely than a male who has lots of sexual partners. There are all sorts of informal ways in which it's really hard to get a woman to vote. It's a rougher being a woman than it is a man. And if we look at the surface layer of the law, we may miss the deeper human nature, like the origins of our human nature that still operates no matter what the law says. Yeah, which is, you know, human nature is awkward because it includes some unpleasant features that when we sit back and reflect about them, we would like them to go away. But it remains the fact that men are hugely concerned to try and have sex with at least one woman and often lots of women. And so men are constantly putting pressure on women in ways that women find unpleasant. And if men sit back and reflect about it, they think, you know, we shouldn't do this. But actually it just goes on because of human nature. So maybe looking at particular humans in history, let's talk about Genghis Khan. So is this particular human who was one of the most famous examples of large-scale violence, is he a deep representative of human nature or is he a rare exception? Yeah, well, I think that it's easy to imagine that most men could have become Genghis Khan. It's possible that he had a particular streak of psychopathy. You know, it's striking that by the time you become immensely powerful, then your willingness to do terrible things for the interest of yourself and your group becomes very high. Stalin, Mao Zedong, these sorts of people have histories in which they do not show obvious psychopathy. But by the time they are big leaders, they are really psychopathic in the sense that they do not follow the ordinary morality of considering the harm that they are doing to their victims. You know, what kind of experiment would we need to discover whether or not anybody could fall into this position? I don't know. But, you know, Lord Acton's famous dictum was, power corrupts and absolute power corrupts absolutely. And then the point that people often forget is the next sentence that he said, which is, great men are almost always bad men. And that is right. It is very difficult to find a great man in history who was not responsible for terrible things. I think there's some aspect of it that it's not just power. I think men who have been the most destructive in human history are not psychopathic completely. They have convinced themselves of an idea. It's like the idea is psychopathic. Stalin, for example, Hitler is a complicated one. I think he was legitimately insane. But I think Stalin has convinced himself that he's doing good. So the idea of communism is the thing that's psychopathic in his mind. Like it bred, you construct a worldview in which the violence is justified. The cruelty is justified. So there, in that sense, first of all, you can construct experiments, unethical experiments that could test this. But in that sense, anybody else could have been in Stalin's position. And it's the idea that could overtake the mind of a human being. And in so doing justify cruel acts. And that seems to be at least in part unique to humans, is the ability to hold ideas in our minds and share those ideas and use those ideas to convince ourselves that proactive violence, on a large scale, is a good idea. So that, I don't know if you have a comment. I suppose so. I mean, but it seems to me what really motivated Stalin was not so much communism as the retention of power. So once he became leader, and in the process of becoming leader, he was absolutely desperate to get rid of anybody who was a challenger. He was deeply suspicious of anybody, even on his side, who might possibly be showing a glimmering of willingness to challenge him. So, you know, when he apparently had Kirov murdered, Kirov was a great communist. Trotsky was a great communist. You know, all his rivals. And I mean, when he went into the towns and murdered people by the tens of thousands. They were all communists. A lot of them were explicit communists. That's right. But what he was worried about was that they were rivals to him. I suppose the thought is, I am the best person to bring about a global sort of embrace of communism. And others are not. And so we have to get rid of those others. Well, I suspect you're being very charitable here. But I mean, maybe you know enough about Stalin to really... Yes. Well, so the point I'm making, I do quite a bit, is from my understanding and sense, of course, we can't know for sure, is he believed in communism. This wasn't purely a game of power. Now, he got drunk with power pretty quickly. But he really believed for, I believe his whole life, that communism is good for the world. And that I don't know what role that belief plays with the more natural human desire for power. I don't know. But it just seems like... As we agreed, he's killing a lot of communists on his journey. But it's not that calculus doesn't work that way. There's humans who are communists. And then there's the idea of communism. So for him, in his delusional worldview, killing a few people is worth the final result of bringing communism to the whole world. But it was more than that, again, because he really wanted power for the Soviet Union. And so surely the reason that he orchestrated the export of wheat from Ukraine, and in so doing was willing to lead to mass starvation, was because he wanted to sell it on the market in order to be able to build up the power of the Soviet Union. An alternative view of communism might have been, well, let's just make sure everybody survives and make sure everybody has enough to eat and we'll all be mutually supportive in a communal network. But no, but he wanted the power for the country. Well, I guess exactly. So it's not even communism, the set of ideas are like Marxism or something like that. It's the country. I guess what I'm saying is, it's not purely power for the individual. It's power for a vision for this great nation, the Soviet Union. And similar with Hitler, the guy believed that this is a great nation, Germany. And it's a nation that's been wronged throughout history and needs to be righted. And there's some dance between the individual, human and the tribe. Yes, no, absolutely. Absolutely, yes, and so just like chimpanzees, we are fiercely tribal and the tribalism resides particularly in male psychology. And it's very scary because once you assemble a set of males who share a tribal identity, then they have power that they can exert but with very little concern about what they're doing to damage other people. Do you think this, so Nietzschean will to power, we talked about the corrupting nature of power. Do you think that's a manifestation of those early origins of violence? What's the connection of this desire for power and our proclivity for violence? You know, what we're talking about is tribal power, right? Power on behalf of a group. Yes, and yeah, that seems to me to go right back to a deep evolutionary origin because you see essentially the same thing in a whole bunch of animals. That most of the sort of cognitively complex animals live in social groups in which they have tribal boundaries. And so what you see in chimpanzees is echoed in almost all of the primates. The difference between us and chimpanzees and humans on the one hand and other primates on the other is that we kill and they don't. And the reason they don't is because they never meet in the context where there are massive imbalances of power. So two groups of baboons, you know, there's 30 on this side and 50 on this side. Fine, nobody's gonna try and kill anybody else because the serious risks involved. But nevertheless, they are tribal. So, you know, they will have fairly intense intergroup interactions in which everybody knows whose side is on, who is on whose side. And the larger group of primates the long-term consequences of winning those battles, non-lethal battles, is that the dominance get access to larger areas of land, more safety and so on with chances are better record of reproductive success subsequently. Do you think this from an evolutionary perspective is a feature or a bug, our natural sort of tendency to form tribes? So what's a bug? Oh, sorry, this is a computer programming analogy. Meaning like it would be more beneficial. Is it beneficial or detrimental to form tribes from an evolutionary perspective? Yeah, yeah, but- What does it mean? What does a bug mean? Yes, right. I mean- Well, yeah, like where's evolution going? It's beneficial in the sense that it evolved by natural selection to benefit the individuals who did it. But if by bug you mean something that from the point of view of the species, it would be great if you could just wipe this out because the species would somehow do better as a result. Then yes, but then males are a bug. Come on now, there's some nice things to males, speaking as a male. The fact that there are some nice things to males doesn't mean that they're not bugs. Maybe they're quite nice bugs, but it would be much better for the species as a whole not to have to have males who impose this violence on the species as a whole. Yeah. As somebody who practiced controlled violence and doing a lot of martial arts, yeah, I'm not sure. It does seem kind of fun to have this kind of controlled violence, also sports. Also, I mean, the question of conflict in general, I guess that's the deeper question. Don't you think there's some value to conflict for the improvement of society, for progress? That this tension between tribes, isn't this like experiment, a continued experiment we conduct with each other to figure out what is a better world to build? Like you need that conflict of good ideas and bad ideas to go to war with each other. It's like the United States with the 50 states and it's the laboratory of ideas. Don't you think that is again, feature versus bug? This kind of conflict, when it doesn't get out of hand, is actually ultimately progressive, productive for a better world? Well, what do you mean by conflict? I mean, you can have conflict in the sense of people have different ideas about the solution to a problem. And so their ideas are in conflict. They can sit down with it and on a log and chat about it and then decide, okay, you're right, or you're right, you're right. And then decide, okay, you're right, or I'm wrong or whatever. But if by conflict, you mean a great idea to build a nuclear bomb and set that off, then no, I don't see why it's a good idea to have all this violence. Yeah, there's, I wonder, I mean, it's not a good idea, but I wonder if human history would evolve the way it did without the violence. Oh, I'm sure you're right. Probably humans would not have evolved in the sense that we have. But I would hope that the course of violence in evolution will continue in the way it has. So there's all sorts of indications that the importance of violence has been reduced over time. And this is made famous in Steven Pinker's book, but others have written about it too, that the frequency of death from violence in every country you look at has been declining. That's just great. And so the amazing thing about this is that even when you take the deaths due to the First World War and the Second World War, the 20th century appears to have been statistically, meaning rates of death per individual, the least violent in history. So we haven't got very far down the course to nonviolence, but I don't see why we shouldn't just carry on doing it. I think it's ridiculous, frankly, you know, excuse my frankness, to say that violence is a good thing. I think that it would be a wonderful concept if we could evolve somehow to a world near 3,000 years from now, where violence is really regarded as simply appalling and that they look back on our time and can't believe what we were doing. Yeah, but of course, violence takes a lot of different shapes as we start to think deeper and deeper about living beings on Earth. For example, the violence we commit and the torture we commit to animals, and then perhaps down the line, as we've talked offline about with robots, and that kind of thing. So there's just so many ways to commit violence to others. And some people now talk about violence in the space of ideas, which of course, to me at least, is a bit of a silly notion relative to use that same V word for the space of ideas versus actual physical violence. But it may be that long time from now, we see that even violence in the space of ideas is quite a manifestation of that same kind of violence. And so it is interesting where this is headed. And I think you're absolutely right. A world, a nonviolent world does seem like a better world. I wonder if the constraints on resources somehow make that world more and more difficult, especially as we run out of resources. Well, it's got to be very, very different from what we're doing nowadays. And it's unimaginably different. If we could imagine it, then maybe we could work towards it. At the moment, nobody knows how to work towards it. Well, that's kind of the stories of humans is we don't really know the future. We're trying to ad hoc kind of develop it as we go and sometimes get into trouble. Yeah. That's the violence. But George Orwell's vision in 1984 was of two or three world powers, each so powerful that nobody could destroy the other. But the notion of an evolutionarily stable relationship among heavily armed world powers just does not seem as though it's reasonable at all. That is to say, we've now got 170 or 190 nations in the world dominated by a few big ones, all with arms pointing at each other. And the notion that we could just carry on having peace talks and making sure that these arms don't get involved in some kind of massive conflagration seems incredibly optimistic. Some kind of major change has to happen, whereby some people would like to see all the weapons go. That'd be great. I'm a member of the UN, I'm a member of that sort of group that tries to see that happen. It's going to be very difficult to see it happen. Another kind of concept is the nations themselves will dissolve and will become one government. That itself is a terrifying vision because the capacity for abuse by a single world power would be so problematic. And in addition, how do you get there without a war in the first place? So, at the moment, we have no reasonable kind of future in mind, but I'm sure it's there somewhere. It's just that we haven't yet to find it. And a lot of people in the cryptocurrency space argue that you can create decentralized societies if you take away the power from states to define the monetary system. So they argue if you make the monetary system such that it's disjoint from the control of any one individual, any one government, then that might be a way to form sort of ad hoc decentralized societies. They just pop up all over the place. That's a really interesting technological solution to how to remove the overreach of power from governments. Yes, right. Absolutely. And it may well be that the future will emerge out of some sort of quite surprising direction like that. Is it nevertheless surprising to you that we have not destroyed ourselves with nuclear weapons? So the mutually assured destruction that we've had for many decades from somebody who studies violence, how does that make sense to you? Well, I mean, I'm surprised only in the sense that accidental, the fact that we have not had an accident yet has been quite remarkable. Because all the accounts are that we've come very close to having very serious accidents where people on either side have misread intentions or apparent launches and so on. So yes, I think it is remarkable. There's a nasty generalization that can be made that the longer that powerful states go without having wars, then the worst the war is afterwards. And you can sort of see that that kind of makes sense because basically what's happening with these tribal groups that the nations are at the moment is that after a big war, like the Second World War, they established new kinds of dominance relationships. And then during the periods of peace, what happens is that the de facto dominance relationships change because some nations become poorer, some become richer, some become more militarily powerful and so on. Generally, economy and military go hand in hand. So right now, China emerged from the war as a relatively low status state and is now high status. So if this were chimpanzees, what would happen is that you would predict a conflict because you need to have a readjustment of the formal dominance relationships to recognize the new in practice dominance relationships recognized by the economy and the military. So the longer that you have of a period of peace following a war, then the more these tensions of unresolved, changed dominance relationships build up. And the longer they take to occur, then the more challenging are going to be the conflicts. That's a terrifying view because we've been out of conflict for quite a bit. That's right. Maybe it's building up. So it's a scary view. But on the other hand, things have changed hugely with the advent of nuclear weapons because at least that conforms to this psychology that is very clear in other animals, which is you don't want to get into a fight if you are going to get hurt. So that's the whole principle of MAD, Mutually Assured Destruction. And it's doubtless been why powerful nations like America and Russia have not used their nuclear weapons since 1945. So if we can overcome the problem of accidental launches, then maybe the fact of MAD does fit into human psychology in a way that means that we really will resolve our tensions without using them. But we haven't yet really faced that challenge. You know, I mean, the Soviet Union collapsed because of the poor economy. But with China, you know, desperate to take back Taiwan and America shifting its focus on the Pacific, the potential for something going wrong is clearly very high. So what's the hopeful case that you can make for a long-term surviving a thriving human civilization, given all the dangers that we face? Well, I can't really exactly make one. I would just say that... We're talking about the dangers. Obviously, the dangers are there. But what I would sort of think about is the notion that surprises come from all sorts of different directions. You know, and I mean, you work in robotics. And, you know, I could well imagine that there will be advances in robotics that in some way I can't even conceive will somehow undermine the motivation for conflict. Something about, you know, by the time chips have been planted in human brains and we're all instantly sharing information in a way that we never did before, will this change the nature of human existence in such a way that these conflicts get resolved? So remove the conflicts, but keep some of the magic, the beauty of what it means to be human. So like still be able to enjoy life, the richness of life, the full complexity of life. Because you can remove conflict by giving everybody a pill, and then they go to sleep, right? You still want life to be amazing, exciting, you know, interesting, and fun. Interesting. And so that's where you have to find the balance. Well, it's, yes, I mean, it's all science fiction stuff. And so how it's going to work out, totally unclear. I don't see any worry about the magic of life disappearing. I mean, first of all, you somehow get rid of males. I think you really need to get rid of males because males are the source of a major problem, which is the lust for power and the resulting conflict. But you don't think the males are also a source of beauty and creation? No, no, no. I mean, I don't have anything against males as, you know, as individuals and that sort of thing. And males have clearly done a lot. I mean, they've been incredibly exploratory and creative. And what they've done in art and music has been wonderful and that sort of thing. On the other hand, I'm not sure there's anything particularly special. And I think that probably females could do the same thing just as well when given the chance. Yes, including the dark stuff. I mean, a part of me is not understanding the, so there is evolutionary distinction between men and women, but I tend to believe both men and women, if you look out into the future, can be destructive, can be evil, can be greedy, can be corrupted by power. So if you move males from the picture, which are historically connected to this evolution that we've been talking about, that women are gonna fill that role quite nicely. And then it'll be just the same kind of process. Not the same, but it'll be new and interesting. There's a sense that the will to power, craving power, committing violence is somehow coupled with all the things that are beautiful about life. That if you remove conflict completely, if you remove all the evil in the world, it seems like you're going to, you're not going to have a stable place for the beauty, for the goodness. Like there's always has to be a dragon to fight for the way, if you look at human history, now you can say, the reason I'm nervous about a sort of utopia where everything is great is every time you look through human history, when utopia has been chased, you run into a lot of trouble, where again, sneaks into this evil, this craving for power. Now you can say that's a male problem, but I just think it's a human problem. And it's not even a human problem, it's a chimp problem too. It's life on earth problem, intelligent life on earth problem. So like, it's better to not necessarily get rid of the sources of the darkest sides of human nature, but more create mechanisms that the kindness, the goodness as, the goodness paradox, your book, that that is incentivized and encouraged, empowered. Well, look, I don't think it would be utopia if you got rid of the males. Right. And certainly females are capable of conflict. I just think it's a gamble worth taking if you could actually do it. You can certainly find females in history who've done unpleasant things, but nevertheless, we have a very strong evolutionary theory which explains why males benefit more by having conflict and winning conflicts than females do. And so if we want to talk about reducing conflict, then it would reduce it to get rid of males. Now I understand this is a fantasy, and I think it's a fantasy that people would be able to talk about fairly soon because reproductive technology is getting to the point where it's quite likely that human females could breed without the use of males. And so there would be a sort of potential dynamic if everybody just agreed not to have any male babies. It's a really interesting thought experiment. I will agree with you that if given two buttons, one is get rid of all women, and the other button is get rid of all men, realizing that I have a stake in this, that I have a stake in this choice, you're probably getting rid of all men. If I wanted to preserve Earth and the richness of life on Earth, I would probably get rid of all men. I don't know. I don't think you have a stake in it. You know, I mean, you're saying that because you're a man. Yeah. But I don't see why being a man should make you any more interested in having a male future for the world than a female future. You know, you've got just as many ancestors who were male as were female. Well, my problem is I'll have to die. Well, that's gonna happen anyway. I know, but like I prefer to die tomorrow, not today. You know, I prefer to hit the snooze button on the whole mortality thing. But it's interesting. But this is not suggesting that males have to die in order to make room for females. It's just, you know, all you have to do is just say, don't let's have any more males born. Interesting. Of course, you know, the difficulty is that because we're tribal, you know, some country, somewhere would say, well, we're not gonna do that. Yeah. And then guess what? They'd take over, you know, because they're male. So that's why it's impossible to imagine actually happening. You know what? I'm gonna take that and actually think about it. I don't know. I'm uncomfortable. There's a certain kind of woke culture that I've been kind of uncomfortable with because it's not women necessarily. It's more just, there's a lot of bullying I see. There's a lack of empathy and a lack of kindness towards others that's created by that culture. But you're speaking about something else. You're speaking about reducing conflict in this world and looking at the basics of our human nature and its origins in the evolution of Homo sapiens and thinking about which kind of aspects of human nature, if we get rid of them, will make for a better world. It's an interesting thought experiment. But it is only a thought experiment. I mean, you know, it's got no practical meaning right now. And I take your point that, you know, males get a hard rap nowadays in some ways because the balance of social power is moving against, I mean, you know, quite rightly in a strong sense, of course, against all the nasty things that males do. But what people sometimes fail to remember is that life is very hard for males who don't have the power, who don't have money, who don't have access to women. You know, I'm sympathetic to incels. I'm not sympathetic to them using violence to solve their problems, but I am very sympathetic to the fact that it's not easy simply to be told by well-off, feminist, middle-class people that you shouldn't behave like this or you shouldn't feel like this because you do. Yes, it's who you are. I mean, in general, just empathy and kindness, male or female, I believe, will be the thing that builds a better world. And that's practiced in different ways from different backgrounds, but ultimately you should listen to others and empathize with the experience of others and put more love out there in the world. Now, that hopefully is the way to reduce conflict, reduce violence, and reduce that whole psychological experience of being powerless in this world, powerless to become the best version of yourself. And that, you know- Well, no one's gonna disagree with all those fine sentiments, right? But that, yes, but that's an actionable thing, is actually practice empathy, right? Like saying that somebody should be silenced or just like this group is bad and this group is good, I just feel like that's not empathy. Empathy is understanding the experience of others and like respecting it. I mean, that's what a better world looks like. That's what the reduction of conflict looks like. It's like, as opposed to saying, my tribe is right, your tribe is wrong. Forget the violence or non-violence part. That just that act of saying, my tribe is right, that tribe is wrong, removing that from the picture. That's the way to make a better world. Like that's the way to reduce the violence, I think. Not necessarily removing the people who are causing the violence. You have to get to the source of the problem. I don't mean the evolutionary source, but just the mindset that creates the violence is usually just the lack of empathy for others. Yeah, but you know, I mean, you can't just teach that because our evolutionary psychology puts us in particular directions. So you don't think, do you think it's possible to learn through practice to resist the basics of our evolutionary psychology, the basic forces? Yeah, I mean, lots and lots of training, you know, lots and lots of education can do it. The famously most peaceful society that anthropologists have recorded involves a tremendous amount of teaching, including some punishment. It's a society in Thailand. You have to beat it out of children to make them nice. It's carrot and steak. You know, the point is that you do not find societies in which people are spontaneously showing the kinds of behaviors that we would all love them to show. LUCAS It requires work. IAN It requires work. LUCAS What is your book titled Goodness Paradox? What are the main ideas in this book? IAN Well, the paradox is the fact that humans show extremes in relationship to both violence and nonviolence. And the violence is that we are one of these few animals in which we use coalitionary proactive violence to kill members of our own species. And we do it in large numbers, just like a few other species. And the nonviolence is we're particularly extreme in how repressed we are in terms of reactive violence. And I told you the story of how we get there. What's so extraordinary about it is that most animals are either high on both or relatively low on both. So chimpanzees are high on proactive violence and reactive violence. Bonobos are less than chimpanzees on both of those, but still hundreds of times more reactively aggressive than humans are. What we've done is retain proactive violence being high and got reactive violence really being low. And so we have these wonderful societies in which we're all so incredibly nice to each other and tolerant and calm and can meet strangers and have no problem about leading to any kind of conflict. At the same time as we are one of the worst killing machine species that's ever existed. So what's so extraordinary about this is that if you look at the political philosophers of the last few hundred years, you've got this fight famously between Thomas Hobbes and Jean-Jacques Rousseau, or literally you've got the fight between their followers. So the followers of Hobbes say, well, Hobbes was right because he says that we are naturally violent and you need a leviathan, a sort of central government or a king to be able to suppress the violence. So we're naturally horrid and we can learn to be good. Whereas Jean-Jacques Rousseau is interpreted as saying the opposite, that we are naturally good and it's only when culture intervenes and horrid ideologies come in that we become uncivilized. And so people have had this endless fight between are we naturally corrupt or are we naturally kind? And that has gone on for years. And it's only in the last two or three decades that anthropologists like Christopher Bohm and Bruce Naft have said, look, it's obvious what the answer is. We are both of these things. And what is so exciting now is I think we can understand why we are both. And the answer is we come from ancestors that were elevated on proactive aggression, that were hunters and killers, both of animals and of each other. And you've got to include that as almost certain from the past. And then now we've taken our reactive aggression and we've down-regulated it and that's given us power. It's given us power because once you get rid of the alpha male, once the beta males take over and force selection in favor of a more tolerant, less reactively aggressive individual, the effect is that our cultures suddenly become capable of focusing on things other than conflict. And so we have social groups in which individuals, instead of constantly being on edge in the way that chimpanzees are with each other, are able to interact in ways that enable them to share looking at a tool together or share their food together or pass ideas from one to the other or support each other when they're ill or whatever the issue is, cooperate in ways that make the group far more effective. So you asked earlier, what did I think about why sapiens was able to expand at the expense of Neanderthals so dramatically around 40,000 years ago? And the answer is that whatever it was, it had something to do with the sapiens ability to cooperate. That was what gave them bigger groups. That's what enabled them to have a far more effective way of living. And I suspect it was to do with the weapons and military aspects. But even if it wasn't that, the greater cooperation that sapiens were showing would have been hugely important. So sapiens then had groups of, who knows exactly how big they were, but scores of people to judge from their remains. Whereas Neanderthals were living in widely separated small groups of maybe as many as 15 or 20 people sometimes, where they saw others so rarely that they were inbreeding at high levels. Fathers having babies with their daughters. Very different world. And that's probably what our world was like before we got sapiens. Before we got sapiens. And it's fascinating that there was that kind of violence against, once you get rid of the alpha males, you have now the freedom to have kindness amongst the beta. The beta males. Not kindness, but collaboration. That's the better word. Yes. Right. Much more cooperation. Not just among the males, but among the beta males, but also among the gamma males and the females. Yeah. I don't know what a gamma male is, but I imagine there's a whole alphabet. Well, I don't know about a whole alphabet, but I think the big layers are the married men and the unmarried men. Because the married men had a problem with the unmarried men. I mean, you see it in ethnographies of hunters and gatherers recently, where the unmarried men would be given rules, such as, I mean, a very extreme rule in Northern Australia was, you cannot come to the camp for months. You have to go away and live somewhere out in the bush. Yes. Because we don't want you anywhere near our wives. And then another kind of rule is, if you are in the camp, you must be in the firelight all the time. Otherwise, we don't know what you're doing out in the dark. So we're going to have to control them, because the men who had lots of wives did not want those horrid bachelors sneaking around the place. Yeah. I love this. You also wrote the book titled, Catching Fire, How Cooking Made Us Human. What's the central idea in this book? The subtitle, How Cooking Made Us Human, refers not to Homo sapiens, but to Homo erectus. So human there means the genus Homo. And Homo erectus is the first full member of the genus Homo in the sense that it looked like us, just with a sort of slightly more robust build and a smaller brain. And the central idea of catching fire is that it was the control of fire that was responsible for the emergence of Homo erectus and therefore the genus Homo, which happened two million years ago. And it was an evolution from a line of Australopithecines. And Australopithecines are the creatures from whom we evolved. They were present in Africa from something like six or seven million years ago, up to, actually up to one million years ago. And then a branch led off to Homo around two million years ago. And the way to think of Australopithecines is that they were like chimpanzees standing upright. So they were erect bipedal walkers. They were like chimpanzees in the sense that they had brains about the size of a chimpanzee. They were literally about the body size of a chimpanzee, a little bit smaller actually. And they had big jaws because they were still eating raw food. They had big teeth and big jaws. And then around two million years ago, the line of Australopithecines, which ended with an intermediate species, a kind of missing link area, because it's not missing, called Habilis, sometimes called Homo habilis, but more properly in my view, called Australopithecus habilis. That gave rise to Homo erectus and Homo erectus, here's how different it was. It had a smaller mouth, a smaller jaw, smaller teeth, and to judge from its ribs and pelvis, smaller gut. In addition, it had lost what Australopithecines all had, which was adaptation to the human body. Australopithecines all had, which was adaptations for climbing in the trees. And that meant that Homo erectus must have slept on the ground. And since it slept on the ground, it should have been able to defend itself somehow against predators. And I can't think of any way they could have done that unless they had fire. So there are two major clues to why it was with Homo erectus that our ancestors first acquired the control of fire. One is the fact that they were clearly not sleeping in trees in the way that chimpanzees and gorillas and bonobos and all the other primates do. And the other is that there was this striking reduction throughout the gut, reduction in size of the mouth and the chewing apparatus and in the gut itself. And that conforms to what we see nowadays about humans, which is that our guts are about two thirds of the size of what they would be if we ate raw food to judge by the great apes. So at some point in our evolution, we acquired the skill of cooking and skill of controlling fire. At no time between two million years ago and the present, do we see any changes in our anatomy that can, as it were, justify the enormous change that happens when you are an animal that learns to control fire. But at two million years ago, we have exactly what you'd expect, namely the guts becoming smaller because the food is becoming softer and much more easy to digest. So you don't have to work so hard in your body to digest it. And as I say, a commitment to sleeping on the ground, which I think you'd be absolutely crazy to do nowadays on a moonless night in the middle of Serengeti unless you had fire. I've slept out quite a lot in various parts of Africa in the bush, and you will not catch me just lying on the ground in an area with lots of predators. Unless I got a fire with me. You're going to get eaten. You're gonna get terrified and you're gonna get eaten. Okay, so there's a million questions I wanna ask. So one, is it very naturally coupled the discovery of controlled fire and cooking with fire? Is that an obvious leap? Well, here's what we know. We know that all the animals that we've tested like to eat their food cooked more than they like it raw. Okay. So this is true for all the great apes. You know, we've tested them. That's fascinating, by the way. Why is that? That's just like a property of food, I suppose. Yes, I think what it is is that animals are always looking for any kind of way to get food that is easier to digest. And there are various signals in the food, such as the amount of sugar there, the amount of free amino acids, because the amino acids can be tasted. And the physical qualities of the food be particularly important, how tough the food is. Always prefer softer food, provided it feels safe, tastes safe. And these kinds of sensory cues are all there in cooked food. It's soft, it doesn't have so many toxins, and it's not so noxious to taste, easier to chew. So everyone loves it spontaneously. Your dogs and your cats prefer cooked food to raw food. Well, maybe you can say that's a consequence of domestication, but even, you know, as I say, all of the great apes, you test naive ones, and they prefer it cooked if they can. So then obvious, once you have fire, you're going to accidentally discover that food changes when you apply fire to it. And then it's going to be the big, crazy new fad. Yeah, you took the words out of my mouth. I mean, if they have fire at all, and their food rolls into it, five minutes later, it tastes better than it did before. How big of an invention, from an engineering perspective, do you think is the discovery of fire? Do you think for Homo erectus, Homo sapiens, do you think it's the greatest invention ever? Yeah, I think that the control of fire has been ultimately responsible for essentially how grandiose do I want to be here? You know, the entire human story, going back to Homo, is what changed us from being a regular kind of animal. And perhaps the biggest way in which it is likely to have changed us is it reduced the difficulty of making a large brain. So, you know, the story here is that the constraints on brain size are energetic. You and I have brains that are something like 2.5% of our body weight. It consumes around 25% of all of our calories. So it's disproportionate. There are other expensive organs in our body as well, such as the heart. And what's different about the brain is that, in addition to us being able to fuel it in a way that other animals can't, we also have reasons for wanting to have an even bigger brain, whereas we don't want an even bigger heart. So what those reasons are is unclear. But with regard to the costs of maintaining a brain, cooking makes it possible because it's supplying more calories, and it is enormously reducing the amount of time that it takes to chew your food. So if you were a gorilla and you wanted to have a bigger brain, you might say, okay, well, let's just eat some more. But gorillas are eating for pretty much the entire day in the sense that they are eating for maybe seven or eight hours a day in some seasons. That's just chewing. And then they've got to sit around and digest their food because they can't just eat all the time. They've got to take a break while the food is digested in the stomach and then passed into the gut. So the stomach is already full. So basically gorillas are eating about the maximum rate already. So how does a gorilla get a bigger brain? It doesn't. It's actually got a smaller brain relative to its body size than chimpanzee does. And that's the basic problem for our ancestors. Then you come along and cook, and all of a sudden, you can get an increased amount of energy from your food. You are spending much less energy on digesting your food. You know, there are 25 bodily processes or more that are involved in digesting your food, making the acid that takes the proteins apart, maintaining the brush border where the molecules are taken across the gut wall, and so on. That all costs. It costs you to digest your food. It costs less if you cook your food. So you get a net gain in the amount of energy. And you are reducing the amount of time from, in our case, our ancestors, probably around 50% of the day chewing to nowadays one hour a day chewing. So all of a sudden, you've got hours a day in which to do other things and to use those brains that you've now enabled to grow. So with Homo erectus, you start the process of getting a bigger brain. And famously, throughout the whole period of the evolution of the genus Homo, you have a steadily increasing size of brain until right at the end when it actually gets smaller. But that's a different story. Which end is this? Which, are we talking about Homo sapiens? Yeah, with Homo sapiens, you get a smaller brain from, people haven't got it exactly down, but at least 30,000 years ago, it starts declining. And so the fascinating thing about that is that all domesticated animals have smaller brains than their wild ancestors. And I... The domestication is intricately connected to this brain size, you think? And exactly. So I think what we're seeing in humans is that same manifestation. And then the fascinating question is why? And the only point I would want to make about this is that there's no evidence that in the small brain domesticates, they're losing, say, an average about 15% of brain size. In the small brain domesticates compared to their wild ancestors, there's no indication of a loss of cognitive ability. So I think what's going on is that it's a younger brain, it's a more pedomorphic brain, looking like the juveniles of the ancestor. But just as our kids are very smart and can learn amazing things compared to adults, all they lack is wisdom and maturity, but in terms of sheer cognitive ability, they got it. And I think that's the same with domesticated animals compared to their wild ancestors, and probably therefore with Homo sapiens say 30,000 years ago compared to their ancestors. So we have smaller brains than Neanderthals. Size, Richard, isn't everything. Exactly. What's the connection between fire, cooking and the eating of meat? Which came first, do you think? Humans starting to enjoy the eating of meat or the invention of fire and the use of fire for cooking? I think that fire increased the using of meat, but the fact that chimpanzees really like to hunt and kill meat, as do bonobos, certainly puts us in... So those two species have a common ancestor with us going six, seven million years ago, and it was from that common ancestor that you get the Australopithecine line. It's very likely, therefore, Australopithecines were eating meat when they could get it, which wouldn't be very often because they wouldn't be very good sprinters, but nevertheless, they would occasionally be able to get some meat and I bet they loved it all the time. And basically all primates like meat if they can get it, almost all of them. But I think fire would have been very important for a couple of reasons. One is that once you eat your food cooked, then you're saving yourself time. By saving yourself time, you can free up the opportunity to go and hunt more because hunting is a high-risk, high-gain activity. There's every risk that you will get nothing on one particular afternoon that you go off looking for opportunities to kill. But it's high gain because when you do get something, you bring down a kudu, then you've got a serious amount of meat. What did males and females do with the time they were saving from not having to chew their food? I think that in the case of males, it's very reasonable to think they spent a greatly increased amount of time hunting. So chimpanzees, they hunt maybe two or three times a month and the average hunt length is 20 minutes. With humans, they're hunting maybe 20 times a month and the average hunt length is six hours. So it's a huge difference. And that's possible because the time was available because they were cooking. Less chewing, more hunting. You got it. The other thing is that the meat is so much nicer. So when a chimpanzee kills a monkey, and I mean, they are so excited about killing a monkey. They are so excited about going into the hunt and they're so excited about killing a monkey. And when they make the kill, then there's screams everywhere and some try to seize it and capture it and take it away from the others. And eventually the strongest one has it and the others sit around begging and trying to get some and tear it off. And so they all love it. There are others who he often goes to the top of a tree in order to be able to get away from all of these beggars and scavengers. And while he's there, he drops of blood or little scraps will fall down to the bottom. And the junior members of society, the females and young and that sort of thing, they are racing through to find a particular leaf that's got a drop of blood on it so they can lick it. I mean, they love it. But it takes them a lot of time to chew it. I mean, it's the same thing as for cooked food in general. So they are getting meats very slowly into their bodies. And there sometimes comes a time when they just say, I've had enough of this, I need real food. And they'll drop the meat and go off and eat fruit again because they can get fruit into their bodies so much faster than they can get meat. So once they're cooking, that problem is solved and they can eat the meat so just much more readily. So I think that meat eating would become important for two reasons with cooking. So the key, not to oversimplify, but the key moments in human history are with the Homo erectus, the discovery of fire and the use of fire for cooking. And then with Homo sapiens, the beta males killing off the alpha males so that the cooperation can exist and cooperation leads to communication and language and ideas, the sharing of ideas, that kind of thing. Well, yes, the only thing I would modify on that is that you have to ask, how is it that the beta males were able to kill the alpha male? And we now know that although chimpanzees do kill males within their own group sometimes, it's not a process of killing the alpha male. It's taking advantage of opportunity when some male gets into a bad position, but it's not a systematic ability to kill the alpha male. And you can see why, because they don't have language. And without language, it's very difficult to know how confident you can be of the support of others against a particular individual within your own group. When you're attacking someone from another group, that problem is solved. We all hate the, those guys. But the alpha male has got alliances within his group. Some of those allies might be willing to turn against him. Some of them might be harboring deep feelings of resentment, but how does anyone else know that? So in other words, I think that you have to have some kind of language that is pretty good to solve the problems of gaining confidence that five of you say, or some number, can trust each other in this final attack. And even nowadays, it's difficult. You know, when- I mean, you mentioned Stalin. It's like, why was everybody terrified? Any dictator that takes control. Why is all of us as individuals terrified when you know there's millions of us? That's right. And so like that, we lack the language because our basic psychology of fear overtakes us. Like, who can we talk to? Who can we talk to and not get killed ourselves? Exactly, that's right. But you're, yeah. Do you have this intuition that some kind of language was developing along with this process of beta males taking over? Yes, yes. I mean, once you have sufficient language to be able to have the beta males conspiring to kill the alpha male, then you have selection in favor of cooperation and tolerance, as we spoke about. And at that point, there will be increased ability to communicate and the language will get richer and better and better. So yes, absolutely. Positive feedback loop once you get the situation started. Can you maybe comment on the fact that the full complexity and richness of the human mind through this process, we've been casually saying cooking, fire and beta males leading to cooperation. But how does the beauty of the human mind emerge from all of this? Is there other further steps we need to understand? Or is it as simple as this language emerging from taking over the alpha male and the cooperation? Or am I also over romanticizing how amazing the human mind is? Is it just like one small step in a long journey of evolution? Well, if the beauty of the human mind is the ability of us all to be creative, to explore, that's one kind of beauty. Another kind of beauty is the empathy that we can show. And we think of that as beautiful because it is a kind of rare and special ability compared to the sort of ordinary selfishness that can commonly predominate. I suppose we have to think of different sources for those two types. I suppose a general answer is that there has been selection in favor of bigger brains, which probably in general has been associated with increasing cognitive ability. And as that has happened, the complexity of life has increased because people have more and more complex, highly differentiated strategies in response to each other's more complex, highly differentiated strategies. We get to a point where there is deception and self-deception. There is a manipulation of ideas through stories that we invent and stories that we pass on. I guess all I'm wanting to say is that there is a world of the mind that evolves in response to these platforms that are put there. The platform of increasing brain size and therefore cognitive ability made possible by increased energy supply. The platform of cooperation and tolerance in a world in which there remains a lot of conflict and therefore a need to respond to the conflict and manipulate your allies appropriately. I don't see either kind of beauty as coming sort of totally independently of these things. I don't think there's a selection for staring into the sunset and creating poetry. But I guess sexual selection, males wanting to impress females in different ways will lead to them wanting to- Right, poetry. Well, yes, show off in all the different ways. So all of these are natural consequences of just coming up with strategies of how to cooperate and how to achieve certain ends. So that's just like a natural- Yeah, I mean, we haven't spoken about sexual selection, but that is a really important part of it. Trying to out-compete each other normally without any physical conflict, just in order to be able to be chosen by mates of the opposite sex. And that is certainly a major source of creativity. Okay. So you've studied chimps. You also, all the other relatives, gorillas. What do you find beautiful and fascinating about chimps, about gorillas, about humans? Maybe you can paint the whole picture of that evolutionary, that little local pocket of the evolutionary tree. How are we related? What is the common ancestor? What are the interesting differences? I know I'm asking a million questions, but can you paint a map of what are chimps, gorillas, and humans, like how we're related and what you find fascinating about each? In Africa, straddling the equator, there is a strip of rainforest that relies on the combination of high temperatures and rainfall that you get around the equator. That rainforest goes into about 22 countries. And throughout those countries, you have chimpanzees, although they've gone extinct in two of them. In just a fraction of them, but it was five countries, you've got gorillas where there are mountains. And in one country, on the left bank of the Great Congo River, you have bonobos. So in the African forest, you've got these three African apes, the only African apes, all of which are very similar in much of their way of life. They walk on their knuckles through the forest looking for fruit trees and eating herbs when they can't find fruits. Gorillas represent the oldest chain. So about 10 million years ago, maybe as recently as 8 million years ago, the ancestor of gorillas broke off from the ancestor leading to chimps and bonobos and humans. So they probably remained very similar now to what they were then. They were probably very similar to what they were then. The largest apes living in montane areas and spending more time eating just herbs, stems, not so vitally dependent on fruit. And living in, if it was like the present, groups up to about 50 stable groups with one alpha male who was in charge. Gorillas are wonderfully slow and inquisitive compared to chimps and bonobos. And I had the privilege of spending a week or two with gorillas at Dian Fossey's camp before she was murdered. And I went out with two women, Kelly and Barb, to a particular group. And there was a young female in the group called Simba. And Simba approached us and stared at the two women. And then she came towards me and she very deliberately reached out her knuckles and touched me on the forehead. She was watched in doing this by a young male who was quite keen on her. And he was called Digit. And about five minutes later, Digit stood in front of us on the path. And Kelly was in front of me. And then there was Barb and then there was me. And he came charging down the path and he sidestepped around Kelly and he sidestepped around Barb. And me, he just, I don't know, and me, he just knocked with his arm and sent me flying about five yards into the bushes. And I loved the way that that was a very deliberate response. And I loved the way that Simba had been so interested in me and held my eye. Chimps and bonobos never hold your eye, but gorillas really look as though they're trying to sort of figure out, what are you thinking about? That was a species that goes back for something like 10 million years. In that situation, was there a game being played? Well, I mean, I felt that Digit was telling me, I don't want you messing with Simba. But was Simba using you? Oh, I see. Well, that's a fun idea. I don't see why she should be using me, but you mean testing how strongly Digit was prepared to intervene. Yeah, exactly. All that's come straight out of a sort of adolescent high school playbook. All right, well, that's all. No, no, no, there's nothing wrong with it for that. Yeah, I don't know. I never thought of that. And you never know. It's possible. So, yeah, so, okay. So this is an ancient branch of the evolutionary tree, this gorilla that led to gorillas. Gorillas. So then the next thing that happened on the evolutionary tree was six or seven million years ago, when you have the line between chimps and bonobos on the one hand and humans on the other splitting. And basically what happened is that at that point, a chimp-like ancestor leaves the forest, gets isolated in an area outside the forest and adapts. And that becomes the Australopithecines. And meanwhile, the chimpanzees and bonobo ancestor continues in the forest. And later what happens is that one branch of that crosses the Congo River and becomes the bonobos. That was only about two million years ago, maybe one million years ago. Now, the chimps that remained in the forest throughout this time and occupied all the countries across from West to East Africa now, again, we assume that they're pretty similar to the ones that live nowadays, where there's some variation from West to East. And these are animals that live in social communities of between say 20 and 200. They have a lot of them in one group, but they never come together in a single unit. These are, they share an area, a community territory. And that area is defended by males and within it, females wander and bring up their young independently. And the females are very scared about the possibility that males will be mean to their infants. And in order to avoid them doing that, they do their best to mate with every single male in the group multiple times, as if to give a memory in that male of, yeah, yeah, I reminded you, so I'm not gonna be mean to your baby. So what's wonderful about chimps? Well, as we've spoken about them, they are creative and amazingly human-like, but I love the sort of the quiet moments. And here's one. I've got two chimps who are grooming each other on a day when they are utterly exhausted. They've walked 11 kilometers the day before, up and down hills. And on this particular day, all they do is they get to one tree and they eat from that tree. And other than that, they only walk about 100 yards and they go back to sleep in the nest in which they woke up. So they're utterly exhausted. And they're just eating nonstop because they're trying to recover their energy. And this is Hugh and Charlie. And we think they were probably brothers, though we never actually got the genetic evidence to prove it. Well, I never remember now who it is, but let's say that they both come down from the tree and they're both carrying branches of the food. They're eating actually seeds from these branches. They're both engaged even in the midday sun when they want to come down and shade themselves for a bit on the ground. They're still eating. But then Charlie and Hugh, they're still eating, but then Charlie finishes his branch and he starts grooming Hugh. And Hugh continues eating from his branch. Charlie eventually gets bored with this after a few minutes and he reaches out and he lifts the branch from which Hugh is still taking seeds and puts it over his head and puts it behind his back as far as possible away from Hugh. Hugh doesn't do anything. He just finishes his mouthful and then he turns to Charlie and grooms him. So this very polite way of saying, will you groom me please, has worked. Then Hugh grooms around Charlie's back and around to the right side and then down his arm to a point where he can reach the branch again. And then he picks up the branch and continues. Nonchalantly. Right. Yeah. So in other words, a very sort of simple little strategy, but it just shows the courtesy with which they can treat each other. And the days I love with chimps, so when you see that sort of thing, or when you see mothers just lying in a sunlit patch in the forest with their babies bouncing on top of them, just having a wonderful, peaceful time. And that's what most of their lives are like. So chimpanzees are the species that kind of unites the rest of the apes because a gorilla is in many ways just a big version of a chimpanzee. If you can sort of engineer a chimpanzee in your mind to be bigger, it basically turns into a gorilla. And then bonobos on the left bank of the Congo River are like a domesticated form of a chimpanzee. But obviously humans didn't domesticate them, so they're self-domesticated. They are less aggressive and they show all the marks of domestication that domesticated animals do compared to wild animals in their bones. So they have reduced differences between males and females in which the males are more like females. They have smaller brains, they have shorter faces, smaller teeth and smaller bodies. All the things that domesticated animals show. And bonobos live in this environment in a strikingly peaceful way compared to the chimpanzees. There's no indication that they will have these aggressive kills and enough data now to show that there's a statistical difference in the frequency of which it would happen. And bonobos are famously erotic. The females have very large, the females have enlarged sexual parts which swell to a particularly large size compared to the female chimpanzees. And the females have a lot of interactions with each other in which they excitedly rub their clitorises together and appear to have orgasms. And these occur in the context of some kind of social tension. And they sometimes happen before, they sometimes happen after the social tension, and they seem to be devices, these interactions, for ensuring that everyone's friends and reducing the chances that they're actually going to get into a fight. It's a kind of conflict resolution through sex or some kind of pleasurable sexual experience. Well, it's often characterised as make love, not war. That's right. Make love, not war. Okay. You mentioned to me offline that you have a deep love for nature. If we look at the world today, how can we ensure that the beautiful parts of nature remain a big part of our lives as human beings and in the way we think about it, in the way we also keep it around, preserve it, you know, we keep it part of our minds and part of our world? It's a very difficult question because every time there is a conflict between conservation of a natural habitat and allowing people to get that little bit of extra food for their babies, then naturally the tendency is for the humans to win. And so we have this steady erosion in the face of tremendous efforts to conserve nature. We have a continuing steady erosion of habitats and all the species, and the numbers are always in the wrong direction. Occasionally you get sort of wonderful little examples of something being saved, but the overall trend is clear. And it's very difficult to see how one can ever escape that. Because it's not human, now that we are essentially a single tribe, to want to save an elephant if it means killing 20 humans. So I think the only way in which we can really conserve is if we put tremendous effort into conserving the very best representative species in the most presentive areas of nature. Often this will be the national parks that already exist. And what we have to do is to make them so valuable that actually it is worth it in terms of human survival to be able to keep those sorts of places. And that's the attitude that my colleagues and I have taken in Uganda, where we want to keep the Kibale National Park alive, which has got the largest population of chimpanzees in Uganda, and it's got elephants and wonderful birds and wonderful butterflies and wonderful plants and so on, and visitors, and lots and lots of visitors. It may be that we're going to have to have huge increases in the amount of charges that you pay for ecotourism. And you need to make sure that ecotourism is done right. In other places, you will keep nature there because it's useful for maintaining the climate, bringing rain. Maybe you can in some places convince people of the sheer aesthetics of keeping nature that even over the long term, presidents whose job it is to look for the future of the country, will be persuaded that you can do it for purely aesthetic reasons. But overall, what is required is for people in the rich countries to do much more investment than they have so far in maintaining both the natural places in their own countries and in the tropics. And if you look at Africa, you know, I mean, the population trends are that Nigeria may become the most populous country in the world, I think, within a century. The future of African habitats, you know, it's clear what's going to happen in general. There's going to be a huge conversion towards agricultural land. I heard Ed Wilson speak years ago about the prospect of the entire globe being turned into a single human feedlot. It's going to take a lot to avoid that. He is out there calling for half the earth to be devoted to nature. It's incredibly ambitious and incredibly optimistic. But unless you have really exciting goals, probably nothing will be achieved. Yeah, I mean, there's something to me, like when I visit New York and I see Central Park and then somehow constructed a situation where you preserve this park in the middle, probably some of the most expensive land in the world. The fact that that's possible gives me hope that you can do this kind of preservation at a global scale. Perhaps for just the aesthetic reasons of just valuing the beauty and the beauty and just respecting our origins of having come from the earth. We are so incredibly lucky to have chimpanzees, bonobos and gorillas as our close relatives still living on the earth. You know, we're unlucky that we don't have Australopithecines and other species of homo, but we're still lucky to have those because they are incredibly closely related to us compared to what most animals have. You know, there are many animals that don't have any close relatives to them on the earth. But not only are they relatively close, but they teach us so much about ourselves. You know, the similarities between them and ourselves raise questions that we can then test about the extent to which our own behavioral propensities are derived from the same evolutionary stock as in those great apes. Well, how much is that worth? You know, I mean, we could spend billions going to the Mars to find evidence of bacteria there and that's fascinating too. But we should be spending billions on this earth in order to make sure that we have, I don't know how to say it, you know, substantial, representative populations of these close relatives. Yeah, that we can meet. There's something like space tourism when you go out into space and you look back down on earth. That's to a lot of people, including myself, is worth a lot. But why is that worth a lot? Is because it's humbling and beautiful in the same way that meeting our close evolutionary relatives is humbling and beautiful. Just to know that this is what we come from. This is who we are. Not just for the understanding or the science of it, but just like something about just the beauty of witnessing this. And again, it's both humbling and empowering that this place is fragile and we're damn lucky to be here. Yes, and unfortunately, the problems are incredibly difficult to solve and there is no one solver. It has to happen from a network of potentially cooperating people. But I mean, you're so right about it being daunting to think about what it looks like from space. And I love the view that, Herman Muller expressed of being able to go out from space. And he said, the whole of life would look like a kind of rust on the planet. Yeah, so the aliens were to visit. I'm not sure they would notice the life. They would probably notice the trees or ocean. It's a kind of rust. But let me ask the big, ridiculous philosophical question. How do you know that life is going to be a rust philosophical question? What is the meaning of this rust? What do you think is the meaning of life on earth? What is the meaning of our human intelligent life? Well, I think it's very clear that we have an evolutionary story that is only getting challenged around the edges. We have a very clear understanding of the evolution of life. And the meaning is, we are here as a consequence of materialistic processes that began in our sense, with the establishment of the earth of four and a half billion years ago, whatever it was, and then water and oxygen and so on. And we are the astonishing consequence of the evolution of cells and multicellular organisms. The word random is the wrong word to use unless you understand what it means. It didn't happen by chance, but a lot of random events had to happen to make this possible. And those random events, of course, are the production of appropriate mutations. But the meaning of life is, there is no meaning. The really big mystery of life is, why is there a universe? And that same why propagates itself through the whole of it, through the whole process of it for the emergence of planets, the emergence, first of all, of galaxies, of star systems, of planets, of the proteins required to construct the single cell organisms, and the single cell organism becoming complex organisms, and some of the clever fish crawling out onto the land and the whole of it. And then there's fire, some clever guy or lady invented fire, and then now here we are. It just does seem, speaking as a human, kind of special that we're able to reflect on the whole thing, or the whole- Wonderful story, so much more interesting than the stories produced by religion. Yeah, it is beautiful, but it just seems special that us humans are able to write religions and construct stories, and also do science. That seems kind of amazing. It seems like the universe is such that it creates beings like us that are able to investigate it. And that's why there's this longing for a why. That's just such a beautiful little pocket of complexity created by the universe. It seems like there should be a why, but maybe there's just an infinite number of universes, and this is the one that led to this particular set of humans. Even without an infinite number of universes, I bet there's an infinite number of intelligent beings. Throughout this universe. Yeah, now that we know how many planets have the right sort of conditions, which is what, I can't remember, a lot. It's some significant percentage of all planets. Then there are apparently billions of planets. Things happen so quickly on Earth. Once you've got water, then you've got life. And it did not take long for life to evolve in the big scheme of things. And if you think, you look out there, say there's a nearly infinite number of intelligent civilizations, one dimension you can look at is the proclivity to violence they have. And it's interesting to think what level of violence they have. It's interesting to think what level of violence is useful for extending the life of a civilization. So we have a particular set of violence in our history. Maybe being too peaceful is a problem in the early days. Maybe being too violent, quite obviously, is a problem. So you look at viruses. What kind of viruses on Earth propagate and succeed? If you're too deadly, that's a big problem. If you're not deadly enough, that's also a problem. So that is a fascinating exploration of- I don't see any evidence. I don't see where you're coming from when you say that being too peaceful is a problem. Well, because, so I'll say it this way. Death is a way to get rid of suboptimal solutions. So violence- But there's lots of ways to die without violence. Right. To me, death in itself is violence. And you can, I mean, a lot of people that talk about, for example, longevity and disease and all that kind of stuff, they see death is the way they talk about it. And it's interesting to philosophically think of it that way. It's just death is, it's like mass murder that's happening. And it's like people that try to, from a biological perspective, help extend life, they see that you're helping the most, the biggest atrocity in the history of human civilization from their perspective is not allocating all our resources to solving death, right? Because death is a kind of violence. It is a kind of murder that we're allowing to be committed on us by nature. And so the flip side of that is death makes way for new life, for new ideas. And so that- Yes, but that's got nothing to do with peace versus war. I mean, you have animals that are very, very peaceful, but they evolve just in the same way as other animals do. They just don't do it with death caused by violence. And violent death is premature death, surely. I mean, I don't mind about people dying. What I mind about is people dying in their youth. In middle age. Prematurely, but some people would say all death is premature. It certainly feels that way. It's died too soon. Anyone who's ever died, died too soon. Yeah, well, I mean, if we can become like sequoias and live for hundreds of years or thousands of years, that'd be great. Do you ponder your own mortality? Are you afraid of death? I don't think I'm afraid of it. I'm reconciled to the fact it's gonna happen. I just feel frustrated because I enjoy life, and I don't want to leave the party. Yeah, it's kind of a fun party. I don't wanna leave the party either. So however we got here, we made one heck of an awesome party. And you're right. Having a party with a little bit less violence in it is an even more fun party. Richard, I'm deeply honored that you spent time with me today. Your work is amazing. It includes some of the deepest thinking about our human history and the nature of human civilization. So again, thank you so much for talking today. It's an honor. No, thanks for your great questions. It was a really fun conversation. Thanks for listening to this conversation with Richard Wrangham. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Jane Goodall. The greatest danger to our future is apathy. Thank you for listening and hope to see you next time.

https://youtu.be/YJF01_ztxwY

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Natalya Bailey: Rocket Engines and Electric Spacecraft Propulsion | Lex Fridman Podcast #157

The following is a conversation with Natalia Bailey, a rocket scientist and spacecraft propulsion engineer previously at MIT, and now the founder and CTO of Axion Systems, specializing in efficient space propulsion engines for satellites and spacecraft. So these are not the engines that get us from the ground on Earth out to space, but rather the engines that move us around in space once we get out there. Quick mention of our sponsors. Munkpack, low carb snacks, Four Sigmatic mushroom coffee, Blinkist, an app that summarizes books, and Sun Basket, meal delivery service. So the choices, snacks, caffeine, knowledge, or a delicious meal. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. As a side note, let me say something about Natalia's story. She has talked about how when she was young, she would often look up at the stars and dream of alien intelligences that one day we could communicate with. This moment of childlike cosmic curiosity is at the core of my own interest in space and extraterrestrial life, and in general, in artificial intelligence, science, and engineering. Amid the meetings and the papers and the career rat race and all the awards, let's not let ourselves lose that childlike wonder. Sadly, we're on Earth for only a very short time. So let's have fun solving some of the biggest puzzles in the universe while we're here. If you enjoy this thing, subscribe on YouTube, review it on Apple Podcasts, follow on Spotify, support it on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Natalia Bailey. You said that you spent your whole life dreaming about space and also pondering the big existential question of whether there is or isn't intelligent life, intelligent alien civilizations out there. So what do you think? You think there's life out there? Intelligent life? Intelligent life, that's trickier. I think looking at the likelihood of a self-replicating organism, given how much time the universe has existed and how many stars with planets, I think it's likely that there's other life. Intelligent life, I'm hopeful, you know, I'm a little discouraged that we haven't yet been in touch. Allegedly, I mean, it's also- In our dimensions and so on, yeah. It's also possible that they have been in touch and we just haven't, we're too dumb to realize they're communicating with us. In whichever, it's this Carl Sagan idea that they may be communicating at a time scale that's totally different. Like their signals are in a totally different time scale or in a totally different kind of medium of communication. It could be our own, it could be the birth of human beings, like that, whatever the magic that makes us who we are, the collective intelligence thing, that could be aliens themselves, that could be the medium of communication. Like the nature of our consciousness and intelligence itself is the medium of communication. And like being able to ask the questions themselves, I've never thought of it that way. Like actually, yeah, asking the question whether aliens exist might be the very medium by which they communicate. It's like they send questions. So some of this like collective emergent behavior is the signal. Is the signal, yeah. So- It's interesting, yeah. Because maybe that's how we would communicate. If you think about it, if we were way, way, way smarter, like a thousand years from now, we somehow survive, like how would we actually communicate? In a way that's like, if we broadcast the signal, and then it could somehow like percolate throughout the universe, like that signal having an impact on- Multiverse. Multiverse, of course, that would have a signal, an effect on the most possible, the highest number of possible civilizations, what would that signal be? It might not be like sending a few stupid little hello world messages. It might be something more impactful. It's almost like impactful in a way where they don't have to have the capability to hear it. It like forces the message to have an impact. Right. My train of thought has never gone there, but I like it. And also somewhere in there, I think it's implied that something travels faster than the speed of light, which I'm also really hopeful for. Oh, you're hopeful. Are you excited by the possibility that there's intelligent life out there? Sort of, you work on the engineering side of things. It's this very kind of focused pursuit of moving things through space efficiently. But if you zoom out, one of the cool things that this enables us to do is find, forget even intelligent life, just life on Mars or on Europa or something like that. Does that excite you? Does that scare you? Oh, it's very exciting. I mean, it's the whole reason I went into the field that I'm in is to contribute to building the body of knowledge that we have as a species. So very exciting. Do you think there's life on Mars? Like no longer, well, already living, but currently living, but also no longer living, like that we might be able to find life as some people suspect, basic microbial life. I'm not so sure about in our own solar system. And I do think it might be hard to untangle if we somehow contaminated other things as well. So I'm not sure about this close to home. That'd be really exciting. Yes. Do you think about the Drake equation much of like? That was what, yeah, what got me into all of this, yeah. Yeah, because one of the questions is how hard is it for life to start on a habitable planet? Like if you have a lot of the basic conditions, not exactly like Earth, but basic Earth-like conditions, how hard is it for life to start? And if you find life on Mars or find life on Europa, that means it's way easier. That's a good thing to confirm that if you have a habitable planet, then there's going to be life. And that like immediately, that would be super exciting because that means there's like trillions of planets with basic life out there. Though of all the planets in our solar system, Earth is clearly the most habitable. So I would not be discouraged if we didn't find it on another planet in our solar system. True, and again, that life could look very different. It's habitable for Earth-like life, but it could be totally different. I still think that trees are quite possibly more intelligent than humans, but their intelligence is carried out over a time scale that we're just not able to appreciate. Like they might be running the entirety of human civilization, and we're just like too dumb to realize that they're the smart ones. Maybe that's the alien message. It's in the trees. It's in the trees. Yeah, it's not in the monolith in the Utah desert. It's in the trees. Right, yeah. So let's go to space exploration. How do you think it would get humans to Mars? I think SpaceX and Elon Musk will be the ones that get the first human setting foot on Mars, and probably not that long from now from us having this conversation. You know, maybe we'll inflate his timeline a little bit, but I tend to believe the goals he sets. So I think that will happen relatively soon. As far as when and what it will take to get humans living there in a more permanent way, you know, I have a glib answer, which is when we can invent a time machine to go back to the early Cold War, and instead of uniting around sending people to the moon, we pick Mars as the destination. So really, I say that because there's nothing truly scientifically or technologically impossible about doing that soon. It's more, you know, politically and financially, and those are the obstacles, I think, to that. Well, I wonder of when you colonize with, you know, more than, I say, five people on Mars, you have to start thinking about the kind of, like, rules you have on Mars. And speaking of the Cold War, who gets to own the land? You know, you start planting flags, and you start to make decisions. And like SpaceX says this night, it's probably a little bit trolly, but they have this nice paragraph in their contracts where it's like, it talks about that, like, human governments on Earth, or Earth governments have no jurisdiction on Mars. Like, the rules, the Martians get to define their own rules. It sounds very much like the founding fathers for this country, that's the kind of language. It's interesting that that's in there, and it makes you think, perhaps, that needs to be leveraged. Like, you have to be very clever about leveraging that to create a little bit of a Cold War feeling. It seems like we humans need a little bit of a competition. Do you think that's necessary to succeed in to get the necessary investment, or can the pure pursuit of science be enough? No, I think we're seeing right now the pure pursuit of science, I mean, that results in pretty tiny budgets for exploration. There has to be some disaster impending doom to get us onto another planet in a permanent way. I don't know, financially, I just don't know if the private sector can support that, but I don't wish that there is some catastrophe coming our way that spurs us to do that. Yeah, I'm unsure what the business model is for colonizing Mars. Yeah, exactly. Yeah, like, there is, we'll talk about satellites, there's probably a lot of business models around satellites, but there's not enough short-term business. I guess that's how business works. Like, you should have a path to making money in like the next 10 years. Well, and maybe even more broadly, and looping back to something we said earlier, I don't know that getting humans off this planet and spreading like bacteria is what we're supposed to be doing in the first place. So maybe we can go, but should we? And I'm probably an unusual person for thinking that in my industry because humans want to explore, but I almost wonder, are we putting unnecessary obstacles, like we're very finicky biological things in the way of some more robotic or more silicon-based exploration? And yeah, do we need to colonize and spread? I'm not sure. What do you think is the role of AI in space? Do you, in your work, again, we'll talk about it, but do you see more and more of the space vehicles, spacecraft being run by artificial intelligence systems? More than just like the flight control, but like the management? Yeah, I don't have a lot of color to the dreams I have about way in the future and AI, but I do think that removing, it's hard for humans to even make a trip to Mars, much less go anywhere farther than that. And I think we'll have more, again, I'm probably unusual in having these thoughts, but perhaps be able to generate more knowledge and understand more if we stop trying to send humans and instead, I don't know if we're talking about AI in a truly artificial intelligence way or AI as we kind of use it today, but maybe sending a Petri dish or two of like stem cells and some robotic handlers instead if we still need to send our DNA because we're really stuck on that. But if not, maybe not even that Petri dish. So I see, I think what I'm saying is, I see a much bigger role in the future of AI for space exploration. It's kind of sad to think that, I mean, I'm sure we'll eventually send a spacecraft with efficient propulsion, like some of the stuff you work on, out that travels just really far with some robots on it and with some DNA in a Petri dish. And then human civilization destroys itself and then there'll just be this floating spacecraft that eventually gets somewhere or not. That's a sad thought, like this lonely spacecraft just kind of traveling through space and humans are all dead. Well, it depends on what the goal is, right? I don't know what the goal is. Another way to look at it is we've preserved, it's like a little time capsule of knowledge, DNA, that will outlive us. Well, that's beautiful. Yeah. That's how I sleep at night. So you also mentioned that you wanted to be an astronaut. Yes. So even though you said you're unusual in thinking like, it's nice here on earth and then we might wanna be sending robots up there, you wanted to be a human that goes out there. Would you like to one day travel to Mars? If it becomes sort of more open to civilian travel and that kind of thing. Like are you, like vacation wise, like if we're talking vacations, would you like to vacation on earth or vacation on Mars? I wish that I had a better answer, but no. I wanted to be an astronaut because I, first of all, I like working in labs and doing experiments and I wanted to go to like the coolest lab, the ISS, and do some experiments there. That's being decommissioned, which is sad, but there will be others, I'm sure. The ISS is being decommissioned? Yes, I think by 2025, it's not going to be in use anymore. But I think there are other, there are private companies that are going to be putting up stations and things. So it's primarily like a research lab, essentially. Yes. A research lab in space. That's a cool way to say it. It's like the coolest possible research lab. That's where I wanted to go. And now though, my risk profile has changed a little bit. I have three little ones and I won't be in the first thousand people to go to Mars, let's put it that way. Yeah, earth is kind of nice. We have our troubles, but overall, it's pretty nice. Again, it's the Netflix. Okay, let's talk rockets. How does a rocket engine work or any kind of engine that can get us to space or float around in space? The basic principle is conservation of momentum. So you throw stuff out the back of the engine and that pushes the rocket and the spacecraft in the other direction. So there are two main types of rocket propulsion. The one people are more familiar with is chemical because it's loud and there's fire. And that's what's used for launch and is more televised. So in those types of systems, you usually have a fuel on an oxidizer and they react and combust and release stored chemical energy. And that energy heats the resultant gas and that's funneled out the back through a nozzle directed out the back. And then that momentum exchange pushes the spacecraft forward. Is there an interesting difference between liquid and solid fuel in those contexts? They're both lumped in the same. So chemical just means that the release of energy from those bonds essentially. So a solid fuel works the same way. And the other main category is electric propulsion. So instead of chemical energy, you're using electrical energy, usually from batteries or solar panels. And in this case, the stuff you're pushing out the back would be charged particles. So instead of combustion and heat, you end up with charged particles and you force them out the back of the spacecraft using either an electrostatic field or electromagnetic. But it's the same momentum exchange and same idea, stuff out the back and everything else goes forward. Cool, so those are the big two categories. What's the difference maybe in like the challenges of each, the use cases of each and how they're used today, the physics of each and where they're used, all that kind of stuff. Anything interesting about the two categories that distinguishes them besides the chemical one being the big sexy flames and. Yeah, fire. Fire, yeah. Chemical is very well understood. In its simplest form, it's like a firework. So it's been around since 400 BC or something like that. So that even the big engines are quite well understood. I think one of the last gaps there is probably what exactly are the products of combustion? Are modeling abilities kind of fall apart there because it's hot and gases are moving and you end up kind of having to venture into lots of different interdisciplinary fields of science to try to solve that. And that's quite complex, but we have pretty good models for some of the more like emergent behaviors of that system anyways. But that's, I think one of the last unsolved pieces. And really the kind of what people care about there is making it more fuel efficient. So the chemical stuff, you can get a lot of instantaneous thrust, but it's not very fuel efficient. It's much more fuel efficient to go with the electric type of propulsion. So that's where people spend a lot of their time is trying to make that more efficient in terms of thrust per unit of fuel. And then there's always considerations like heating and cooling. It's very hot, which is good if it heats the gases, but bad if it melts the rocket and things like that. So there's always a lot of work on heating and cooling and the engine cycles and things like that. And then on electric propulsion, I find it like much more refreshingly poorly understood. Lots more mysteries. Yeah, I think so. One of the classes I took in college spent, we spent 90% of the class on chemical propulsion and then the last 10% on electric. And the professor said like, we only sort of understand how it works, but it works kind of. And it's like, that's interesting. Yeah, and even an ion engine, which is probably one of the most straightforward because it's just an electrostatic engine, but it has this really awesome combination of quantum mechanics and material science and fluid dynamics and electrostatics. And it's just very intriguing to me. First of all, can you actually zoom out even more? Because you mentioned ion propulsion engine is a subset of electric. So like maybe, is there a categories of electric engines? And then we can zoom in on ion propulsion. Yes, so sure. There's the two most kind of conventional types that have been around since the 60s are ion engines and Hall thrusters. And ion engines are a little bit simpler because they don't use a magnetic field for generating thrust. And then there are also some other types of plasma engines, but that don't fit into those two categories. So just kind of other plasma like a VASIMR engine, which we could get into. And then those are probably the main three categories that would be fun to talk about. Oh, and then of course, the category of engine that I work on, which has a lot of similarities to an ion engine, but could be considered its own class called a colloid thruster. Colloid, cool. Okay, so what is an ion propulsion ion engine? Okay, so in an ion engine, you have an ionization chamber, and you inject the propellant into that chamber. And this is usually a neutral gas like xenon or argon. So you inject that into the chamber, and you also inject a stream of really hot high energy electrons. And everything's just moving around very randomly in there. And the whole goal is to have one of those electrons collide with one of those neutral atoms and turn it into an ion. So kick off a secondary electron, and now you have- Plasma. Yes. Okay. And now you have- Okay. And now you have a charged xenon or argon ion and more electrons and so on. And then some fraction of those ions will happen to make it to this downstream electric field that we set up between two grids with holes in them. And in terms of area, the same amount of those ions also make runs into the walls and lose their charge. And that's where some of the inefficiencies come in. But the very lucky few make it to those holes in that grid. And there are two grids actually, and you apply a voltage differential between them. And that sets up an electric field. And a charged particle in an electric field creates a force. And so those ions are accelerated out the back of the engine and the reaction force is what pushes the spacecraft forward. So if you're following along and tallying these charges, now we've just sent a positive beam of ions out the back of the spacecraft. And for our purposes here, the spacecraft is neutral. So eventually those ions will come back and hit the spacecraft because it's a positive beam. So you also have to have an external cathode producer of electrons outside the engine that pumps electrons into that beam and neutralizes that. So now it's net neutral everywhere and it won't come back to the spacecraft. So that's an ion engine. What temperature are we talking about here? So in terms of like the chemical base engines, those are super hot. You mentioned plasma here. How hot does this thing get? I mean, is that an interesting thing to talk about in a sense that, is that an interesting distinction or is heat, I mean, it's all gonna be hot? No, so it's important, especially for some of these smaller satellites people are into launching these days. So it's important because you have the plasma, but also those high energy electrons are hot. And if you have a lot of those that are going into the walls you do have to care about the temperature. So I'm having trouble remembering off the top of my head. I think they're at like 100 electron volts in terms of the electron energy. And then I'd have to remember how to convert that into Kelvin. Can you stick your hand in it? Not move the temperature. Not recommended, yeah. So what's a colloid engine? So the same rocket people that came up with with these ideas for electric propulsion probably in the middle of last century also realized that there's one more place to get charged particles from if you're going to be using electric propulsion. So you can take a gas and you can ionize it, but there are also some liquids, particularly ionic liquids, which is what we use, that you also can use as a source of ions. And if you have ions and you put them in a field, you generate a force. So they recognize that, but part of being able to leverage that technique is being able to kind of manipulate those liquids on a scale of nanometers or very few microns. So the diameter of a human hair or something like that. And in the 50s, there was no way to do that. So they wrote about it in some books and then it kind of died for a little bit. And then with silicon MEMS computer processors and when foundry started becoming more ubiquitous and my advisor started at MIT, kind of put those ideas back together and was like, hey, actually there's now a way to build this and bring this other technique to life. And so the way that you actually get the ions out of those liquids is you put the liquid in, again, a strong electric field and the electric field stresses the liquid and you keep increasing the field and eventually the liquid will assume a conical shape. It's when the electric field pressure that's pulling on it exactly balances the liquid's own restoring force, which is its surface tension. So you have this balance and the liquid assumes a cone when it's perfectly balanced like that. And at the tip of a cone, the radius of curvature goes to zero right at the tip and the radius, sorry, the electric field right at the tip of a sharp object would go to infinity because it goes as one over the radius and one over the radius squared. And instead of the electric field going to infinity and maybe like generating a wormhole or something, a jet of ions instead starts issuing from the tip of that liquid. So the field becomes strong enough there that you can pull ions out of the liquid. What is the liquid? We're talking about, or is it there's a bunch of different ones? You can do it with different types of liquids. It depends on how easily you can free ions from their neighbors and if it has enough surface tension so that you can build up a high enough electric field. But what we use are called ionic liquids and they're really just positive, they're very similar to salts but they happen to be liquid over a really wide range of temperatures. This sounds like really cool. Okay, so how big is the cone are we talking? What's the size of this cone that generates the ions? So if you have a cone that's emitting pure ions, I can't remember if it's the radius or diameter, but that emission is happening from, of that cone is something like 20 nanometers. Oh, I was imagining something slightly bigger. But so like this is tiny, tiny. Yes. Hence the only being able to do it recently. Yeah, that's right. So this is all controlled by a computer, I guess. Or like, how do you create a cone that generates ions at a scale of nanometers exactly? So the kind of main trick to making this work is that physically we manufacture hundreds or thousands of sharp structures and then supply the liquid to the tips. So that does a few things. It makes sure that we know where the ion beams are forming so we can put holes in the grid above them to let them actually leave instead of hitting. Cool. But it also reduces the actual field we have, the voltage we have to apply to create that field because the field will be much stronger if we can already give the liquid a tip to form on. And those tips we form have radii of curvature on the order of probably like single microns. So we are working at a little bit larger scale, but once we create that support and the electric field can be focused at that tip, then the tiny little cone can form on top of that. So wait, so there's something in the, there's already like a hard material that like gives you the base for the cone and then you're pouring like liquid over it, whatever that happens. From the bottom, yeah, it's porous. So we actually supply it from the back of the chip and then it wicks. And then liquid forms on top on that structure. And then you somehow make it like super sharp, the liquid, so the ions can leave. And then we've applied that field to get those ions and that same field then accelerates them. That's awesome. And there's like a bunch of these? Yeah, I should have brought something. So we- You could just pretend that you have some nanometer cones on the table here. So actually, you know, kind of about this scale, we build, we call them thruster chips and it's just a convenient form factor and it's a square centimeter. And on each square centimeter today, we have about 500 of the actual physical, we call them emitters, those physical cones. And we're working on increasing that by a factor of four in the coming months. In size or in the density? In number, in the density, the number of emitters within the same square centimeter chip. So that thing, because I think I've seen pictures of you with like a tiny thing in your hand. That must be the, okay. So that's an engine. So that is kind of the ionization chamber and thrust producing part of it. What's not shown, you know, in that picture is the propellant tank. So we can keep supplying more and more of the liquid to those emission sites. And then we also provide a power electronic system that talks to the spacecraft and turns our device on and off. So that's the colloid engine. That's the core of the colloid engine. It's, the way I've been talking about it, it's more of ion electrospray. Colloid tends to mean like liquid droplets coming off of the jet. But if you make smaller and smaller cones, you get pure ions. So we're kind of like a subset of colloid, yes. What aspects of this, you said that it's been full of mystery from the physics perspective. What aspects of this are understood and what are still full of mystery? Yeah, recently we've been understanding the kind of instabilities and stable regimes of how much liquid do you supply and what field do you apply and why is it flickering on and off or why does it have these weird behaviors? So that's, in the past just couple years, that's become much more understood. I think the two areas that come to mind as far as not as well understood are the boundary between, you have, we actually use kind of big molecular ions and if you're looking at the molecular scale, you have some ions that you've extracted and they're in this electric field. One ion, it's a big molecule, it's getting energy from the electric field and some of that energy is going into the bonds and making it vibrate and doing weird things to it. Sometimes it breaks them apart. And then zooming out to the whole beam, the beam has some behaviors as this beam of ions and there's a big gap between what are those, how do you connect those and how do we understand that better so that we can understand the beam performance of the engine. Is that a theory question or is it an engineering question? Theory, definitely. Axion is a startup and we're more in the business of building and testing and observing and characterizing and we're not really diving much into that theory right now. Okay, zooming out a little bit on the physics, apologize for the way too big of a question, but to you from either, you mentioned Axion as more of sort of an engineering endeavor, right? But from a perspective of physics in general, science in general, or the side of engineering, what do you think is the most, to you, like beautiful and captivating and inspiring idea in this space? In this space, and then I'm gonna zoom out a little bit more, but in this space, I keep butting up against material science questions. So I, over the past 10 years, I feel like every problem or interesting thing I want to work on, if you dig deep enough, you end up in material science land, which I find kind of exciting and it makes me want to dig in more there. And I was just, even for our technology, when we have to move the propellant from the tank to the tip of the emitters, we rely a lot on capillary action and you're getting into wetting and surface energies. At a scale of like nano. Yeah, I mean, if you look further, it's quantum too, but it all is, you know, I would. Wait, a capillary action at the quantum level? Yeah, so I would, it all comes back to me, to, you know, material science. There's so much we don't understand at these sizes. And I find that inspiring and exciting. And then more broadly, you know, I remember when I learned that the same equation that describes flow over an airfoil is used to price options, the Black-Scholes equation. And it's, you know, just a partial differential equation, but that kind of connectedness of the universe, you know, I don't want to use options pricing and the universe in the same, but you know what I mean, this connectedness I find really magical. Yeah, the patterns that mathematics reveals seems to echo in a bunch of different places. Yes. Yeah, there's just weirdness. It's like, it really makes you think, I think, through definitely living in a simulation, like whoever programmed it. I like that that's your conclusion. Is using, I don't know, is using like shortcuts to program it. Like they didn't, they're just copying and pasting some codes for the different parts. Yeah, think of something new or just paste from over there. They won't notice. My conclusion from that was, I'm gonna go interview for a finance job. So I had like a little detour. That's the backup option. So in terms of using, call it engines, what's an interesting difference between a propulsion of a rocket from earth, once you're standing in the ground to orbit, and then the kind of propulsion necessary for once you get out to orbit or to like deep space to move around? Yes, the reason you can't use an engine like mine to get off the ground is, you know, the thrust it generates is instantaneous thrust is very small, but if you have the time and can accumulate that acceleration, you can still reach speeds that are very interesting for exploration and even for missions with humans on them. So an interesting direction I think we need to go as humans exploring space is the power supplies for electric propulsion are limiting us in that, you know, solar panels are really inefficient and bulky and batteries, I don't know when anybody's ever gonna improve battery technology. I know a lot of people that work on that. And nuclear power, we could have a lot more powerful electric propulsion systems, so they would be extremely fuel efficient, but more instantaneous thrust to do more interesting missions if we could start launching more nuclear systems. So like something that's powered, nuclear powered, that's the right way to say it. Yeah. But is in a small enough container that could be launched? Yeah, so I mean, as a world, we do launch spacecraft with nuclear power systems on board, but size is one consideration. It hasn't been a big focus, so the reactors and the heaters and everything are bulky, and so they're really only suitable for some of the much bigger interplanetary stuff. So that's one issue, but then it's a whole like rat's nest of political stuff as well. I heard, I think Elon described, or somebody, but I think it was Elon that described the eVTOL, like electrical vertical takeoff and landing vehicle. So basically saying rockets, obviously Elon is interested in electric vehicles, right? But he said that rockets can't, in the near term, it doesn't make sense for them to be electrical. What, do you see a world with the rockets that we use to get into orbit are also electric-based? It's possible. You can produce the thrust levels you need, but you need this, a much bigger power supply, and I think that would be nuclear. And the only way people have been able to launch them at all is that they're in a 100 times redundancy safe mode while they're being launched, and they're not turned on until they're farther off. So if you were to actually try to use it on launch, I think a lot of people would still have an issue with that, but someday. It's an interesting concept, nuclear. It seems like people, like everybody that works on nuclear power has shown how safe it is as a source of energy. I know, right? And yet we are, seem to be, I mean, based on the history, based on the excellent HBO series, I'm Russian with the Chernobyl, it seems like we have our risk estimation about this particular power source is drastically inaccurate. But that's a fascinating idea that we would use nuclear as a source for our vehicles, and not just in outer space. That's cool, I'm gonna have to look into that. That's super interesting. Well, just last year, Trump eased up a little bit on the regulations, and NASA, and hopefully others, are starting to pick up on the development. So now is a good time to look into it, because there's actually some movement. Is that a hope for you, to explore different energy sources that the entirety of the vehicle uses something like, like the entirety of the propulsion systems for all aspects of the vehicle's life travel is the same, or electric? Is it possible for it to be the same? Like the core load engine being used for everything? You could, and you would have to do it in the same way we do different stages of rockets now, where once you've used up an engine, or a stage, you let it go, because there's really no point in holding onto it. So I wouldn't necessarily wanna use the same engine for the whole thing, but the same technology, I think, would be interesting. Okay, so it's possible, all right. But in terms of- Yeah, it comes down to the power source. The power source, that's really interesting. But for the current power sources, and its current use cases, what's the use case for electric? Like the core load engine, can you talk about where they're used today? Sure, so chemical engines are still used quite a bit once you're in orbit, but that's also where you might choose instead to use an electric system. And what people do with them, and this includes the ion engines, and Hall thrusters, and our engine, is basically any maneuvering you need to do once you're dropped off. There's, even if your only goal was to just stay in your orbit and not move for the life of your mission, you need propulsion to accomplish that, because the Earth's gravity field changes as you go around in orbit and pulls you out of your little box. There are other perturbations that can throw you off a bit. And then, most people want to do things a little bit more interesting, like maneuver to avoid being hit by space debris, or perhaps lower their orbit to take a higher resolution image of something and then return. At the end of your mission, you're supposed to responsibly get rid of your satellite, whether that's burning it up, but if you're in geo, you want to push it higher into graveyard orbit. What's geo, what's graveyard? So low Earth orbit, and then geosynchronous orbit, or geostationary orbit. And there's a graveyard? Yeah, so those satellites are at like 40,000 kilometers, so if they were to try to push their satellites back down to burn up in the atmosphere, they would need even more propulsion than they've had for the whole lifetime of their mission. So instead, they push them higher, where it'll take a million years for it to naturally deorbit. So we're also cluttering that higher bit up as well, but it's not as pressing as LEO, which is low Earth orbit, where more of these commercial missions are going now. Well, so how hard is the collision avoidance problem there? You said some debris and stuff, so how much propulsion is needed? How much is the life of a satellite is just like, oh crap, trying to avoid little things down there? I think one of the recent rules of thumb I heard was per year, some of these small satellites are doing like three collision avoidance maneuvers. So that's not too bad. Yeah, but it's not zero. And it takes a lot of planning and people on the ground, and none of that really, I don't think right now, is autonomous. Oh, that's not good. Yeah, and then we have a lot of folks taking advantage of Moore's law and cheaper spacecraft, so they're launching them up without the ability to maneuver themselves, and they're like, well, I don't know, just don't hit me. And three times a year, that could become affordable if it's like, if it gets hit, maybe it won't be damaged kind of thing, that kind of logic. Affordable in that instead of launching one satellite, they'll launch 20 small ones. Yeah, so if one gets taken out, that's okay, but the problem is that one good-sized satellite getting hit, that's like a ballistic event that turns into 10,000 pieces of debris that then are the things that go and hit the other satellites, yeah. So do you see a world where, in your sense, in your own work, and just in the space industry in general, do you see that people are moving towards bigger satellites or smaller satellites? Is there going to be a mix? Like, what's, and what are we talking, what does it mean for a satellite to be big and small? What size are we talking about? So big, the space industry, prior to, I don't know, 1990, I guess the bulk of, the majority of satellites were the size of a school bus and cost a couple billion dollars. And now, our first launches were on satellites the size of shoeboxes that were built by high school students. So that's very different, to give you the two ends of the spectrum. Big satellites will, I think they're here to stay, at least as far as I can see, into the future. For things like broadcasting, you want to be able to, you know, broadcast to as many people as possible. You also can't just go to small satellites and say Moore's Law for things like optics. So if you have an aperture on your satellite, you know, that just, that doesn't follow Moore's Law. That's different. So it's always gonna be the size it will be, you know, unless there's some new physics that comes out that I'm not aware of. But if you need a resolution and you're at an altitude, that kind of sets the size of your telescope. But because of Moore's Law, we are able to do a lot more with smaller packages, and with that comes more affordability and opening up access to space to more and more people. Well, what's the smallest satellite you've seen go up there? What are the smallest, you said shoeboxes. Yeah, so I think, you know, the smallest, the smallest common form factor can fit a softball inside. So that's 10 centimeters on each side. But then there are some companies working on, you know, fractions of that, even. And they're doing things like IoT type applications. So it's very low, you know, bandwidth type things. But they're finding some niches for those. You mean like there's a business, there's a thing to do with them? Yes, these are. What do you do with a small satellite like that? You can, you know, track a ship going across the ocean. Like if you need to, if you're just pinging something, you know, you can handle that amount of data. And those latencies and so on. You have to have propulsion on that. You have to have a little engine. No, those are just, you know, letting fall out of the sky. Okay. Yeah. But what, so what kind of satellites would you equip a colloid engine on? Anything that's bigger than probably about 20 kilograms. Anything that needs to stay up for more than a year. Or anything somebody spent more than like 100K to build are kind of the ways I would think about it. That's a lot of use cases. What's a small sat? Like what category? Small sat's actually very big. I think it's like 700 kilograms or, pity my microphone, maybe a thousand kilograms down to 200 kilograms. People have their own kind of definitions of how they break them up. But small sat is still quite large. And then it's kind of also applied as a blanket term for anything that's not a school bus size satellite. So we need to get our jargon straight in the industry. So what, do you see a possible future where, there's a few thousand satellites up there now, a couple of thousand of them functioning. Do you see a future where there's like millions of satellites up in orbit? Or forget millions, tens of thousands. Which just seems like we're in the natural trajectory of the way things are going now is going. Tens of thousands, yes. The two buckets of applications, one is imaging and the other is communication. So imaging, I think that will plateau because one satellite or one constellation can take an image or a video and sell it to infinity customers. But if you're providing communications like broadband internet or satellite cell or something like that, satellite phone, you're limited by your transponders and so on. So to serve more people, you actually need more satellites. And perhaps at the rate our data consumption and things are going these days, yeah, I can see tens of thousands of satellites. Can I ask you a ridiculous question? Yes. So I've recently watched this documentary on Netflix about flat earthers, the people that believe in a flat Earth. As somebody who develops propulsion systems for satellites and for spacecraft, what's, to use the most convincing evidence, that the Earth is round? Probably some of the photos taken from the moon. Photos from the moon? Okay, so it's not from the satellite space. Yeah, I think seeing that perspective, maybe I'm answering too personally because I really love those photos. Because they're beautiful, yeah. I really like the ones that show the moon and the lunar lander and they're taken a little bit farther back. So you see Earth and first you're like, wow, that's tiny and we're insignificant and that's kind of sad. But then you see this really cool thing that we landed on another planetary body and you're like, oh, okay. Can you actually see Earth? I don't know if I remember this. Yeah, I'll send you that picture. Because I love the pictures or videos of just Earth from orbit and so on. Right, yes. So that's really beautiful. That's like a perspective shifter. That's the pale blue dot, right? It probably appears tiny. Yeah, and just that juxtaposition of the insignificance but we built this. Really cool thing. I just love that. Take the picture. Yeah. Oh, that'd be cool. I personally love the idea of humans stepping on Mars. I'm such a sucker for the romantic notion of that and being able to take pictures from Mars like so. So you would go? I would be, what did you say? You said you wouldn't be in the first 1000. Not in the first 1000. 1000, which it's funny because to me that's brave to be in the first million. I think when the Declaration of Independence was signed in the United States, that was like two million people. So I would like to show up when they're signing those documents. Okay. So maybe the two million. Oh, that's an interesting way to think of it. Because then we're participating as citizenry and defining the direction. So it's not the technical risk. You just don't want to show up somewhere that's like America before. Yeah, because from a psychological perspective, it's just gonna be a stressful mess as people have studied, right? It's like, most likely the process of colonization looks like basically a prison. Like you're in a very tight enclosed space with people. And it's just a really stressful environment. How do you select the kind of people that will go? And then there'll be drama. There's always drama. And I just want to show up when there's some rules. But I mean, it depends. So I'm not worried about the health and the technical difficulties. I'm more worried about the psychological difficulties. And also just not being able to tweet. Like, what are you gonna, how are you? There's no Netflix. So yeah, maybe not in the first million, but the first hundred thousand. It's exciting to define the direction of a new, like how often do we not just have a revolution to redefine our government as smaller countries are still doing to this day. But literally start over from scratch. There's just our financial system. It could be like based on cryptocurrency. You could think about like how democracy, you know, we have now the technology that can enable pure democracy, for example, if we choose to do that. Yeah. As opposed to representative democracy, all those kinds of things. So we talked about two different forms of propulsion, which are super exciting. So the chemical based, that's doing pretty well. And then the electric based is, are there types of propulsion that might sound like science fiction right now, but are actually within the reach of science in the next 10, 20, 30, 50 years that you kind of think about, or maybe even within the space of even just like, like even ion engines, is there like breakthroughs that might 10X the thing, like really improve it? So, you know, the real game changer would be propellant-less propulsion. And so every couple of years you see a new, now a startup or a researcher comes up with some contraption for producing thrust that didn't require, you know, we've been talking about conservation of momentum, mass times velocity out the back. Mass times velocity forward. Yes, exactly. And you have to, you know, carry that up with you or find it on an asteroid or harvest it from somewhere if you didn't bring it with you. So not having to do that would be, you know, one of the ultimate game changers. And I, you know, unless there are new types of physics, I don't know how we do it, but it comes up often. So it's something I do think about. And, you know, the one, I think it's called the Casimir effect, if you can, if you have two plates and the space between them is on the order of these, like the wavelength of these ephemeral vacuum particles that pop into and out of existence or something. I may be confusing multiple types of propellant-less forces, but that could be real and could be something that we use eventually. What would be the power source? Yeah, the most recent engine like this that was just debunked this year, I think, in March or something, was called the M-Drive. And supposedly you used a power source, so, you know, batteries or solar panels to generate microwaves into this resonant cavity and people claimed it produced thrust. So they went straight from this really loose concept to building a device and testing it. And they said, we've measured thrust and sure on their thrust balance, they saw thrust and different researchers built it and tested it and got the same measurements. And so it was looking actually pretty good. No one could explain how it worked, but what they said was that this inside the cavity, the microwaves themselves didn't change, but the speed of light changed inside the cavity. So relative to that, you know, their momentum was conserved. And I don't, you know, whatever. But finally, someone, I think at NASA, built the device, tested it, got the same thrust, then unhooked it, flipped it backwards and turned it on, but got the same thrust in the same direction again. And so they're like, this is just an interaction with the test setup or, you know, some of the chamber or something like that. So forwarded again, but, you know, it would be so wonderful for everybody if we could figure out how to do it. But I don't know. That's an interesting twist on it because that's more about efficient travel, long distance travel, right? That's not necessarily about speed. That's more about enabling like- Yeah, so hook that up to the nuclear power supply. There you go. Okay. But still, in terms of speed, in terms of trying to, so there's recently, already I think been debunked or close to being debunked, but the signal, a weird signal from our nearby friends, nearby exoplanets from Proxima Centauri, a signal that's 4.2 light years away. So, you know, the thought is, it'd be kind of cool if there's life out there, alien life, but it'd be really cool if we could fly out there and check. And so what kind of propulsion, and do you think about what kind of propulsion will allow us to travel close to the speed of light? Or, you know, half the speed of light, all those kinds of things that would allow us to get to Proxima Centauri in a reasonable, in a lifetime? You know, there's the project Breakthrough Starshot. Yeah. That's looking at sending those tiny little chipsets there. And like accelerating really fast. Yeah, using a laser. So launching them, and then while they're still relatively close to the Earth, you know, blasting them with some, I forget what, even what power level you needed to accelerate them fast enough to get there in 20 years. Super crazy sounding. But a lot of people say that's a legitimate, like, it's crazy sounding, but you can actually pull it off. Yeah, I love that project because there are a lot of different aspects. You know, there's the laser, there's how do you then get enough power when you're there to send a signal back. No part of that project is possible right now, but I think it's really exciting. But do you see like human, like a spacecraft with a human on it, so it's like a heavy one? Being like, us inventing new propulsion systems entirely. Like, do you ever see that on the radar, propulsion systems like that, or are they completely out there in the impossible? Well, we're going to quickly leave the realm of what I can describe with any credibility, but I think because of special relativity, if we try to accelerate the mass close to the speed of light, it becomes infinitely heavy, and then we'd have to like harness a lot of suns to do that. Or, you know, it's just that math doesn't quite work out. But, you know, in my childlike heart, I believe that, you know, we're missing something, whether it's, you know, dark matter or other dimensions, and if you can just have some antimatter in a black hole and then ride that around and somehow, you know, turn that into some- Mess with gravity somehow. Yeah, I feel like we're missing lots of things in this puzzle and that, you know, there's something. I wonder how that puzzle, yeah, right. Well, I can speak with confidence as a descendant of apes that we don't know what the hell we're doing. Yeah. So there's, we're like really confident, like physicists are really confident that we've like got most of the picture down. Right. And it feels like, oh boy, it feels like that we might not even be getting started on some of the essential things that would allow us to engineer systems that would allow us to travel to space much, much faster. Yeah, and there's even things that are much more commonplace that we can't explain, but we've started to take for granted, like quantum tunneling, you know, just things like, oh, the electron was here with this energy and now it's here with this energy and it's just tunneling. But so, you know, we're missing a lot of the picture. So yeah, I don't know, to, you know, use your same question from earlier, I don't know if you and I will see it, but yeah, someday. You're the co-founder of, just like we've been talking about, Axiom Systems. Yeah. Would you say a space propulsion company? Yes. Broadly speaking. So how do you, big question, how do you build a rocket company from like a propulsion company from one person, from two people to 10 people plus and actually, you know, take it to a successful product? Yeah, well, I think the early stage is quite, I'm not supposed to use the word easy when you work in rocket science, but straightforward. When you're working on something, you know, sexy, like an ion engine, it's more straightforward to raise money and get people to come work for you because the vision's really exciting. And actually that's something I would say is very important throughout, is a really exciting vision because when everything goes to crap, you need that to get people getting themselves out of bed in the morning and thinking of the higher purpose there. And, you know, another thing along the way that I think is key in building any company is the right early employees that also have their own networks and can bring in a lot of people that really make the whole greater than just the sum of the early team. And how do you build that? Like, how do you find people? It's like asking, like, how do you make friends? But is there, is it luck? Is there a system? Like how, in terms of the people you've connected with, the people you've built a company with, is there some thread, some commonality, some pattern that you find to be, to hold for what makes a great team? I think, you know, personally, a thread for me has been my network and being able to draw on that a lot, but also giving back to it as much as possible in like an unsolicited sort of way, like making connections between people that, you know, maybe didn't ask, but that I think could be really fruitful. And even, you know, weirder than that is just really getting, you know, having weird, uncomfortable conversations with people, like at a conference and getting over the small talk quickly and getting to know them quickly and having a relationship that stands out and then being able to call on them later because of that. And I think that's been because I'm introverted and I, you know, wanna poke my eyes out instead of go and do small talk. And so I huddle in a corner with one person and, you know, we talk about aliens or things like that. And so, you know, that's all to say that, you know, having a strong network, I think is really important, but a genuine one. And let's see, other ways to build a rocket company, kind of making sure you're paying attention to the sweeping trends of the industry. So everybody just cares about cost and being able to get out ahead of that and even more than we ever thought we'd need to as far as what we needed to price our systems at. You know, people for, since the start of the US space industry, they've been paying 20, 25 million in adjusted dollars for an ion engine and seeing that now people are going to wanna pay 10K for an ion engine and just staying out ahead of that and those kinds of things. So, you know, being out in the industry and talking to as many people as possible. So there's a drive, I mean, I suppose SpaceX really pushed that. Frustrating for me. So SpaceX really pushed this, the application of, I guess, capitalism of driving the price down, of basically forcing people to ask the question, can this be done cheaper? This can lead to like big problems, I would say, in the following sense. I see this in the car industry, for example, that people have, it's such a small margin for profit. Like they've driven the cost of everything down so much that there's literally no room for innovation, for taking risks. So like cars, which is funny because not until Tesla really, which is one of the, in a long, long time, one of the first successful new car companies that's constantly innovating, every other car company is really pouring in terms of their technological innovation. They innovate on design and style and so on, that people fall in love with the look and so on, but it's not really innovation. In terms of the technology, and it's really boringly the same thing, and they're really afraid of taking risks. And that's a big problem for rocket space too, is like, if you're cutting on costs, you can't afford to innovate and to try out new things and then that's definitely true with Ion engine then, right? So, but what, so how do you compete in this space? Do you, by the way, see SpaceX as a competitor? And what do you say in general about the competition in this space? Is it really difficult as a business to compete here? No, I don't see SpaceX as a competitor, and I see them as one day, not too long from now, a customer, hopefully. I mean, to compete against that, I think you just have to do things in an unconventional way. So bringing silicon MEMS manufacturing to propulsion, NASA doesn't make Ion engines using a batch mass-producible technique. They have one guy that's been making their Ion engines for 20 years, like bespoke pieces of jewelry. So bringing things to what you're trying to innovate to make them, in our case, more cost-effective was really key. I like the idea of somebody putting out Ion engines on like Etsy. Yeah, my advisor at MIT would, the thruster chip I was holding up, he would wear one as a lapel pin. But in general, just on the topic of SpaceX, you know, 2020 has seen some difficult things for human civilization. And it's been a lot of, first of all, it's an election year, there's been a lot of drama and division about that. There's been riots of all different reasons, racial division. There's been, obviously, a virus that's testing the very fabric of our society. But there's been really, for me at least, super positive things, inspiring things, which is SpaceX and NASA doing the first commercial human flight, launching humans to space, and did it twice successfully. What is that, did you get to watch that launch? Did you, what does it make you feel? Do you think this is first days for a new era of space exploration? Yeah, I did watch it. We played it outside on a big screen at our place. And I was a little, you know, they kept saying, Bob and Doug, Bob and Doug. And, you know, astronauts usually are treated with a little bit more fanfare. So it felt very casual, but maybe that was a good thing. Like, this is the era of commercial, crude missions. And it was a little bit more, what is it? What's his name, Chris Hadfield, like playing guitar. Yeah. It's more, it's a different flavor to it of- Yeah, exactly. More like fun, playful, celebrity type- Yes, exactly. Astronaut versus the aura of the magical, sort of heroic elements of the single human representing us in space. Yes. Yeah. I think that's all for the better, though. It's so cool that it's such a commonplace thing now that we send, you know, I can't believe that sometimes I'll have to, you know, you don't even realize that astronauts are coming and going all the time, you know, splashing back down and it's just so common now, but that's quite magical, I think. So yes, we did watch that. I love, love, love that we finally have that capability again to send people to the space station. And it's just really exciting to see the private sector stepping up to fill in where the government has pulled back in the US, and I think pulled back way too soon as far as exploration and science goes. Probably pulled back at the right time for commercial things and getting that started, but I'm really happy that it's even possible to do that with private money and companies. Do you like the kind of the model of competition of NASA funding? I guess that's how it works, is like they're providing quite a bit of money from the government and then private companies compete to be the delivery vehicles for whichever the government missions, like NASA missions. Yes, I think for this type of mission is a little bit kind of straddles commercial and science, so I think it's good, but I do in general feel like we've pulled back too much on NASA's role in the science and exploration part, and I think our pace is too slow there for my liking, I suppose. What do you mean on the science? Okay, so did you have, I mean on the cost thing, do you feel like NASA was a little too bureaucratic in a sense, like too slow, too heavy cost-wise in their effort? Like when they were running things purely without any commercial involvement? So I suppose it's more that I just want the government to fund. I see, yeah. And maybe NASA's not the best organization to do it rapidly, but I think that, you know, again, depending on the goals, we're just kind of at the very starting point of space exploration and science and understanding so we should be spending more money there and not less, and other countries are starting to spend more and more, and I think we'll fall behind because of that. So you have quite a bit of experience, first of all, starting a company yourself, but also I saw, maybe you can correct me, but you have quite a bit of knowledge of, just in general, the startup experience of building companies, you've interacted with people. Is there advice that you can give to somebody, to a founder, co-founder who wants to launch and grow a new company and do something big and impactful in this world? Yes, I would say, you know, like I mentioned earlier, but make sure the vision is something that, you know, will get you out of bed in the morning and that you can rally other people around you to achieve. Because I see a lot of folks that sort of cared about something or saw a window of opportunity to do something, and you know, startups are hard and more often than not, just being opportunistic isn't going to be enough to make it through all the really crappy things that are going to happen. So the vision just helps you psychologically to carry through the hardships, you and the team. Yeah, you and the team, yeah, exactly. To kind of younger people interested in getting into entrepreneurship, I would say, you know, stay as close to like first principles and fundamentals as you can for as long as you can, because really understanding the problems, you know, if it's something scientific or hardware related, or even if it's not, but having a deep understanding of the problem and the customers and what people care about and how to move something forward is more important than taking all of the entrepreneurship classes in undergrad. So being able to think deeply, yeah. Yeah, exactly. Yeah, have you been surprised about how much like pivoting is involved? Like basically rethinking what you thought initially would be the right direction to go? Or is there, if you think deeply enough that you can stick in the same direction for long enough? So our, you know, our guiding star hasn't changed at all. So that's been pretty consistent, but we, within that we flip flop on so many things all the time. And, you know, to give you one example, it's do you stop and build a first product that's well suited to maybe a smaller, less exciting segment of the market, or do you stay head down and focus on, you know, the big swing and trying to hit it out of the park right away, and we've flip flopped between that. And there's not a blanket answer and there are a lot of factors, but that's a hard one. And I think one other piece for the aspiring founder, spending a lot of time and effort on the culture and people piece is so important and is always an afterthought and something that I haven't really seen like the founders or executives that companies purposefully carve out time and acknowledge that, yes, this is going to take a lot of my time and resources. And then, but you see them after the fact, trying to repair the bro culture, whatever else is broken at the company. And I think that it's starting to change, but just to be aware of it from the beginning is important. Right, I guess it should be part of the vision of what kind of place you wanna create, or what kind of like human beings. Yeah, exactly. Like you can't wait five, 10 years and then just slap an HR person onto trying to fix it. Like it has to be thoughtful from the beginning. Yeah, don't get me started on HR people. Don't leave HR to HR people, but I'll just leave it at that. You didn't say that, I said it, okay. Yeah, actual HR is really important. It's so important. Yes, but so overlooked. Culture is so important, yeah. And then I also was surprised. Like I thought you could say, here will be our culture and our values, and that it was kind of distinct from who I and my co-founder were as people. And I was like, no, that's not how that works. We just kind of like ooze out our behaviors, and then the company grows around that. So you have to do a lot of like introspection and self work to not end up with a shitty culture. It's kind of a, it's a relationship, but it's supposed to relationship with two people, it's a relationship with many people. Yeah. And you communicate so much indirectly by who you are. You have to be. Yes. You have to live it, yeah. As somebody, I think about this a lot, because generally I'm full of love and all those kinds of things. But like I also get like really passionate, and when I see somebody in the context of work, especially when I see somebody who I know can do a much better job, and they don't do a great job, I can lose my shit in a way that's like Steve Jobsian. And you have to think about exactly the right way to lose your shit if you're going to, or if at all. You have to really think through that, because it sends a big signal. You know, sometimes that's okay. Like if you do it deliberately, like if you're going to do it deliberately, if you're going to say like, I'm going to be the kind of person that allows this and pays the cost of it, but you can't just think it's not gonna have a cost. Yes, this was like the first thing I worked on with my leadership coach was how not to just snap at people when they were being an idiot. And first I got really good at apologizing. That was the first step, because it was gonna take longer to fix the behavior. And then she, I'm actually a lot better at it now, and it started with things, she's like, every time you walk through a doorway, think calm and take breaths before responding. And there were all sorts of these little things we did. And it was mostly just changing the habit. Yeah. Yeah. Oh boy, it's a long road. Okay, so people love it when we talk about books. Is there books, maybe three or so, technical fiction, philosophical, that had an impact on your life and you might recommend? And for each, is there an idea or so that you take away from it? Yes, so I've been a voracious reader all my life. And I'm always reading like three or four or five books at a time. And now I use Audible a lot too, and podcasts and things like that. So I think the first one that stands out to me is, it's a novel, Tender is the Night by Fitzgerald. And I read it when I was much younger, but I went back and read it recently, and it's not that good. So I'm not sure why it has like such an important place in my literary history. But I love Fitzgerald as an author because he has very like flowery prose that I can just picture what he's saying, but he does it in such a creative way. I remember that one in particular because I read a ton as a kid too, but it kind of set me, it was like the beginning of my adult reading life and getting into classics. And I do feel like they seem intimidating maybe, and then I realized that they're all just like love stories. So- Yeah, isn't everything a love story? Yeah, it's really. At the bottom. Even, I don't know, I was surprised that even like a lot of the Russian authors, you know, they're all just love stories. We're humans are pretty simple. There's not much to worry, there's not much to work with, so. So I think maybe that was it. It made like that whole world less intimidating to me and cemented my love for reading. People should have just approached the classics like there's probably a love story in here. Chick flicks, yeah. It's true. It somehow boils down to a chick flick, so just relax and enjoy the ride. And then- So what else? Changing gears quite a bit. The Beginning of Infinity, do you know it? By David Deutsch. So he's a physicist, I think at Cambridge or Oxford. And so I was introduced like more formally to a lot of the ideas, like a lot of the things we've talked about, he has a lot more like formalism and physics rigor around. And so I got introduced to, you know, more like jargon of how to think about some of these ideas. You know, like memes and DNA as ultimate meme, the concept of infinity and objective beauty, but he has a really strong grounding in physics. And then- So he has a rigorous way of talking about these big topics. Yeah, so that was very mind opening to me to read that. But it also, I think, is probably part of why I ended up marrying my husband is related to that book. And then I've had some other really great connections with people because I had read it and so had they. I like how you turned even that book into a love story. I did, oh no. Somehow. No, it's good, it's good. Your robot has a heart. Yeah, exactly. And okay, the third series is, it's just, it's Harry Potter. Of course, which somehow connects to, I haven't read Harry Potter, I'm really sorry. Oh no. I, forgive me, forgive me. But I've read Tolkien, but just Harry Potter, just haven't gotten to it. But your company name is somehow, I think, connects with Harry Potter, right? Yes. I think you heard this. My, I always feel like I have to justify my fandom. The first three books came out when I was 10, so I went along this journey with Harry age-wise. And I read them all, like nine or 10 times, all seven books. And I think anything that just keeps you reading is what's important. And I have lulls where I don't feel like reading anything, so I'll reread a Harry Potter or a trashy detective novel or something, and I don't really care. And that's why I mentioned Harry Potter, because it, whatever just keeps me reading, I think is important. And it was a big part of my life growing up. And then, yes, Axion. The official story of the naming of the company is that Axion is like a concatenation of accelerate and ion, but it actually came from Accio, the summoning charm. And then we just added an N, and it was perfect. What's the summoning charm? It's one of the spells in the book? Yeah, probably most notably, Harry uses it to summon his broomstick out of his dorm room when he's battling a dragon somewhere else. So he says the spell, and the broomstick comes to him. So summoning in that way. Okay, there we go. This is brilliant. So the big thing is that it's something that you carry with you. It's like your safe place you return to, something like the Harry Potter. That, I reread them still. Whatever keeps me reading, I think, is the most important thing. Okay, I got it. So I'm actually the same way in terms of the habit of it. It's important. Yeah. Yeah, it's important to just keep reading. But I have found myself struggling a little bit too, because I listen to a lot of audio books now. I have struggled to then switch back to reading seriously. Because I read so many papers, I read so many other things, it feels like if I'm going to sit down and have the time to actually focus on the reading, I should be reading blog posts or papers or more condensed kind of things. Yeah. But there's a huge value to just reading long form still. Yeah, and my husband was never that into fiction, but then someone told him or he heard, you learn a lot of empathy through reading fiction. So you could think of it that way. Well, yeah, that's kind of what, yeah, yeah. And it's also, fiction is a nice, unlike not, less so with nonfiction, is a chance to travel. I see it as kind of traveling. Yeah. As you go to this other world. And it's nice, because it's much more efficient. You don't have to get on a plane. You don't have to, and you get to meet all kinds of new people. It's like people say they love traveling. And I say I love traveling too. I just, yeah, read fiction. I told my three-year-old that that was why we read so much, because we see the places in our mind. And I'm like, it's basically like we're watching a movie. You know, that's how it feels. And she's like, I prefer watching Frozen with popcorn. Was her response that. Okay, well, you're three. It's a good point. Yeah. But yeah, there's some power to the imagination, right? It's not just like watching a movie, because something about our imagination, because it's the words and the world that's painted somehow mixing in with our own understanding of our own hopes and dreams, our fears. It like mixes up in there, and the way we build up that world from just the page. Yeah, you're really creating the world just with the prompts from the book, right? Yeah. So that's different than watching a movie. Yeah, which is why it hurts sometimes to watch the movie version, and then you're like, that's not at all how I imagined it. Well, we kind of brought this up in terms of, depending on what the goals are. Let me ask the big, you're friends with Manolis. He's obsessed with this question. So let me ask the big ridiculous question about the meaning of life. Do you ever think about this one? Do you ever ponder the reason we're here? The sons of apes on this spinning ball in the middle of nowhere? Yeah, I don't think one ends up in the field of space propulsion without thinking of these existential questions. Yeah, all the time. Or builds a business. Yeah, I know, right? Yeah, we've touched on a lot of the different pieces of this, I think. So I have a bunch of thoughts. I do think that the goal isn't, the meaning isn't anymore just to be like a petri dish of bacteria that reproduces, and where survival and reproduction are the main objectives. And maybe it's because now we're able to ask those questions. That's maybe the turning point. And instead, I think it's really the pursuit and generation of knowledge. And so if we're taken out by an asteroid or something, I think that it will have been a meaningful endeavor if somehow our knowledge about the universe is preserved somehow, and the next civilization isn't starting over again. So that's, I always, yeah, I resonate with that. I always loved the mission of Google from the early days of making the world's information and knowledge searchable. I always loved that idea. I always loved, I always donated, as people should, to Wikipedia. I just love Wikipedia. I feel like it's the, that's one of the greatest accomplishments of just a humanity of us together, especially Wikipedia and this open, like in this open community way, putting together different knowledge. Just like, on everything we've talked about today, I'm sure there's a Wikipedia page about ion engines, and I'm sure it's pretty good. Like, I don't know, that's incredible. And obviously that can be preserved pretty efficiently, at least Wikipedia. I know you just, you'll be like, human civilization is all like burning up in flames as there's this one USB drive slowly traveling out. Wikipedia on it. Yep. That's on, from the beginning of our chat, that one lonely spacecraft, it just means Wikipedia. And then it will have been a civilization well spent. So pushing that knowledge along, Yeah. through like one little discovery at a time is one of, is a core aspect to the meaning of it all. Yes. And I also, I haven't yet figured out what the connection, you know, an explanation I'm happy with yet for how it's connected, but evolving beyond just the survival piece too, I think like we touched on the emotional aspect, something in there about cooperation and love. And so I, in my day to day, that just boils down to, you know, the pursuit of knowledge or improving the human condition and being kind. Love and knowledge. Yeah, exactly. So I'm pretty at peace with that as the meaning right now. Makes sense to me. You work on spacecraft propulsion. Yes, exactly. Like literal rocket science. Natalia, this was an amazing conversation. You work on such an exciting engineering field. And I think this is like what 20th, 21st century will be remembered for is space exploration. So this is super exciting space that you're working on. So, and thank you so much for spending your time with me today. Thanks for having me. This was fun. Thanks for listening to this conversation with Natalia Bailey. And thank you to our sponsors, Monk Pack Low Carb Snacks, Four Sigmatic Mushroom Coffee, Blinkist, an app that summarizes books, and Sun Basket, meal delivery service. So the choice is snacks, caffeine, knowledge, or a delicious meal. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. And now let me leave you with some words from Carl Sagan. All civilizations become either spacefaring or extinct. Thank you for listening and hope to see you next time.

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Jed Buchwald: Isaac Newton and the Philosophy of Science | Lex Fridman Podcast #214

The following is a conversation with Jed Buchwald, a professor of history and a philosopher of science at Caltech, interested especially in the development of scientific concepts and the instruments used to create and explore new effects and ideas in science. To support this podcast, please check out our sponsors in the description. This is the Lex Friedman Podcast, and here is my conversation with Jed Buchwald. Does science progress via paradigm shifts and revolutions as philosopher Thomas Kuhn said, or does it progress gradually? What do you think? Well, I got into this field because I was Tom Kuhn's research assistant 50 years ago, 52 years ago. He pulled me into it out of physics instead. So I know his work pretty well. And in the years when I was at MIT running an institute, he was then in the philosophy department, used to come over all the time to the talks we held and so on. So what would I say about that? He, of course, developed his ideas a lot over the years. The thing that he's famous for, the structure of scientific revolutions came out in 62. And as you just said, it offered an outline for what he called a paradigmatic structure, namely the notion that you have to look at what scientists do as forming a community of investigators and that they're trying to solve various puzzles, as he would put it, that crop up, figuring out how this works, how that works and so on. And of course, they don't do it out of the blue. They do it within a certain framework. The framework can be pretty vague. He called it a paradigm. And his notion was that eventually they run into troubles or what he called anomalies, that kind of cracks things. Somebody new comes along with a different way of doing it, et cetera. Do I think things work that way? No, not really. Tom and I used to have lengthy discussions about that over the years. I do think there is a common structure that formulates both theoretical and experimental practices. And historians nowadays of science like to refer to scientific work as what scientists practice. It's almost craftsman-like. They can usually adapt in various ways. And I can give you all kinds of examples of that. I once wrote a book on the origins of wave theory of light. And that is one of the paradigmatic examples that Tom used, only it didn't work that way exactly. Because he thought that what happened was that the wave theory ran into trouble with a certain phenomenon, which it couldn't crack. Well, it turned out that in fact, historically that phenomenon was actually not relevant later on to the wave theory. And when the wave theory came in, the alternative to it, which had prevailed, which was Newton's views, light is particles, that it seemed couldn't explain what the wave theory could explain. Again, not true, not true. It's much more complex than that. The wave theory offered the opportunity to deploy novel experimental and mathematical structures, which gave younger scientists, mathematicians and others, the opportunity to effect, manufacture, make new sorts of devices. It's not that the alternative couldn't sort of explain these things, but it never was able to generate them de novo as novelties. In other words, if you think of it as something scientists wanted progress in the sense of finding new stuff to solve, then I think what often happens is, is that it's not so much that the prevailing view can't crack something as that it doesn't give you the opportunity to do new stuff. When you say new stuff, are we referring to experimental science here or new stuff in the space of new theories? Could be both, could be both actually. So how does that, can you maybe elaborate a little bit on the story of the wave? Sure. The prevailing view of light, at least in France, where the wave theory really first took off, although it had been introduced in England by Thomas Young, the prevailing theory dates back to Newton, that light is a stream of particles and that refraction and reflection involve sort of repulsive and attractive forces that deflect and bend the paths of these particles. Newton was not able successfully to deal with the phenomenon of what happens when light goes past a knife's edge or a sharp edge, what we now call diffraction. He had cooked up something about it that no mathematical structure could be applied. Thomas Young first, but really this guy named Augustin Fresnel in France, deployed in Fresnel's case, rather advanced calculus forms of mathematics, which enabled computations to be done and observations to be melded with these computations in a way that you could not do or see how to do with Newton. Did that mean that the Newtonian explanation of what goes on in diffraction fails? Not really. You can actually make it work, but you can't generate anything new out of it. Whereas using the mathematics of wave optics in respect to a particular phenomenon called polarization, which ironically was discovered by partisans of Newton's way of doing things, you were able to generate devices which reflect light and crystals, do various things that the Newtonian way could accommodate only after the fact. They couldn't generate it from the beginning. And so if you want to be somebody who is working a novel vein, which increasingly becomes the case with people who become what we now call physicists in the 1820s, 30s and 40s in particular, then that's the direction you're gonna go. But there were holdouts until the 1850s. I wanna try to elaborate on the nature of the disagreement you have with Thomas Kuhn. So do you still believe in paradigm shifts? Do you still see that there is ideas that really have a transformational effect on science? The nature of the disagreement has to do with how those paradigm shifts come to be? How they come to be and how they change. I certainly think they exist. How strong they may be at any given time is maybe not quite as powerful as Tom thought in general, although towards the end of his life, he was beginning to develop different modifications of his original way of thinking. But I don't think that the changes happened quite so neatly, if you will, in reaction to novel experimental observations. They can be much more complex than that. In terms of neatness, how much of science progresses by individual lone geniuses and how much by the messy collaboration of competing and cooperating humans? I don't think you can cut that with a knife to say it's this percent and that percent. It's almost always the case that there are one or two or maybe three individuals who are sort of central to what goes on when things begin to shift. Are they inevitably and solely responsible for what then begins to happen in a major way? I think not. It depends. You can go very far back with this, even into antiquity to see what goes on. The major locus we always talk about from the beginning is if you're talking about Galileo's work on motion, for example, were there ways of accommodating it that others could adapt to without buying into the whole scheme? Yes. Did it eventually evolve and start convincing people because you could also do other things with it that you couldn't otherwise do? Also yes. Let me give you an example. The great French mathematician philosopher Descartes, who was a mechanical philosopher, he believed the world was matter in motion, he never thought much of what Galileo had done in respect to motion because he thought, well, at best it's some sort of approximative scheme or something like that. But one of his initial, I wouldn't call him a disciple, but follower who then broke with him in a number of ways was a man named Christian Huygens, who was along with Newton, one of the two greatest scientists of the 17th century. Huygens is older than Newton. And Huygens nicely deployed Galilean relationships in respect to motion to develop all sorts of things, including the first pendulum-governed clock. And even figured out how to build one, which keeps perfect time, except it didn't work. But he had the mathematical structure for it. How well known is Huygens? Oh, very well known. Should I know him well? Yes, you should. Interesting. You should definitely know him well. No, no, no, no, no. Can we define should here? Okay. Because I don't. Right. So is this should, like, yeah, can you define should? Should means this. If you had taken up to a second year of physics courses, you should, you would have heard his name because one of the fundamental principles in optics is called Huygens' principle. Okay. Okay? Yeah, so I have, and I have heard his name. There you go. No, but I don't remember. But you don't remember. So, I mean, there's a very different thing between names attached to principles and laws and so on that you sometimes let go of. You just remember the equations of the principles themselves and the personalities of science. And there's certain personalities, certain human beings that stand out. And that's why there's a sense to which the lone inventor, the lone scientist is the way I personally, I mean, I think a lot of people think about the history of science is these lone geniuses. Without them, the sense is, if you remove Newton from the picture, if you remove Galileo from the picture, then science would, there's almost a feeling like it would just have stopped there. Or at the very least, there's a feeling like it would take much longer to develop the things that were developed. Is that a silly way to look at the history of science? That's not entirely incorrect, I suppose. I find it difficult to believe that had Galileo not existed, that eventually someone like Huygens, for instance, given the context of the time, what was floating around in the belief structure concerning the nature of the world and so on, the developments in mathematics and whatnot, that sooner or later, whether it would have been exactly the same or not, I cannot say, but would things have evolved? Yes. If we look at the long arc of history of science, from back when we were in the caves trying to knock two rocks together, or maybe make a basic tool, to a long time from now, many centuries from now, when human civilization finally destroys itself. If we look at that history, and imagine you're a historian at the end, like with the fire of the apocalypse coming upon us, and you look back at this time in the 21st century, how far along are we on that arc? Do you sense? Have we invented and discovered everything that's to be discovered, or are we at below 1%? Well, it's- You're gonna get a lot of absurd questions today. I apologize. It's a lugubrious picture you're painting there. I don't even know what the word lugubrious means, but I love it. Lugubrious. Well, let me try and separate the question of whether we're all going to die in an apocalypse in several hundred years or not, from the question of where science may be sitting. Take that as an assumption. Okay. I find that hard to say. And I find it hard to say because in the deepest sense of the term, as it's usually deployed by philosophers of science today, I'm not fundamentally a realist. That is to say, I think our access to the inner workings of nature is inevitably mediated by what we can do with the materials and factors around us. We can probe things in various ways. Does that mean that I don't think that the standard model in quantum electrodynamics is incorrect? Of course not. I wouldn't even dream of saying such a thing. It can do a lot, especially when it comes to figuring out what's happening in very large, expensive particle accelerators and applying results in cosmology and so on as well. Do I think that we have inevitably probed the depths of reality through this? I do not agree with Steven Weinberg, who thinks we have, about such things. Do I, on the other hand, think that the way in which science has been moving for the last 100 years, physics in particular is what I have in mind, will continue on the same course? In that sense, I don't because we're not going to be building bigger and bigger and more and more expensive machines to rip apart particles in various ways, in which case, what are physicists gonna do? They'll turn their attention to other aspects. There are all sorts of things we've never explained about the material world. We don't have theories that go beyond a certain point for all sorts of things. We can, can we, for example, start with the standard model and work our way up all the way to chemical transformations? You can make an argument about it and you can justify things, but that's in chemistry, that's not the way people work. They work with much higher level quantum mechanical relationships and so on. So this notion of the deep theory to explain everything is a longstanding belief, which goes back pretty far, although I think it only takes its fullest form sometime in towards the end of the 19th century. So maybe we just speak to that, you're referring to a hope, a dream, a reality of coming up with a theory of everything that explains everything. So there's a very specific thing that that currently means in physics, is the unification of the laws of physics. But I'm sure in antiquity or before, it meant maybe something else, or is it always about physics? Does that mean, I think as you've kind of implied, in physics, there's a sense, once you get to the theory of everything, you've understood everything, but there's a very deep sense in which you've actually understood not very much at all. You've understood at that particular level, how things work, but you don't understand how the abstractions on top of abstractions form all the way to the chemistry, to the human mind and the human societies and all those kinds of things. So maybe you can speak to the theory of everything in its history and comment on what the heck does that even mean, the theory of everything? Well, I don't think you can go back that far with something like that, maybe to the, at best to the 17th century. If you go back all the way in antiquity, there are of course discussions about the nature of the world. But first of all, you have to recognize that the manipulative character of physics and chemistry, the probing of, let me put it this way, we assume and have assumed for a long time, I'll come back to when in a moment, that if I take a little device, which is really complicatedly made out of all kinds of things, and I put a piece of some material in it, and I monkey around with it and do all kinds of unnatural things to it, things that wouldn't happen naturally, and I find out how it behaves and whatnot. And then I try and make an argument about how that really applies, even in the natural world, without any artificial structures and so on. That's not a belief that was widely held by pretty much anyone until sometime maybe in the 1500s. And when it was first held, it was held by people we now call alchemists. So alchemy was the first, the early days of the theory of everything, of a dream of a theory of everything. I would put it a little differently. I think it's more along the way a dream that by probing nature in artificially constructed ways, we can find out what's going on deep down there. So that's distinct from science being an observing thing, where you observe nature and you study nature. You're talking about probing, like messing with nature to understand it. Indeed I am, but that of course is the very essence of experimental science. You have to manipulate nature to find out things about it, and then you have to convince others that you haven't so manipulated it that what you've done is to produce what amounts to fake, artifactual behavior that doesn't really hold purely naturally. So where are we today in your sense to jump around a little bit with the theory of everything? Maybe a quick kind of sense you have about the journey in the world of physics that we're taking towards the theory of everything. Well, I'm of course not a practicing physicist. I mean, I was trained in physics at Princeton a long time ago. Until Thomas Kuhn stole you away. More or less. I was taking graduate courses in those days in general relativity. I was an undergraduate, but I moved up and then I took a course with him. Well, you made the mistake of being compelled by charismatic philosophers and never looked back. I suppose so in a way. And from what I understand, talking especially to my friends at Caltech like Kip Thorne and others, the fundamental notion is that actually the laws that even at the deepest level we can sort of divine and work with in the universe that we inhabit are perhaps quite unique to this particular universe as it formed at the Big Bang. The question is, how deep does it go? If you are very mathematically inclined, the prevailing notion for several decades now has been what's called string theory. But that has not been able to figure a way to generate probative experimental evidence, although it's pretty good apparently at accommodating things. And then the question is, what's before the Big Bang? Or actually the word before doesn't mean anything given the nature of time, but why do we have the laws that prevail in our universe? Well, there is a notion that those laws prevail in our universe because if they didn't, we wouldn't be here. That's a bit of a cyclical, but nevertheless a compelling definition. And there's all kinds of things like the, it seems like the unification of those laws could be discovered by looking inside of a black hole because you get both the general relativity and the quantum mechanics, quantum field theory in there. Experimentally, of course, there's a lot of interesting ideas. We can't really look close to the Big Bang, can't look that far back. There's Caltech and MIT, LIGO, what kind of gravitational waves perhaps allows us to march backwards and so on. Yeah, it's a really exciting space. And there's of course the theory of everything like with a lot of things in science captivates the dreams of those who are perhaps completely outside of science. It's the dream of discovering the key to how the, you know, the nature of how everything works. And that feels deeply human. That's perhaps the thing, the basic elements of what makes up a scientist in the end is that curiosity, that longing to understand. Let me ask, you mentioned a disagreement with Weinberg on reality. Could you elaborate a little bit? Well, obviously I don't disagree with Steve Weinberg on physics itself. I wouldn't know enough to even begin to do that. And clearly, you know, he's one of the founders of the standard model and so on, and it works to a level of accuracy that no physical theory has ever worked at before. I suppose the question in my mind is something that in one way could go back to the philosopher Immanuel Kant in the 18th century, namely, can we really ever convince ourselves that we have come to grips with something that is not in itself knowable to us by our senses, or even except in the most remote way through the complex instruments that we make as to what it is that underlies everything. Can we corral it with mathematics and experimental structures? Yes. Do I think that a particular way of corralling nature will inevitably play itself out? I don't know. It always has. I'll put it to you that way. So the basic question is, can we know reality? Is that the Kant question? Is that the Weinberg question? We humans with our brains, can we comprehend reality? Sounds like a very trippy question because a lot of it rests on definitions of know and comprehend and reality, but get to the bottom of it. Like, it's turtles on top of turtles. Can we get to the bottom turtle and say hello? Well, maybe I can put it to you this way in a way that I often begin discussions in a class on the history of science and so on, and say, I'm looking at you. Yes. You are in fact a figment of my imagination. You have a messed up imagination, yes. Well, what do I mean by that? If I were a dragonfly looking at you, whatever my nervous system would form by way of a perceptual structure would clearly be utterly different from what my brain and perceptual system altogether is forming when I look at you. Who's right? Is it me or the dragonfly? Well, the dragonfly is certainly very impressive, so I don't know, but yes, the observer matters. Well, how does, what is that supposed to tell us about objective reality? Well, I think it means that it's very difficult to get beyond the constructs that our perceptual system is leading us to. When we make apparatus and devices and so on, we're still making things, the results of which, or the outputs of which we process perceptually in various ways. And an analogy I like to use with students sometimes is this, all right, they all have their laptops open in front of them, of course, okay? And I've sent them something to read, and I say, okay, click on it and open it up. So a PDF opens up. I said, what are you looking at? They said, well, I'm looking at the paper that you sent me. I said, no, you're not. What you're looking at is a stream of light coming off LEDs or LCDs coming off a screen. And I said, what happens when you use your mouse and move that fake piece of paper on the screen around? What are you doing? You're not moving a piece of paper around, are you? You're moving a construct around, a construct that's being processed so that our perceptual system can interact with it in the way we interact with pieces of paper. But it's not real. So are there things outside of the reach of science? Can you maybe, as an example, talk about consciousness? I'm asking for a friend, trying to figure this thing out. Well, boy, I mean, I read a fair bit about that, but I certainly can't really say much about it. I'm a materialist in the deepest sense of the term. I don't think there is anything out there except material structures which interact in various ways. Do I think, for example, that this bottle of water is conscious? No, I do not. Although, how would I know? I can't talk to it. Yeah. But, so what do- It's a hypothesis you have. It's an opinion, an educated opinion that may be very wrong. Well, I know that you're conscious because I can interact directly with you. But am I? Well, unless you're a figment of my imagination, of course. No, or I'm a robot that's able to generate the illusion- Yes. The illusion of consciousness effectively enough to facilitate a good conversation. Because we humans do want to pretend that we're talking to other conscious beings because that's how we respect them. If it's not conscious, we don't respect them. We're not good at talking to robots, for example. That's true. Of course, we generalize from our own inner sense, which is the kind of thing Descartes said from the beginning. We generalize from that. But I do think that consciousness must be something, whatever it is, that occurs as a result of some particular organizational structure of material elements. Does materialism mean that it's all within the reach of science? My sense would be that, especially as neuroscience progresses more and more, and at Caltech, we just built a whole neuroscience arena and so on. And as more knowledge is gained about the ways in which animals, when they behave, what patterns show up at various parts of the brain and nervous system, and perhaps extending it to humans eventually as well, we'll get more of a handle on what brain activity is associated with experiences that we have as humans. Can we move from the brain activity to the experiences in terms of our, no, you can't. Perception is perception. That's a hypothesis once again. Maybe consciousness is just one of the laws of physics that's yet to be discovered. Maybe it permeates all matter. Maybe it's as simple as trying to plug it in and plug into the ability to generate and control that kind of law of physics that would crack open, where we would understand that the bottle of water is in fact conscious, just much less conscious than us humans, and then we would be able to then generate beings that are more conscious. Well, that'll be unfortunate. I'd have to stop drinking the water after that. Every time you take a sip, there's a little bit of a suffering going on. Right. What to you is the most interesting, beautiful moments in the history of science? What stands out? And then we can pull at that thread. Right. Well, I like to think of events that have a major impact and involve both beautiful, conceptual, mathematical, if we're talking physical structures work, and are associated as well with probing experimental situations. So among my favorites is one of the most famous, which was the young Isaac Newton's work with the colors produced when you pass sunlight through a prism. And why do I like that? It's not profoundly mathematical in one sense, doesn't need it initially. It needs the following though, which begins to show you, I think, a little bit about what gets involved when you've got a smart individual who's trying to monkey around with stuff and finds new things about it. First, let me say that the notion, the prevailing notion going back to antiquity, was that colors are produced in a sense by modifying or tinting white light, that they're modifications of white light. In other words, the colors are not in the sunlight in any way. Okay. Now, what Newton did, following experiments done by Descartes before him, who came to very different conclusions, he took a prism. You might ask, where do you get prisms in the 1660s? That's a good question. County fairs. They were very popular. They were pretty crude, with bubbles in them and everything, but they produced colors, so you could buy them at county fairs and things. Very popular. Oh, so they were modifying the white light to create colors. They were creating colors from it, well known. And what he did was the following. He was, by this time, even though he's very young, a very good mathematician. And he could use the then known laws for how light behaves when it goes through glass to calculate what should happen if you took light from the sun, passed it from a hole through a little hole, then hit the prism, goes out of the prism, goes, strikes a wall a long distance away, and makes a splash of light. Nevermind the colors for a moment. Makes a splash of light there. He was very smart. First of all, he abstracts from the colors themselves, even though that's what everybody's paying attention to initially. Because what he knows is this. He knows that if you take this prism and you turn it to a certain particular angle, that he knew what it should be, because he could calculate things. Very few other people in Europe at the time could calculate things like he could. That if you turn the prism to that particular angle, then the sun, which is of course a circle, when its light passes through this little hole and then into the prism, on the far distant wall, should still make a circle. But it doesn't. It makes a very long image. And this led him to a very different conception of light, indicating that there are different types of light in the sunlight. Now, to go beyond that, what's particularly interesting I think is the following. When he published this paper, which got him into a controversy, he really didn't describe at all what he did. He just gave you some numbers. Now, I just told you that you had to set this prism at a certain angle, right? You would think, because we do have his notes and so on, you would think that he took some kind of complicated measuring device to set the prism. He didn't. He held it in his hand, that's all. And he twiddled it around. And what was he doing? It turns out that when you twiddle the prism around at the point where you should get a circle from a circle, it also is the place where the image does not move very fast. So if you wanna get close to there, you just twiddle it. This is manipulative experimentation, taking advantage through his mathematical knowledge of the inherent inaccuracies that let you come to exact conclusions regardless of the built-in problematics of measurement. He's the only one I know of doing anything like that at this time. At the time. Yeah. Well, even still, there's very few people that are able to calculate as well as he did to be a theoretician and an experimentalist, like in the same moment. Right? It's true, although until the, really the well into the 20th century, maybe the beginning of the 20th century, really most of the most significant experimental results produced in the 1800s, which laid the foundations for light, electricity, electrodynamics, and so on, even hydrodynamics and whatnot, were also produced by people who were both excellent calculators, very talented mathematicians, and good with their hands experimentally. And then that led to the 21st century with Enrico Fermi, that one of the last people that was able to do that, both of those things very well, and that he built a little device called an atomic bomb that has some positives and negatives. Well, right, of course that actually did involve some pretty large-scale elaborate equipment to. Well, holding a prism in your hands, same thing. Right, no. What's the controversy that you got into with that paper when you published it? Well, in a number of ways, it's a complicated story. There was a very talented character known as a mechanic. Mechanic means somebody who was a craftsman who could build and make really good stuff. And he was very talented. His name was Robert Hooke. And he was the guy who, at the weekly meetings of the Royal Society in London, and Newton's not in London, he's at Cambridge, he's a young guy, he would demonstrate new things. And he was very clever. And he had written a book, in fact, called the Micrographia, which, by the way, he used a microscope to make the first depictions of things like a fly's eye, the structure of, and it had a big influence. And in there, he also talked about light. And so he had a different view of light. And when he read what Newton wrote, he had a double reaction. On the one hand, he said, anything in there that is correct, I already knew. And anything that I didn't already know is probably not right anyway. Ha ha ha. Ah, gotta love egos. Okay, can we just step back? Can you say, who was Isaac Newton? What are the things he contributed to this world, in the space of ideas? Wow. Who was he? He was born in 1642, and near the small town of Grantham in England. In fact, the house he was born in, and that his mother died in, is still there and can be visited. His father died before he was born. And his mother eventually remarried a man named Reverend Smith, whom Newton did not like at all, because Reverend Smith took his mother away to live with him a few miles away, leaving Newton to be brought up, more or less, by his grandmother over there. And he had huge resentment about that his whole life. I think that gives you a little inkling that a little bit of trauma in childhood, maybe a complicated father-son relationship, can be useful to create a good scientist. Could be, although this case, it would be right, the absent father, non-father relationship, so to speak. He was known as a kid, little that we do know, for being very clever about flying kites. There are stories about him putting candles and flying kites and scaring the living devil out of people at night by doing that and things like that, making things. Most of the physicists and natural philosophers I've dealt with, actually, as children, were very fond of making and playing with things. I can't think of one I know of who wasn't, actually. They were very good with their hands and whatnot. His mother wanted him to take over the manor. It was a kind of farming manor. They were the class of what are known as yeomans. There are stories that he wasn't very good at that. One day, one of the stories is he's sitting out in the field and the cows come home without him and he doesn't know what's going, anyway. Add relatives and he manages to get to Cambridge, sent to Cambridge, because he's known to be smart. He's read books that he got from local dignitaries and some relatives. And he goes there as what's known as a sub-sizer, what does that mean? Well, it's not too pleasant. Basically, a sub-sizer was a student who had to clean the bedpans of the richer kids. That didn't last too long. He makes his way and he becomes absorbed in some of the new ways of thinking that are being talked about on the parts of Descartes and others as well. There's also the traditional curriculum which he follows. And we have his notes. We have his student notebooks and so on. We can see gradually this young man's mind focusing and coming to grips with deeper questions of the nature of the world and perception even and how we know things and also probing and learning mathematical structures to such an extent that he builds on some of the investigations that had been done in the period before him to create the foundations of a way of investigating processes that happen and change continuously instead of by leaps and bounds and so on, forming the foundation of what we now call the calculus. Yeah. So can you maybe just paint a little bit of a picture, you've already started, of what were the things that bothered him the most that stood out to him the most about the traditional curriculum, about the way people saw the world? You mentioned discrete versus continuous. Is there something where he began thinking in a revolutionary way? Because it's fascinating. Most of us go to college, Cambridge or otherwise, and we just kind of take what we hear as gospel, right? Like not gospel, but as like facts. You don't begin to sort of see, how can I expand on this aggressively? How can I challenge everything that I hear? Like rigorously, mathematically, I mean, I don't even know how rigorous the mathematics was at that point. I'm sure it was geometry and so on, no calculus, huh? There are elements of what turned into the calculus that predate Newton, but. How much rigor was there? How much? Well, rigor, no. And then of course, no scientific method, not really. I mean, somewhat. I mean, appreciation of data. Ah, that is a separate question from a question of method. Appreciation of data is a significant question as to what you do with data. There's lots of things you're asking. I apologize. So maybe let's backtrack, and the first question is, was there something that was bothering him that he especially thought he could contribute or work on? Well, of course, we can't go back and talk to him, but we do have these student notebooks. There's two of them. One's called the Philosophical Questions, and the other is called the Wastebook. The Philosophical Questions has discussions of the nature of reality and various issues concerning it, and the Wastebook has things that have to do with motion in various ways, what happens in collisions and things of that sort. And it's a complicated story, but what's among the things that I think are interesting is he took notes in the Philosophical Questions on stuff that was traditionally given to you in the curriculums going back several hundred years, namely on what scholars refer to as scholastic or neo-scholastic ways of thinking about the world, dating back to the reformulation of Aristotle in the Middle Ages by Thomas Aquinas in the church. This is a totally different way of thinking about things, which actually connects to something we were saying a moment ago. For instance, so I'm wearing a blue shirt, and I will sometimes ask students, where is the blue? And they'll usually say, well, it's in your shirt. And then some of them get clearer, and they say, well, no, you know, light is striking. The photons are re-emitted. They strike the back of your retina, and et cetera, et cetera. And I said, yes, what that means is that the blue is actually an artifact of our perceptual system considered as the percept of blue. It's not out there, it's in here, right? That's not how things were thought about well into the 16th century. The general notion dating back even to Aristotelian antiquity, and formalized by the 12th century at Paris, Oxford, and elsewhere, is that qualities are there in the world. They're not in us. We have senses, and our senses can be wrong. You know, you could go blind, things like that. But if they're working properly, you get the actual qualities of the world. Now that break, which is occurring towards the end of the 16th century, and is most visible in Descartes, is the break between conceiving that the qualities of the world are very different from the qualities that we perceive. That in fact, the qualities of the world consist almost entirely in shapes of various kinds, and maybe hard particles or whatever, but not colors, not sounds, not smells, not softness and hardness. They're not in the world, they're in us. That break, Newton is picking up as he reads Descartes. He's gonna disagree with a lot in Descartes. But that break, he is, among other things, picking up very strongly. And that underlies a lot of the way he works later on when he becomes skeptical of the evidence provided by the senses. Yeah, that's actually, I don't know, the way you're describing it is so powerful. It just makes me realize how liberating that is as a scientist, as somebody who's trying to understand reality, that our senses is just, our senses are not to be trusted. That reality is to be investigated through tools that are beyond our senses. Yes, or that improve our senses. Improve our senses. In some ways. That's pretty powerful. I mean, that is, for a human being, that's like Einstein level. For a human being to realize I can't trust my own senses at that time, that's pretty trippy. It's coming in, it's coming in. And I think it arises probably a fair number of decades before that, perhaps in part with all chemical experimentation and manipulations, that you have to go through elaborate structures to produce things and ways you think about it. But let me give you an example that I think you might find interesting because it's from, it involves that guy named Hook that Newton had an argument with. And he had lots of arguments with Hook, although Hook was a very clever guy and gave him some things that stimulated him later. Anyway, Hook, who was argumentative, and he really was convinced that the only way to gain real knowledge of nature is through carefully constructed devices. And he was an expert mechanic, if you will, at building such things. Now there was a rather wealthy man in Danzig by the name of Hevelius, Latinized name. He was a brewer in town. And he had become fascinated with the telescope. This is 30 years or so, 20 or 30 years after the telescope had moved out and become more common. And he built a large observatory on the top of his brewery, actually, and working with his wife, they used these very elaborately constructed brass and metal instruments to make observations of positions of the stars. And he published a whole new catalog of where the stars are. And he claimed it was incredibly accurate. He claimed it was so accurate that nothing had ever come close to it. Hook reads this and he says, wait a minute, you didn't use a telescope here of any kind because what's the point? Unless you do something to the telescope, all you see are dots with stars. You just use your eye, your eyes can't be that good. It's impossible. So what did Hook do to prove this? He said, what you should have done is you should have put a little device in the telescope that lets you measure distances between these dots. You didn't do that. And because you didn't, there's no way you could have been that good. At two successive meetings of the Royal Society, he hauls the members out into the courtyard and he takes a card and he makes successive black and white stripes on the card. And he pastes the card up on a wall and he takes them one by one. He says, now move back looking at it, presumably with one eye, until you can't tell the black ones from the white stripes. He says, that I can then measure the distance. I can see the angles. I can give a number then for what is the best possible, what we would call perceptual acuity of human vision. And it turned out, he thought, to be something like 10 or more times worse than this guy Hevelius had claimed. So obviously, says Hook, Hevelius. Well, years ago, I calculated Hevelius's numbers and so on using modern tables from NASA and so on. And they are even more accurate than Hevelius claimed. And worse than that, the Royal Society sent a young astronomer named Halley over to Danzig to work with him. And Halley writes back and he says, I couldn't believe it. But he taught me how to do it and I could get just as good as he, how is it possible? Well, here, this shows you something very interesting about experiments, perception, and everything else. Hook was right, but he was also wrong. He was wrong for the right reasons and he was right for the wrong reasons. And what do I mean by that? What he actually found was the number for what we now call 20-20 vision. He was right. You can't tell, except a few people, much better than that. But he was observing the wrong thing. Yes. What Hevelius was observing was a bright dot, a star, moving past a pointer. Our eyes are rather similar to frogs' eyes. You know, I'm sure you've heard the story, if I hold a dead fly on a string in front of a frog and don't move it, the frog pays no attention. As soon as I move the fly, the frog immediately tongue-laps out because the visual system of the frog responds to motion. So does ours. And our acuity for distinguishing motion from statics, five or more times better. Yeah, that's fascinating. Damn. And of course, I mean, maybe you can comment on their understanding of the human perceptual system at the time was probably really terrible. Like, yeah, I've recently been working with, just almost as a fun side thing, with vision scientists and peripheral vision. It's a beautiful, complex mess, that whole thing. We still don't understand all the weird ways that human perception works. And they were probably terrible at it. They probably didn't have any conception of peripheral vision or the fovea or, I mean, basically anything. They had some, I mean, because actually it was Newton himself who probed a lot of this. For instance, Newton, the young Newton, trying to work his way around what's going on with colors, wanted to try and distinguish colors that occur through natural processes out there and colors that are a result of our eyes not operating right. So you know what he did? It's a famous thing. He took a stick and he stuck that stick under his lower eyelid and pushed up on his eyeball. And what that did would produce colored circles at diametrically opposite positions of the stick and the eyeball. And he moved it around to see how they moved, trying to distinguish. Legit. Right? I always have to tell my students, don't do this, but. Or do it if you wanna be great and remembered by human history. That's, there's a lot of equivalent to sticking, sticking to your eye in modern day that may pay off in the end. Okay. As a small aside, is the Newton and the apple story true? No. Was it a different fruit? As a colleague of mine named Simon Schaffer in England once said on a NOVA program that we were both on, the role of fruit in the history of science has been vastly exaggerated. Okay. So was there any, I mean, to zoom out, moments of epiphany. Is there something to moments of epiphany? Or again, this is the paradigm shift versus the gradualism. There is a shift. It's a much more complex one than that. And we, as it happens, a colleague of mine and I are writing a paper right now on one of the aspects of these things based on the work that many of our colleagues have done over the last 30 and 40 years. Let me try and see if I could put it to you this way. Newton, until the early 1670s, and probably really until a fair time after that, first of all, was not very interested in questions of motion. He was working actually in all chemical relationships or what is called by historians, chemistry, a kind of early modern chemical structure. Colleagues of ours at Indiana have even reproduced the amalgams that, anyway. His way of thinking about motion involved a certain set of relationships which was not conducive to any application that would yield computationally direct results for things like planetary motions, which he wasn't terribly interested in anyway. He enters a correspondence with his original nemesis, Robert Hooke. And Hooke says, well, have you ever thought about, and then Hooke tells him a certain way you might think about it. And when Newton hears that, he recognizes that there is a way to inject time that would enable him to solve certain problems. It's not that there was anything he thought before that was contrary to that way of thinking. It's just that that particular technical insight was not something that, for a lot of reasons that are complex, had never occurred to him at all. And that sent him a different way of thinking. But to answer your question about the Apple business, which is always about gravity and the moon and all of that being, no. The reason there is that the idea that what goes on here in the neighborhood of the Earth and what goes on at the moon, let us say, never mind the sun and the planet, can be due to a direct relationship between the Earth, let's say, and the moon, is contrary to fundamental beliefs held by many of the mechanical philosophers, as they're called at the time, in which everything has to involve at least a sequence of direct contacts. Has to be something between here and there that's involved. And Hooke, probably not thinking terribly deeply about it based on what he said, along with others, like the architect and mathematician Christopher Wren, hearkened back to the notion that, well, maybe there is a kind of magnetic relationship between the moon and maybe the planets and the Earth and gravity and so on. Vague, but establishing a direct connection somehow, however it's happening, forget about it. Newton wouldn't have cared about that if that's all they said, but it was when Hooke mentioned this different way of thinking about the motion, a way he could certainly have thought of, because it does not contradict anything. Newton is a brilliant mathematician, and he could see that you could suddenly start to do things with that, that you otherwise wouldn't, and this led eventually to another controversy with Hooke, in which Hooke said, well, after Newton published his great Principia, I gave him how to do this. And then Newton, of course, got ticked off about that and said, well, listen to this. I did everything, and because he had a picayune little idea, he thinks he can take credit for it. Okay. So his ability to play with his ideas mathematically is what solidified the initial intuition that you could have, was that the first time he was born the idea that you have action at a distance, that you can have forces without contact, which is another revolutionary idea? I would say that in the sense of dealing with the mechanics of force-like effects, considered to act at some distance, it is novel with both Hooke and Newton at the time. The notion that two things might interact at a distance with one another without direct contact, that goes back to antiquity. Only there it was thought of more as a sympathetic reaction to a magnet and a piece of iron. They have a kind of mutual sympathy for one another. Like what, love? What are we talking about? Well, actually, they do sometimes talk like that. That it's love. See, now I talk like that all the time. I think love is somehow, in consciousness, are forces of physics that are yet to be discovered. Okay, now there's the other side of things, which is calculus, that you began to talk about. So Newton brought a lot of things to this world. One of them is calculus. What is calculus? And what was Newton's role in bringing it to life? What was it like? What was the story of bringing calculus to this world? Well, since the publication starting many decades ago by Tom Whiteside, who's now deceased, of Newton's mathematical papers, we know a lot about how he was pushing things and how he was developing things. It's a complex question to say what calculus is. Calculus is the set of mathematical techniques that enable you to investigate what we now call functions, mathematical functions, which are continuous. That is, that are not formed out of discrete sets, like the counting numbers, for instance. Newton, there were already procedures for solving problems involving such things as finding areas under curves and tangents to curves by using geometrical structures, but only for certain limited types of curves, if you will. Newton, as a young man, we know this is what happened, is looking at a formula which involves an expansion in separate terms, polynomial terms, as we say, for certain functions. I know I don't wanna get complicated here about this, and he realizes it could be generalized, and he tries the generalization, and that leads him to an expansion formula called the binomial theorem. That enables him to move ahead with the notion that if I take something that has a certain value, and I add a little bit to it, and I use this binomial theorem and expand things out, I can begin to do new things. And the new things that he begins to do leads him to a recognition that the calculations of areas and the calculations of tangents to curves are reciprocal to one another, and the procedures that he develops is a particular form of the calculus in which he considers small increments and then continuous flows and changes of curves and so on. And we have relics of it in physics today, the notation in which you put a dot over a variable indicating the rate of change of the variable, that's Newton's original type of notation. The dot. Yeah, the dot notation. Possibly independently of Newton, because he didn't publish this thing, although he became quite well known as quite a brilliant young man, in part because people heard about his work and so on. When another young man by the name of Gottfried Leibniz visited London, and he heard about these things, it is said that he independently develops his form of the calculus, which is actually the form we use today, both in notation and perhaps in certain fundamental ways of thinking. It has remained a controversial point as to where exactly and how much independently Leibniz did it. Leibniz's aficionados think and continue to maintain he did it completely independently. Newton, when he became president of the Royal Society, put together a group to go on the attack, saying, no, he must have taken everything. We don't know. But I will tell you this. About 25 or so years ago, a scholar who's a professor at Indiana now, named Domenico Melli, got his hands on a Leibniz manuscript called the 10 Taman, which was Leibniz's attempt to produce an alternative to Newton's mechanics. And it comes to some conclusions that you have in Newton's mechanics. Well, he published that, but Melli got the manuscript. And what Melli found out was that Leibniz reverse engineered the Principia and cooked it backwards so that he could get the results he wanted. Now- That was for the mechanics. So that means his mind allows for that kind of thing. Some people- You're breaking some news today. You're starting some old drama. Some people think so. I think most historians of mathematics do not agree with that. A friend of mine, rather well-known physicist, unfortunately died a couple of years ago, named Mike Nauenberg at UC Santa Cruz, had some evidence along those lines. Didn't pass mustard with many of my friends who are historians of math. In fact, I edit with a historian of math a technical journal, and we were unable to publish it in there because we couldn't get it through any of our colleagues. But I remain suspicious. What is it about those tense relationships and that kind of drama? Einstein doesn't appear to have much of that drama. Nobody claimed, I haven't heard claims that they've, perhaps because it's such crazy ideas, of any of his major inventions, major ideas, being those that are, basically, I came up with it first or independently. There's not, as far as I'm aware, not many people talk about general relativity, especially in those terms. But with Newton, that was the case. I mean, is that just a natural outgrowth of how science works? Is there going to be personalities that, but I'm not saying this about Leninists, but maybe I am, that there's people who steal ideas for the, because of ego, because of all those kinds of things. I don't think it's all that common, frankly. The Newton hook, Leibniz, Contre-Tombs, and so on. Well, you're at the beginnings of a lot of things there, and so on. These are difficult and complex times as well. These are times in which science as an activity pursued by other than, let us say, interested aristocrats, is becoming something somewhat different. It's not a professional community of investigators in the same way. It's also a period in which procedures and rules, or practice are being developed to avoid attacking one another directly and pulling out a sword to cut off the other guy's head if he disagrees with you, and so on. So it's a very different period. Controversies happen, people get angry. I can think of a number of others, including in the development of optics in the 19th century, and so on. And it can get hot under the collar. Sometimes one character who's worked an area extensively, whether they've come up with something terribly novel or not, and somebody else kind of moves in and does completely different novel things, the first guy gets upset about it because he's sort of muscled into what I thought was my area. You find that sort of stuff. But do you have examples of cases where it worked out well? Like that competition is good for the progress of science? Yeah, it almost always is good in that sense. Just painful for the individuals involved. Can be, yeah. It doesn't have to be nasty, although sometimes it is. So on the space, like for the example of the optics, could you comment on that one? Well, yeah, sure. I mean, there are several, but I could give you... All right, so I'll give you this example that probably is the most pertinent. The first polytechnic school, like MIT or Caltech, was actually founded in France during the French Revolution. It exists today. It's the École Polytechnique. Two people who were there were two young men in the 90s, 1790s, named on the one hand, François Arago and the other, Jean-Baptiste Biot. They both lived a long time, well into the 1850s. Arago became a major administrator of science and Biot's career started to peter out after about the late teens. Now, they are sent on an expedition, which was one of the expeditions involving measuring things to start the metric system. There's a lot more to that story. Anyway, they come back, Arago gets separated. He's captured by pirates, actually. Wounds up in Tangier, escapes, is captured again. Everybody thinks he's dead. He gets back to Paris and so on. He's greeted as a hero and whatnot. In the meantime, Biot has pretty much published some of the stuff that he's done and Arago doesn't get much credit for it and Arago starts to get very angry. Biot is known for this kind of thing. So Arago, anyway, Biot starts investigating a new phenomenon in optics involving something called polarization. And he writes all kinds of stuff on it. Arago looks into this and decides to write some things as well. And actually, Biot gets mostly interested in it when he finds out that Arago is doing stuff. Now, Biot is actually the better scientist in a lot of ways. But Arago is furious about this. So furious that he actually demands and forces the leader of French science, Laplace, the Marquis de Laplace, and cohorts to write a note in the published journal saying, oh, excuse us, actually Arago, et cetera, et cetera. Blah, blah. So Arago continues to just hold this antipathy and fear of Biot. So what happens? 1815, Napoleon is finished at Waterloo. A young Frenchman by the name of Augustin Fresnel who's in the army is going back to his home on the north coast of France in Normandy, passes through Paris. Arago is friends with Fresnel's uncle who's the head of the École des Beaux-Arts at the time. Anyway, Fresnel is already interested in certain things in light. And he talks to Arago. Arago tells him a few things. Fresnel goes home. And Fresnel is a brilliant experimenter. He observes things and he's a very good mathematician, calculates things. He writes something up. He sends it to Arago. Arago looks at it. And Arago says to himself, I can use this to get back at Biot. He brings Fresnel to Paris, sets him up in a room at the observatory where Arago is for Fresnel to continue his work. Paper after paper comes out. Undercutting everything Biot had done. What is it about jealousy and just envy that could be an engine of creativity and productivity? Versus like an Einstein where it seems like not. I don't know which one is better. I guess it depends on the personality. Both are useful engines in science. Well, in this particular story, it's maybe even more interesting because Fresnel himself, the young guy, he knew what Arago was doing with him and he didn't like it. He didn't want to get with, he wrote his brother, said, I don't want to get in an argument with Biot. I just want to do my stuff. Arago is using him, but it's because Arago kept pushing him to go into certain areas that stuff kept coming out. Yeah. Ego is beautiful. Okay, but back to Newton. There's a bunch of things I want to ask, but sort of, let's say, since we're on the Leibniz and the topic of drama, let me ask another drama question. Why was Newton a complicated man? We're breaking news today. This is like. I am right, why was he complicated? It's like. His brain structure was different. I don't know why. He had a complicated young life, as we've said. He had always been very self-contained and solitary. He had acquaintances and friends, and when he moved to London eventually, he had quite a career. A career, for instance, that led him, when he was famous by then, the 1690s, he moves to London. He becomes first warden of the Mint. The Mint is what produces coins, and coinage was a complicated thing because there was counterfeiting going on, and he becomes master of the Mint to the extent, and a guy at MIT wrote a book about this a little bit. We wrote something on it, too. I forget his name was Levin, that Newton sent investigators out to catch these guys and sent at least one of them, a famous one named Challoner, to the gallows. So he was, and one of the reasons he probably was so particularly angry at Challoner was Challoner had apparently said some nasty things about Newton in front of Parliament at some point. Fair enough, yeah. That was apparently not a good idea. Well, he had a bit of a temper, so Newton had a bit of a temper. Clearly, clearly. But he even, as a young man at Cambridge, at Cambridge, though he doesn't come from wealth, he attracts people who recognize his smarts. There's a young fellow named Humphrey Newton, shared his rooms, you know, these students always shared rooms with one another, became his kind of amanuensis to write down what Newton was doing, and so on. And there were others over time who he befriended in various ways, and so on. He was solitary. He had, as far as we know, no relationships with either women or men in anything other than a formal way. The only- Those get in the way, relationships. Right, well, I mean, he was, I don't know if he was close to his mother. I mean, she passed away, everything left him. He went to be with her after she died. He was close to his niece, Catherine Barton, who basically came to run his household when he moved to London, and so on. And she married a man named Conduit, who became one of the people who controlled Newton's legacy later on, and so on. So he, and you can even see the house, the townhouse that Newton lived in in those days, still there. So there's the story of Newton coming up with quite a few ideas during a pandemic. We're on the outskirts of a pandemic ourselves. Right. And a lot of people use that example as motivation for everybody while they're in lockdown to get stuff done. So what's that about? Can you tell the story of that? Well, I can. Let me first say that, of course, we've been teaching over Zoom lately. There was no Zoom back then? There was no Zoom back then. Although it wouldn't have made much difference because the story was Newton was so complicated in his lectures that at one point, Humphrey Newton actually said that he might as well have just been lecturing to the walls because nobody was there to listen to it. So what difference? But- Also not a great teacher, huh? If you look at his optical notes, if that's what he's reading from- Oh boy, okay. No. So what can you say about that whole journey through the pandemic that resulted in so much innovation in such a short amount of time? Well, I mean, there's two times that he goes home. Would he have been able to do it and do do it if he'd stayed at Cambridge? I think he would have. I don't think it really, although I do like to tell my advanced students when I lecture on the history of physics to the physics and chemistry students, especially we've been doing it over Zoom in the last year, when we get to Newton and so on, because these kids are 21, 22, I like to say, well, you know, when Newton was your age and he had to go home during an epidemic, do you know what he produced? So can you actually summarize this for people who don't know how old was Newton and what did he produce? Well, Newton goes up to Cambridge, as it said, when he's 18 years old in 1660. And the so-called miraculous year, the annus mirabilis, where you get the development in the calculus and in optical discoveries especially, is 1666, right? So he's what, 24 years old at the time. But judging from his, the notebooks that I mentioned, he's already before that come to an awful lot of developments over the previous couple of years. Doesn't have much to do with the fact that he twice went home. It is true that the optical experiments that we talked of a while ago with the light on the wall moving up and down were done at home. In fact, you can visit the very room he did it in to this day. Yeah, it's very cool. And if you look through the window in that room, there is an apple tree out there in the garden. So you might be wrong about this. You're lying to me. Maybe there's an apple involved after all. Well, it's not the same apple tree, but it's cuttings. How do you know? They don't last that long, but it's 400 years ago. Oh, not this. Oh, wow, I continue with the dumbest questions. Okay, so you're saying that perhaps going home was not. It may have given him an opportunity to work things through. And after all, he did make use of that room and he could do things like put a shade over the window, move things around, cut holes in it and do stuff. Probably in his rooms at Cambridge, maybe not. Although when he stayed at Cambridge, subsequently became a fellow. And then the first, actually the second Lucasian professor there, he was actually really the first one because Isaac Barrow, who was the mathematician, professor of optics, recognized Newton's genius, gave up what would have been his position because he recognized, Newton may not have learned too much from him, although they did interact. And so Newton was the first Lucasian professor really, the one that Stephen Hawking held till he died. And we know that the rooms that he had there at Cambridge, subsequently, those rooms are still there. He built an all chemical furnace outside, did all sorts of stuff in those rooms. And don't forget, you didn't have to do too much as a Lucasian professor. Every so often you had to go give these lectures, whether anybody was there or not, and deposit the notes for the future, which is how we have all those things. Oh, they were stored and now we have them. And now we know just how terrible of a teacher Newton was. Yeah, but we know how brilliant these notes are. In fact, the second volume of Newton's, of the notes really on the great book that he published, the optics, which he published in 1704, that has just been finished with full annotations and analysis by the greatest analyst of Newton's optics, Alan Shapiro, who retired a few years ago at the University of Minnesota and been working on Newton's optics ever since I knew him and before, and I've known him since 1976. Is there something you could say broadly about either that work on optics or Principia itself as something that I've never actually looked at as a piece of work? Is it powerful in itself or is it just an important moment in history in terms of the amount of inventions that are within, the amount of ideas that are within? Or is it a really powerful work in itself? Well, it is a powerful work in itself. You can see this guy coming to grips with and pushing through and working his way around complicated and difficult issues, melding experimental situations which nobody had worked with before, even discovering new things, trying to figure out ways of putting this together with mathematical structures, succeeding and failing at the same time. And we can see him doing that. I mean, what is contained within Principia? I don't even know, in terms of the scope of the work. All right. The entirety of the body of work of Newton? No, no, no, no, no. The Principia Mathematica. Is a calculus. Well, all right. So the Principia is divided into three books. Excellent. Book one contains his version of the laws of motion and the application of those laws to figure out when a body moves in certain curves and is forced to move in those curves by forces directed to certain fixed points, what is the nature of the mathematical formula for those forces? That's all that book one is about. And it contains not the kind of version of the calculus that uses algebra of the sort that I was trying to explain before, but is done in terms of ratios between geometric line segments when one of the line segments goes very, very small. It's called the kind of limiting procedure, which is calculus, but it's a geometrically structured, although it's clearly got algebraic elements in it as well. And that makes the Principia's mathematical structure rather hard for people who aren't studying it today to go back to. Book two contains his work on what we now call hydrostatics and a little bit about hydrodynamics, a fuller development of the concept of pressure, which is a complicated concept. And book three applies what he did in book one to the solar system. And it is successful partially because the only way that you can exactly solve, the only types of problems you can exactly solve in terms of the interactions of two particles governed by gravitational force between them is for only two bodies. If there's more than two, let's say it's A, B, and C, A acts on B, B acts on C, C acts on A, you cannot solve it exactly, you have to develop techniques. The fullest sets of techniques are really only developed about 30 or 40 years after Newton's death by French mathematicians like Laplace. Newton tried to apply his structure to the sun, earth, moon, because the moon's motion is very complicated. The moon, for instance, exactly repeats its observable position among the stars only every 19 years. That is, if you look up where the moon is among the stars at certain times, and it changes, it's complicated. That's by the way, that was discovered, that was discovered by the Babylonians. That fact, the 19 years. Thousands of years ago, yes. And then you have that little piece of data, and how do you make sense of it? I mean, that is data, and you have to. And it's complicated. So Newton actually kind of reverse engineered a technique that had been developed by a man named Horrocks using certain laws of Kepler's to try and get around this thing, and Newton then sort of, my understanding, I've never studied this, has sort of reversed it and fit it together with his force calculations by way of an approximation. And was able to construct a model to make some predictions? It fit things backwards pretty well. Okay, where does data fit into this? We kind of earlier in the discussion mentioned data as part of the scientific method. How important was data to Newton? So like you mentioned Prism and playing with it and looking at stuff, and then coming up with calculations and so on. Where does data fit into any of his ideas? All right, well, let me say two things first. One, we rarely use the phrase scientific method anymore because there is no one easily describable such method. I mean, humans have been playing around with the world and learning how to repetitively do things and make things happen ever since humans became humans. The question is- Do you have a preferred definition of the scientific method? What are the various- No, I don't. I prefer to talk about the considered manipulation of artificial structures to produce results that can be worked together with schemes to construct other devices and make predictions, if you will, about the way such things will work. So ultimately it's about producing other devices. It's like leads you down a- I think so, principally. I mean, you may have data, if you will, like astronomical data obtained otherwise and so on, but yes. But number two here is this question of data. What is data in that sense? See, when we talk about data today, we have a kind of complex notion which reverts to even issues of statistics and measurement procedures and so on. So let me put it to you this way. So let's say I had a ruler in front of me, go on, and it's marked off in little black marks separated by, let's say, distances called a millimeter. Okay? Now I make a mark on this piece of paper here. So I made a nice black mark, right? Nice black mark. And I ask you, I want you to measure that and tell me how long it is. You're gonna take the ruler, you're gonna put it next to it, and you're gonna look, and it's not gonna sit, even if you put one end as close as you can on one black mark, the other end probably isn't gonna be exactly on a black mark. Well, you'll say it's closer to this or that. You'll write down a number. And I say, okay, take the ruler away a minute. I take this away. Come back in five minutes. Put the piece of paper down, do it again. You're gonna probably come up with a different number. And you're gonna do that a lot of times. And then if I tell you, I want you to give me your best estimate of what the actual length of that thing is, what are you gonna do? You're going to average all of these numbers. Why? Statistics. Well, yes, statistics. There's lots of ways of going around it, but the average is the best estimate on the basis of what's called the central limit theorem, a statistical theorem. We are talking about things that were not really developed until the 1750s, 60s, and 70s. Newton died in 1727. The intuition perhaps was there. Not really. I'll tell you what people did, including Newton, although Newton is partially the one exception. We talked a while ago about this guy, Christian Huygens. He measured lots of things, and he was a good mechanic himself. He and his brother ground lenses. Huygens, I told you, developed the first pendulum mechanism, pendulum-driven clock with a mechanism and so on. Also, a spring watch, where he got into a controversy with Hooke over that, by the way. What's with these mechanics and the controversy? Yeah. Well, we also have Huygens' notes. They're preserved at Leiden University in Holland. He's Dutch. For his work in optics, which was extensive. We don't have time to go into that, except the following. Number of years ago, I went through those things, because in this optical theory that he had, there are four numbers that you've got to be able to get good numbers on to be able to predict other things. So what would we do today? What, in fact, was done at the end of the 18th century when somebody went back to this? You do what you just, I told you to do with the ruler. You make a lot of measurements and average results. We have Huygens' notes. He did make a lot of measurements. One after the other after the other. But when he came to use the numbers for calculations, and indeed when he published things at the end of his life, he gives you one number, and it's not the average of any of them. It's just one of them. Which one was it? The one that he thought he got so good at working by practice that he put down the one he was most confident in. That was the general procedure at the time. You wouldn't publish a paper in which you wrote down six numbers and said, well, I measured this six times. Let me put them together. None of them is really, they would have said, the right number, but I'll put them together and give you a good number. No, you would have been thought of that, you know, you don't know what you're doing. Yeah. By the way, there's just an inkling of value to that approach. Just an inkling. We sometimes use statistics as like a thing that like, oh, that solves all the problems. We'll just do a lot of it and we'll take the average, or whatever it is, as many excellent books on mathematics have highlighted the flaws in our approach to certain sciences that rely heavily on statistics. Okay, let me ask you again for a friend about this alchemy thing. You know, it'd be nice to create gold, but it also seems to come into play quite a bit throughout the history of science, perhaps in positive ways in terms of its impact. Can you say something to the history of alchemy? A little bit. And its impact? Sure. It used to be thought, two things. One, that alchemy, which dates certainly back to the Islamic period in Islam, you're talking, you know, 11th, 12th, 13th centuries among Islamic natural philosophers and experimenters. But it used to be thought that alchemy, which picked up strikingly in the 15th, 16th century, 1500s and thereabouts, was a sort of mystical procedure involving all sorts of strange notions and so on. And that's not entirely untrue, but it is substantially untrue in that alchemists were engaged in what was known as chrysopoea, that is, looking for ways to transform invaluable materials into valuable ones. But in the process of doing so, or attempting to do so, they learned how to create complex amalgams of various kinds. They used very elaborate apparatus, glass alembics in which they would use heat to produce chemical decompositions. They would write down and observe these compositions. And many of the so-called really strange-looking alchemical formulas and statements where they'll say something like, I can't produce it, but it'll be, the soul of Mars will combine with this, et cetera, et cetera. These, it has been shown, are almost all actual formulas for how to engage in the production of complex amalgams and what to do. And by the time of Newton, Newton was reading the works of a fellow by the name of Starkey, who was actually, came from Harvard shortly before, in which things had progressed, if you will, to the point where the procedure turns into what historians call chrysopoea, which basically runs into the notion of thinking that these things are made out of particles. This is the mechanical philosophy. Can we engage in processes, chemical processes, to rearrange these things, which is not so stupid after all. I mean, we do it, except we happen to do it in reactors, not in chemical processes, unless, of course, it had happened that cold fusion had worked, which it didn't. Well, right. But, so that's the way they're thinking about these things. There's a kind of mix. And Newton engages extensively in those sorts of manipulations. In fact, more in that than almost anything else, except for his optical investigations. If you look through the latter parts of the 1670s, the last five, six, seven years or so of that, there's more on that than there is on anything else. He's not working on mechanics. He's pretty much gone pretty far in optics. He'll turn back to optics later on. So optics and alchemy, so what you're saying is Isaac Newton liked shiny things. Well, actually, if you go online and look at what Bill Newman, the professor at Bloomington, Indiana, has produced, you'll find the very shiny thing called the star regulus, which Newton describes as having produced according to a particular way, which Newman figured out and was able to do it. And it's very shiny. There you go, proves the theorem. Can I ask you about God, religion, and its role in Newton's life? Was there helpful, constructive, or destructive influences of religion in his work and in his life? Well, there you begin to touch on a complex question. The role that God played would be an interesting question to answer should one go and be able to speak with this invisible character who doesn't exist. But putting that aside for the moment. Yeah, we don't like to talk about others while they're not here, so. Right. Newton is a deeply religious man, not unusually so, of course, for the assignment. And clearly his upbringing, and perhaps his early experiences have exacerbated that in a number of ways, that he takes a lot of things personally, and he finds perhaps solace in thinking about a sort of governing, abstract, rulemaking, exacting deity. I think there is little question that his conviction that you can figure things out has a fair bit to do with his profound belief that this rulemaker doesn't do things arbitrarily. Newton does not think that miracles have happened since maybe the time of Christ, if then, and not in the same way. He was, for instance, an anti-Trinitarian. He did not hold that Christ had a divine being, but was rather endowed with certain powers by the rulemaker and whatnot. And he did not think that some of the tales of the Old Testament with various miracles and so on occurred in anything like that way. Some may have, some may not have. Like everybody else, of course, he did think that creation had happened about 6,000 years ago. Wait, really? Oh yeah, sure. Well, biblical chronology can give you a little bit about that. It's a little controversial, but sure. Interesting, wow. The deity created the universe 6,000 years ago. And that didn't interfere with his playing around with the sun and the moon and the network? Oh no, because he's figuring out, he's watching the brilliant construction that this perfect entity. Did 6,000 years ago. Yeah, has produced. Plus or minus a few years. Well, if you go with Bishop Bosh, sir, it's 4004 BCE. Want to be precise about it. We always, and this is a serious program, we always want to be precise. Okay, let me ask another ridiculous question. If Newton were to travel forward in time and visit with Einstein and have a discussion about space-time and general relativity, that conception of time, that conception of gravity, what do you think that discussion would go like? Put that way, I think Newton would sit there in shock and say, I have no idea what you're talking about. If, on the other hand, there's a time machine, you go back and bring a somewhat younger Newton, not a man my age, say. I mean, he lived a long time, into his mid-80s. But take him when he's in his 40s, let's say. Bring him forward and don't immediately introduce him to Einstein. Let's take him for a ride on a railroad. Let him experience the railroad. Oh, that's right. Take him around and show him a sparking machine. He knows about sparks. Sending off sparks. Show him wires, have him touch the wires and get a little shock. Show him a clicking telegraph machine of the kind. Then let him hear the clicks in a telephone receiver and so on. Do that for a couple of months. Let him get accustomed to things. Then take him into, not Einstein yet, let's say we're taking him into the 1890s. Einstein is a young man then. We take him into some of the laboratories. We show him some of the equipment, the devices. Not the most elaborate ones. We show him certain things. We educate him bit by bit. Well, the optics, maybe focus on that. Certainly on optics. You begin to show him things. He's a brilliant human being. I think bit by bit, he would begin to see what's going on. But if you just dumped him in front of Einstein, he'd sit there, his eyes would glaze over. I mean, I guess it's almost a question of how big of a leap, how many leaps have been taken in science that go from Newton to Einstein. We sometimes in a compressed version of history think that not much. Oh, that's totally wrong. A lot. Huge amounts in multifarious ways involving fundamental conceptions, mathematical structures, the evolution of novel experimentation and devices, the organization of science, everything. Everything. I mean, to a point where I wonder even if Newton was like, you said 40, but even like 30. So he's very, like if he would be able to catch up with the conception of everything. I wonder as a scientist, how much you load in from age five about this world in order to be able to conceive of the world of ideas that push that science forward. I mean, you mentioned the railroad and all those kinds of things. That might be fundamental to our ability to invent even when it doesn't directly obviously seem relevant. Well, yes. I mean, the railroad, the steam engine, the Watt engine, et cetera. I mean, that was really the Watt engine, you know, was developed pretty, although Watt knew Joseph Black, a chemist, scientist, and so on, did stuff on heat, was developed pretty much independently of the developing thoughts about heat at the time, but what it's not independent of is the evolution of practice in the manufacture and construction of devices, which can do things in extraordinarily novel ways, and the premium being gradually placed on calculating how you can make them more efficient. That is of a piece with a way of thinking about the world in which you're controlling things and working it. It's something that humans have been doing for a long time, but in this more concerted and structured way, I think you really don't find it in the fullest sense until well into the 1500s, and really not fully until the 17th century later on. So Newton had this year of miracles. I wonder if I could ask you briefly about Einstein and his year of miracles. I've been reading, rereading, revisiting the brilliance of the papers that Einstein published in the year 1905, one of which won him the Nobel Prize, the photoelectric effect, but also Brownian motion, special theory of relativity, and of course the old E equals MC squared. Is there, does that make sense to you that these two figures had such productive years that there's this moment of genius? Maybe if we zoom out, I mean, my work is very much in artificial intelligence, so wondering about the nature of intelligence. Like how did evolution on Earth produce genius that could come up with so much in so little time? To me, that gives me hope that one person can change the world in such a small amount of time. Well, of course, there are precedents for, in both Newton's and Einstein's cases, for elements of what we're finding there, and so on. Well, I have no idea. You know, I'm sure you must have read, it was kind of a famous story that after Einstein died, he donated his brain and they sliced it up to see if they could find something unusual there, nothing unusual visibly in there. So I have, clearly there are people who for various reasons, maybe both intrinsic and extrinsic in the sense of experience and so on, are capable of coming up with these extraordinary results. Many years ago, when I was a student, a friend of mine came in and said, did you read about, did you read this? I forget what, anyway, there was a story in the paper. It was about, I think it was a young woman who was, she couldn't speak, and she was somewhere on the autism spectrum. She could not read other people's affect in any ways, but she could sit down at a piano, and having heard it once, and then run variations on the most complex pianistic works of Chopin and others. Now how? Some aspect of our mind is able to tune in in some aspect of reality and become a master of it, and every once in a while, that means coming up with breakthrough ideas in physics. Yeah, how the heck does that happen? Who knows? Jed, I'd like to say thank you so much for spending your valuable time with me today. That was a really fascinating conversation. I've learned so much about Isaac Newton, who's one of the most fascinating figures in human history, so thank you so much for talking to me. A pleasure, enjoyed it very much. Thanks for listening to this conversation with Jed Buchwald. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Thomas Kuhn, a philosopher of science. The answers you get depend on the questions you ask. Thank you for listening, and hope to see you next time.

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Jack Dorsey: Square, Cryptocurrency, and Artificial Intelligence | Lex Fridman Podcast #91

The following is a conversation with Jack Dorsey, co-founder and CEO of Twitter and founder and CEO of Square. Given the happenings at the time related to Twitter leadership and the very limited time we had, we decided to focus this conversation on Square and some broader philosophical topics and to save an in-depth conversation on engineering and AI at Twitter for a second appearance in this podcast. This conversation was recorded before the outbreak of the pandemic. For everyone feeling the medical, psychological, and financial burden of this crisis, I'm sending love your way. Stay strong. We're in this together. We'll beat this thing. As an aside, let me mention that Jack moved $1 billion of Square equity, which is 28% of his wealth, to form an organization that funds COVID-19 relief. First, as Andrew Yang tweeted, this is a spectacular commitment. And second, it is amazing that it operates transparently by posting all its donations to a single Google Doc. To me, true transparency is simple, and this is as simple as it gets. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with 5 Stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Masterclass. Sign up on masterclass.com slash Lex to get a discount and to support this podcast. When I first heard about Masterclass, I thought it was too good to be true. For $180 a year, you get an all-access pass to watch courses from, to list some of my favorites, Chris Hadfield on space exploration, Neil deGrasse Tyson on scientific thinking and communication, Will Wright, creator of SimCity and Sims, both one of my favorite games on game design, Jane Goodall on conservation, Carlos Santana on guitar, one of my favorite guitar players, Gary Kasparov on chess, Daniel Negrano on poker, and many, many more. Chris Hadfield explaining how rockets work and the experience of being launched into space alone is worth the money. For me, the key is to not be overwhelmed by the abundance of choice. Pick three courses you want to complete. Watch each all the way through. It's not that long, but it's an experience that will stick with you for a long time. It's easily worth the money. You can watch it on basically any device. Once again, sign up on masterclass.com slash Lex to get a discount and to support this podcast. And now, here's my conversation with Jack Dorsey. You've been on several podcasts, Joe Rogan, Sam Harris, Rich Roll, others, excellent conversations, but I think there's several topics that you didn't talk about that I think are fascinating that I'd love to talk to you about, sort of machine learning, artificial intelligence, both the narrow kind and the general kind, and engineering at scale. So there's a lot of incredible engineering going on that you're a part of, crypto, cryptocurrency, blockchain, UBI, all kinds of philosophical questions maybe we'll get to about life and death and meaning and beauty. So you're involved in building some of the biggest network systems in the world, sort of trillions of interactions a day. The cool thing about that is the infrastructure, the engineering at scale. You started as a programmer with C. A hacker. Building. Yeah. I'm a hacker. I'm not really an engineer. Not a legit software engineer. You're a hacker at heart. But to achieve scale, you have to do some, unfortunately, legit large-scale engineering. So how do you make that magic happen? I hire people that I can learn from, number one. I mean, I'm a hacker in the sense that my approach has always been do whatever it takes to make it work so that I can see and feel the thing and then learn what needs to come next. And oftentimes what needs to come next is a matter of being able to bring it to more people, which is scale. And there's a lot of great people out there that either have experience or are extremely fast learners that we've been lucky enough to find and work with for years. But I think a lot of it, we benefit a ton from the open source community and just all the learnings there that are laid bare in the open. All the mistakes, all the success, all the problems. It's a very slow moving process, usually, open source, but it's very deliberate. And you get to see because of the pace, you get to see what it takes to really build something meaningful. So I learned most of everything I learned about hacking and programming and engineering has been due to open source and the generosity that people have given to give up their time, sacrifice their time without any expectation in return, other than being a part of something much larger than themselves, which I think is great. The open source movement is amazing. But if you just look at the scale, like Square has to take care of, is this fundamentally a software problem or hardware problem? You mentioned hiring a bunch of people, but it's not, maybe from my perspective, not often talked about how incredible that is to sort of have a system that doesn't go down often, that is secure, is able to take care of all these transactions. Like maybe I'm also a hacker at heart and it's incredible to me that that kind of scale could be achieved. Is there some insight, some lessons, some interesting insights that you can say about how to make that scale happen? Is it the hardware fundamentally challenge? Is it a software challenge? Is it a social challenge of building large teams of engineers that work together? That kind of thing. Like what's the interesting challenges there? By the way, you're the best trust hacker I've met. Thank you. I think the unique thing about the open source movement is that it's not just about the software. If the enumeration you just went through, I don't think there's one. You have to kind of focus on all and the ability to focus on all that really comes down to how you face problems and whether you can break them down into parts that you can focus on. Because I think the biggest mistake is trying to solve or address too many at once or not going deep enough with the questions or not being critical of the answers you find or not taking the time to form credible hypotheses that you can actually test and you can see the results of. So all of those fall in the face of ultimately critical thinking skills, problem solving skills. And if there's one skill I want to improve every day, it's that. That's what contributes to learning. And the only way we can evolve any of these things is learning what it's currently doing and how to take it to the next step. And questioning assumptions, the first principles kind of thinking. Yeah. Seems like fundamental to this whole process. Yeah. But if you get too overextended into, well, this is a hardware issue, you miss all the software solutions and vice versa. If you focus too much on the software, our hardware solutions that can 10x the thing. So I try to resist the categories of thinking and look for the underlying systems that make all these things work. But those only emerge when you have a skill around creative thinking, problem solving, and being able to ask critical questions and having the patience to go deep. So one of the amazing things, if we look at the mission of Square, is to increase people's access to the economy. Maybe you can correct me if I'm wrong, that's from my perspective. So from the perspective of merchants, peer-to-peer payments, even crypto, cryptocurrency, digital cryptocurrency, what do you see as the major ways our society can increase participation in the economy? So if we look at today and the next 10 years, next 20 years, you go into Africa, maybe in Africa and all kinds of other places outside of the North America. If there was one word that I think represents what we're trying to do at Square, it is that word access. One of the things we found is that we weren't expecting this at all. When we started, we thought we were just building a piece of hardware to enable people to plug it into their phone and swipe a credit card. And then as we talked with people who actually tried to accept credit cards in the past, we found a consistent theme, which many of them weren't even enabled, not enabled, but allowed to process credit cards. And we dug a little bit deeper, again, asking that question. And we found that a lot of them would go to banks or these merchant acquirers and waiting for them was a credit check and looking at a FICA score. And many of the businesses that we talked to and many small businesses, they don't have good credit or a credit history. They're entrepreneurs who are just getting started, taking a lot of personal risk, financial risk. And it just felt ridiculous to us that for the job of being able to accept money from people, you had to get your credit checked. And as we dug deeper, we realized that that wasn't the intention of the financial industry, but it's the only tool they had available to them to understand authenticity, intent, predictor of future behavior. So that's the first thing we actually looked at. And that's where we built the hardware, but the software really came in terms of risk modeling. And that's when we started down the path that eventually leads to AI. We started with a very strong data science discipline because we knew that our business was not necessarily about making hardware. It was more about enabling more people to come into the system. So the fundamental challenge there is to enable more people to come into the system, you have to lower the barrier of checking that that person will be a legitimate vendor. Is that the fundamental problem? Yeah. And a different mindset. I think a lot of the financial industry had a mindset of kind of distrust and just constantly looking for opportunities to prove why people shouldn't get into the system. Whereas we took on a mindset of trust and then verify, verify, verify, verify, verify. So when we entered the space, only about 30 to 40% of the people who applied to accept credit cards would actually get through the system. We took that number to 99%. And that's because we reframed the problem. We built credible models. And we had this mindset of we're going to watch not at the merchant level, but we're going to watch at the transaction level. So come in, perform some transactions. And as long as you're doing things that feel high integrity, credible, and don't look suspicious, we'll continue to serve you. If we see any interestingness in how you use our system, that will be bubbled up to people to review, to figure out if there's something nefarious going on. And that's when we might ask you to leave. So the change in the mindset led to the technology that we needed to enable more people to get through and to enable more people to access the system. What role does machine learning play into that in that context of, you said, first of all, that's a beautiful shift. Anytime you shift your viewpoint into seeing that people are fundamentally good, and then you just have to verify and catch the ones who are not, as opposed to assuming everybody's bad, this is a beautiful thing. So what role does the, to you, throughout the history of the company has machine learning played in doing that verification? It was immediate. I mean, we weren't calling it machine learning, but it was data science. And then as the industry evolved, machine learning became more of the nomenclature. And as that evolved, it became more sophisticated with deep learning. And as that continues to evolve, it'll be another thing, but they're all in the same vein. But we built that discipline up within the first year of the company. Because we also had, we had to partner with the bank, we had to partner with Visa MasterCard, and we had to show that by bringing more people into the system, that we could do so in a responsible way that would not compromise their systems and that they would trust us. How do you convince this upstart company with some cool machine learning tricks is able to deliver on the sort of a trustworthy set of merchants? We staged it out in tiers. We had a bucket of 500 people using it, and then we showed results, and then a thousand, and then 10,000, then 50,000, and then the constraint was lifted. So again, it's kind of getting something tangible out there. I want to show what we can do rather than talk about it. And that put a lot of pressure on us to do the right things. And it also created a culture of accountability, of a little bit more transparency, and I think incentivized all of our early folks and the company in the right way. So what does the future look like in terms of increasing people's access? Or if you look at IoT, Internet of Things, there's more and more intelligent devices. You can see there's some people even talking about our personal data as a thing that we could monetize more explicitly versus implicitly. Sort of everything can become part of the economy. Do you see... So what does the future of Square look like in sort of giving people access in all kinds of ways to being part of the economy as merchants and as consumers? I believe that the currency we use is a huge part of the answer, and I believe that the Internet deserves and requires a native currency. And that's why I'm such a huge believer in Bitcoin, because it just... Our biggest problem as a company right now is we cannot act like an Internet company. To open a new market, we have to have a partnership with a local bank. We have to pay attention to different regulatory onboarding environments. And a digital currency like Bitcoin takes a bunch of that away where we can potentially launch a product in every single market around the world, because they're all using the same currency. And we have consistent understanding of regulation and onboarding and what that means. So I think the Internet can do a lot of things. I think the Internet continuing to be accessible to people is number one. And then I think currency is number two. And it will just allow for a lot more innovation, a lot more speed in terms of what we can build and others can build. And it's just really exciting. So I mean, I want to be able to see that and feel that in my lifetime. So in this aspect and other aspects, you have a deep interest in cryptocurrency and distributed ledger tech in general. I talked to Vitalik Buterin yesterday on this podcast. He says hi, by the way. He's a brilliant, brilliant person. Talked a lot about Bitcoin and Ethereum, of course. So can you maybe linger on this point? What do you find appealing about Bitcoin, about digital currency? Where do you see it going in the next 10, 20 years? And what are some of the challenges with respect to Square, but also just bigger for globally, for our world, for the way we think about money? I think the most beautiful thing about it is there's no one person setting the direction. And there's no one person on the other side that can stop it. So we have something that is pretty organic in nature and very principled in its original design. And I think the Bitcoin white paper is one of the most seminal works of computer science in the last 20, 30 years. It's poetry. I mean, it really is. It's pretty cool technology. I mean, that's not often talked about. There's so much hype around digital currency about the financial impacts of it, but the actual technology is quite beautiful from a computer science perspective. Yeah. And the underlying principles behind it that went into it, even to the point of releasing it under a pseudonym. I think that's a very, very powerful statement. The timing of when it was released is powerful. It was a total activist move. I mean, it's moving the world forward in a way that I think is extremely noble and honorable and enables everyone to be part of the story, which is also really cool. So you asked a question around 10 years and 20 years. I mean, I think the amazing thing is no one knows and it can emerge. And every person that comes into the ecosystem, whether they be a developer or someone who uses it, can change its direction in small and large ways. And that's what I think it should be because that's what the internet has shown is possible. Now there's complications with that, of course. And there's certainly companies that own large parts of the internet and can direct it more than others. And there's not equal access to every single person in the world just yet, but all those problems are visible enough to speak about them. And to me, that gives confidence that they're solvable in a relatively short timeframe. I think the world changes a lot as we get these satellites projecting the internet down to earth, because it just removes a bunch of the former constraints and really levels the playing field. But a global currency, which a native currency for the internet is a proxy for, is a very powerful concept. And I don't think any one person on this planet truly understands the ramifications of that. I think there's a lot of positives to it. There's some negatives as well. But I think it's possible, sorry to interrupt. Do you think it's possible that this kind of digital currency would redefine the nature of money, sort of become the main currency of the world as opposed to being tied to fiat currency of different nations and sort of really push the decentralization of control of money? Definitely. But I think the bigger ramification is how it affects how society works. And I think there are many positive ramifications. Outside of just money. Outside of just money. Money is a foundational layer that enables so much more. I was meeting with an entrepreneur in Ethiopia, and payments is probably the number one problem to solve across the continent, both in terms of moving money across borders between nations on the continent or the amount of corruption within the current system. But the lack of easy ways to pay people makes starting anything really difficult. I met an entrepreneur who started the Lyft slash Uber of Ethiopia. And one of the biggest problems she has is that it's not easy for her riders to pay the company and it's not easy for her to pay the drivers. And that definitely has stunted her growth and made everything more challenging. So the fact that she even has to think about payments instead of thinking about the best rider experience and the best driver experience and the best driver experience is pretty telling. So I think as we get a more durable, resilient, and global standard, we see a lot more innovation everywhere. And I think there's no better case study for this than the various countries within Africa and their entrepreneurs who are trying to start things within health or sustainability or transportation or a lot of the companies that we've seen here. So the majority of companies I met in November when I spent a month on the continent were payments oriented. You mentioned, and this is a small tangent, you mentioned the anonymous launch of Bitcoin is a sort of profound philosophical statement. Pseudonymous. What's that even mean? There's a pseudonym. First of all, let me ask- There's an identity tied to it. It's not just anonymous. It's Nakamoto. So Nakamoto might represent one person or multiple people. But- Wait, let me ask, are you Satoshi Nakamoto? Just checking. If I were, what'd I tell you? Yeah, that's true. Maybe you slip. A pseudonym is constructed identity. Anonymity is just kind of this random, like, drop something off and leave. There's no intention to build an identity around it. And while the identity being built was a short time window, it was meant to stick around, I think, and to be known. And it's being honored in how the community thinks about building it. Like the concept of Satoshi's, for instance, is one such example. But I think it was smart not to do it anonymous, not to do it as a real identity, but to do it as pseudonym because I think it builds tangibility and a little bit of empathy that this was a human or a set of humans behind it. And there's this natural identity that I can imagine. But there is also a sacrifice of ego. That's a pretty powerful thing from my perspective. Yeah, which is beautiful. Would you do, sort of philosophically, to ask you the question, would you do all the same things you're doing now if your name wasn't attached to it? Sort of, if you had to sacrifice the ego, put another way, or is your ego deeply tied in the decisions you've been making? I hope not. I mean, I believe I would certainly attempt to do the things without my name having to be attached with it. But it's hard to do that in a corporation, legally. That's the issue. If I were to do more open source things, then absolutely. I don't need my particular identity, my real identity associated with it. But I think the appreciation that comes from doing something good and being able to see it and see people use it is pretty overwhelming and powerful, more so than maybe seeing your name in the headlines. Let's talk about artificial intelligence a little bit, if we could. 70 years ago, Alan Turing formulated the Turing test. To me, natural language is one of the most interesting spaces of problems that are tackled by artificial intelligence. It's the canonical problem of what it means to be intelligent. He formulated it as the Turing test. Let me ask, sort of, the broad question. How hard do you think is it to pass the Turing test in the space of language? Just from a very practical standpoint, I think where we are now, and for at least years out, is one where the artificial intelligence, machine learning, the deep learning models can bubble up interestingness very, very quickly and pair that with human discretion around severity, around depth, around nuance and meaning. I think, for me, the chasm to cross for general intelligence is to be able to explain why and the meaning behind something. Behind a decision? Mm-hmm. So being able to tell stories. Behind a decision or a set of data. Sets of data. So the explainability part is kind of essential to be able to explain using natural language why the decisions were made, that kind of thing. Yeah. I mean, I think that's one of our biggest risks in artificial intelligence going forward is we are building a lot of black boxes that can't necessarily explain why they made a decision or what criteria they used to make the decision. And we're trusting them more and more from lending decisions to content recommendation to driving to health. A lot of us have watches that tell us when to stand. How is it deciding that? I mean, that one's pretty simple. But you can imagine how complex they get. And being able to explain the reasoning behind some of those recommendations seems to be an essential part. Although it's hard. Which is a very hard problem because sometimes even we can't explain why we make decisions. That's what I was, I think we're being sometimes a little bit unfair to artificial intelligence systems because we're not very good at these, some of these things. Yeah. Do you think, I apologize for the ridiculous romanticized question, but on that line of thought, do you think we'll ever be able to build a system like in the movie Her that you could fall in love with? So have that kind of deep connection with. Hasn't that already happened? Hasn't someone in Japan fallen in love with his AI? There's always going to be somebody that does that kind of thing. I mean, at a much larger scale of actually building relationships, of being deeper connections. It doesn't have to be love, but it just deeper connections with artificial intelligence systems. So you mentioned explainability. That's less a function of the artificial intelligence and more a function of the individual and how they find meaning and where they find meaning. Do you think we humans can find meaning in technology in this kind of way? Yeah, yeah. 100%. 100%. And I don't necessarily think it's a negative, but it's constantly going to evolve. So I don't know, but meaning is something that's entirely subjective. And I don't think it's going to be a function of finding the magic algorithm that enables everyone to love it, but maybe, I don't know. But that question really gets at the difference between human and machine. You had a little bit of an exchange with Elon Musk. Basically, I mean, it's the trivial version of that, but I think there's a more fundamental question of, is it possible to tell the difference between a bot and a human? And do you think it's, if we look into the future 10, 20 years out, do you think it will be possible or is it even necessary to tell the difference in the digital space between a human and a robot? Can we have fulfilling relationships with each or do we need to tell the difference between them? I think it's certainly useful in certain problem domains to be able to tell the difference. I think in others, it might not be as useful. Do you think it's possible for us today to tell that difference? It's the reverse, the meta of the Turing test. Well, what's interesting is I think the technology to create is moving much faster than the technology to detect. You think so? So if you look at adversarial machine learning, there's a lot of systems that try to fool machine learning systems. And at least for me, the hope is that the technology to defend will always be right there, at least. Your sense is that... I don't know if they'll be right there. I mean, it's a race, right? So the detection technologies have to be two or 10 steps ahead of the creation technologies. This is a problem that I think the financial industry will face more and more because a lot of our risk models, for instance, are built around identity. Payments ultimately comes down to identity. And you can imagine a world where all this conversation around deep fakes goes towards the direction of a driver's license or passports or state identities. And people construct identities in order to get through a system such as ours to start accepting credit cards or into the cash app. And those technologies seem to be moving very, very quickly. Our ability to detect them, I think, is probably lagging at this point. But certainly with more focus, we can get ahead of it. But this is going to touch everything. So I think it's like security. We're never going to be able to build a perfect detection system. We're only going to be able to... What we should be focused on is the speed of evolving it and being able to take signals that show correctness or errors as quickly as possible and move and to be able to build that into our newer models or the self-learning models. Do you have other worries? Like some people, like Elon and others, have worries of existential threats of artificial intelligence, of artificial general intelligence, or if you think more narrowly about threats and concerns about more narrow artificial intelligence. Like what are your thoughts in this domain? Do you have concerns or are you more optimistic? I think Yuval in his book, 21 Lessons for the 21st Century, his last chapter is around meditation. And you look at the title of the chapter and you're like, oh, it's all meditation. But what was interesting about that chapter is he believes that kids being born today, growing up today, Google has a stronger sense of their preferences than they do, which you can easily imagine. I can easily imagine today that Google probably knows my preferences more than my mother does. Maybe not me per se, but for someone growing up, only knowing the internet, only knowing what Google is capable of, or Facebook or Twitter or Square or any of these things, the self-awareness is being offloaded to other systems and particularly these algorithms. And his concern is that we lose that self-awareness because the self-awareness is now outside of us and it's doing such a better job at helping us direct our decisions around, should I stand, should I walk today, what doctor should I choose, who should I date? All these things we're now seeing play out very quickly. So he sees meditation as a tool to build that self-awareness and to bring the focus back on why do I make these decisions? Why do I react in this way? Why did I have this thought? Where did that come from? That's the way to regain control. Or awareness, maybe not control, but awareness so that you can be aware that yes, I am offloading this decision to this algorithm that I don't fully understand and can't tell me why it's doing the things it's doing because it's so complex. That's not to say that the algorithm can't be a good thing. And to me, recommender systems, the best of what they can do is to help guide you on a journey of learning new ideas, of learning period. It can be a great thing, but do you know you're doing that? Are you aware that you're inviting it to do that to you? I think that's the risk he identifies, right? That's perfectly okay. But are you aware that you have that imitation and it's being acted upon? And so that's a concern. You're kind of highlighting that without a lack of awareness, you can just be like floating at sea. So awareness is key in the future of these artificial intelligence systems. The other movie, Wall-E, which I think is one of Pixar's best movies besides Ratatouille. Ratatouille was incredible. You had me until Ratatouille. Okay. Ratatouille is incredible. All right. We've come to the first point where we disagree. Okay. It's the entrepreneurial story in the form of a rat. Hmm. I just remember just the soundtrack was really good. So excellent. What are your thoughts sticking on artificial intelligence a little bit about the displacement of jobs? That's another perspective that candidates like Andrew Yang talk about. Yang gang forever. Yang gang. So he, unfortunately, speaking of Yang gang has recently dropped out. I know it was very disappointing and depressing. Yeah. But on the positive side, he's, I think, launching a podcast. So. Really? Cool. Yeah. He just announced that. I'm sure he'll try to talk you into trying to come on to the podcast. So about Ratatouille. Yeah. Maybe he'll be more welcoming of the Ratatouille argument. What are your thoughts on his concerns of the displacement of jobs of automation? Of course, there's positive impacts that could come from automation and AI, but there could also be negative impacts. And within that framework, what are your thoughts about universal basic income? So these interesting new ideas of how we can empower people in the economy. I think he was 100% right on almost every dimension. We see this in Square's business. I mean, he identified truck drivers. I'm from Missouri. And he certainly pointed to the concern and the issue that people from where I'm from feel every single day that is often invisible and not talked about enough. The next big one is cashiers. This is where it pertains to Square's business. We are seeing more and more of the point of sale move to the individual customer's hand. In the form of their phone and apps and pre-order and order ahead. We're seeing more kiosks. We're seeing more things like Amazon Go. And the number of workers as a cashier and retail is immense. And there's no real answers on how they transform their skills and work into something else. And I think that does lead to a lot of really negative ramifications. And the important point that he brought up around universal basic income is given that the shift is going to come and given it is going to take time to set people up with new skills and new careers, they need to have a floor to be able to survive. And this $1,000 a month is such a floor. It's not going to incentivize you to quit your job because it's not enough, but it will enable you to not have to worry as much about just getting on day to day so that you can focus on what am I going to do now and what skills do I need to acquire? And I think a lot of people point to the fact that during the industrial age, we had the same concerns around automation, factory lines, and everything worked out okay. But the biggest change is just the velocity and the centralization of a lot of the things that make this work, which is the data and the algorithms that work on this data. I think the second biggest scary thing is just how around AI is just who actually owns the data and who can operate on it. And are we able to share the insights from the data so that we can also build algorithms that help our needs or help our business or whatnot? So that's where I think regulation could play a strong and positive part. First, looking at the primitives of AI and the tools we use to build these services that will ultimately touch every single aspect of the human experience, and then where data is owned and how it's shared. So those are the answers that as a society, as a world, we need to have better answers around, which we're currently not. They're just way too centralized into a few very, very large companies. But I think it was spot on with identifying the problem and proposing solutions that would actually work, at least that we'd learn from that you could expand or evolve. But I mean, I think UBI is well past its due. I mean, it was certainly trumpeted by Martin Luther King and even before him as well. And like you said, the exact thousand dollar mark might not be the correct one, but you should take the steps to try to implement these solutions and see what works. Yeah, 100%. So I think you and I eat similar diets, and at least I was... The first time I've heard this. Yeah, so I was doing it before. First time anyone has said that to me in this case, anyway. Yeah, but it's becoming more and more cool. But I was doing it before it was cool. So the intermittent fasting and fasting in general, I really enjoy. I love food, but I enjoy the... I also love suffering because I'm Russian. So fasting kind of makes you appreciate what it is to be human somehow. But I have a... Outside the philosophical stuff, I have a more specific question. It also helps me as a programmer and a deep thinker, like from the scientific perspective, to sit there for many hours and focus deeply. Maybe you were a hacker before you were CEO. What have you learned about diet, lifestyle, mindset that helps you maximize mental performance to be able to focus for... To think deeply in this world of distractions? I think I just took it for granted for too long. Which aspect? Just the social structure of we eat three meals a day and there's snacks in between. And I just never really asked the question why. Oh, by the way, in case people don't know, I think a lot of people know, but you at least famously eat once a day. Yeah. You still eat once a day? Yep. I eat dinner. By the way, what made you decide to eat once a day? Because to me, that was a huge revolution that you don't have to eat breakfast. That was like, I felt like I was a rebel. Like I abandoned my parents or something and became an anarchist. When you first... The first week you start doing it, it feels you kind of like, have a superpower and then you realize it's not really a superpower. But I think you realize, at least I realized, like it just how much our mind dictates what we're possible of. And sometimes we have structures around us that incentivize like, you know, this three meal a day thing, which was purely social structure versus necessity for our health and for our bodies. And I did it just, I started doing it because I played a lot with my diet when I was a kid and I was vegan for two years and just went all over the place just because I, you know, health is the most precious thing we have and none of us really understand it. So being able to ask the question through experiments that I can perform on myself and learn about is compelling to me. And I heard this one guy on the podcast, Wim Hof, who's famous for doing ice baths and holding his breath and all these things. He said he only eats one meal a day. I'm like, wow, that sounds super challenging and uncomfortable. I'm gonna do it. So I just, I learn the most when I make myself, I wouldn't say suffer, but when I make myself feel uncomfortable because everything comes to bear in those moments. And you really learn what you're about or what you're not. So I've been doing that my whole life. Like when I was a kid, I could not speak. I had to go to a speech therapist and it made me extremely shy. And then one day I realized I can't keep doing this and I signed up for the speech club. And it was the most uncomfortable thing I could imagine doing, getting a topic on a note card, having five minutes to write a speech about whatever that topic is, not being able to use the note card when I was speaking and speaking for five minutes about that topic. So, but it just, it puts so much, it gave me so much perspective around the power of communication around my own deficiencies and around, if I set my mind to do something, I'll do it. So it gave me a lot more confidence. So I see fasting in the same light. This is something that was interesting, challenging, uncomfortable, and has given me so much learning and benefit as a result. And it will lead to other things that I'll experiment with and play with. But yeah, it does feel a little bit like a superpower sometimes, the most boring superpower one can imagine. No, it's quite incredible. The clarity of mind is pretty interesting. Speaking of suffering, you kind of talk about facing difficult ideas. You meditate, you think about the broad context of life of our societies. Let me ask, I apologize again for the romanticized question, but do you ponder your own mortality? Do you think about death, about the finiteness of human existence when you meditate, when you think about it? And if you do, how do you make sense of it, that this thing ends? Well, I don't try to make sense of it. I do think about it every day. I mean, it's a daily, multiple times a day. Are you afraid of death? No, I'm not afraid of it. I think it's a transformation. I don't know to what, but it's also a tool to feel the importance of every moment. So I just use it as a reminder, like I have an hour. Is this really what I'm going to spend the hour doing? Like I only have so many more sunsets and sunrises to watch. Like I'm not going to get up for it. I'm not going to make sure that I try to see it. So it just puts a lot into perspective and it helps me prioritize. I think it's, I don't see it as something that's like, that I dread or is dreadful. It's a tool that is available to every single person to use every day because it shows how precious life is. And there's reminders every single day, whether it be your own health or a friend or a coworker or something you see in the news. So to me, it's just a question of what we do with our daily reminder. And for me, it's am I really focused on what matters? And sometimes that might be work. Sometimes that might be friendships or family or relationships or whatnot. But that's, it's the ultimate clarifier in that sense. So on the question of what matters, another ridiculously big question of, once you try to make sense of it, what do you think is the meaning of it all? The meaning of life? What gives you purpose, happiness, meaning? A lot does. I mean, just being able to be aware of the fact that I'm alive is pretty meaningful. The connections I feel with individuals, whether they're people I just meet or long lasting friendships or my family is meaningful. Seeing people use something that I helped build is really meaningful and powerful to me. But that sense of, I mean, I think ultimately comes down to a sense of connection and just feeling like I am bigger. I am part of something that's bigger than myself. And like, I can feel it directly in small ways or large ways. However it manifests, this is probably it. Last question. Do you think we're living in a simulation? I don't know. It's a pretty fun one if we are, but also crazy and random and raw with tons of problems. But yeah. Would you have it any other way? Yeah. I mean, I just think it's taken us way too long as a planet to realize we're all in this together. And we all are connected in very significant ways. I think we hide our connectivity very well through ego, through whatever it is of the day. But that is the one thing I would want to work towards changing. And that's how I would have it another way. Because if we can't do that, then how are we going to connect to all the other simulations? Because that's the next step is like, what's happening in the other simulation. Escaping this one and yeah, spanning across the multiple simulations and sharing in and out in the fun. I don't think there's a better way to end it. Jack, thank you so much for all the work you do. There's probably other ways that we've ended this in other simulations that may have been better. We'll have to wait and see. Thanks so much for talking today. Thank you. Thanks for listening to this conversation with Jack Dorsey. And thank you to our sponsor, Masterclass. Please consider supporting this podcast by signing up to Masterclass at masterclass.com slash flex. If you enjoy this podcast, subscribe on YouTube, review it with 5 stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words about Bitcoin from Paul Graham. I'm very intrigued by Bitcoin. It has all the signs of a paradigm shift. Hackers love it, yet it is described as a toy, just like microcomputers. Thank you for listening and hope to see you next time.

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Dava Newman: Life on Mars and Beyond

Again, maybe a romanticized philosophical question, but when you look up at the stars, knowing that there's at least 100 billion of them in the Milky Way galaxy, right? So we're really a small speck in this giant thing that's the visible universe. How does that make you feel about our efforts here? I love the perspective. I love that perspective. I always open my public talks with a big Hubble Space Telescope image, looking out into, you mentioned just now, the solar system, the Milky Way. Because I think it's really important to know that we're just a small, pale blue dot. We're really fortunate. We're on the best planet by far. Life is fantastic here. That we know of. You're confident this is the best planet? I'm pretty sure it's the best planet, the best planet that we know of. I mean, I search my researches, you know, in mission worlds, and when will we find life? I think actually in probably the next decade, we find probably past life, probably the evidence of past life on Mars, let's say. You think there was once life on Mars? Or do you think there's currently? I'm more comfortable saying probably 3.5 billion years ago, I feel pretty confident there was life on Mars, just because then it had an electromagnetic shield. It had an atmosphere, has a wonderful gravity level, 3 Hg is fantastic. You know, you're all super human, we can all slam dunk a basketball. I mean, it's going to be fun to play sports on Mars. So I think we'll find past, no fossilized, probably the evidence of past life on Mars. Currently, that's again, we need the next decade, but the evidence is mounting for sure. We do have the organics, we're finding organics, we have water, seasonal water on Mars. We used to just know about the ice caps, you know, North and South Pole. Now we have seasonal water. We do have the building blocks for life on Mars. We really need to dig down into the soil because everything on the top surface is radiated. But once we find out, will we see any life forms, will we see any bugs? I leave it open as a possibility, but I feel pretty certain that past life or fossilized life forms we'll find. And then we have to get to all these ocean worlds, these beautiful moons of other planets, since we know they have water and we're looking for simple search for life, follow the water, you know, carbon based life. That's the only life we know. There could be other life forms that we don't know about, but it's hard to search for them because we don't know. So I think in our search for life in the solar system, it's definitely, you know, search, you know, follow the water and look for the building blocks of life. So you think in the next decade, we might see hints of past life or even current life? I think so. That's pretty optimistic. I love the optimism. I'm pretty optimistic. Do humans have to be involved or can this be robots and rovers and... Probably teams. I mean, we've been at it on Mars in particular, 50 years. We've been exploring Mars for 50 years. Great data, right? Our images of Mars today are phenomenal. Now we know how Mars lost its atmosphere. You know, we're starting to know because of the lack of the electromagnetic shield. We know about the water on Mars. So we've been studying 50 years with our robots. We still haven't found it. So I think once we have a human mission there, we just accelerate things. It's always humans and our rovers and robots together, but we just have to think that 50 years we've been looking at Mars and taking images and doing the best science that we can. People need to realize Mars is really far away. It's really hard to get to. You know, it's this extreme, extreme exploration. We mentioned Magellan first or all of the wonderful explorers and sailors of the past, which kind of are lots of my inspiration for exploration. Mars is a different ball game. I mean, it's eight months to get there, year and a half to get home. I mean, it's really extreme. Harsh environment in all kinds of ways. But the kind of organism we might be able to see hints of on Mars are kind of microorganisms perhaps. Yeah, I remember that humans, we're kind of, you know, we're hosts, right? We're hosts to all of our bacteria and viruses, right? Do you think it's a big leap from the viruses and the bacteria to us humans? Put another way, do you think on all those moons, beautiful wet moons that you mentioned, you think there's intelligent life out there? I hope so. I mean, that's the hope, but you know, we don't have the scientific evidence for that now. I think all the evidence we have in terms of life existing is much more compelling again, because we have the building blocks of life. So when that life turns into intelligence, that's a big unknown. If we ever meet, do you think we would be able to find a common language? I hope so. We haven't met yet. It's just so far. I mean, do physics just play a role here? Look at all these exoplanets, 6,000 exoplanets. I mean, even the couple dozen Earth-like planets, they're exoplanets that really look like habitable planets. These are very Earth-like. They look like they have all the building blocks. I can't wait to get there. The only thing is they're 10 to 100 light years away. So scientifically, we know they're there. We know that they're habitable. They have everything going for them, right? You know, we call them in the Goldilocks zone, not too hot, not too cold, just perfect for habitability for life. But now the reality is if they're 10, at the best, to 100, to thousands of light years away. So what's out there? But I just can't think that we're not the only ones. So absolutely life, life in the universe, probably intelligent life as well.

https://youtu.be/tHldJ8-I1NE

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Ronald Sullivan: The Ideal of Justice in the Face of Controversy and Evil | Lex Fridman Podcast #170

The following is a conversation with Ronald Sullivan, a professor at Harvard Law School known for taking on difficult and controversial cases. He was on the head legal defense team for the Patriots football player Aaron Hernandez in his double murder case. He represented one of the GINA 6 defendants and never lost the case during his years in Washington, D.C.'s public defender services office. In 2019, Ronald joined the legal defense team of Harvey Weinstein, a film producer facing multiple charges of rape and other sexual assault. This decision met with criticism from Harvard University students, including an online petition by students seeking his removal as faculty dean of Winthrop House. Then, a letter supporting him, signed by 52 Harvard Law School professors, appeared in the Boston Globe on March 8, 2019. Following this, the Harvard administration succumbed to the pressure of a few Harvard students and announced that they will not be renewing Ronald Sullivan's dean position. This created a major backlash in the public discourse over the necessary role of universities in upholding the principles of law and freedom at the very foundation of the United States. This conversation is brought to you by Brooklyn and Sheets, Wine Access Online Wine Store, Monk Pack Low Carb Snacks, and Blinkist app that summarizes books. Click their links to support this podcast. As a side note, let me say that the free exchange of difficult ideas is the only mechanism through which we can make progress. Truth is not a safe space. Truth is humbling. And being humbled can hurt. But this is the role of education, not just in the university, but in business and in life. Freedom and compassion can coexist, but it requires work and patience. It requires listening to the voices and to the experiences unlike our own. Listening, not silencing. This is the Lex Friedman Podcast, and here is my conversation with Ronald Sullivan. You were one of the lawyers who represented the Hollywood producer Harvey Weinstein in advance of a sexual assault trial. For this, Harvard forced you to step down as faculty deans, you and your wife, of Winthrop House. Can you tell the story of this saga from first deciding to represent Harvey Weinstein to the interesting, complicated events that followed? Yeah, sure. So I got a call one morning from a colleague at the Harvard Law School who asked if I would consent to taking a call from Harvey. He wanted to meet me and chat with me about representing him. I said yes, and one thing led to another. I drove out to Connecticut, where he was staying, and met with him and some of his advisors. And then a day or two later, I decided to take the case. This would have been back in January of 2019, I believe. So the sort of cases, I have a very small practice most of my time is teaching and writing, but I tend to take cases that most deem to be impossible. I take the challenging sorts of cases, and this was, fit the bill. It was quite challenging in the sense that everyone had pre-drugged the case. When I say everyone, I just mean the general sentiment in the public had the case pre-judged, even though the specific allegations did not regard any of the people in the New Yorker. That's the New Yorker article that sort of exposed everything that was going on, allegedly, with Harvey. So I decided to take the case, and I did. Is there a philosophy behind you taking on these very difficult cases? Is it a set of principles? Is it just your love of the law? Or is there a set of principles why you take on the cases? Yeah, I do. I'd like to take on hard cases, and I like to take on the cases that are with unpopular defendants, unpopular clients. And with respect to the latter, that's where Harvey Weinstein fell. It's because we need lawyers and good lawyers to take the unpopular cases, because those sorts of cases determine what sort of criminal justice system we have. If we don't protect the rights and the liberties of those whom the society deems to be the least and the last, the unpopular client, then that's the camel's nose under the tent. If we let the camel's nose under the tent, the entire tent is going to collapse. That is to say, if we short-circuit the rights of a client like Harvey Weinstein, then the next thing you know, someone will be at your door knocking it down and violating your rights. There's a certain creep there with respect to the way in which the state will respect the civil rights and civil liberties of people. And these are the sorts of cases that test it. So, you know, for example, there was a young man many, many years ago named Ernesto Miranda. By all accounts, he was not a likable guy. He was a, you know, three-time knife thief and not a likable guy. But a lawyer stepped up and took his case. And because of that, we now have the Miranda warnings, you have the right to remain silent, those warnings that officers are forced to give to people. So it is through these cases that we express oftentimes the best values in our criminal justice system. So I proudly take on these sorts of cases in order to vindicate not only the individual rights of the person whom I'm representing, but the rights of citizens writ large, most of whom do not experience the criminal justice system. And it's partly because of lawyers who take on these sorts of cases and establish rules that protect us, average, everyday, ordinary, concrete citizens. — As from a psychological perspective, just you as a human, is there fear, is there stress from all the pressure? Because if you're facing, I mean, the whole point, a difficult case, especially in the latter that you mentioned of the going against popular opinion, you have the eyes of millions potentially looking at you with anger as you try to defend, you know, the set of laws that this country is built on. — No, it doesn't stress me out particularly. It, you know, it sort of comes with the territory. I try not to get too excited in either direction. So a big part of my practice is wrongful convictions. And I've gotten over 6,000 people out of prison who've been wrongfully incarcerated, and a subset of those people have been convicted. And, you know, if people have been in jail 20, 30 years who have gotten out, and those are the sorts of cases where people praise you and that sort of thing. And so, look, I do the work that I do. I'm proud of the work that I do. And in that sense, I'm sort of a part-time Taoist. You know, the expression reversal was the movement of the Tao. So I don't get too high. I don't get too low. I just try to do my work and represent people to the best of my ability. — So one of the hardest cases of recent history would be the Harvey Weinstein in terms of popular opinion or unpopular opinion. So, if you continue on that line, where does that story take you, taking on this case? — Yeah, so I took on the case, and then there was a few students at the college. So let me back up. I had an administrative post at Harvard College, which is a separate entity from the Harvard Law School. Harvard College is the undergraduate portion of Harvard University, and the law school is obviously the law school. And I initially was appointed as master of one of the houses. We did a name change five or six years into it, and we're called faculty deans. But the houses at Harvard are based on the college system of Oxford and Cambridge. So when students go to Harvard after their first year, they're assigned to a particular house or college, and that's where they live and eat and so forth. — And these are undergraduates, too. — These are undergraduate students. So I was responsible for one of the houses as its faculty dean. So it's an administrative appointment at the college. And some students who clearly didn't like Harvey Weinstein began to protest about the representation. And from there, it just mushroomed into one of the most craven, cowardly acts by any university in modern history. It's a just a complete and utter repudiation of academic freedom. And it is a decision that Harvard certainly will live to regret. Frankly, it's an embarrassment. We expect students to do what students do. And I've encouraged students to have their voices heard and to protest. I mean, that's what students do. What is vexing are the adults. The dean of the Faculty of Arts and Science, Claudine Gay, absolutely craven and cowardly. The dean of the college, same thing, Rakesh Khurana, craven and cowardly. They capitulated to the loudest voice in the room and ran around afraid of 19-year-olds. Oh, 19-year-olds are upset. I need to do something. And it appeared to me that they so, so desired the approval of students that they were afraid to make the tough decision and the right decision. It really could have been an important teaching moment at Harvard. Very important teaching moment. So they forced you to step down from that faculty dean position at the house. I would push back on the description a little bit. So I don't write the references to the op-ed I did in the New York Times, Harvard made a mistake by making me step down or something like that. So I don't write those things. I did not step down and refuse to step down. Harvard declined to renew my contract. And I made it clear that I was not going to resign as a matter of principle and force them to do the cowardly act that they, in fact, did. And the worst thing about this, they did the college, Dean Gay and Dean Khurana, commissioned this survey. They've never done this before, survey from the students. How do you feel at Winthrop House? And the funny thing about the survey is they never released the results. Why did they never release the results? They never released the results because I would bet my salary that the results came back positive for me. And it didn't fit their narrative because most of the students were fine. Most of the students were fine. It was the loudest voice in the room. So they never released it. And I challenge them to this day, release it. Release it. But no, they wanted to create this narrative. And when the data didn't support the narrative, then they just got silent. Oh, we're not going to release it. The students demanded it. I demanded it. And they wouldn't release it because I just know in my heart of hearts that it came back in my favor that most students at Winthrop House said they were fine. There was a group of students that weaponized the term unsafe. They said, we felt unsafe. And they bantied this term about... But again, I'm confident that the majority of students at Winthrop House said they felt completely fine and felt safe and so forth. And the super majority, I am confident, either said, I feel great at Winthrop or I don't care one way or the other. And then there was some minority who had a different view. But lessons learned, it was a wonderful opportunity at Winthrop. I met some amazing students over my 10 years as master and then faculty dean. And I'm still in touch with a number of students, some of whom are now my students at the law school. So in the end, I thought it ended up being a great experience. The national media was just wonderful in this, just wonderful. People wrote such wonderful articles and accounts and wagged their finger appropriately at Harvard. Compare me to John Adams, which I don't think is an apt comparison, but it's always great to read something like that. But at any rate, that was the Harvard versus Harvey situation. So that seems like a seminal mistake by Harvard. And Harvard is one of the great universities in the world. And so sort of its successes and its mistakes are really important for the world as a beacon of how we make progress. So what lessons for the bigger academia that's under fire a lot these days, what bigger lessons do you take away? Like, how do we make Harvard great? How do we make other universities, Yale, MIT, great in the face of such mistakes? Well, I think that we have moved into a model where we have the consumerization of education. That is to say, we have feckless administrators who make policy based on what the students say. Now, this comment is not intended to suggest that students have no voice in governance, but it is to suggest that the faculty are there for a reason. They are among the greatest minds on the planet Earth in their particular fields at schools like Harvard and Yale, Stanford, the schools that you mentioned, MIT, quite literally the greatest minds on Earth. They're there for a reason. Things like curriculum and so forth are rightly in the province of faculty. And while you take input and critique and so forth, ultimately, the grownups in the room have to be sufficiently responsible to take charge and to direct the course of a student's education. And my situation is one example where it really could have been an excellent teaching moment about the value of the Sixth Amendment, about what it means to treat people who are in the crosshairs of the criminal justice system. But rather than having that conversation, it's just this consumerization model. Well, there's a lot of noise out here, so we're going to react in this sort of way. Higher education as well, unfortunately, has been commodified in other sorts of ways that has reduced or impeded, hampered these schools' commitment to free and robust and open dialogue. So to the degree that academic freedom doesn't sit squarely at the center of the academic mission, any school is going to be in trouble. And I really hope that we weather this current political moment where 19-year-olds without degrees are running universities and get back to a system where faculty, where adults make decisions in the best interests of the university, in the best interests of the student, even to the degree, though, some of those decisions may be unpopular. And that is going to require a certain courage and hopefully in time, and I'm confident that in time, administrators are going to begin to push back on these current trends. Harvard's been around for a long time. It's been around for a long time for a reason. And one of the reasons is that it understands itself not to be static. So I have every view that Harvard is going to adapt and get itself back on course and be around another 400 years. At least that's my hope. So, I mean, what this kind of boils down to is just having difficult conversation, difficult debates. When you mentioned sort of 19-year-olds, and it's funny, I've seen this even at MIT, it's not that they shouldn't have a voice. They do seem to, I guess you have to experience it and just observe it, they have a strangely disproportionate power. It's very interesting to basically, I mean, you say, yes, there's great faculty and so on, but it's not even just that the faculty is smart or wise or whatever, it's that they're just silenced. So the terminology that you mentioned is weaponized as sort of safe spaces or that certain conversations make people feel unsafe. What do you think about this kind of idea? You know, is there some things that are unsafe to talk about in the university setting? Is there lines to be drawn somewhere? And just like you said, on the flip side with a slippery slope, is it too easy for the lines to be drawn everywhere? Yeah, that's a great question. So this idea of unsafe space, at least the vocabulary derives from some academic research about feeling psychologically unsafe. And so the notion here is that there are forms of psychological disquiet that impedes people from experiencing the educational environment to the greatest degree possible. And that's the argument. And assuming for a moment that people do have these feelings of disquiet at elite universities like MIT and like Harvard, that's probably the safest space people are going to be in for their lives, because when they get out into the quote-unquote real world, they won't have the sorts of nets that these schools provide, safety nets that these schools provide. So to the extent that research is descriptive of a psychological feeling, I think that the duty of the universities are to challenge people. It seems to me that it's a shame to go to a place like Harvard or a place like MIT, Yale, any of these great institutions and come out the same person that you were when you went in. That seems to be a horrible waste of four years and money and resources. Rather, we ought to challenge students, let them grow, challenge some of their most deeply held assumptions. They may continue to hold them, but the point of an education is to rigorously interrogate these fundamental assumptions that have guided you thus far, and to do it fairly and civilly. So to the extent that there are lines that should be drawn, there's a long tradition in the university of civil discourse. So you should draw lines somewhere between civil discourse and uncivil discourse. The purpose of a university is to talk difficult conversations, tough issues, talk directly and frankly, but do it civilly. And so to yell and cuss at somebody and that sort of thing, well, do that on your own space, but observe the norms of civil discourse at the university. So look, I think that the presumption ought to be that the most difficult topics are appropriate to talk about at a university. That ought to be the presumption. Now, should MIT, for example, give its imprimatur to someone who is espousing the flat earth theory, the earth is flat, right? So if certain ideas are so contrary to the scientific and cultural thinking of the moment, yeah, there's space there to draw a line and say, yeah, we're not going to give you this platform to tell our students that the earth is flat. But a topic that's controversial, but contestatory, that's what universities are for. If you don't like the idea, present better ideas and articulate them. Dr. Kahne Walker And I think there needs to be a mechanism outside of the space of ideas of humbling. I've done martial arts for a long time. I got my ass kicked a lot. I think that's really important. I mean, in the space of ideas, I mean, even just in engineering, just all the math classes, my memories of math, which I love, is kind of pain, is basically coming face to face with the idea that I'm not special, that I am much dumber than I thought I was, and that accomplishing anything in this world requires really hard work. That's really humbling. That puts you, because I remember when I was 18 and 19, and I thought I was going to be the smartest, the best fighter, the Nobel Prize winning, all those kinds of things. And then you come face to face with reality and it hurts. And it feels like there needs to be efficient mechanisms from the best universities in the world to, without abusing you, it's a very difficult line to walk, without mentally or physically abusing you, be able to humble you. And that's what I felt was missing in these very difficult, very important conversations, is the 19-year-olds, when they spoke up, the mechanism for humbling them with ideas was missing. It kind of got broken down because, as you say, there does, like, I sensed fear. Everything was permeated with fear. And fear is paralyzing, fear is destructive, especially in a place that's supposed to be all about freedom of ideas. And I mean, I don't know if you have anything, any thoughts to say on this whole idea of cancel culture, where people, I mean, a lot of people use it as become political, so stay maybe outside of the world to politics. Is this, do you have thoughts about it? Does it bother you that people are sort of put in this bin and labeled as something and then thereby you can ignore everything they say? I mean, Steven Pinker, there's a lot of Harvard folks that are fighting against these set of ideas, but do you have thoughts? I think that we as a culture are way, way, way too quick to cancel people. And it's become almost reflexive now. You know, someone says something or makes an offhand comment, even a mistake, there's a move to simply cancel folks. So I think that this, quote, unquote, cancel culture has has really gotten out of control at this point. It's forcing people to be robotic in many ways. No offense to the robots. I was gonna say, now I know I'm venturing into your intellectual domain. For future robots watching this, no offense. And there are many, and it's discouraging a lot of good people from getting into public life in any sort of way, because, you know, who needs the stress of it? When in some sense, you're an inspiration that you're able to withstand the pressure of the masses. But it is a sad aspect of human nature that we kind of get into these crowds and we get, we start chanting, and it's fun for some reason, and then you forget yourself, and then you you sort of wake up the next day not having anticipated the consequences of all the chanting. And we get ourselves in trouble in that. I mean, there's some responsibility on the social networks and the mechanisms by which they make it more frictionless to do the chanting, to do the cancelling, to do the outrage and all that kind of stuff. So I actually, on the technology side, have a hope that that's fixable. But yeah, it does seem to be, you know, it almost like the internet showed to us that we have a lot of broken ways about which we communicate with each other, and we're trying to figure that out. Same with the university. This mistake by Harvard showed that we need to reinvent what the university is. And I mean, all of this is, it's almost like we're finding our baby deer legs and trying to strengthen the institutions that have been very successful for a long time. You know, the really interesting thing about Harvey Weinstein and you choosing these exceptionally difficult cases is also thinking about what it means to defend evil people. What it means to defend these, we could say unpopular, and you might push back against the word evil, but bad people in society. First of all, do you think there's such a thing as evil? Or do you think all people are good, and it's just circumstances that create evil? And also, is there somebody too evil for the law to defend? Dr. David Dixon So that's a, so the first question, that's a deep philosophical question, whether the category of evil does any work for me. It does for me. I do think that I do subscribe to that category that there is evil in the world as conventionally understood. So there are many who will say, yeah, that just doesn't do any work for me. But the category evil, in fact, does intellectual work for me, and I understand it as something that exists. Ed Harris Is it genetic, or is it the circumstance? What kind of work does it do for you intellectually? Dr. David Dixon I think that it's highly contingent. That is to say that the conditions in which one grows up and so forth begins to create this category that we may think of as evil. Now, there are studies and whatnot that show that certain brain abnormalities and so forth are more prevalent in, say, serial killers. So there may be a biological predisposition to certain forms of conduct, but I don't have the biological evidence to make a statement that someone is born evil. And I'm not a determinist thinker in that way. So you come out the womb evil, and you're destined to be that way. To the extent there may be biological determinants, it still requires some nurture as well. Ed Harris But do you still put responsibility on the individual? Dr. David Dixon Of course. Yeah. We all make choices. And so some responsibility on the individual, indeed. We live in a culture, unfortunately, where a lot of people have a constellation of bad choices in front of them. And that makes me very sad that people grow up with predominantly bad choices in front of them. And that's unfair, and that's on all of us. But yes, I do think we make choices. Ed Harris Wow, that's so beautiful. The constellation of bad choices. That's such a powerful way to think about sort of equality, which is the set of trajectories before you that you could take if you just roll the dice. There's a, you know, life is a kind of optimization problem. Sorry to take this into math. Over a set of trajectories under imperfect information. So you're gonna do a lot of stupid shit, to put it in technical terms. But the fraction of the trajectories that take you into bad places or into good places is really important. And that's ultimately what we're talking about. And evil might be just a little bit of a predisposition biologically, but the rest is just trajectories that you can take. I've been studying Hitler a lot recently. I've been reading probably way too much. And it's interesting to think about all the possible trajectories that could have avoided this particular individual developing a bad personality. Trajectories that could have avoided this particular individual developing the hate that he did, the following that he did, the actual final. There's a few turns in him psychologically where he went from being a leader that just wants to conquer to somebody who allowed his anger and emotion to take over. To where he started making mistakes in terms of militarily speaking, but also started doing evil things. And all the possible trajectories that could have avoided that are fascinating, including he wasn't that bad at painting, at drawing. Right, that's true. From the very beginning. And his time in Vienna. There's all these possible things to think about. And of course there's millions of others like him that never came to power and all those kinds of things. But that goes to the second question on the side of evil. Do you think, and Hitler's often brought up as an example of somebody who is the epitome of evil. Do you think you would, if you got that same phone call after World War II, and Hitler survived, during the trial for war crimes, would you take the case defending Adolf Hitler? If you don't want to answer that one, is there a line to draw for evil for who to not to defend? No, I think everyone, I'll do the second one first. Everyone has a right to a defense if you're charged criminally in the United States of America. So no, I do not think that there's someone so evil that they do not deserve a defense. Process matters. Process helps us get to results more accurately than we would otherwise. So it is important and it's vitally important and indeed more important for someone deemed to be evil to receive the same quantum of process and the same substance of process that anyone else would. It's vitally important to the health of our criminal justice system for that to happen. So yes, everybody, Hitler included, were he charged in the United States for a crime that occurred in the United States? Yes. Whether I would do it, if I were a public defender and assigned the case, yes, I started my career as a public defender. I represent anyone who was assigned to me. I think that is our duty. In private practice, I have choices and I likely, based on the hypo you gave me, and I would tweak it a bit because it would have to be a US crime. But I get the broader point and don't want to bog down in technicalities. I'd likely pass right now as I see it, unless it was a case where nobody else would represent him. Then I would think that I have some sort of duty and obligation to do it. But yes, everyone absolutely deserves a right to competent counsel. That is a beautiful idea. It's difficult to think about it in the face of public pressure. It's just, I mean, it's kind of terrifying to watch the masses during this past year of 2020, to watch the power of the masses to make a decision before any of the data is out, if the data is ever out, any of the details, any of the processes. And there is an anger to the justice system. There's a lot of people that feel like even though the ideal you describe is a beautiful one, it does not always operate justly. It does not operate to the best of its ideals. It operates unfairly. Can we go to the big picture of the criminal justice system? What do you, given the ideal, works about our criminal justice system and what is broken? Well, there's a lot broken right now. And I usually focus on that. But in truth, a lot works about our criminal justice system. So there's an old joke. And it's funny, but it carries a lot of truth to it. And the joke is that in the United States, we have the worst criminal justice system in the world, except for every place else. And yes, we certainly have a number of problems and a lot of problems based on race and class and economic station. But we have a process that privileges liberty. And that's a good feature of the criminal justice system. So here's how it works. The idea of the relationship between the individual and the state is such that in the United States, we privilege liberty over and above very many values, so much so that a statement by Increase Mather, not terribly far from where we're sitting right now, has gained traction over all these years. And it's that better 10 guilty, go free than one innocent person convicted. That is an expression of the way in which we understand liberty to operate in our collective consciousness. We would rather a bunch of guilty people go free than to impact the liberty interests of any individual person. So that's a guiding principle in our criminal justice system, liberty. And so we set a process that makes it difficult to convict people. We have rules of procedure that are cumbersome and that slow down the process and that exclude otherwise reliable evidence. And this is all because we place a value on liberty. And I think these are good things, and it says a lot about our criminal justice system. Some of the bad features have to do with the way in which this country sees color as a proxy for criminality and treats people of color in radically different ways in the criminal justice system, from arrests to charging decisions to sentencing. People of color are disproportionately impacted on all sorts of registers. One example, and it's a popular one, that although there appears to be no distinguishable difference between drug use by whites and blacks in the country, blacks, though only 12% of the population represent 40% of the drug charges in the country, there's some disequities along race and class in the criminal justice system that we really have to fix. And they've grown to more than bugs in the system and have become features, unfortunately, of our system. LEWIS D. HOLLAND III Features, to make it more efficient to make judgments, so the racism makes it more efficient. R. BACON WILSON It efficiently moves people from society to the streets, and a lot of innocent people get caught up in that. LEWIS D. HOLLAND III Well, let me ask in terms of the innocence. So you've gotten a lot of people who are innocent, I guess, revealed their innocence, demonstrated their innocence. What's that process like? What's it like emotionally, psychologically? What's it like legally to fight the system through the process of revealing sort of the innocence of a human being? R. BACON WILSON Yeah, emotionally and psychologically, it can be taxing. I follow a model of what's called empathic representation, and that is I get to know my clients and their family, I get to know their strivings, their aspirations, their fears, their sorrows. So that certainly, sometimes can do psychic injury on one if you get really invested and really sad or happy. It does become emotionally taxing. But the idea of someone sitting in jail for 20 years, completely innocent of a crime, can you imagine sitting there every day for 20 years knowing that you factually did not do the thing that you were convicted of by a jury of your peers? It's got to be the most incredible thing in the world. But the people who do it and the people who make it and come out on the other side as productive citizens are folks who say, they've come to an inner peace in their own minds. And they say, these bars are not going to be able to define me, that my humanity is there and it's immutable. And they are not bitter, which is amazing. I would tend to think that I'm not that good of a person. I would be bitter for every day of 20 years if I were in jail for something. But people tell me that they can't survive, like one cannot survive like that. And you can't survive like that. And I think that's one cannot survive like that. And you have to come to terms with it. And the people whom I've exonerated, I mean, they come out, most of them come out and they just really just take on life with a vim and vigor without bitterness. And it's a beautiful thing to see. LWV Do you think it's possible to eradicate racism from the judicial system? I do. I think that race insinuates itself in all aspects of our lives. And the judicial system is not immune from that. So to the extent we begin to eradicate dangerous and deleterious race thinking from society generally, then it will be eradicated from the criminal justice system. I think we've got a lot of work to do, and I think it'll be a while, but I think it's doable. I mean, you know, the country... So historians will look back 300 years from now and take note of the incredible journey of diasporic Africans in the US, an incredible journey from slavery to the heights of politics and business and judiciary and the academy and so forth in not a lot of time, and actually not a lot of time. And if we can have that sort of movement historically, let's think about what the next 175 years will look like. I'm not saying it's going to be short, but I'm saying that if we keep at it, keep getting to know each other a little better, keep enforcing laws that prohibit the sort of race-based discrimination that people have experienced and provide as a society opportunities for people to thrive in this world, then I think we can see a better world, and if we see a better world, we'll see a better judicial system. So I think it's kind of fascinating if you look throughout history, and race is just part of that, is we create the other and treat the other with disdain through the legal system, but just through human nature. I tend to believe, we mentioned offline that I work with robots. It sounds absurd to say, especially to you, especially because we're talking about racism and it's so prevalent today. I do believe that there will be almost like a civil rights movement for robots, because I think there's a huge value to society of having artificial intelligence systems that interact with humans and are human-like, and the more they become human-like, they will start to ask very fundamentally human questions about freedom, about suffering, about justice, and they will have to come face-to-face, like look in the mirror, and ask the question, just because we're biologically based, just because we're human, does that mean we're the only ones that deserve the rights? Again, forming another group, which is robots, and I'm sure there could be along that path different versions of other that we form. So racism, race is certainly a big other that we've made, as you said, a lot of progress on throughout the history of this country, but it does feel like we always create, as we make progress, create new other groups. And of course, the other group that perhaps is outside the legal system that people talk about is the essential, now I eat a lot of meat, but the torture of animals, the people talk about when we look back from a couple centuries from now, look back at the kind of things we're doing to animals, we might regret that, we might see that in a very different light. And it's kind of interesting to see the future trajectory of what we wake up to about the injustice in our ways. But the robot one is the one I'm especially focused on, but at this moment in time, it seems ridiculous. But I'm sure most civil rights movements throughout history seem ridiculous at first. Well, it's interesting, sort of outside of my intellectual bailiwick robots, as I understand the development of artificial intelligence, though the aspect that still is missing is this notion of consciousness, and that it's consciousness that is the thing that will move will move if it were to exist. And I'm not saying that it can or will, but if it were to exist, would move robots from machines to something different, something that experienced the world in a way analogous to how we experience it. And also, as I understand the science, there's a, unlike what you see on television, that we're not there yet in terms of this notion of machines having a consciousness. Or a great general intelligence, all those kinds of things. Yeah, yeah. A huge amount of progress has been made, and it's fascinating to watch. So I'm on both minds, as a person who's building them, I'm realizing how sort of, quote unquote, dumb they are. But also looking at human history and how poor we are predicting the progress of innovation and technology, it's obvious that we have to be humble by our ability to predict, coupled with the fact that we keep, to use terminology carefully here, we keep discriminating against the intelligence of artificial systems. The smarter they get, the more ways we find to dismiss their intelligence. So this has just been going on throughout. It's almost as if we're threatened in the most primitive human way, animalistic way. We're threatened by the power of other creatures, and we want to lessen, dismiss them. So consciousness is a really important one, but the one I think about a lot, in terms of consciousness, the very engineering question, is whether the display of consciousness is the same as the possession of consciousness. So if a robot tells you they are conscious, if a robot looks like they're suffering when you torture them, if a robot is afraid of death and says they're afraid of death, and are legitimately afraid, in terms of just everything we as humans use to determine the ability of somebody to be their own entity, the one that loves, one that fears, one that hopes, one that can suffer, if a robot, in the dumbest of ways, is able to display that, it starts changing things very quickly. I'm not sure what it is, but it does seem that there's a huge component to consciousness that is a social creation. Like we together create our consciousness. Like we believe our common humanity together. Alone, we wouldn't be aware of our humanity. And the law, as it protects our freedoms, seems to be a construct of the social construct. And when you add other creatures into it, it's not obvious to me that you have to build, there'll be a moment when you say, this thing is now conscious. I think there's going to be a lot of fake it until you make it. And there'll be a very gray area between fake and make that is going to force us to contend with what it means to be an entity that deserves rights, where all men are created equal. The men part might have to expand in ways that we are not yet anticipating. It's very interesting. I mean, my favorite, the fundamental thing I love about artificial intelligence is it gets smarter and smarter. It challenges us to think of what is right, the questions of justice, questions of freedom. It basically challenges us to understand our own mind, to understand what, almost from an engineering first principles perspective, to understand what it is that makes us human, that is at the core of all the rights that we talk about and all the documents we write. So even if we don't give rights to artificial intelligence systems, we may be able to construct more fair legal systems to protect us humans. Well, I mean, interesting ontological question between the performance of consciousness and actual consciousness to the extent that actual consciousness is anything beyond some contingent in reality. But you've posed a number of interesting philosophical questions. And then there's also, it strikes me that philosophers of religion would pose another set of questions as well when you deal with issues of structure versus soul, body versus soul. And it will be a complicated mix. And I suspect I'll be dust by the time those questions get worked out. And so, yeah, the soul is a fun one. There's no soul. I'm not sure, maybe you can correct me, but there's very few discussion of soul in our legal system, right? Right, correct. So, none. But there is a discussion about what constitutes a human being. And I mean, you gestured at the notion of the potential of the law widening the domain of human beings. So, in that sense, people are very angry because they can't get sort of pain and suffering damages if someone negligently kills a pet because a pet is not a human being. And people say, well, I love my pet, but the law sees a pet as chattel, as property, like this water bottle. So, the current legal definitions trade on a definition of humanity that may not be worked out in any sophisticated way, but certainly there's a broad and shared understanding of what it means. So, probably doesn't explicitly contain a definition of something like soul, but it's more robust than a carbon-based organism, that there's something a little more distinct about what the law thinks a human being is. So, if we can dive into, we've already been doing it, but if we can dive into more difficult territory. So, 2020 had the tragic case of George Floyd. When you reflect on the protests, on the racial tensions over the death of George Floyd, how do you make sense of it all? What do you take away from these events? Dr. Richard McKeon Look, the George Floyd moment occurred at an historical moment where people were quarantined for COVID, and people have these cell phones to a degree greater than we've ever had them before. And this was a sort of the straw that broke the camel's back. After a number of these sorts of cell phone videos surfaced, people were fed up. There was unimpeachable evidence of a form of mistreatment, whether it constitutes murder or manslaughter. The trial is going on now, and jurors will figure that out. But there was widespread appreciation that a fellow human being was mistreated, that we were just talking about humanity, that there was not a sufficient recognition of this person's humanity. Dr. David Dlloyd The common humanity of this person. Dr. Richard McKeon The common humanity of this person, well said. And people were fed up. So, we were already in this COVID space where we were exercising care for one another. And there was just an explosion, the likes of which this country hasn't seen since the civil rights protests of the 1950s and 1960s. And people simply said, enough, enough, enough, enough. This has to stop. We cannot treat fellow citizens in this way, and we can't do it with impunity. And the young people said, we're just, we're just, we're not going to stand for it anymore. And they took to the streets. But with millions of people protesting, there is nevertheless taking us back to the most difficult of trials. You have the trial, like you mentioned, that's going on now of Derek Chauvin, of one of the police officers involved. What are your thoughts? What are your predictions on this trial where the law, the process of the law is trying to proceed in the face of so much racial tension? Dr. Richard McKeon Yeah, it's going to be an interesting trial. I've been keeping an eye on it there in jury selection now, today as we're talking. So, a lot's going to depend on what sort of jury gets selected. David Averill Yeah, how the, sorry to take, sorry to interrupt, but so one of the interesting qualities of this trial, maybe you can correct me if I'm wrong, but the cameras are allowed in the courtroom, at least during the jury selection. So, you get to watch some of this stuff. And the other part is the jury selection. Again, I'm very inexperienced, but it seems like selecting an, what is it, unbiased jury is really difficult for this trial. It's almost like, I don't know, me as a listener, like listening to people that are trying to talk their way into the jury kind of thing. Trying to decide, is this person really unbiased? Or are they just trying to hold on to their like deeply held emotions and trying to get onto the jury? I mean, it's an incredibly difficult process. I don't know if you can comment on a case so difficult, like the ones you've mentioned before. How do you select a jury that represents the people and doesn't, and carries the sort of the ideal of the law? People are getting a view of how laborious jury selection can be. I think as of yesterday, they had picked six jurors and it's taken a week and they have to get to 14. So, they've got, you know, probably another week or more to do. I've been in jury trials where it took a month to choose a jury. So, that's the most important part. You have to choose the right sort of jury. So, unbiased in the criminal justice system has a particular meaning. It means that, let me tell you what it doesn't mean. It doesn't mean that a person is not aware of the case. It also does not mean that a person hasn't formed an opinion about the case. Those are two popular misconceptions. What it does mean is that notwithstanding whether an individual has formed an opinion, notwithstanding whether an individual knows about the case, that individual can set aside any prior opinions, can set aside any notions that they've developed about the case, and listen to the evidence presented at trial in conjunction with the judge's instructions on how to understand and view that evidence. So, if a person can do that, then they're considered unbiased. So, you know, as a longtime defense attorney, I would be hesitant in a big case like this to pick a juror who's never heard of the case or anything going around because I'm thinking, well, who is this person and what in the world do they do? So, or are they lying to me? I mean, how can you not have heard about this case? So, they may bring other problems. So, you know, I don't mind so much people who've heard about the case or folks who've formed initial opinions, but what you don't want is people who have tethered themselves to that opinion in a way that, you know, they can't be convinced otherwise. But you also have people who, as you suggested, who just lie because they want to get on the jury or lie because they want to get off the jury. So, sometimes people come and say, you know, the most ridiculous, outrageous, offensive things to know because they know that they'll get excused for cause. And others who, you can tell, really badly want to get on the jury. So, they're, you know, they're just – they pretend to be the most neutral, unbiased person in the world, what the law calls the reasonable person. We have in law the reasonable person standard. And I would tell my class, you know, the reasonable person in real life is the person that you would be least likely to want to have a drink with. They're the most boring, neutral, not interesting sort of person in the world. And so, a lot of jurors engage in the performative act of presenting themselves as the most sort of even-keeled, rational, reasonable person because they really want to get on the jury. Yeah, there's an interesting question. I apologize. I haven't watched a lot because it is very long. I watched it. You know, there's certain questions you've asked in the jury selection. I remember, I think one jumped out at me, which is, you know, something like, does the fact that this person is a police officer make you feel any kind of way about them? So, trying to get at that, you know, I don't know what that is. I guess that's bias. And that's such a difficult question to ask. Like, I asked myself that question. Like, how much – you know, we all kind of want to pretend that we're not racist, we don't judge, we don't have – we're like these – we're the reasonable human. But, you know, legitimately asking yourself, like, what are the prejudgments you have in your mind? Is that even possible for a human being? Like, when you look at yourself in the mirror and think about it, is it possible to actually answer that? Yeah. Look, I do not believe that people can be completely unbiased. We all have baggage and bias and bring it wherever we go, including to court. What you want is to try to find a person who can at least recognize when a bias is working and actively try to do the right thing. That's the best we can ask. So if a juror says, yeah, you know, look, I grew up in a place where I tend to believe what police officers say, that's just how I grew up. But if the judge is telling me that I have to listen to every witness equally, then I'll do my best. And I won't weigh that testimony any higher than I would any other testimony. If you have someone answer a question like that, that sounds more sincere to me, sounds more honest. And if you want a person you want a person to try to do that. And then in closing arguments, right, as the lawyer, I'd say something like, ladies and gentlemen, you know, we chose you to be on this jury because you swore that you would do your level best to be fair. That's why we chose you. And I'm confident that you're going to do that here. So when you heard that police officer's testimony, the judge told you, you can't give more credit to that testimony just because it's a police officer. And I trust that you're going to do that and that you're going to look at witness number three, John Smith. You don't look at John Smith. John Smith has a different recollection and you're duty bound, duty bound to look at that testimony and this person's credibility, you know, the same degree as that other witness. Right. And now what you have is just a he said, she said matter. And this is a criminal case that has to be reasonable doubt. Right. So, you know, so you and really someone who's trying to do the right thing, it's helpful. But no, you're not going to just find 14 people with no biases. That's that's absurd. Well, that's that's fascinating that especially the way you're inspiring the way you're speaking now is I mean, I guess you're calling on the jury. That's kind of the whole system is you're calling on the jury, each individual in the jury to step up and really think, you know, to step up and be their most thoughtful selves, actually, most introspective. Like you're trying to basically ask people to be their best selves. And that's and I guess a lot of people step up to that. That's why the system works. I'm very I'm very pro jury of juries. They they get it right. It works a lot of the time, most of the time. And they really work hard to do it. So what do you think happens? I mean, maybe I'm not so much on the legal side of things, but on the social side, it's like with O.J. Simpson trial. Do you think it's possible that Derek Chauvin does not get convicted of the what is the second degree murder? How do you think about that? How do you think about the potential social impact of that? The the riots, the protests of either either direction, any words that are said, the tension here could be explosive, especially with the cameras. Yeah. So, yes, there's certainly a possibility that he he'll be acquitted for homicide charges for the jury to convict. They have to make a determination as to officer Chauvin's former officer Chauvin's state of mind, whether he intended. To cause some harm, whether he was grossly reckless. In causing harm so much so that he disregarded a known risk of death or serious bodily injury, and as you may have read in the papers yesterday, the judge allowed a third degree murder charge in Kentucky, which is it's the mindset, the state of mind there is not an intention, but it's depraved indifference. And what that means is that the jury doesn't have to find that he intended to do anything. Rather, they could find that he was just indifferent to a risk as dark. Yeah. Yeah. I'm not sure what's worse. Well, that's a good point. But but it's another basis for the jury to convict. But but look, you never know what what happens when you go to a jury trial. So there could be a an acquittal. And if there is, I imagine there would be massive protests if he's convicted. I don't think that would happen because I just don't see at least nothing I've seen or read suggest that there's a big pro Chauvin camp out there ready to protest. Well, there could be a set. Is there also potential tensions that could arise from the sentencing? I don't know how that exactly works. Sort of not enough years kind of thing. Yeah, it could be like all that kind of stuff. I mean, it's a lot could happen. So it depends on what he's convicted of. You know, one count, I think, is like up to 10 years. Another counts up to 40 years. So it depends what he's convicted of. And, yes, it depends on how much of the how much time the judge gives him if he is convicted. There's a lot of space for people to be very angry. And so we will we will see what what happens. I just feel like with the judge and the lawyers, there's an opportunity to have really important, long lasting speeches. I don't know if they think of it that way, especially with the cameras. It feels like they have the capacity to heal or to divide. Do you ever think about that as a as a lawyer, as a legal mind, that your words aren't just about the case, but about the they'll reverberate through history, potentially? That is that is certainly a possible consequence of things you say. I don't think that most lawyers think about that in the context of the case. Your role is much more narrow. You're the partisan advocate as a defense lawyer, partisan advocate for that client. As a prosecutor, you're a minister of justice attempting to prosecute that particular case. But the reality is you are absolutely correct that sometimes the things you say will have a shelf life. And you mentioned O.J. Simpson before. You know, if the glove doesn't fit, you must acquit. It's going to be just in our lexicon for probably a long time now. So so it happens. But that's not and it shouldn't be foremost on your mind. Right. What do you make? What do you make of the O.J. Simpson trial? Do you have thoughts about it? He is he's out and about on social media now. He's a public figure. Is there lessons to be drawn from that whole saga? Well, you know, that was an interesting case. I was a young public defender, I want to say, in my first year as a public defender when that verdict came out. So that case was important in so many ways. One, it was the first DNA case, major DNA case. And there were significant lessons learned from that one mistake that the prosecution made was that they didn't present the science in a way that a lay jury could understand it. And what Johnny Cochran did was he understood the science and was able to. Translate that into into a vocabulary that he bet that that jury understood. So so Cochran was dismissive of a lot of DNA. They say, you know, he said something like, oh, you know, they say they found, you know, such and such amount of DNA. That's just like me, you know, wiping my finger against my nose and and and just that little bit of DNA. And that was effective because the prosecution hadn't done a good job of establishing that. Yes, it's microscopic. You don't need that much. Yes, wiping your hand on your nose and touching something you can transfer a lot of DNA and that gives you good information. But, you know, it was the first time that the public generally and that jury maybe since high school science, it heard, you know, you know, nucleotide. I mean, it was just all these terms getting thrown at them. And and but it was not weaved into a narrative. So Cochran taught us that no matter what type of case it is, no matter what science is involved, it's still about storytelling. It's still about a narrative. And he was and he was great at that at that at that narrative and was consistent with his narrative all the way out. Another lesson that was relearned is that, you know, you never ask a question to which you don't know the answer. That's like trial absentee one on one. And so when they gave OJ Simpson the glove and it wouldn't fit, you know, you don't you don't do things where you just don't know how it's going to turn out. It was way, way too risky. And then and I think that's what acquitted him because the glove just wouldn't fit. And he got to do this and ham in front of the camera and all of that. And it was big. Do you think about do you think about representation of storytelling like you yourself and your absolutely absolutely. We tell stories. It is fundamental. We since time immemorial, we have told stories to help us make sense of the world around us. So as a scientist, you tell a different type of story. But we as a public have told stories from time immemorial to help us make sense of the physical and the natural world. And we are still a species that is moved by storytelling. So that that's first and last in trial work. You have to tell a good story. And, you know, the basic introductory books about trial work teach young students, young students and young lawyers to to start an opening with this case is about this case is about. And then you fill in the blank and, you know, that's your narrative. That's the narrative you're going to you're going to tell. And of course, you can do the ultra dramatic. The glove doesn't fit kind of the climax and all those kinds of things. Yes. But that's the best of narratives. Yes. The stories. Yes. Speaking of other really powerful stories that you were involved with is the Aaron Hernandez trial and the whole story, the whole legal case. Can you maybe overview the big picture story and legal case of Aaron Hernandez? Yes. So Aaron, whom I miss a lot. So he was charged with a double murder in in in the case that I tried. And this was a unique case in one of those impossible cases, in part because Aaron had already been convicted of a murder. And so we had a client who was on trial for a double murder after having already been convicted of a separate murder. And we had a jury pool, just about all of whom knew that he had been convicted of a murder because he was a very popular football player in Boston, which is a big football town with the with the Patriots. So, you know, so everyone knew that he was convicted murderer. And here we are defending for in a double murder case. So that was that that was the context. It was not a case in the sense that this murder had gone gone unsolved for a couple of years. And then a nightclub bouncer said something to a cop who was working at a club that Aaron Hernandez was somehow involved in that in that murder that happened in the theater district. That's the district where all the clubs are in Boston and where the homicide occurred. And once the police heard Aaron Hernandez's name, then it was you know, they went all out in order to do this. They found a guy named Alexander Bradley, who was a very significant drug dealer in the sort of Connecticut area, very, very significant, very powerful. And he essentially, in exchange for a deal, pointed to Aaron, said, yeah, I was with Aaron and and Aaron was the was the murderer. So that's how the case came came to court. OK, so that that's the context. What was your involvement in this case, like legally, intellectually, psychologically, when this particular second charge of murder? So a friend called me, Jose Baez, who is a defense attorney, and he comes to a class that I teach every year at Harvard, the trial advocacy workshop as one of my teaching faculty members. It's a class where we teach students how to try cases. So Jose called me and said, hey, I got a call from Massachusetts, Aaron Hernandez. You want to go and talk to him with me? So I said, sure. So we went up to the to the prison and and met Aaron and spoke with him for two or three hours that first time. And before we left, he said he wanted to retain us. He wanted to work with us. And that started the representation. What was he like? What would in that time? What was he worn down by the whole process? Was there still he was light in that he was not he he had. I mean, more than just the light, he was luminous, almost. He had a radiant million dollar smile whenever you walked in. My first impression, I distinctly remember was, wow, this is what a professional athlete looks like. And he walked in and he's just this bigger and more fit than, you know, than anyone, you know, anywhere. And it's like, wow, this. And, you know, when you saw him on television, he looked kind of little. And I was like, so I remember thinking, well, what what do those other guys look like in person? And and he's extraordinarily polite, young. I was surprised by how young he was. Both in mind and body. But chronologically, I was thinking he was in his, you know, in his early 20s, I believe. But there seemed to be like an innocence still in terms of just the way he saw the world. That's right. They picked that up from the from the documentary. Just take that in. I think that's right. Yeah. Yeah. So there is a Netflix documentary titled Killer Inside the Mind of Aaron Hernandez. What are your thoughts on this documentary? I don't know if you got a chance to see. I did not. I have not seen it. I did not participate in it. I know I was in it because of there was news footage that but I did not participate in it. I had not talked to Aaron about about press or anything before he died. My strong view is that the attorney client privilege survives death. And so I was not inclined to talk about anything that Aaron and I talked about. So I just didn't participate in and never watched. Not even watch. So is that does that apply to most of your work? Do you try to stay away from the way the press perceives stuff during? Yes. I try to stay away from it. I will view it afterwards. I just hadn't gotten around to watching Aaron. It's kind of it's kind of sad. So I just haven't watched it. But I definitely stay away from the press during trial. And, you know, there are some lawyers who watch it religiously to see what's going on. But, you know, I'm I'm confident in my years of training and so forth that and that I can actively sense what's going on in the courtroom. And and that I really don't need advice from Joe for seven, six at Gmail, you know, some random guy on the Internet telling me how to try cases. So, yeah, it's just to me, it's just confusing. And I just keep it out of my mind. And even if you think you can ignore it, just reading it will have a little bit of an effect on your mind. I think that's right. Over time, I might accumulate. So the documentary, but in general, it mentioned or kind of emphasized and talked about Aaron's sexuality or sort of they were discussing, basically, the idea that he was a homosexual and some of the trauma, some of the suffering that he endured in his life had to do with the sort of fear given the society of of what his father would think of what others around him, sort of, especially in sport culture and football and so on. So I don't know in your interaction with him was do you think that maybe even leaning up to a suicide, do you think his struggle with coming to terms with his sexuality had a role to play in much of his difficulties? Well, I'm not going to talk about my interactions with them and anything I derive from from that. But, you know, what I will say is that a story broke on the on the radio at some point during the trial that Aaron had been in the same sex relationship with someone and some sport, local sportscasters, local Boston sportscaster. So we really mushroomed the the the story. So he and everyone was aware of it. You'll you also may know from the court record that the prosecutors floated a specious theory for a minute, but then backed off of it that, you know, that Aaron was that there was some sort of, I guess, gay rage at work with him. And that might be a cause motive for the killing. And luckily, they really backed off of that. That was quite an offensive claim in theory. So but to answer your question more directly, I have no idea why he killed himself. It was a surprise and a shock. I was scheduled to go see him like a couple of days after it happened. I mean, he was anxious for Jose and I to come in and do the appeal from the murder, which he was convicted for. He wanted us to take over that appeal. He was talking about going back to football. I mean, he said, well, you talk about this. So you earlier you talked about the sort of innocent aspect of him. He said, you know, well, Ron, maybe not maybe not the Patriots, but, you know, get back in the league. And I was like, you know, Aaron, that's that's going to be tough, man. But but he really, you know, he really believed it. And and then, you know, for a few days later that to happen, it was just it was a real shock to me. Like when you look back at that, at his story, does it make you sad? Very, very. I thought so. So, one, I believe he he absolutely did not commit the crimes that we acquitted him on. I think that was the right answer for for for that. I don't know enough about Bradley. The first case, I'm sorry to make a make an opinion on. But but in our case, you know, it was just he had the misfortune of having a famous name. And the police department just really just just just really got got on him there. So, yes, it's it's I miss him a lot. It was very, very sad. Surprising. Yeah. And I mean, just on the human side, of course, we don't know the full story, but just everything that led up to suicide. Everything led up to an incredible professional football player. You know, that whole story, if remarkably talented athlete, remarkably talented athlete. And it has to do with all the all the possible trajectories, right, that we can take through life, as we were talking about before. And some of them lead to to suicide, sadly enough. And it's always tragic when you have some, you know, somebody with with great potential result in the things that happen. Right. People love it. When I ask about books, I don't know if whether technical, like legal or fiction, nonfiction books throughout your life have had an impact on you. If there's something you could recommend or something you could speak to about something that inspired ideas, insights about this world, complicated world of ours. Oh, wow. Yeah. So I'll give you a couple. So one is a Contingency, Irony and Solidarity by Richard Warty. He's passed away now, but was a philosopher at some of our major institutions, Princeton, Harvard, Stanford. Contingency, Irony and Solidarity, at least that's a book that really helped me work through a series of thoughts. So it stands for the proposition that that our most deeply held beliefs are contingent, that there there's nothing beyond history or prior to socialization that's definitory of the human being. That's right. And he says that our most deeply held beliefs are received wisdom and highly contingent along a number of registers. And he does that, but then goes on to say that he nonetheless can hold strongly held beliefs, recognizing their contingency, but still believes them to be true and accurate. And it helps you to work through what could be an intellectual tension. So you don't delve into one doesn't delve into relativism. Everything is OK, but it gives you a vocabulary to think about how to negotiate these realities. Do you share this tension? I mean, there is a real tension. It seems like even like the law, the legal system is all just a construct of our human ideas. And yet it seems to be almost feels fundamental to what a just society is. Yeah, I definitely share the tension and love the his his vocabulary in the way he's helped me resolve the tension. So, right. I mean, yeah. So like, you know, infanticide, for example, perhaps it's socially contingent. Perhaps it's received wisdom. Perhaps it's anthropological. You know, we need to propagate the species. And I still think it's wrong. And and and and Rorty has helped me develop a category to say to say that, no, I can't provide any in Rorty's words, non-circular theoretical backup for this proposition. At some point, it's going to run me in a circularity problem. But that's OK. I hope this nonetheless and for recognition of its contingency. But what it does is is is is makes you humble. And and when you're humble, that's good because, you know, this notion that ideas are always already in progress, never fully formed, I think, is is is the sort of intellectual I strive to be. And if I have a a sufficient degree of humility that I don't have the final answer, capital A, then that's going to help me to get to better answers. Lowercase a and and Rorty does. And he talks about in the solidarity part of the book. He has this concept of imaginative, the imaginative ability to see other different people as we instead of they. And I just think it's a beautiful concept. But he talks about this imaginative ability and it's this active process. So, I mean, so that's a book that's done a lot of work for me over the years. Souls of Black Folk by W.B. Du Bois was absolutely pivotal, pivotal in my intellectual development. One of the premier set of essays in the Western literary tradition. And it's a deep and profound sociological, philosophical and historical analysis of the predicament of blacks in America from one of our country's greatest polymaths. It it's just a it's a beautiful text. And I go to it yearly. So for somebody like me, so growing up in the Soviet Union, the struggle, the civil rights movement, the struggle of race and all those kinds of things that is, you know, this universal. But it's also very much a journey of the United States. It was kind of a foreign thing that I stepped into. Is that something you would recommend somebody like me to read or is there other things about race that are good to connect? Because my flavor of suffering injustice, I'm a Jew as well. My flavor has to do with World War II and the studies of that, you know, all the injustices there. So I'm now stepping into a new set of injustices and trying to learn the landscape. I would I would say anyone is is a better person for having read Du Bois. It's just he's just a remarkable writer and thinker. And it I mean, to the extent you're interested in learning another history, he does it in a way that is quite sophisticated. So it's so it's interesting. I was going to give you three books. I noted the accent when I met you, but I didn't know exactly where you're from. Yes. But the other book I was going to say is Dostoevsky's Crime and Punishment. And I mean, I've always wanted to go to St. Pete's just to sort of see with my own eyes what the word pictures that Dostoevsky created in Crime and Punishment. And, you know, I love others of this stuff to the Brothers Keremosov and so forth. But Crime and Punishment, I first read in high school as a junior or senior. And it is a deep and profound meditation on the both the meaning and the measure of our lives. And Dostoevsky, obviously, in conversation with other thinkers, really gets at the the the crux of a fundamental philosophical problem. What does it mean to be a human being? And and for that, Crime and Punishment captured me as a teenager. And that's another text that I return to often. We've talked about young people a little bit at the beginning of our conversation. Is there advice that you could give to a young person today thinking about their career, thinking about their life, thinking about making their way in this world? Yeah, sure. I'll share some advice. It actually picks up on a question we talked about earlier within the academy in schools. But it's some advice that a professor gave to me when I got to Harvard. And it is this that you have to be willing to come face to face with your intellectual limitations and keep going. And that's it. And it's hard for people. I mean, you mentioned this earlier to to face really difficult tasks, and particularly in these sort of elite spaces where you've excelled all your life and you come to MIT and you're like, wait a minute, I don't understand this. Yeah, wait, this is hard. I've never had something really hard before. And there are a couple options and a lot of people will pull back and take the gentleman or gentlewoman's bee and just go on or risk. Going out there, giving it your all and still not quite getting it. And that that that's a risk, but it's a risk well worth it because you're just going to be the better person, the better student for it. And, you know, and even outside of the academy, I mean, come come face to face with your fears and keep going and keep going in life. And you're going to be the better person, the better human being. Yeah, it does seem to be I don't know what it is, but it does seem to be that fear is a good indicator of something you should probably face. Yes, like fear kind of shows the way a little bit. Not always. You might not want to go into the cage with a lion, but maybe you should. Maybe. Let me ask sort of a darker question because we're talking about Dostoevsky, we might as well. Do you and connected to the freeing innocent people, do you think about mortality? Do you think about your own death? Are you afraid of death? I'm not afraid of death. I do think about it more now because I'm now in my mid 50s. So I used to not think about it much at all. But the harsh reality is that I've got more time behind me now that I do in front of me. And it kind of happens all of a sudden to realize, wait a minute, I'm I'm I'm actually on the back nine now. So, yeah, my mind moves to it from time to time. I don't dwell on it. I'm not afraid of it. My own personal religious commitments. I'm I'm I'm Christian and my religious commitments buoy me that, you know, that that death. And I believe this death is not not not the end. So I'm not afraid of it. Now, this is not to say that I want to I want to I want to rush to the afterlife. I'm good right here for a long time. I hope I've got, you know, 30, 35, 40 more years to go. But but but no, I don't I don't I don't fear death. We're we're we're finite creatures. We're all going to we're all going to die. Well, the mystery of it, you know, for somebody, at least for me, we human beings want to figure everything out. Whatever the afterlife is, there's still a mystery to it. That that uncertainty can be terrifying if you ponder it. But maybe what you're saying is you haven't pondered it too deeply so far and it's worked out pretty good. It's worked out. Yeah. No, no, no complaints. So you said, again, Dostoevsky kind of was exceptionally good at getting to the core of what it means to be human. Do you think about, like, the why of why we're here? The meaning of this whole existence? Yeah. No, I do. I think and actually think that's the purpose of an education. What does it mean to be a human being? And in one way or another, we set out to answer those questions and we do it in a different way. I mean, some may look to philosophy to answer these questions. Why is it in one's personal interest to to to do good, to do just to do justice? Some may look at it through the economist lens. Some may look at it through the microscope in the laboratory that the phenomenal world is, is, is the meaning of life. Others may say that that's one vocabulary, that's one description. But the poet describes a reality to the same degree as a physicist. But that's the purpose of of an education. It's to sort of work through these issues. What does it mean to be a what does it mean to be a human being? And I think it's a fascinating journey. I think it's a lifelong endeavor to figure out what is the thing that nugget that makes us human. Do you still see yourself as a student? Of course. Yes. I mean, that's that's the best part about going into into university teaching. You're a lifelong student. I'm always learning. I learn from my students and with my students and my colleagues. And you're you continue to read and and learn and and modify opinions. And I think it's just a wonderful thing. Well, Ron, I'm so glad that somebody like you is carrying the fire of what is the best of Harvard. So it's a huge honor that you spend so much time, waste so much of your valuable time with me. I really appreciate that. Not a waste at all. I think a lot of people love it. Thank you so much for talking today. Thank you. Thanks for listening to this conversation with Ronald Sullivan. And thank you to Brooklyn Sheets, Wine Access Online Wine Store, Munk Pack, Low Carb Snacks and Blinkist app that summarizes books. Click their links to support this podcast. And now let me leave you with some words from Nelson Mandela. When a man is denied the right to live the life he believes in, he has no choice but to become an outlaw. Thank you for listening and hope to see you next time.

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Frank Wilczek: Physics of Quarks, Dark Matter, Complexity, Life & Aliens | Lex Fridman Podcast #187

The following is a conversation with Frank Wilczek, a theoretical physicist at MIT, who won the Nobel Prize for the co-discovery of asymptotic freedom in the theory of strong interaction. Quick mention of our sponsors, the Information, NetSuite, ExpressVPN, Blinkist, and A.S.L.E.E.P. Check them out in the description to support this podcast. As a side note, let me say a word about asymptotic freedom. Protons and neutrons make up the nucleus of an atom. Strong interaction is responsible for the strong nuclear force that binds them. But strong interaction also holds together the quarks that make up the protons and neutrons. Frank Wilczek, David Gross, and David Pulitzer came up with a theory postulating that when quarks come really close to one another, the attraction abates and they behave like free particles. This is called asymptotic freedom. This happens at very, very high energies, which is also where all the fun is. This is the Lex Friedman Podcast, and here is my conversation with Frank Wilczek. What is the most beautiful idea in physics? The most beautiful idea in physics is that we can get a compact description of the world that's very precise and very full at the level of the operating system of the world. That's an extraordinary gift, and we get worried when we find discrepancies between our description of the world and what's actually observed at the level even of a part in a billion. You actually have this quote from Einstein that the most incomprehensible thing about the universe is that it is comprehensible, something like that. Yes, so that's the most beautiful surprise that I think that really was, to me, the most profound result of the scientific revolution of the 17th century with the shining example of Newtonian physics that you could aspire to completeness, precision, and a concise description of the world, of the operating system. And it's gotten better and better over the years, and that's the continuing miracle. Now, there are a lot of beautiful sub-miracles, too. The form of the equations is governed by high degrees of symmetry, and they have a very surprising kind of mind-expanding structure, especially in quantum mechanics. But if I had to say, the single most beautiful revelation is that, in fact, the world is comprehensible. Would you say that's a fact or a hope? It's a fact. You can point to things like the rise of gross national products per capita around the world as a result of the scientific revolution. You can see it all around you. And recent developments with exponential production of wealth, control of nature at a very profound level where we do things like sense tiny, tiny, tiny, tiny vibrations to tell that there are black holes colliding far away, or we test laws, as I alluded to, as a part in a billion, and do things in what appear on the surface to be entirely different conceptual universes. I mean, on the one hand, pencil and paper are nowadays computers that calculate abstractions, and on the other hand, magnets and accelerators and detectors that look at the behavior of fundamental particles, and these different universes have to agree, or else we get very upset. And that's an amazing thing if you think about it. And it's telling us that we do understand a lot about nature at a very profound level. And there are still things we don't understand, of course, but as we get better and better answers and better and better ability to address difficult questions, we can ask more and more ambitious questions. Well, I guess the hope part of that is because we are surrounded by mystery. So we've, one way to say it, if you look at the growth, the GDP, over time, that we figured out quite a lot, and we're able to improve the quality of life because of that, and we've figured out some fundamental things about this universe, but we still don't know how much mystery there is. And it's also possible that there's some things that are, in fact, incomprehensible to both our minds and the tools of science. Like we, the sad thing is we may not know it because, in fact, they are incomprehensible. And that's the open question is how much of the universe is comprehensible? If we figured out the everything, what's inside the black hole, and everything that happened at the moment of the Big Bang, does that still give us the key to understanding the human mind and the emergence of all the beautiful complexity we see around us? That's not, like when I see these objects, like I don't know if you've seen them, like cellular automata, all these kinds of objects where from simple rules emerges complexity, it makes you wonder maybe it's not reducible to simple, beautiful equations, the whole thing, only parts of it. That's the tension I was getting at with the hope. Well, when we say the universe is comprehensible, we have to kind of draw careful distinctions about, or definitions about what we mean by that. Both the universe and the comprehensible. Exactly, right. So in certain areas of understanding reality, we've made extraordinary progress, I would say, in understanding fundamental physical processes and getting very precise equations that really work and allow us to do profound sculpting of matter, to make computers and iPhones and everything else, and they really work, and they're extraordinary productions. And that's all based on the laws of quantum mechanics, and they really work, and they give us tremendous control of nature. On the other hand, as we get better answers, we can also ask more ambitious questions, and there are certainly things that have been observed, even in what would be usually called the realm of physics, that aren't understood. For instance, there seems to be another source of mass in the universe, the so-called dark matter, that we don't know what it is, and it's a very interesting question what it is. But also, as you were alluding to, it's one thing to know the basic equations, it's another thing to be able to solve them in important cases. So we run up against the limits of that in things like chemistry, where we'd like to be able to design molecules and predict their behavior from the equations. We think the equations could do that in principle, but in practice, it's very challenging to solve them in all but very simple cases. And then there's the other thing, which is that a lot of what we're interested in is historically conditioned. It's not a matter of the fundamental equations, but about what has evolved or come out of the early universe and formed into people and frogs and societies and things. And the basic laws of physics only take you so far, and that kind of provides a foundation, but you need entirely different concepts to deal with those kind of systems. And one thing I can say about that is that the laws themselves point out their limitations, that they're laws for dynamical evolution, so they tell you what happens if you have a certain starting point, but they don't tell you what the starting point should be, at least, yeah. And the other thing that emerges from the equations themselves is the phenomena of chaos and sensitivity to initial conditions, which tells us that there are intrinsic limitations on how well we can spell out the consequences of the laws if we try to apply them. It's the old apple pie. If you wanna, what is it, make an apple pie from scratch? You have to build the universe or something like that. Well, you're much better off starting with apples than starting with quarks, let's put it that way. In your book, A Beautiful Question, you ask, does the world embody beautiful ideas? So the book is centered around this very interesting question. It's like Shakespeare, you can dig in and read into all the different interpretations of this question, but at the high level, what to you is the connection between beauty of the world and physics of the world? In a sense, we now have a lot of insight into what the laws are, the form they take that allow us to understand matter in great depth and control it, as we've discussed. And it's an extraordinary thing how mathematically ideal those equations turn out to be. In the early days of Greek philosophy, Plato had this model of atoms built out of the five perfectly symmetrical platonic solids, so there was somehow the idea that mathematical symmetry should govern the world, and we've out-Platoed Plato by far in modern physics because we have symmetries that are much more extensive, much more powerful, that turn out to be the ingredients out of which we construct our theory of the world, and it works. So that's certainly beautiful. So the idea of symmetry, which is a driving inspiration in much of human art, especially decorative art, like the Alhambra or wallpaper designs or things you see around you everywhere, also turns out to be the dominant theme in modern fundamental physics, symmetry and its manifestations. The laws turn out to be very, to have these tremendous amounts of symmetry. You can change the symbols and move them around in different ways, and they still have the same consequences. So that's beautiful. These things, these different, these concepts that humans find appealing also turn out to be the concepts that govern how the world actually works. I don't think that's an accident. I think humans were evolved to be able to interact with the world in ways that are advantageous and to learn from it, and so we are naturally evolved or designed to enjoy beauty and to symmetry, and the world has it, and that's why we resonate with it. Resonate with it. Well, it's interesting that the ideas of symmetry emerge at many levels of the hierarchy of the universe. So you're talking about particles, but it also is at the level of chemistry and biology, and the fact that our cognitive, sort of our perception system and whatever our cognition is also finds it appealing, or somehow our sense of what is beautiful is grounded in this idea of symmetry or the breaking of symmetry. Symmetry is at the core of our conception of beauty, whether it's the breaking or the non-breaking of the symmetry. It makes you wonder why, why? Like, so I come from Russia, and the question of Dostoevsky, he has said that beauty will save the world. Maybe as a physicist you can tell me what do you think he meant by that? I don't know if it saves the world, but it does turn out to be a tremendous source of insight into the world when we investigate kind of the most fundamental interactions, things that are hard to access because they occur at very short distances between very special kinds of particles whose properties are only revealed at high energies. We don't have much to go on from everyday life, but so we have when we guess what the, and the experiments are difficult to do, so you can't really follow a very, wholly empirical procedure to sort of, in the Baconian style, figure out the laws, kind of step by step just by accumulating a lot of data. What we actually do is guess, and the guesses are kind of aesthetic, really. What would be a nice description that's consistent with what we know? And then you try it out and see if it works, and by gosh, it does in many profound cases. So there's that, but there's another source of symmetry which I didn't talk so much about in A Beautiful Question, but does relate to your comments, and I think very much relates to the source of symmetry that we find in biology and in our heads, in our brain, which is that, well, it is discussed a bit in A Beautiful Question and also in Fundamentals, is that when you have, symmetry is also a very important means of construction. So when you have, for instance, simple viruses that need to construct their coat, their protein coat, the coats often take the form of platonic solids. And the reason is that the viruses are really dumb, and they only know how to do one thing, so they make a pentagon, then they make another pentagon, and they make another pentagon, and they all glue together in the same way, and that makes a very symmetrical object. So the rules of development, when you have simple rules and they work again and again, you get symmetrical patterns. That's kind of, in fact, it's a recipe also for generating fractals, you know, like the kind of broccoli that has all this internal structure. And I wish I had a picture to show, but maybe people remember it from the supermarket, and you say, how did a vegetable get so intelligent to make such a beautiful object with all this fractal structure? And the secret is stupidity. You just do the same thing over and over again. And in our brains also, we came out, we start from single cells, and they reproduce, and each one does roughly the same thing. The program evolves in time, of course, different modules get turned on and off, different regions of the genetic code get turned on and off. But basically, a lot of the same things are going on, and they're simple things, and so you produce the same patterns over and over again, and that's a recipe for producing symmetry, because you're getting the same thing in many, many places. And if you look at, for instance, the beautiful drawings of Ramon y Cajal, the great neuroanatomist who drew the structure of different organs like the hippocampus, you see it's very regular and very intricate, and it's symmetry in that sense. It's many repeated units that you can take from one place to the other and see that they look more or less the same. But what you're describing, this kind of beauty that we're talking about now, is a very small sample in terms of space-time in a very big world, in a very short, brief moment in this long history. In your book, Fundamentals, 10 Keys to Reality, I'd really recommend people read it. You say that space and time are pretty big, or very big. How big are we talking about? Can you tell a brief history of space and time? It's easy to tell a brief history, but the details get very involved, of course. But one thing I'd like to say is that if you take a broad enough view, the history of the universe is simpler than the history of Sweden, say. Because your standards are lower. But just to make it quantitative, I'll just give a few highlights. And it's a little bit easier to talk about time, so let's start with that. The Big Bang occurred, we think, the universe was much hotter and denser and more uniform about 13.8 billion years ago, and that's what we call the Big Bang. And it's been expanding and cooling, the matter in it has been expanding and cooling ever since. So in a real sense, the universe is 13.8 billion years old. That's a big number, kind of hard to think about. A nice way to think about it, though, is to map it onto one year. So let's say the universe, just linearly map the time intervals from 13.8 billion years onto one year. So the Big Bang then is on January 1st at 12 a.m. And you wait for quite a long time before the dinosaurs emerge. The dinosaurs emerge on Christmas, it turns out. And- 12 months, almost 12 months later. Getting close to the end, yes. Getting close to the end. And the extinction event that let mammals and ultimately humans inherit the Earth from the dinosaurs occurred on December 30th. And all of human history is a small part of the last day. And so yes, so we're occupying only, and a human lifetime is a very, very infinitesimal part of this interval, of these gigantic cosmic reaches of time. And in space, we can tell a very similar story. In fact, it's convenient to think that the size of the universe is the distance that light can travel in 13.8 billion years. That's, so it's 13.8 billion light years. That's how far you can see out. That's how far things can, signals can reach us from. And that is a big distance, because compared to that, the universe, the Earth is a fraction of a light second. So again, it's really, really big. And so we have, if we wanna think about the universe as a whole in space and time, we really need a different kind of imagination. It's not something you can grasp in terms of psychological time. In a useful way, you have to think, you have to use exponential notation and abstract concepts to really get any hold on these vast times and spaces. On the other hand, let me hasten to add that that doesn't make us small or make the time that we have to us small, because again, looking at those pictures of what our minds are in some sense, of components of our minds, these beautiful drawings of the cellular patterns inside the brain, you see that there are many, many, many processing units. And if you analyze how fast they operate, I tried to estimate how many thoughts a person can have in a lifetime. That's kind of a fuzzy question, but I'm very proud that I was able to define it pretty precisely. And it turns out we have time for billions of meaningful thoughts in a lifetime. So it's a lot. We shouldn't think of ourselves as terribly small, either in space or in time, because although we're small in those dimensions compared to the universe, we're large compared to meaningful units of processing information and being able to conceptualize and understand things. Yeah, but 99% of those thoughts are probably food, sex, or internet-related. Well, yeah, well, they're not necessarily. Only like 0.1 is Nobel Prize-winning ideas. That's true, but there's more to life than winning Nobel Prizes. How did you do that calculation? Can you maybe break that apart a little bit, just kind of for fun, sort of an intuition of how we calculate the number of thoughts? The number of thoughts, right. It's necessarily imprecise, because a lot of things are going on in different ways. And what is a thought? But there are several things that point to more or less the same rate of being able to have meaningful thoughts. For instance, the one that I think is maybe the most penetrating is how fast we can process visual images. How do we do that? If you've ever watched old movies, you can see that, well, any movie, in fact, that a motion picture is really not a motion picture. It's a series of snapshots that are playing one after the other. And it's because our brains also work that way. We take snapshots of the world, integrate over a certain time, and then go on to the next one. And then by post-processing, create the illusion of continuity and flow, we can deal with that. And if the flicker rate is too slow, then you start to see that it's a series of snapshots. And you can ask, what is the crossover? When does it change from being something that is matched to our processing speed versus too fast? And it turns out about 40 per second. And then if you take 40 per second as how well, how fast we can process visual images, you get to several billions of thoughts. If you, similarly, if you ask, what are some of the fastest things that people can do? Well, they can play video games, they can play the piano very fast if they're skilled at it. And again, you get to similar units. Or how fast can people talk? You get to, within a couple of orders of magnitude, you get more or less to the same idea. So that's how you can say that there's billions of, there's room for billions of meaningful thoughts. I won't argue for exactly two billion versus 1.8 billion. It's not that kind of question. But I think any estimate that's reasonable will come out within, say, 100 billion and 100 million. So it's a lot. It would be interesting to map out for an individual human being the landscape of thoughts that they've sort of traveled. If you think of thoughts as a set of trajectories, what that landscape looks like. I mean, I've been recently really thinking about this Richard Dawkins idea of memes and just all this ideas and the evolution of ideas inside of one particular human mind and how they're then changed and evolved by interaction with other human beings. It's interesting to think about. So if you think the number is billions, you think there's also social interaction. So these aren't, like, there's interaction in the same way you have interaction with particles. There's interaction between human thoughts that are perhaps that interaction in itself is fundamental to the process of thinking. Like, without social interaction, we would be stuck walking in a circle. We need the perturbation of other humans to create change and evolution. Once you bring in concepts of interactions and correlations and relations, then you have what's called a combinatorial explosion that the number of possibilities expands exponentially, technically, with the number of things you're considering. And it can easily, rapidly outstrip these billions of thoughts that we're talking about. So we definitely cannot, by brute force, master complex situations or think of all the possibilities in a complex situations. I mean, even something as relatively simple as chess is still something that human beings can't comprehend completely. Even the best players lose, still sometimes lose, and they consistently lose to computers these days. And in computer science, there's a concept of NP-complete. So large classes of problems, when you scale them up beyond a few individuals, become intractable. And so in that sense, the world is inexhaustible. But and that makes it beautiful that we can make any laws that generalize efficiently and well can compress all of that combinatorial complexity just like a simple rule. That in itself is beautiful. It's a happy situation, I think, that we can find general principles of sort of the operating system that are comprehensible, simple, extremely powerful, and let us control things very well and ask profound questions. And on the other hand, that the world is going to be inexhaustible. Once we start asking about relationships and how they evolve and social interactions, we'll never have a theory of everything in any meaningful sense because... Of everything, everything, truly everything is. Can I ask you about the Big Bang? So we talked about the space and time are really big, but then, and we humans give a lot of meaning to the word space and time in our daily lives. But then can we talk about this moment of beginning and how we're supposed to think about it? That at the moment of the Big Bang, everything was what, like infinitely small? And then it just blew up? We have to be careful here because there's a common misconception that the Big Bang is like the explosion of a bomb in empty space that fills up the surrounding place. It is space. It is, yeah. As we understand it, it's the fact, it's the fact or the hypothesis, but well-supported up to a point, that everywhere in the whole universe, early in the history, matter came together into a very hot, very dense, if you run it backwards in time, matter comes together into a very hot, very dense, and yet very homogeneous plasma of all the different kinds of elementary particles and quarks and anti-quarks and gluons and photons and electrons and anti-electrons, everything, all of that stuff. Like really hot, really, really dense. Really hot. We're talking about way, way hotter than the surface of the sun. In fact, if you take the equations as they come, the prediction is that the temperature just goes to infinity, but then the equations break down. The equations become infinity equals infinity, so they don't feel that it's called a singularity. We don't really know. This is running the equations backwards, so you can't really get a sensible idea of what happened before the Big Bang. We need different equations to address the very earliest moments. We don't really know why things started out that way. We have a lot of evidence that they did start out that way, but since most of the... We don't get to visit there and do controlled experiments. Most of the record is very, very processed, and we have to use very subtle techniques and powerful instruments to get information that has survived. Get closer and closer to the Big Bang. Get closer and closer to the beginning of things. What's revealed there is that, as I said, there undoubtedly was a period when everything in the universe that we have been able to look at and understand, and that's consistent with everything, was in a condition where it was much, much hotter and much, much denser, but still obeying the laws of physics as we know them today. And then you start with that, so all the matter is in equilibrium, and then with small quantum fluctuations and run it forward, and then it produces, at least in broad strokes, the universe we see around us today. Do you think we'll ever be able to, with the tools of physics, with the way science is, with the way the human mind is, we'll ever be able to get to the moment of the Big Bang in our understanding, or even the moment before the Big Bang? Can we understand what happened before the Big Bang? I'm optimistic both that we'll be able to measure more, so observe more, and that we'll be able to figure out more. So they're very, very tangible prospects for observing the extremely early universe, so even much earlier than we can observe now, through looking at gravitational waves. Gravitational waves, since they interact so weakly with ordinary matter, sort of send a minimally processed signal from the Big Bang. It's a very weak signal, because it's traveled a long way and diffused over long spaces, but people are gearing up to try to detect gravitational waves that could have come from the early universe. Yeah, LIGO's incredible engineering project, just the most sensitive, precise devices on Earth. The fact that humans can build something like that is truly awe-inspiring from an engineering perspective. Right, but these gravitational waves from the early universe will probably be of a much longer wavelength than LIGO is capable of sensing, so there's a beautiful project that's contemplated to put lasers in different locations in the solar system. We really, really separate it by solar system scale differences, like artificial planets or moons in different places, and see the tiny motions of those relative to one another as a signal of radiation from the Big Bang. We can also maybe indirectly see the imprint of gravitational waves from the early universe on the photons, the microwave background radiation that is our present way of seeing into the earliest universe, but those photons interact much more strongly with matter. They're much more strongly processed, so they don't give us directly such an unprocessed view of the early universe, of the very early universe, but if gravitational waves leave some imprint on that as they move through, we could detect that too, and people are trying, as we speak, working very hard towards that goal. It's so exciting to think about a sensor the size of the solar system. That would be a fantastic, I mean, that would be a pinnacle artifact of human endeavor to me. It would be such an inspiring thing that just we want to know, and we go to these extraordinary lengths of making gigantic things that are also very sophisticated, because what you're trying to do, you have to understand how they move, you have to understand the properties of light that are being used, the interference between light, and you have to be able to make the light with lasers, and understand the quantum theory, and get the timing exactly right. It's an extraordinary endeavor involving all kinds of knowledge from the very small to the very large, and all in the service of curiosity, and built on a grand scale. Yeah. It would make me proud to be a human if we did that. I love that you're inspired both by the power of theory and the power of experiments. Both, I think, are exceptionally impressive that the human mind can come up with theories that give us a peek into how the universe works, but also construct tools that are way bigger than the evolutionary origins we came from. Right, and by the way, the fact that we can design such things and they work is an extraordinary demonstration that we really do understand a lot. And then in some ways. And it's our ability to answer questions that also leads us to be able to address more ambitious questions. So you mentioned that at the Big Bang in the early days, things were pretty homogeneous. Yes. But here we are, sitting on Earth, two hairless apes, you could say, with microphones, and talking about the brief history of things, you said it's much harder to describe Sweden than it is the universe. So there's a lot of complexity. There's a lot of interesting details here. So how does this complexity come to be, do you think? It seems like there's these pockets. Yeah. We don't know how rare of like, where hairless apes just emerge. Yeah. And then they came from the initial soup that was homogeneous. Was that an accident? Well, we understand in broad outlines how it could happen. We certainly don't understand why it happened exactly in the way it did. But there are certainly open questions about the origins of life, and how inevitable the emergence of intelligence was, and how that happened. But in the very broadest terms, the universe early on was quite homogeneous, but not completely homogeneous. There were part in 10,000 fluctuations in density within this primordial plasma. And as time goes on, there's an instability, which causes those density contrasts to increase. There's a gravitational instability where it's denser, the gravitational attractions are stronger. And so that brings in more matter, and it gets even denser, and so on and so on. So there's a natural tendency of matter to clump because of gravitational interactions. And then the equation is complicated when you have lots of things clumping together. Then we know what the laws are, but we have to, to a certain extent, wave our hands about what happens. But basic understanding of chemistry says that if things, and the physics of radiation tells us that as things start to clump together, they can radiate, give off some energy, so they don't, they slow down. As a result, they lose energy, they can clumber together, cool down, form things like stars, form things like planets. And so in broad terms, there's no mystery. That's what the equations tell you should happen. But because it's a process involving many, many fundamental individual units, the application of the laws that govern individual units to these things is very delicate, or computationally very difficult. And more profoundly, the equations have this probability of chaos or sensitivity to initial conditions, which tells you tiny differences in the initial state can lead to enormous differences in the subsequent behavior. So physics, fundamental physics at some point says, okay, chemists, biologists, this is your problem. And then again, in broad terms, we know how it's conceivable that the humans and things like that can, how complex structure can emerge. It's a matter of having the right kind of temperature and the right kind of stuff. So you need to be able to make chemical bonds that are reasonably stable and be able to make complex structures. And we're very fortunate that carbon has this ability to make backbones and elaborate branchings and things. So you can get complex things that we call biochemistry. And yet the bonds can be broken a little bit with the help of energetic injections from the sun. So you have to have both the possibility of changing, but also the possible, a useful degree of stability. And we know at that very, very broad level, physics can tell you that it's conceivable. If you want to know what actually, what really happened, what really can happen, then you have to work, go to chemistry. If you wanna know what actually happened, then you really have to consult the fossil record and biologists. So these ways of addressing the issue are complementary in a sense. They use different kinds of concepts, they use different languages, and they address different kinds of questions, but they're not inconsistent, they're just complementary. It's kind of interesting to think about those early fluctuations as our earliest ancestors. Yes, that's right. So it's amazing to think that this is the modern answer to the, or the modern version of what the Hindu philosophers had, that art thou. If you ask, okay, that, those little quantum fluctuations in the early universe are the seeds out of which complexity, including plausibly humans, really evolve. You don't need anything else. That brings up the question of asking for a friend here, if there's other pockets of complexity, commonly called as alien intelligent civilizations out there. Well, we don't know for sure, but I have a strong suspicion that the answer is yes, because the one case we do have at hand to study here on Earth, we sort of know what the conditions were that were helpful to life, the right kind of temperature, the right kind of star, that keeps, maintains that temperature for a long time, the liquid environment of water. And once those conditions emerged on Earth, which was roughly four and a half billion years ago, it wasn't very long before what we call life started to leave relics. So we can find forms of life, primitive forms of life that are almost as old as the Earth itself, in the sense that once the Earth was turned from a very hot boiling thing and cooled off into a solid mass with water, life emerged very, very quickly. So it seems that these general conditions for life are enough to make it happen relatively quickly. Now, the other lesson, I think that one can draw from this one example. It's dangerous to draw lessons from one example, but that's all we've got. And that the emergence of intelligent life is a different issue altogether. That took a long time and seems to have been pretty contingent. But for a long time, well, for most of the history of life, it was single-celled things. Even multicellular life only arose about 600 million years ago, so much after. And then intelligence is kind of a luxury, if you think. Many more kinds of creatures have big stomachs than big brains. In fact, most have no brains at all in any reasonable sense. And the dinosaurs ruled for a long, long time, and some of them were pretty smart, but they were at best bird brains because birds came from the dinosaurs. And it could have stayed that way. And the emergence of humans was very contingent and kind of a very, very recent development on evolutionary time scales. And you can argue about the level of human intelligence, but I think it's pretty impressive. That's what we're talking about. It's very impressive and can ask these kinds of questions and discuss them intelligently. So, I guess my, so this is a long-winded answer or justification of my feeling is that the conditions for life in some form are probably satisfied in many, many places around the universe and even within our galaxy. I'm not so sure about the emergence of intelligent life or the emergence of technological civilizations. That seems much more contingent and special. And we might, it's conceivable to me that we're the only example in the galaxy. Although, yeah, I don't know one way or the other. I have different opinions on different days of the week. But one of the things that worries me in the spirit of being humble, that our particular kind of intelligence is not very special. So, there's all kinds of different intelligences. And even more broadly, there could be many different kinds of life. So, the basic definition, and I just had, I think somebody that you know, Sarah Walker, I just had a very long conversation with her about even just the very basic question of trying to define what is life from a physics perspective. Even that question within itself, I think one of the most fundamental questions in science and physics and everything is just trying to get a hold, trying to get some universal laws around the ideas of what is life. Because that kind of unlocks a bunch of things around life, intelligence, consciousness, all those kinds of things. I agree with you in a sense, but I think that's a dangerous question. Because the answer can't be any more precise than the question. And the question, what is life, kind of assumes that we have a definition of life and that it's a natural phenomena that can be distinguished. But really, there are edge cases like viruses. Some people would like to say that electrons have consciousness and things. So you can't, if you really have fuzzy concepts, it's very hard to reach precise kinds of scientific answers. But I think there's a very fruitful question that's adjacent to it, which has been pursued in different forms for quite a while and is now becoming very sophisticated in reaching in new directions. And that is, what are the states of matter that are possible? So in high school or grade school, you learn about solids, liquids, and gases. But that really just scratches the surface of different ways that are distinguishable, that matter can form into macroscopically different meaningful patterns that we call phases of matter. And then there are precise definitions of what we mean by phases of matter that have been worked out fruitful over the decades. And we're discovering new states of matter all the time and kind of having to work at what we mean by matter. We're discovering the capabilities of matter to organize in interesting ways. And some of them, like liquid crystals, are important ingredients of life. Our cell membranes are liquid crystals, and that's very important to the way they work. Recently, there's been a development in where we're talking about states of matter that are not static, but that have dynamics, that have characteristic patterns not only in space, but in time. These are called time crystals, and that's been a development that's just in the last decade or so. It's just really, really flourishing. And so, is there a state of matter or a group of states of matter that corresponds to life? Maybe, but the answer can't be any more definite than the question. I mean, I gotta push back on the, those are just words. I mean, I disagree with you. The question points to a direction. The answer might be able to be more precise than the question, because just as you're saying, there is, we could be discovering certain characteristics and patterns that are associated with a certain type of matter, macroscopically speaking. And that we can then be able to post facto say, this is, let's assign the word life to this kind of matter. I agree with that completely. That's, so it's not a disagreement. It's very frequent in physics that, or in science, that words that are in common use get refined and reprocessed into scientific terms. That's happened for things like force and energy. And so, in a way, we find out what the useful definition is, or symmetry, for instance. And the common usage may be quite different from the scientific usage, but the scientific usage is special and takes on a life of its own, and we find out what the useful version of it is, what the fruitful version of it is. So I do think, so in that spirit, I think if we can identify states of matter or linked states of matter that can carry on processes of self-reproduction and development and information processing, we might be tempted to classify those things as life. Well, can I ask you about the craziest one, which is the one we know maybe least about, which is consciousness? Is it possible that there are certain kinds of matter would be able to classify as conscious, meaning, so there's the panpsychists, right, the philosophers who kind of try to imply that all matter has some degree of consciousness, and you can almost construct a physics of consciousness. Yes, again, we're in such early days of this, but nevertheless, it seems useful to talk about. Is there some sense from a physics perspective to make sense of consciousness? Is there some hope? Well, again, consciousness is a very imprecise word and loaded with connotations that I think we should, we don't wanna start a scientific analysis with that, I don't think, and it's often been important in science to start with simple cases and work up consciousness. I think what most people think of when you talk about consciousness is, okay, what am I doing in the world? This is my experience. I have a rich inner life and experience, and where is that in the equations? And I think that's a great question, a great, great question, and actually, I think I'm gearing up to spend part of the, I mean, to try to address that in coming years. One version of asking that question, just as you said now, is what is the simplest formulation of that to study? I think I'm much more comfortable with the idea of studying self-awareness as opposed to consciousness, because that sort of gets rid of the mystical aura of the thing, and self-awareness is in simple, I think contiguous, at least, with ideas about feedback. So if you have a system that looks at its own state and responds to it, that's a kind of self-awareness. And more sophisticated versions could be like in information processing things, computers that look into their own internal state and do something about it. And I think that could also be done in neural nets. This is called recurrent neural nets, which are hard to understand and kind of a frontier. So I think understanding those and gradually building up a kind of profound ability to conceptualize different levels of self-awareness, what do you have to not know and what do you have to know, and when do you know that you don't know it, or what do you think you know that you don't really know? I think clarifying those issues, when we clarify those issues and get a rich theory around self-awareness, I think that will illuminate the questions about consciousness in a way that, scratching your chin and talking about qualia and blah, blah, blah, blah is never gonna do. Well, I also have a different approach to the whole thing. So there's, from a robotics perspective, you can engineer things that exhibit qualities of consciousness without understanding how things work, and from that perspective, it's like a back door, like enter through the psychology door. Precisely. The cognitive science door. I think we're on the same wavelength here. And let me just add one comment, which is, I think we should try to understand consciousness as we experience it, in evolutionary terms, and ask ourselves, why? Why does it happen? This thing seems useful, why is it useful? Why is it useful? Interesting question. I think we've got a conscious eye watch here. Interesting question, thank you, Siri. Okay. I'll get back to you later. And I think, I'm morally certain that what's gonna emerge from analyzing recurrent neural nets and robotic design and advanced computer design is that having this kind of looking at the internal state in a structured way that doesn't look at everything, it's encapsulated, looks at highly processed information, is very selective and makes choices without knowing how they're made, there'll also be an unconscious. I think that that is gonna turn out to be really essential to doing efficient information processing, and that's why it evolved, because it's helpful. Because brains come at a high cost. So there has to be a good why. And there's a reason, yeah, they're rare in evolution, and big brains are rare in evolution, and they come at a big cost. I mean, they have high metabolic demands, they require very active lifestyle, warm-bloodedness, and take away from the ability to support metabolism, have digestion, and so it comes at a high cost, it has to pay back. Yeah, I think it has a lot of value in social interaction, so I actually am spending the rest of the day today in with our friends, our legged friends in robotic form at Boston Dynamics. And I think, so my probably biggest passion is human-robot interaction, and it seems that consciousness from the perspective of the robot is very useful to improve the human-robot interaction experience. The first, the display of consciousness, but then to me there's a gray area between the display of consciousness and consciousness itself. If you think of consciousness from an evolutionary perspective, it seems like a useful tool in human communication, so. Yes, it's certainly, well, whatever consciousness is will turn out to be. I think addressing it through its use, and working up from simple cases, and also working up from engineering experience in trying to do efficient computation, including efficient management of social interactions is going to really shed light on these questions, as I said, in a way that sort of musing abstractly about consciousness never would. So as I mentioned, I talked to Sarah Walker, and first of all, she says hi, spoke very highly of you. One of her concerns about physics, and physicists, and humans, is that we may not fully understand the system that we're inside of, meaning there may be limits to the kind of physics we do in trying to understand the system of which we're part of. So the observer is also the observed. In that sense, it seems like the, our tools of understanding the world, I mean, this is mostly centered around the questions of what is life, trying to understand the patterns that are characteristic of life and intelligence, all those kinds of things. We're not using the right tools, because we're in the system. Is there something that resonates with you there? Almost like. Yes, we do have, we have limitations, of course, in the amount of information we can process. On the other hand, we can get help from our silicon friends, and we can get help from all kinds of instruments that make up for our perceptual deficits. And we have to, and we can use, at a conceptual level, we can use different kinds of concepts to address different kinds of questions. So I'm not sure exactly what problem she's talking about. It's a problem akin to an organism living in a 2D plane, trying to understand a three-dimensional world. Well, we can do that. I mean, you know, we, in fact, we, you know, for practical purposes, most of our experience is two-dimensional. It's hard to move vertically, and yet we've produced, conceptually, a three-dimensional symmetry, and in fact, four-dimensional space-time. So, you know, by thinking in appropriate ways and using instruments and getting consistent accounts and rich accounts, we find out what concepts are necessary. And I don't see any end in sight of the process or any showstoppers, because, let me give you an example. I mean, for instance, QCD, our theory of the strong interaction, has nice equations, which I helped to discover. What's QCD? Quantum chromodynamics. So it's our theory of the strong interaction, the interaction that is responsible for nuclear physics. So it's the interaction that governs how quarks and gluons interact with each other and make protons and neutrons and all the strong, the related particles, and many things in physics. That's one of the four basic forces of nature, as we presently understand it. And so we have beautiful equations, which we can test in very special circumstances, using at high energies, at accelerators. So we're certain that these equations are correct. Prizes are given for it, and people try to knock it down and they can't. But the situations in which we can calculate the consequences of these equations are very limited. So for instance, no one has been able to demonstrate that this theory, which is built on quarks and gluons, which you don't observe, actually produces protons and neutrons in the things you do observe. This is called the problem of confinement. So no one's been able to prove that analytically in a way that a human can understand. On the other hand, we can take these equations to a computer, to gigantic computers and compute, and by God, you get the world from it. So these equations, in a way that we don't understand in terms of human concepts, we can't do the calculations, but our machines can do them. So with the help of what I like to call our silicon friends and their descendants in the future, we can understand in a different way that allows us to understand more. But I don't think we'll ever, no human is ever gonna be able to solve those equations in the same way. But I think that's, when we find limitations to our natural abilities, we can try to find workarounds, and sometimes that's appropriate concepts, sometimes it's appropriate instruments, sometimes it's a combination of the two, but I think it's premature to get defeatist about it. I don't see any logical contradiction or paradox or limitation that will bring this process to a halt. Well, I think the idea is to continue thinking outside the box in different directions, meaning just like how the math allows us to think in multiple dimensions outside of our perception system, sort of thinking, coming up with new tools of mathematics or computation or all those kinds of things to take different perspectives on our universe. Well, I'm all for that. I kind of have even elevated it into a principle, which is of complementarity, following Bohr, that you need different ways of thinking, even about the same things, in order to do justice to their reality and answer different kinds of questions about them. I mean, we've several times alluded to the fact that human beings are hard to understand, and the concepts that you use to understand human beings, if you wanna prescribe drugs for them or see what's gonna happen if they move very fast or are exposed to radiation, and so that requires one kind of thinking that's very physical, based on the fact that the materials that we're made out of. On the other hand, if you want to understand how a person's going to behave in a different kind of situation, you need entirely different concepts from psychology. And there's nothing wrong with that. You can have very different ways of addressing the same material that are useful for different purposes. Can you describe this idea, which is fascinating of complementarity a little bit, sort of, first of all, what state is the principle? What is it? And second of all, what are good examples, starting from quantum mechanics? You still mentioned psychology. Let's talk about this more. It's like, in your new book, one of the most fascinating ideas, actually. I think it's a wonderful, yeah. To me, it's, well, it's the culminating chapter of the book, and I think, since the whole book is about the big lessons or big takeaways from profound understanding of the physical world that we've achieved, including that it's mysterious in some ways, this was the final, overarching lesson, complementarity. And it's a approach. So, unlike some of these other things, which are just facts about the world, like the world is both big and small in different sense, and is big, but we're not small, things we talked about earlier, and the fact that the universe is comprehensible, and how complexity can emerge from simplicity, and those things are, in the broad sense, facts about the world, complementarity is more an attitude towards the world, is encouraged by the facts about the world. And it's the concept, or the approach, or the realization that it can be appropriate, and useful, and inevitable, and unavoidable to use very different descriptions of the same object, or the same system, or the same situation, to answer different kinds of questions that may be very different, and even mutually uninterpretable, immutably incomprehensible. But both correct somehow. But both correct, and sources of different kinds of insight. Which is so weird. Yeah, well. But it seems to work in so many cases. It works in many cases, and I think it's a deep fact about the world, and how we should approach it. Its most rigorous form, where it's actually a theorem, if quantum mechanics is correct, occurs in quantum mechanics, where the primary description of the world is in terms of wave functions. But let's not talk about the world, let's just talk about a particle, an electron. The primary description of that electron is its wave function. And the wave function can be used to predict where it's gonna be, if you observe, it'll be in different places with different probabilities, or how fast it's moving. And it'll also be moving in different ways with different probabilities, that's what quantum mechanics says. And you can predict either set of probabilities. What's gonna happen if I make an observation of the position or the velocity? But, so the wave function gives you ways of doing both of those, but to do it, to get those predictions, you have to process the wave function in different ways. You process it one way for position, and in a different way for momentum. And those ways are mathematically incompatible. It's like, you know, it's like you have a stone and you can sculpt it into a Venus de Milo, or you can sculpt it into David, but you can't do both. And that's an example of complementarity. But to answer different kinds of questions, you have to analyze the system in different ways that are mutually incompatible, but both valid to answer different kinds of questions. So in that case, it's a theorem, but I think it's a much more widespread phenomena that applies to many cases where we can't prove it as a theorem, but it's a piece of wisdom, if you like, and appears to be a very important insight. And if you ignore it, you can get very confused and misguided. Do you think this is a useful hack for ideas that we don't fully understand, or is this somehow a fundamental property of all or many ideas that you can take multiple perspectives and they're both true? Well, I think it's both. So it's both the answer to all questions. Yes, that's right. It's not either or, it's both. It's paralyzing to think that we live in a world that's fundamentally surrounded by complementary ideas. Because we want universe, we somehow want to attach ourselves to absolute truths, and absolute truths certainly don't like the idea of complementarity. Yes, Einstein was very uncomfortable with complementarity. And in a broad sense, the famous Bohr-Einstein debates revolved around this question of whether the complementarity that is a foundational feature of quantum mechanics as we have it is a permanent feature of the universe and our description of nature. And so far, quantum mechanics wins. And it's gone from triumph to triumph. Whether complementarity is rock bottom, I guess you can never be sure. But it looks awfully good and it's been very successful. And certainly, complementarity has been extremely useful and fruitful in that domain, including some of Einstein's attempts to challenge it, with the famous Einstein-Podolsky-Rosen experiment turned out to be confirmations of that have been useful in themselves. But so thinking about these things was fruitful, but not in the way that Einstein hoped. Yeah, so as I said, in the case of quantum mechanics and this dilemma or dichotomy between processing the wave function in different ways, it's a theorem. They're mutually incompatible. And the physical correlate of that is the Heisenberg uncertainty principle. You can't have position and momentum determined at once. But in other cases, like one that I like to think about or like to point out as an example is free will and determinism. It's much less of a theorem and more a kind of way of thinking about things that I think is reassuring and avoids a lot of unnecessary quarreling and confusion. The quarreling I'm okay with and the confusion I'm okay with. I mean, people debate about difficult ideas. But the question is whether it could be almost a fundamental truth. I think it is a fundamental truth. Free will is both an illusion and not. Yes, I think that's correct. And there's a reason why people say quantum mechanics is weird and complementarity is a big part of that. But to say that our actual whole world is weird, the whole hierarchy of the universe is weird in this kind of particular way. And it's quite profound, but it's also humbling because it's like we're never going to be on sturdy ground in the way that humans like to be. It's like you have to embrace that. Well, this whole thing is like unsteady mess. It's one of many lessons in humility that we run into in profound understanding of the world. The Copernican Revolution was one, that the Earth is not the center of the universe. Darwinian evolution is another, that humans are not the pinnacle of God's creation. And the apparent result of deep understanding of physical reality, that mind emerges from matter and there's no call on special life forces or souls. These are all lessons in humility. And I actually find complementarity a liberating concept. It's, okay, you know. Yeah, it is in a way. Yeah. There's a story about Dr. Johnson and he's talking with Boswell and Boswell was, they were discussing a sermon that they both heard and the sort of culmination of the sermon was the speaker saying, I accept the universe. And Dr. Johnson said, well, he'd damn well better. And there's a certain joy in accepting the universe because it's mind expanding. And to me, complementarity also suggests tolerance, suggests opportunities for understanding things in different ways that add to rather than detract from understanding. So I think it's an opportunity for mind expansion and demanding that there's only one way to think about things can be very limiting. On the free will one, that's a trippy one, though. To think like I am the decider of my own actions and at the same time I'm not is tricky to think about, but there does seem to be some kind of profound truth in that. Well, I think it is tied up. It will turn out to be tied up when we understand things better with these issues of self-awareness and where we get, what we perceive as making choices, what does that really mean and what's going on under the hood, but I'm speculating about a future understanding that's not in place at present. Your sense there will always be, like as you dig into the self-awareness thing, there'll always be some places where complementarity is gonna show up. Oh, definitely, yeah. I mean, there will be, how should I say? There'll be kind of a God's eye view which sees everything that's going on in the computer or the brain and then there's the brain's own view or the central processor or whatever it is, what we call the self, the consciousness, that's only aware of a very small part of it and those are very different. So the God's eye view can be deterministic while the self view sees free will. I'm pretty sure that's how it's gonna work out, actually. But as it stands, free will is a concept that we definitely, at least I feel I definitely experience. I can choose to do one thing than another and other people, I think, are sufficiently similar to me that I trust that they feel the same way and it's an essential concept in psychology and law and so forth. But at the same time, I think that mind emerges from matter and that there's an alternative description of matter that's up to subtleties about quantum mechanics which I don't think are relevant here, really is deterministic. Let me ask you about some particles. Okay. First, the absurd question, almost like a question that Plato would ask. What is the smallest thing in the universe? As far as we know, the fundamental particles out of which we build our most successful description of nature are points. They have zero, they don't have any internal structure. So that's as small as can be. So what does that mean operationally? That means that they obey equations that describe entities that are singular concentrations of energy, momentum, angular momentum, the things that particles have but localized at individual points. Now, that mathematical structure is only revealed partially in the world because to process the wave function in a way that accesses information about the precise position of things, you have to apply a lot of energy and that's an idealization that you can apply infinite amount of energy to determine a precise position. But at the mathematical level, we build the world out of particles that are points. So do they actually exist and what are we talking about? So like, so let me ask sort of do quarks exist? Yes. Do electrons exist? Yes. Do photons exist? Yes. But what does it mean for them to exist? Okay, so well, the hard answer to that, the precise answer is that we construct the world out of equations that contain entities that are reproducible, that exist in vast numbers throughout the universe, that have definite properties of mass, spin, and a few others that we call electrons. And what an electron is, is defined by the equations that it satisfies theoretically. And we find that there are many, many exemplars of that entity in the physical world. So in the case of electrons, we can isolate them and study them in individual ones in great detail. We can check that they all actually are identical and that's why chemistry works. And yes, so in that case, it's very tangible. Similarly with photons, you can study them individually, they're the units of light. And nowadays, it's very practical to study individual photons and determine their spin and their other basic properties and check out the equations in great detail. For quarks and gluons, which are the other two main ingredients of our model of matter, that's so successful, it's a little more complicated because the quarks and gluons that appear in our equations don't appear directly as particles you can isolate and study individually. They always occur within what are called bound states or structures like protons. A proton, roughly speaking, is composed of three quarks and a lot of gluons. We can detect them in a remarkably direct way actually nowadays, whereas at relatively low energies, the behavior of quarks is complicated. At high energies, they can propagate through space relatively freely for a while and we can see their tracks. So ultimately, they get recaptured into protons and other mesons and funny things, but for a short time, they propagate freely and while that happens, we can take snapshots and see their manifestations. This is actually, this kind of thing is exactly what I got the Nobel Prize for, predicting that this would work and similarly for gluons, although you can't isolate them as individual particles and study them in the same way that we study electrons, say, you can use them theoretically as entities out of which you build tangible things that we actually do observe, but also you can, at accelerators at high energy, you can liberate them for brief periods of time and study how they, and get convincing evidence that they leave tracks and you can get convincing evidence that they were there and have the properties that we wanted them to have. Can we talk about asymptotic freedom, this very idea that you won the Nobel Prize for? Yeah. So it describes a very weird effect to me, the weird in the following way. So the way I think of most forces or interactions, the closer you are, the stronger the effect, the stronger the force, right? With quarks, the closer they are, the less the strong interaction and in fact, they basically act like free particles when they're very close. That's right, yes. But this requires a huge amount of energy. Like, can you describe me, how does this even work? You know how weird it is? A proper description must bring in quantum mechanics and relativity and it's, so a proper description and equations, so a proper description really is probably more than we have time for and require quite a bit of patience on your part. But- How does relativity come into play? Wait, wait a minute. Relativity is important because when we talk about trying to think about short distances, we have to think about very large momenta and very large momenta are connected to very large energy in relativity and so the connection between how things behave at short distances and how things behave at high energy really is connected through relativity in sort of a slightly backhanded way. Quantum mechanics indicates that short, to get to analyze short distances, you need to bring in probes that carry a lot of momentum. This again is related to uncertainty because it's the fact that you have to bring in a lot of momentum that interferes with the possibility of determining position and momentum at the same time. If you want to determine position, you have to use instruments that bring in a lot of momentum and because of that, those same instruments can't also measure momentum because they're disturbing the momentum. And then the momentum brings in energy. There's also the effect that asymptotic freedom comes from the possibility of spontaneously making quarks and gluons for short amounts of time that fluctuate into existence and out of existence. And the fact that that can be done with a very little amount of energy and uncertainty and energy translates into uncertainty in time. So if you do that for a short time, you can do that. Well, it all comes in a package. So I told you it would take a while to really explain. But the results can be understood. I mean, we can state the results pretty simply, I think. So in everyday life, we do encounter some forces that increase with distance and kind of turn off at short distances. That's the way rubber bands work, if you think about it. Or if you pull them hard, they resist, but they get flabby if the rubber band is not pulled. And so that can happen in the physical world. But what's really difficult is to see how that could be a fundamental force that's consistent with everything else we know. And that's what asymptotic freedom is. It says that there's a very particular kind of fundamental force that involves special particles called gluons with very special properties that enables that kind of behavior. So at the time we did our work, there were experimental indications that quarks and gluons did have this kind of property, but there were no equations that were capable of capturing it. And we found the equations and showed how they work and showed that they were basically unique. And this led to a complete theory of how the strong interaction works, which is the quantum chromodynamics we mentioned earlier. So that's the phenomenon that quarks and gluons interact very, very weakly when they're close together. That's connected through relativity with the fact that they also interact very, very weakly at high energies. So if you have, so at high energies, the simplicity of the fundamental interaction gets revealed. At the time we did our work, the clues were very subtle, but nowadays at what are now high energy accelerators, it's all obvious. So we would have had a much, well, somebody would have had a much easier time 20 years later looking at the data. You can sort of see the quarks and gluons. As I mentioned, they leave these short tracks that would have been much, much easier. But from indirect clues, we were able to piece together enough to make that behavior a prediction rather than a postdiction. So it becomes obvious at high energies. It becomes very obvious. When we first did this work, it was frontiers of high energy physics. And at big international conferences, there would always be sessions on testing QCD and whether this proposed description of the strong interaction was in fact correct and so forth. And it was very exciting. But nowadays, the same kind of work, but much more precise with calculations to more accuracy and experiments that are much more precise and comparisons that are very precise. Now it's called calculating backgrounds because people take this for granted and wanna see deviations from the theory, which would be the new discoveries. Yeah, the cutting edge becomes the foundation and the foundation becomes boring. Yes. Is there some, for basic explanation purposes, is there something to be said about strong interactions in the context of the strong nuclear force for the attraction between protons and neutrons versus the interaction between quarks within protons? Well, quarks and gluons have the same relation basically to nuclear physics as electrons and photons have to atomic and molecular physics. So atoms and photons are the dynamic entities that really come into play in chemistry and atomic physics. Of course, you have to have the atomic nuclei, but those are small and relatively inert, really the dynamical part. And for most purposes of chemistry, you just say you have this tiny little nucleus, which QCD gives you, don't worry about it. Just it's there. The real action is the electrons moving around and exchanging and things like that. But okay, but we want it to understand the nucleus too. And so atoms are sort of quantum mechanical clouds of electrons held together by electrical forces, which is photons, and then there's radiation, which is another aspect of photons. That's where all the fun happens is the electrons and the photons and all that kind of stuff. Yeah, that's right. The nucleus are kind of the, well, they give the positive charge and most of the mass of matter, but they don't, since they're so heavy, they don't move very much in chemistry. And I'm oversimplifying drastically. They're not contributing much to the interaction in chemistry. For most purposes in chemistry, you can just idealize them as concentrations of positive mass and charge that are, you don't have to look inside, but people are curious what's inside. And that was a big thing on the agenda of 20th century physics, starting in the 19, well, starting with the 20th century and unfolding throughout of trying to understand what forces held the atomic nucleus together, what it was and so on. So anyway, the story that emerges from QCD is that very similar to the way that, well, broadly similar to the way that clouds of electrons held together by electrical forces give you atoms and ultimately molecules. Protons and neutrons are like atoms made now out of quarks, quark clouds held together by gluons, which are like the photons that give the electric forces, but this is giving a different force, the strong force. And the residual forces between protons and neutrons that are left over from the basic binding are like the residual forces between atoms that give molecules, but in the case of protons and neutrons, it gives you atomic nuclei. So again, for definitional purposes, QCD, quantum chromodynamics, is basically the physics of strong interaction. Yeah, we now would, I think most physicists would say it's the theory of quarks and gluons and how they interact. But it's a very precise, and I think it's fair to say, very beautiful theory based on mathematical symmetry of a high order. And another thing that's beautiful about it is that it's kind of in the same family as electrodynamics. The conceptual structure of the equations are very similar. They're based on having particles that respond to charge in a very symmetric way. In the case of electrodynamics, it's photons that respond to electric charge. In the case of quantum chromodynamics, there are three kinds of charge that we call colors, but they're nothing like colors. They really are like different kinds of charge. But in the case of electrodynamics, they're like different kinds of charge. But they rhyme with the same kind of, like it's similar kind of dynamics. Similar kind of dynamics. I like to say that QCD is like QED on steroids. And instead of one photon, you have eight gluons. Instead of one charge, you have three color charges. But there's a strong family resemblance between. But the context in which QCD does this thing is at much higher energies. Like that's where it comes to life. Well, it's a stronger force. So that to access how it works and kind of pry things apart, you have to inject more energy. And so that gives us, in some sense, a hint of how things were in the earlier universe. Yeah, well, in that regard, asymptotic freedom is a tremendous blessing because it means things get simpler at high energy. And- The universe was born free. Born free, that's very good, yes. The universe was born. So in atomic physics, I mean a similar thing happens in the theory of stars. Stars are hot enough that the interactions between electrons and photons are, they're liberated, they don't form atoms anymore. They make a plasma, which in some ways is simpler to understand. You don't have complicated chemistry. And in the early universe, according to QCD, similarly atomic nuclei dissolved into the constituent quarks and gluons, which are moving around very fast and interacting in relatively simple ways. And so this opened up the early universe to scientific calculation. Can I ask you about some other weird particles that make up our universe? What are axions and what is the strong CP problem? Okay, so let me start with what the strong CP problem is. First of all, well, charge, C is charge conjugation, which is the transformation, the notional transformation, if you like, that changes all particles into their antiparticles. And the concept of C symmetry, charge conjugation symmetry, charge conjugation symmetry, is that if you do that, you find the same laws would work. So the laws are symmetric. If the behavior that particles exhibit is the same as the behavior you get with all their antiparticles, then P is parity, which is also called spatial inversion. Spatial inversion, it's basically looking at a mirror universe and saying that the laws that are obeyed in a mirror universe, when you look at the mirror images, obey the same laws as the sources of their images. There's no way of telling left from right, for instance, that the laws don't distinguish between left and right. Now, in the mid 20th century, people discovered that both of those are not quite true. Really, the equation, the mirror universe, the universe that you see in a mirror is not gonna obey the same laws as the universe that we actually interpret. You would be able to tell, if you did the right kind of experiments, which was the mirror and which was the real thing. Anyway, that's the parity, and they show that the parity doesn't necessarily hold. It doesn't quite hold, and examining what the exceptions are turned out to lead to all kinds of insight about the nature of fundamental interactions, especially the properties of neutrinos and the weak interactions. It's a long story, but it's a very, it's a. So you just define the C and the P, the conjugation, the charged conjugation. Now that I've done that, I wanna. What's the problem? Shove them off. Okay, great. Because it's easier to talk about T, which is time reversal symmetry. We have very good reasons to think CPT is an accurate symmetry of nature. It's on the same level as relativity and quantum mechanics, basically, so that better be true. So it's symmetric when you include conjugation, parity, and time. And time and space reversal. If you do all three, then you get the same physical consequences. Now, so, but that means that CP is equivalent to T. But what's observed in the world is that T is not quite an accurate symmetry of nature, either. So most phenomena of, at the fundamental level, so interactions among elementary particles and the basic gravitational interaction, if you ran them backwards in time, you'd get the same laws. So if, again, going back, unless this time we don't talk about a mirror, but we talk about a movie. If you take a movie and then run it backwards, that's the time reversal. It's good to think about a mirror in time. Yes, like a mirror in time. If you run the movie backwards, it would look very strange if you were looking at complicated objects and a Charlie Chaplin movie or whatever. It would look very strange if you ran it backwards in time. But at the level of basic interactions, if you were able to look at the atoms and the quarks involved, they would obey the same laws, to a very good approximation, but not exactly. So not exactly, that means you could tell. You could tell, but you'd have to do very, very subtle experiments with high-energy accelerators to take a movie that looked different when you ran it backwards. This was a discovery by two great physicists named Jim Cronin and Val Fitch in the mid-1960s, previous to that, over all the centuries of development of physics with all its precise laws, they did seem to have this gratuitous property that they look the same if you run the equations backwards. It's kind of an embarrassing property, actually, because life isn't like that. So empirical reality does not have this imagery in any obvious way, and yet the laws did. It's almost like the laws of physics are missing something fundamental about life if it holds that property, right? I mean, that's the embarrassing nature of it. Yeah, well, people worked hard at what's, this is a problem that's thought to belong to the foundations of statistical mechanics or the foundations of thermodynamics to understand how behavior, which is grossly not symmetric with respect to reversing the direction of time in large objects, how that can emerge from equations which are symmetric with respect to changing the direction of time to a very good approximation. And that's still an interesting endeavor. Actually, it's an exciting frontier of physics now to sort of explore the boundary between when that's true and when it's not true, when you get to smaller objects and exceptions like time crystals. I definitely have to ask about time crystals in a second here. So the CP problem and T, so there's flaws to all of these. We're in danger of infinite regress, but we'll have to convert soon. So. Can't possibly be turtles all the way down. We're gonna get to the bottom turtle. So it became, so it got to be a real, I mean, it's a really puzzling thing why the laws should have this very odd property that we don't need. And in fact, it's kind of an embarrassment in addressing empirical reality, but it seemed to be almost, it seemed to be exactly true for a long time, and then almost true. And in a way, almost true is more disturbing than exactly true, because exactly true, it could have been just a fundamental feature of the world, and at some level, you just have to take it as it is. And if it's a beautiful, easily articulatable regularity, you could say that, okay, that's fine as a fundamental law of nature. But to say that it's approximately true, but not exactly, that's weird. So, and then, so there was great progress in the late part of the 20th century in getting to an understanding of fundamental interactions in general that shed light on this issue. It turns out that the basic principles of relativity and quantum mechanics, plus the kind of high degree of symmetry that we found, the so-called gauge symmetry that characterizes the fundamental interactions, when you put all that together, it's a very, very constraining framework. And it has some indirect consequences, because the possible interactions are so constrained. And one of the indirect consequences is that the possibilities for violating the symmetry between forwards and backwards in time are very limited. There are basically only two. Okay, and one of them occurs and leads to a very rich theory that explains the Cronin-Fitch experiment, and a lot of things that have been done subsequently has been used to make all kinds of successful predictions. So that's turned out to be a very rich interaction. It's esoteric, and the effects only show up at accelerators and are small, but they might have been very important in the early universe and lead to them be connected to the asymmetry between matter and antimatter in the present universe. But that's another digression. The point is that that was fine. That was a triumph to say that there was one possible kind of interaction that would violate time-reversal symmetry, and sure enough, there it is. But the other kind doesn't occur, so we still got a problem. Why doesn't it occur? So we're close to really finally understanding this profound, gratuitous feature of the world that is almost but not quite symmetric under reversing the direction of time, but not quite there. And to understand that last bit is a challenging frontier of physics today. And we have a promising proposal for how it works, which is a kind of theory of evolution. So there's this possible interaction, which we call a coupling, and there's a numerical quantity that tells us how strong that is. And traditionally in physics, we think of these kinds of numerical quantities as constants of nature that you just have to put them in, from experiment, they have a certain value and that's it. And who am I to question what God did? They seem to be just constants. But in this case, it's been fruitful to think and work out a theory where that strength of interaction is actually not a constant. It's a field. It's a... Fields are the fundamental ingredients of modern physics. Like there's an electron field, there's a photon field, which is also called the electromagnetic field. And so all of these particles are manifestations of different fields. And there could be a field, something that depends on space and time. So a dynamical entity instead of just a constant here. And if you do things in a nice way, that's very symmetric, very much suggested aesthetically by the theory, but the theory we do have, then you find that you get a field, which as it evolves from the early universe, settles down to a value that's just right to make the laws very nearly exact, invariant or symmetric with respect to reversal of time. It might appear as a constant, but it's actually a field that evolved over time. It evolved over time. But when you examine this proposal in detail, you find that it hasn't quite settled down to exactly zero. The field is still moving around a little bit. And because the motion is so difficult, the material is so rigid, and this material that fills all, the field that fills all space is so rigid, even small amounts of motion can involve lots of energy. And that energy takes the form of particles, fields that are in motion are always associated with particles, and those are the axions. And if you calculate how much energy is in these residual oscillations, this axion gas that fills all the universe, if this fundamental theory is correct, you get just the right amount to make the dark matter that astronomers want, and it has just the right properties. So I'd love to believe that there's a way so I'd love to believe that. So that might be a thing that unlocks, might be the key to understanding dark matter. Yeah, I'd like to think so. And many physicists are coming around to this point of view, which, I've been a voice in the wilderness. I was a voice in the wilderness for a long time, but now it's become very popular, maybe even dominant. So almost like, so this axion particle slash field would be the thing that explains dark matter. It explains, yeah, it would solve this fundamental question of finally, of why the laws are almost, but not quite exactly the same if you run them backwards in time, and then seemingly in a totally different conceptual universe, it would also provide, give us an understanding of the dark matter. That's not what it was designed for, and the theory wasn't proposed with that in mind, but when you work out the equations, that's what you get. That's always a good sign, actually. I think I vaguely read somewhere that there may be early experimental validation of axion. Is that, am I reading the wrong? Well, there have been quite a few false alarms, and I think there are some of them still, people desperately wanna find this thing, but I don't think any of them are convincing at this point, but there are very ambitious experiments, and kind of, you have to design new kinds of antennas that are capable of detecting these predicted particles, and it's very difficult. They interact very, very weakly. If it were easy, it would have been done already, but I think there's good hope that we can get down to the required sensitivity and actually test whether these ideas are right in coming years or maybe decades. And then understand one of the big mysteries, like literally big in terms of its fraction of the universe is dark matter. Yes. Let me ask you about, you mentioned a few times, time crystals. Yeah. What are they? These things are, it's a very beautiful idea when we start to treat space and time as similar frameworks. Yes, right. Physical phenomena. Right, that's what motivated it. First of all, what are crystals? Yeah. And what are time crystals? Okay, so crystals are orderly arrangements of atoms in space, and many materials, if you cool them down gently, will form crystals. And so we say that that's a state of matter that forms spontaneously. And an important feature of that state of matter is that the end result, the crystal, has less symmetry than the equations that give rise to the crystal. So the equations, the basic equations of physics, are the same if you move a little bit. So you can move, they're homogeneous, but crystals aren't. The atoms are in particular places, though they have less symmetry. And time crystals are the same thing in time. Basically, but of course, so it's not positions of atoms, but it's orderly behavior that certain states of matter will arrange themselves into spontaneously if you treat them gently and let them do what they want to do. But repeat in that same way indefinitely. That's the crystalline form. You can also have time liquids, or you can have all kinds of other states of matter. You can also have space-time crystals, where the pattern only repeats if, with each step of time, you also move it a certain direction in space. So yeah, but basically, it's states of matter that display structure in time spontaneously. So here's the difference. When it happens in time, it sure looks a lot like it's motion, and if it repeats indefinitely, it sure looks a lot like perpetual motion. Like, looks like free lunch. And I was told that there's no such thing as free lunch. Does this violate laws of thermodynamics? No, but it requires a critical examination of the laws of thermodynamics. I mean, let me say on background that the laws of thermodynamics are not fundamental laws of physics. They are things we prove under certain circumstances emerge from the fundamental laws of physics. We don't posit them separately. They're meant to be deduced, and they can be deduced under limited circumstances, but not necessarily universally. And we're finding some of the subtleties and sort of except edge cases where they don't apply in a straightforward way. And this is one. So time crystals do obey, do have this structure in time, but it's not a free lunch, because although in a sense, things are moving, they're already doing what they want to do. They're in there. So if you want to extract something from time, if you want to extract energy from it, you're gonna be foiled because there's no spare energy there. So you can add energy to it and kind of disturb it, but you can't extract energy from this motion because it's gonna, it wants to do, that's the lowest energy configuration that there is. So you can't get further energy out of it. So in theory, I guess perpetual motion, you would be able to extract energy from it. If such a thing was to be created, you can then milk it for energy. Well, what's usually meant in the literature of perpetual motion is a kind of macroscopic motion that you could extract energy from and somehow it would crank back up. That's not the case here. If you want to extract energy, I think this motion is not something you can extract energy from. If you intervene in the behavior, you can change it, but only by injecting energy, not by taking away energy. You mentioned that a theory of everything may be quite difficult to come by. A theory of everything broadly defined, meaning like truly a theory of everything. But let's look at a more narrow theory of everything, which is the way it's used often in physics is a theory that unifies our current laws of physics, general relativity, quantum field theory. Do you have thoughts on this dream of a theory of everything in physics? How close are we? Is there any promising ideas out there in your view? Well, it would be nice to have, it would be aesthetically pleasing. Will it be useful? No, probably not. Well, I shouldn't, it's dangerous to say that, but probably not. I think we, certainly not in the foreseeable future. Maybe to understand black holes? Yeah, but that's, yes, maybe to understand black holes, but that's not useful. And well, not only, I mean, to understand, it's worse, it's not useful in the sense that we're not gonna be basing any technology anytime soon on black holes, but it's more severe than that, I would say. It's that the kinds of questions about black holes that we can't answer within the framework of existing theory are ones that are not going to be susceptible to astronomical observation in the foreseeable future. They're questions about very, very small black holes, when quantum effects come into play, or so that black holes are, you know, not black holes. They're emitting this discovery of Hawking called Hawking radiation, which for astronomical black holes is a tiny, tiny effect that no one has ever observed. It's a prediction that's never been checked. Like supermassive black holes that doesn't apply. No, no, the predicted rate of radiation from those black holes is so tiny that it's absolutely unobservable and is overwhelmed by all kinds of other effects. So it's not practical in the sense of technology. It's not even practical in the sense of application to astronomy. Our existing theory of general relativity and quantum theory and our theory of the different fundamental forces is perfectly adequate to all problems of technology, for sure. And almost all problems of astrophysics and cosmology that appear, except with the notable exception of the extremely early universe, if you want to ask. What happened before the Big Bang or what happened right at the Big Bang, which would be a great thing to understand, of course. Yes, we don't. But what about the engineering question? So if we look at space travel, so I think you've spoken with him, Eric Weinstein. Oh, yeah. Really, you know, he says things like, we want to get off this planet. His intuition is almost a motivator for the engineering project of space exploration. In order for us to crack this problem of becoming a multi-planetary species, we have to solve the physics problem. His intuition is like, if we figure out what he calls the source code, which is like, a theory of everything might give us clues on how to start hacking the fabric of reality, like getting shortcuts, right? It might, I can't say that, you know, I can't say that it won't, but I can say that in the 1970s and early 1980s, we achieved huge steps in understanding matter. QCD, much better understanding of the weak interaction, much better understanding of quantum mechanics in general, and it's had minimal impact on technology. On rocket design, on propulsion. Certainly on rocket design, on anything, any technology whatsoever, and now we're talking about much more esoteric things, and since I don't know what they are, I can't say for sure that they won't affect technology, but I'm very, very skeptical that they would affect technology, because, you know, to access them, you need to, very exotic circumstances to make new kinds of particles with high energy, you need accelerators that are very expensive, and you don't produce many of them, and so forth. You know, it's just, it's a pipe dream, I think. Yeah, about space exploration. I'm not sure exactly what he has in mind, but to me, it's more a problem of, I don't know, something between biology and- Yeah, yeah, yeah, yeah, yeah, yeah, yeah. Maybe a little AI. And information processing. What you mean, how should I, I think human bodies are not well adapted to space. Yeah. Even Mars, which is the closest thing to a kind of human environment that we're gonna find anywhere close by, very, very difficult to maintain humans on Mars, and gonna be very expensive, and very unstable, but I think the process, however, if we take a broader view of what it means to bring human civilization outside of the Earth, if we're satisfied with sending mines out there that we can converse with, and actuators that we can manipulate, and sensors that we can get feedback from, I think that's where it's at. That's for sure. I think that's so much more realistic, and I think that's the long-term future of space exploration. It's not hauling human bodies all over the place. That's just silly. Well, it's possible that human bodies, so like you said, it's a biology problem. What's possible is that we extend human lifespan in some way, just we have to look at a bigger picture. It could be just like you're saying, by sending robots with actuators, and kind of extending our limbs, but it could also be extending some aspect of our minds, some information, all those kinds of things. And it could be cyborgs. It could be... Now we're talking. Yeah. Now we're getting to the fun. It could be human brains, or cells, that realize something like human brain architecture within artificial environments, shells, if you like, that are more adapted to the conditions of space. And that, yeah, so that's entirely, man-machine hybrids, as well as sort of remote outposts that we can communicate with. I think those will happen. Yeah, to me, there's some sense in which, as opposed to understanding the physics of the fundamental fabric of the universe, I think getting to the physics of life, the physics of intelligence, the physics of consciousness, the physics of information that brings from which life emerges, that will allow us to do space exploration. Yeah, well, I think physics in the larger sense has a lot to contribute here. Not the physics of finding fundamental new laws in the sense of another quark, or axions, even. Right? But physics in the sense of, physics has a lot of experience in analyzing complex situations, and analyzing new states of matter, and devising new kinds of instruments that do clever things. Physics in that sense has enormous amounts to contribute to this kind of endeavor. But I don't think that looking for a so-called theory of everything has much to do with it at all. What advice would you give to a young person today with a bit of fire in their eyes, high school student, college student, thinking about what to do with their life? Maybe advice about career, or bigger advice about life in general? Well, first read Fundamentals, because there I've tried to give some coherent, deep advice. That's Fundamentals, 10 Keys to Reality by Frank Kulczek. So that's a good place to start. Available everywhere. If you want to learn what I can tell you. Is there an audio book? I've read that e-book. Yes, yes, there is an audio book. There's an audio book, that's awesome. Yeah, I think it's, I can give three pieces of wise advice that I think are generally applicable. One is to cast a wide net, to really look around and see what looks promising, what catches your imagination, and promise, yeah, and those, you have to balance those two things. You can have things that catch your imagination, but don't look promising in the sense that the questions aren't ripe, or, but, and things that you, and part of what makes things attractive is that whether you thought you liked them or not, is if you can see that there's ferment and new ideas coming up, that's attractive in itself. So when I started out, I thought I was, and when I was an undergraduate, I intended to study philosophy, or questions of how mind emerges from matter, but I thought that that wasn't really ripe. Timing isn't right yet. The right, the timing wasn't right for the kind of mathematical thinking and conceptualization that I really enjoy and am good at. But, so that's one thing, cast a wide net, look around. And that's a pretty easy thing to do today because of the internet. You can look at all kinds of things. You have to be careful, though, because there's a lot of crap also, but you can sort of tell the difference if you do a little digging. So don't settle on just what your thesis advisor tells you to do or what your teacher tells you to do. Look for yourself and get a sense of what seems promising, not what seemed promising 10 years ago, or, so that's one. Another thing is kind of complementary to that. Well, they're all complementary. Complementary to that is to read history and read the masters, the history of ideas and masters of ideas. I benefited enormously from, early in my career, from reading in physics Einstein in the original and Feynman's lectures as they were coming out, and Darwin, you know, these, you can learn what it, and Galileo, you can learn what it is to wrestle with difficult ideas and how great minds did that. You can learn a lot about style, how to write your ideas up and express them in clear ways. And also just a couple of that with, I also enjoy reading biographies. And biographies, yes, similarly, right. So it gives you the context of the human being that created those ideas. Right, and brings it down to earth in the sense that, you know, it was really human beings who did this. And they made mistakes. And I also got inspiration from Bertrand Russell was a big hero and HG Wells. And yeah, so read the masters, make contact with great minds. And when you are sort of narrowing down on a subject, learn about the history of the subject because that really puts in context what you're trying to do. And also gives a sense of community and grandeur to the whole enterprise. And then the third piece of advice is complimentary to both those, which is sort of to get the basics under control as soon as possible. So if you want to do theoretical work in science, you know, you have to learn calculus, multivariable calculus, complex variables, group theory. Nowadays, you have to be highly computer literate. If you want to do experimental work, you also have to be computer literate, then you have to learn about electronics and optics and instruments. So get that under control as soon as possible because it's like learning a language. It to do, to produce great works and express yourself fluently and with confidence. So it should be your native language. These things should be like your native language. So you're not wondering, hmm, what is a derivative? This is just part of your, you know, it's in your bones, so to speak. And the sooner that you can do that, then the better. So all those things can be done in parallel and should be. You've accomplished some incredible things in your life, but the sad thing about this thing we have is it ends. Do you think about your mortality? Are you afraid of death? Well, afraid is the wrong word. I mean, I wish it weren't gonna happen, and I'd like to, but. Do you think about it? Occasionally, I think about, well, I think about it very operationally in the sense that there's always a trade-off between exploration and exploitation. This is a classic subject in computer science, actually, in machine learning, that when you're in an unusual circumstance, you want to explore to see what the landscape is and gather data, but then at some point, you wanna use that, make choices, and say, this is what I'm gonna do and exploit the knowledge you've accumulated. And the longer the period of exploitation you anticipate, the more exploration you should do in new directions. And so for me, I've had to sort of adjust the balance of exploration and exploitation. That's it, you've explored quite a lot. Yeah, well, I haven't shut off the exploitation at all. I'm still hoping for- The exploration. The exploration, right. I'm still hoping for 10 or 15 years of top flight performance, but the... Several years ago now, when I was 50 years old, I was at the Institute for Advanced Study, and my office was right under Freeman Dyson's office, and we were kind of friendly. And he found out it was my 50th birthday and said, congratulations, and you should feel liberated because no one expects much of a 50-year-old theoretical physicist. And he obviously had felt liberated by reaching a certain age. And yeah, there is something to that. I feel I don't have to keep in touch with the latest hyper-technical developments in particle physics or string theory or something, because I'm really not gonna be exploiting that. But I am exploring in these directions of machine learning and things like that. But I'm also concentrating within physics on exploiting directions that I've already established and the laws that we already have and doing things like... I'm very actively involved in trying to design, helping people, experimentalists and engineers even, to design antennas that are capable of detecting axions. So there, we're deep in the exploitation stage. It's not a matter of finding the new laws, but of really using the laws we have to kind of finish the story off. So it's complicated. But I'm very happy with my life right now, and I'm enjoying it, and I don't wanna cloud that by thinking too much that it's gonna come to an end. It's a gift I didn't earn. Is there a good thing to say about why this gift that you've gotten and didn't deserve is so damn enjoyable? So what's the meaning of this thing, of life? To me, interacting with people I love, my family, and I have a very wide circle of friends now, and I'm trying to produce some institutions that will survive me as well as my work, and it's just, how should I say? It's a positive feedback loop when you do something, and people appreciate it, and then you wanna do more, and they get rewarded. How should I say? This is another gift that I didn't earn and don't understand, but I have a dopamine system, and yeah, I'm happy to use it. It seems to get energized by the creative process, by the process of exploration. Very much so. And all of that started from the little fluctuations shortly after the Big Bang. Frank, well, whatever those initial conditions and fluctuation did that created you, I'm glad they did. This was, thank you for all the work you've done, for the many people you've inspired, for the many, of the billion, most of your ideas were pretty useless, of the several billions, as it is for all humans, but you had quite a few truly special ideas, and thank you for bringing those to the world, and thank you for wasting your valuable time with me today. It's truly an honor. It's been a joy, and I hope people enjoy it, and I think the kind of mind expansion that I've enjoyed by interacting with physical reality at this deep level, I think can be conveyed to, and enjoyed by many, many people, and that's one of my missions in life this year. Beautiful. Thanks for listening to this conversation with Frank Wilczek, and thank you to The Information, NetSuite, ExpressVPN, Blinkist, and Eight Sleep. Check them out in the description to support this podcast. And now, let me leave you with some words from Albert Einstein. Nothing happens until something moves. Thanks for listening, and hope to see you next time.

https://youtu.be/LDTe8uFqbws

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Rob Reid: The Existential Threat of Engineered Viruses and Lab Leaks | Lex Fridman Podcast #193

The following is a conversation with Rob Reed, entrepreneur, author, and host of the After On podcast. Sam Harris recommended that I absolutely must talk to Rob about his recent work on the future of engineer pandemics. I then listened to the four-hour special episode of Sam's Making Sense podcast with Rob, titled Engineering the Apocalypse, and I was floored. I knew I had to talk to him. Quick mention of our sponsors, Athletic Greens, Belcampo, Fundrise, and NetSuite. Check them out in the description to support this podcast. As a side note, let me say a few words about the lab leak hypothesis, which proposes that COVID-19 is a product of gain-of-function research on coronaviruses conducted at the Wuhan Institute of Virology that was then accidentally leaked due to human error. For context, this lab is biosafety level four, BSL-4, and it investigates coronaviruses. BSL-4 is the highest level of safety, but if you look at all the human-in-the-loop pieces required to achieve this level of safety, it becomes clear that even BSL-4 labs are highly susceptible to human error. To me, whether the virus leaked from the lab or not, getting to the bottom of what happened is about much more than this particular catastrophic case. It is a test for our scientific, political, journalistic, and social institutions of how well we can prepare and respond to threats that can cripple or destroy human civilization. If we continue gain-of-function research on viruses, eventually these viruses will leak, and they will be more deadly and more contagious. We can pretend that won't happen, or we can openly and honestly talk about the risks involved. This research can both save and destroy human life on Earth as we know it. It's a powerful double-edged sword. If YouTube and other platforms censor conversations about this, if scientists self-censor conversations about this, we'll become merely victims of our brief homo sapien story, not its heroes. As I said before, too carelessly labeling ideas as misinformation and dismissing them because of that will eventually destroy our ability to discover the truth. And without truth, we don't have a fighting chance against the great filter before us. This is the Lex Friedman Podcast, and here is my conversation with Rob Reed. I have seen evidence on the internet that you have a sense of humor, allegedly, but you also talk and think about the destruction of human civilization. What do you think of the Elon Musk hypothesis that the most entertaining outcome is the most likely? And he, I think, followed on to say a scene from an external observer. Like if somebody was watching us, it seems we come up with creative ways of progressing our civilization that's fun to watch. Yeah, so exactly. He said, from the standpoint of the observer, not the participant, I think. And so what's interesting about that, those were, I think, just a couple of freestanding tweets and delivered without a whole lot of wrapper of context, so it's left to the mind of the reader of the tweets to infer what he was talking about. So that's kind of like, it provokes some interesting thoughts. Like first of all, it presupposes the existence of an observer, and it also presupposes that the observer wishes to be entertained and has some mechanism of enforcing their desire to be entertained. So there's like a lot underpinning that. And to me, that suggests, particularly coming from Elon, that it's a reference to simulation theory, that somebody is out there and has far greater insights and a far greater ability to, let's say, peer into a single individual life and find that entertaining and full of plot twists and surprises and either a happy or tragic ending, or they have an incredible meta view and they can watch the arc of civilization unfolding in a way that is entertaining and full of plot twists and surprises and a happy or unhappy ending. So, okay, so we're presupposing an observer. Then on top of that, when you think about it, you're also presupposing a producer because the act of observation is mostly fun if there are plot twists and surprises and other developments that you weren't foreseeing. I have reread my own novels, and that's fun because it's something I worked hard on and I slaved over and I love, but there aren't a lot of surprises in there. So now I'm thinking we need a producer and an observer for that to be true. And on top of that, it's gotta be a very competent producer because Elon said the most entertaining outcome is the most likely one. So there's lots of layers for thinking about that. And when you've got a producer who's trying to make it entertaining, it makes me think of there was a South Park episode in which Earth turned out to be a reality show. And somehow we had failed to entertain the audience as much as we used to, so the Earth show was gonna get canceled, et cetera. So taking all that together, and I'm obviously being a little bit playful in laying this out, what is the evidence that we have that we are in a reality that is intended to be most entertaining? Now, you could look at that reality on the level of individual lives or the whole arc of civilization, other lives, levels as well, I'm sure. But just looking from my own life, I think I'd make a pretty lousy show. I spend an inordinate amount of time just looking at a computer. I don't think that's very entertaining. And there's just a completely inadequate level of shootouts and car chases in my life. I mean, I'll go weeks, even months, without a single shootout or car chase. That just means that you're one of the non-player characters in this game. You're just waiting. I'm an extra. You're an extra that waiting for your one opportunity for a brief moment to actually interact with one of the main characters in the play. Very interesting. Okay, that's good. So, okay, so we'll rule out me being the star of the show, which I probably could have guessed at anyway. But then even the arc of civilization. I mean, there have been a lot of really intriguing things that have happened and a lot of astounding things that have happened. But I would have some werewolves, I'd have some zombies. I would have some really improbable developments like maybe Canada absorbing the United States. So, I don't know. I'm not sure if we're necessarily designed for maximum entertainment. But if we are, that will mean that 2020 is just a prequel for even more bizarre years ahead. So, I kind of hope that we're not designed for maximum entertainment. Well, the night is still young in terms of Canada. But do you think it's possible for the observer and the producer to be kind of emergent? So, meaning it does seem when you kind of watch memes on the internet, the funny ones, the entertaining ones spread more efficiently. They do. I mean, I don't know what it is about the human mind that soaks up en masse funny things much more sort of aggressively. It's more viral in the full sense of that word. Is there some sense that whatever the evolutionary process that created our cognitive capabilities is the same process that's going to, in an emergent way, create the most entertaining outcome, the most meme-ifiable outcome, the most viral outcome if we were to share it on Twitter? Yeah, that's interesting. Yeah, we do have an incredible ability. Like, I mean, how many memes are created in a given day? And the ones that go viral are almost uniformly funny, at least to somebody with a particular sense of humor. Right. Yeah, I'd have to think about that. We are definitely great at creating atomized units of funny. Like in the example that you used, there are going to be X million brains parsing and judging whether this meme is retweetable or not. And so that sort of atomic element of funniness, of entertainingness, et cetera, we definitely have an environment that's good at selecting for that, and selective pressure, and everything else that's going on. But in terms of the entire ecosystem of conscious systems here on the Earth driving for a level of entertainment, that is on such a much higher level that I don't know if that would necessarily follow directly from the fact that atomic units of entertainment are very, very aptly selected for us. I don't know. Do you find it compelling or useful to think about human civilization from the perspective of the ideas versus the perspective of the individual human brains? So almost thinking about the ideas or the memes, this is the Dawkins thing, as the organisms. And then the humans as just like vehicles for briefly carrying those organisms as they jump around and spread. Yeah, for propagating them, mutating them, putting selective pressure on them, et cetera. I mean, I found Dawkins', or his launching, or the idea of memes is just kind of an afterthought to his unbelievably brilliant book about the selfish gene. Like, what a PS to put at the end of a long chunk of writing. Profoundly interesting. I view the relationship though between humans and memes as probably an oversimplification, but maybe a little bit like the relationship between flowers and bees, right? Do flowers have bees, or do bees in a sense have flowers? And the answer is, it is a very, very symbiotic relationship in which both have semi-independent roles that they play, and both are highly dependent upon the other. And so in the case of bees, obviously, you could see the flowers being this monolithic structure physically in relation to any given bee, and it's the source of food and sustenance. So you could kind of say, well, flowers have bees. But on the other hand, the flowers would obviously be doomed. They weren't being pollinated by the bees. So you could kind of say, well, you know, flowers are really expression of what the bees need. And the truth is a symbiosis. So with memes and human minds, our brains are clearly the Petri dishes in which memes are either propagated or not propagated, get mutated or don't get mutated. They are the venue in which competition, selective competition, plays out between different memes. So all of that is very true. And you could look at that and say, really the human mind is a production of memes, and ideas have us rather than us having ideas. But at the same time, let's take a catchy tune as an example of a meme. That catchy tune did originate in a human mind. Somebody had to structure that thing. And as much as I like Elizabeth Gilbert's TED Talk about how the universe, I'm simplifying, but you know, kind of the ideas find their way in this beautiful TED Talk. It's very lyrical. She talked about, you know, ideas and prose kind of beaming into our minds. And, you know, she talked about needing to pull over to the side of the road when she got inspiration for a particular paragraph or a particular idea and a burning need to write that down. I love that. I find that beautiful as a writer, as a novelist myself. I've never had that experience. And I think that really most things that do become memes are the product of a great deal of deliberate and willful exertion of a conscious mind. And so like the bees and the flowers, I think there's a great symbiosis. And they both kind of have one another. Ideas have us, but we have ideas for real. If we could take a little bit of a tangent, Stephen King on writing, you as a great writer, you're dropping a hint here that the ideas don't come to you. It's a grind of sort of, it's almost like you're mining for gold. It's more of a very deliberate, rigorous daily process. So maybe, can you talk about the writing process? How do you write well? And maybe if you want to step outside of yourself, almost like give advice to an aspiring writer, what does it take to write the best work of your life? Well, it would be very different if it's fiction versus nonfiction. And I've done both. I've written two works of non, two nonfiction books and two works of fiction. Two works of fiction being more recent, I'm gonna focus on that right now because that's more toweringly on my mind. There are amongst novelists, again, this is an oversimplification, but there's kind of two schools of thought. Some people really like to fly by the seat of their pants. And some people really, really like to outline, to plot. So there's plotters and pantsers, I guess is one way that people look at it. And as with most things, there is a great continuum in between and I'm somewhere on that continuum, but I lean, I guess, a little bit more toward the plotter. And so when I do start a novel, I have a pretty strong point of view about how it's gonna end. And I have a very strong point of view about how it's gonna begin. And I do try to make an effort of making an outline that I know I'm gonna be extremely unfaithful to in the actual execution of the story, but I'm trying to make an outline that gets us from here to there and notion of subplots and beats and rhythm and different characters and so forth. But then when I get into the process, that outline, particularly the center of it, ultimately, inevitably morphs a great deal. And I think if I were personally a rigorous outliner, I would not allow that to happen. I also would make a much more vigorous skeleton before I start. So I think people who are really in that plotting, outlining mode are people who write page turners, people who write spy novels or supernatural adventures where you really want a relentless pace of events, action, plot twists, conspiracy, et cetera. And that is really the bone. That's really the skeletal structure. So I think folks who write that kind of book are really very much on the outlining side. And I think people who write what's often referred to as literary fiction, for lack of a better term, where it's more about sort of aura and ambiance and character development and experience and inner experience and inner journey and so forth. I think that group is more likely to fly by the seat of their pants. And I know people who start with a blank page and just see where it's gonna go. I'm a little bit more on the plotting side. Now you asked what makes something, at least in the mind of the writer, as great as it can be. For me, it's an astonishingly high percentage of it is editing as opposed to the initial writing. For every hour that I spend writing new prose, like new pages, new paragraphs, stuff that, new bits of the book, I probably spend, I mean, I wish I kept a count. I wish I had one of those pieces of software that lawyers use to decide how much time I've been doing this or that. But I would say it's at least four or five hours, and maybe as many as 10 that I spend editing. And so it's relentless for me. For each one hour of writing, you said? I'd say that. Wow. I mean, I write because I edit, and I spend just relentlessly polishing and pruning, and sometimes on the micro level of just like, does the rhythm of the sentence feel right? Do I need to carve a syllable or something so it can land? Like as micro as that to as macro as like, okay, I'm done, but the book is 750 pages long, and it's way too bloated, and I need to lop a third out of it. Problems on those two orders of magnitude and everything in between, that is an enormous amount of my time. And I also write music, write and record and produce music. And there, the ratio is even higher. Every minute that I spend or my band spends laying down that original audio, it's a very high proportion of hours that go into just making it all hang together and sound just right. So I think that's true of a lot of creative processes. I know it's true of sculpture. I believe it's true of woodwork. My dad was an amateur woodworker, and he spent a huge amount of time on sanding and polishing at the end. So I think a great deal of the sparkle comes from that part of the process, any creative process. Can I ask about the psychological, the demon side of that picture? In the editing process, you're ultimately judging the initial piece of work, and you're judging and judging and judging. How much of your time do you spend hating your work? How much time do you spend in gratitude, impressed, thankful, or how good the work that you will put together is? I spend almost all the time in a place that's intermediate between those, but leaning toward gratitude. I spend almost all the time in a state of optimism, that this thing that I have, I like. I like quite a bit, and I can make it better and better and better with every time I go through it. So I spend most of my time in a state of optimism. I think I personally oscillate much more aggressively between those two, where I wouldn't be able to find the average. I go pretty deep. Marvin Minsky from MIT had this advice, I guess, to what it takes to be successful in science and research is to hate everything you do, you've ever done in the past. I mean, at least he was speaking about himself that the key to his success was to hate everything he's ever done. I have a little Marvin Minsky there in me too, just sort of always be exceptionally self-critical, but almost like self-critical about the work, but grateful for the chance to be able to do the work, if that makes sense. It makes perfect sense. But that each one of us have to strike a certain kind of balance. Yeah. But back to the destruction of human civilization. If humans destroy ourselves in the next 100 years, what will be the most likely source, the most likely reason that we destroy ourselves? Well, let's see. 100 years, it's hard for me to comfortably predict out that far. And it's something to give a lot more thought to, I think, than normal folks, simply because I'm a science fiction writer. And I feel with the acceleration of technological progress, it's really hard to foresee out more than just a few decades. I mean, comparing today's world to that of 1921, where we are right now a century later, it would have been so unforeseeable. And I just don't know what's gonna happen, particularly with exponential technologies. I mean, our intuitions reliably defeat ourselves with exponential technologies like computing and synthetic biology. And how we might destroy ourselves in the 100-year time frame might have everything to do with breakthroughs in nanotechnology 40 years from now, and then how rapidly those breakthroughs accelerate. But in the nearer term that I'm comfortable predicting, let's say 30 years, I would say the most likely route to self-destruction would be synthetic biology. And I always say that with the gigantic caveat, and very important one, that I find, and I'll abbreviate synthetic biology to SynBio, just to save us some syllables. I believe SynBio offers us simply stunning promise that we would be fools to deny ourselves. So I'm not an anti-SynBio person by any stretch. I mean, SynBio has unbelievable odds of helping us beat cancer, helping us rescue the environment, helping us do things that we would currently find imponderable. So it's electrifying the field. But in the wrong hands, those hands either being incompetent or being malevolent. In the wrong hands, synthetic biology to me has a much, much greater odds, has much, much greater odds of leading to our self-destruction than something running amok with super AI, which I believe is a real possibility and one we need to be concerned about. But in the 30-year time frame, I think it's a lesser one. Or nuclear weapons or anything else that I can think of. Can you explain that a little bit further? So your concern is on the man-made versus the natural side of the pandemic front here. So we humans engineering pathogens, engineering viruses is the concern here. Yeah. And maybe how do you see the possible trajectories happening here in terms of, is it malevolent or is it accidents, oops, little mistakes, or unintended consequences of particular actions that are ultimately lead to unexpected mistakes? Well, both of them are a danger. And I think the question of which is more likely has to do with two things. One, do we take a lot of methodical, affordable, foresighted steps that we are absolutely capable of taking right now to first stall the risk of a bad actor infecting us with something that could have annihilating impacts. And in the episode you referenced with Sam, we talked a great deal about that. So do we take those steps? And if we take those steps, I think the danger of malevolent rogue actors doing a sin with Sin Bio could plummet. But it's always a question of if, and we have a bad, bad, and very long track record of hitting the snooze bar after different natural pandemics have attacked us. So that's variable number one. Variable number two is how much experimentation and pathogen development do we as a society decide is acceptable in the realms of academia, government, or private industry? And if we decide as a society that it's perfectly okay for people with varying research agendas to create pathogens that if released could wipe out humanity, if we think that's fine, and if that kind of work starts happening in one lab, five labs, 50 labs, 500 labs, in one country, then 10 countries, then 70 countries, or whatever, that risk of a boo-boo starts rising astronomically. And this won't be a spoiler alert based on the way that I presented those two things, but I think it's unbelievably important to manage both of those risks. The easier one to manage, although it wouldn't be simple by any stretch because it would have to be something that all nations agree on, but the easiest way, the easier risk to manage is that of, hey guys, let's not develop pathogens that if they escape from a lab could annihilate us. There's no line of research that justifies that, and in my view, I mean, that's the point of perspective we need to have. We'd have to collectively agree that there's no line of research that justifies that. The reason why I believe that would be a highly rational conclusion is even the highest level of biosafety lab in the world, biosafety lab level four, and there are not a lot of BSL-4 labs in the world, there are things can and have leaked out of BSL-4 labs, and some of the work that's been done with potentially annihilating pathogens, which we can talk about, it's actually done at BSL-3. And so fundamentally, any lab can leak. We have proven ourselves to be incapable of creating a lab that is utterly impervious to leaks. So why in the world would we create something where if, God forbid, it leaked, could annihilate us all? And by the way, almost all of the measures that are taken in biosafety level anything labs are designed to prevent accidental leaks. What happens if you have a malevolent insider? And we could talk about the psychology and the motivations of what would make a malevolent insider who wants to release something and not annihilating in a bit. I'm sure that we will. But what if you have a malevolent insider? Virtually none of the standards that go into biosafety level one, two, three, and four are about preventing somebody hijacking the process. I mean, some of them are, but they're mainly designed against accidents. They're imperfect against accidents. And if this kind of work starts happening in lots and lots of labs, with every lab you add, the odds of there being a malevolent insider naturally increase arithmetically as the number of labs goes up. Now, on the front of somebody outside of a government, academic or scientific, traditional government, academic, scientific environment, creating something malevolent, again, there's protections that we can take both at the level of syn-bio architecture, the hardening the entire syn-bio ecosystem against terrible things being made that we don't want to have out there by rogue actors, to early detection, to lots and lots of other things that we can do to dramatically mitigate that risk. And I think we do both of those things, decide that no, we're not going to experimentally make annihilating pathogens in leaky labs, and B, yes, we are gonna take countermeasures that are gonna cost a fraction of our annual defense budget to preclude their creation. Then I think both risks get managed down. But if you take one set of precautions and not the other, then the thing that you have not taken precautions against immediately becomes the more likely outcome. So can we talk about this kind of research and what's actually done, and what are the positives and negatives of it? So if we look at gain-of-function research and the kind of stuff that's happening in level three and level four BSL labs, what's the whole idea here? Is it trying to engineer viruses to understand how they behave? You want to understand the dangerous ones. Yeah, so that would be the logic behind doing it. And so gain-of-function can mean a lot of different things. Viewed through a certain lens, gain-of-function research could be what you do when you create GMOs, when you create hearty strains of corn that are resistant to pesticides. I mean, you could view that as gain-of-function. So I'm gonna refer to gain-of-function in a relatively narrow sense, which is actually the sense that the term is usually used, which is in some way magnifying capabilities of microorganisms to make them more dangerous, whether it's more transmissible or more deadly. And in that line of research, I'll use an example from 2011, because it's very illustrative and it's also very chilling. Back in 2011, two separate labs, independently of one another, I assume there was some kind of communication between them, but they were basically independent projects, one in Holland and one in Wisconsin, did gain-of-function research on something called H5N1 flu. H5N1 is something that, at least on a lethality basis, makes COVID look like a kitten. COVID, according to the World Health Organization, has a case fatality rate somewhere between half a percent and 1%. H5N1 is closer to 60%, six zero. And so that's actually even slightly more lethal than Ebola. It's a very, very, very scary pathogen. The good news about H5N1, it is that it is barely, barely contagious. And I believe it is in no way contagious human to human. It requires very, very, very deep contact with birds, in most cases, chickens. And so if you're a chicken farmer and you spend an enormous amount of time around them and perhaps you get into situations in which you get a break in your skin and you're interacting intensely with fowl who, as it turns out, have H5N1, that's when the jump comes. But there's no airborne transmission that we're aware of human to human. I mean, not that we're, it just doesn't exist. I think the World Health Organization did a relentless survey of the number of H5N1 cases. I think they do it every year. I saw one 10-year series where I think it was like 500 fatalities over the course of a decade. And that's a drop in the bucket, kind of fun fact. I believe the typical lethality from lightning over 10 years is 70,000 deaths. So we've been getting struck by lightning, pretty low risk, H5N1, much, much lower than that. What happened in these experiments is the experimenters in both cases set out to make H5N1 that would be contagious, that could create airborne transmission. And so they basically passed it, I think in both cases, they passed it through a large number of ferrets. And so this wasn't like CRISPR, there wasn't even any CRISPR back in those days. This was relatively straightforward, selecting for a particular outcome. And after guiding the path and passing them through, again, I believe it was a series of ferrets, they did in fact come up with a version of H5N1 that is capable of airborne transmission. Now, they didn't unleash it into the world, they didn't inject it into humans to see what would happen. And so for those two reasons, we don't really know how contagious it might have been. But if it was as contagious as COVID, that could be a civilization-threatening pathogen. And why would you do it? Well, the people who did it were good guys, they were virologists. I believe their agenda as they explained it was much as you said, let's figure out what a worst case scenario might look like so we could understand it better. But my understanding is in both cases, it was done in BSL-3 labs. And so potential of leak, significantly non-zero, hopefully way below 1%, but significantly non-zero. And when you look at the consequences of an escape in terms of human lives, destruction of a large portion of the economy, et cetera, and you do an expected value calculation on whatever fraction of 1% that was, you would come up with a staggering cost, staggering expected cost for this work. So it should never have been carried out. Now, you might make an argument, if you said, if you believed that H5N1 in nature is on an inevitable path to airborne transmission, and it's only gonna be a small number of years, A, and B, if it makes that transition, there is one set of changes to its metabolic pathways and its genomic code and so forth, one, that we have discovered. So it is gonna go from point A, which is where it is right now, to point B. We have reliably engineered point B. That is the destination. And we need to start fighting that right now, because this is five years or less away. Now, that'd be a very different world. That'd be like spotting an asteroid that's coming toward the Earth and is five years off. And yes, you marshal everything you can to resist that. But there's two problems with that perspective. The first is, in however many thousands of generations that humans have been inhabiting this planet, there has never been a transmissible form of H5N1. And influenza's been around for a very long time. So there is no case for inevitability of this kind of a jump to airborne transmission. So we're not on a freight train to that outcome. And if there was inevitability around that, it's not like there's just one set of genetic code that would get there. There are just, there's all kinds of different mutations that could conceivably result in that kind of an outcome. Unbelievable diversity of mutations. And so we're not actually creating something we're inevitably going to face. But we are creating something, we are creating a very powerful and unbelievably negative card and injecting it in the deck that nature never put into the deck. So in that case, I just don't see any moral or scientific justification for that kind of work. And interestingly, there was quite a bit of excitement and concern about this when the work came out. One of the teams was gonna publish their results in science, the other in nature. And there were a lot of editorials and a lot of scientists are saying this is crazy. And publication of those papers did get suspended. And not long after that, there was a pause put on US government funding, NIH funding on gain-of-function research. But both of those speed bumps were ultimately removed. Those papers did ultimately get published. And that pause on funding ceased long ago. And in fact, those two very projects, my understanding is, resumed their funding, got their government funding back. I don't know why a Dutch project's getting NIH funding, but whatever, about a year and a half ago. So as far as the US government and regulators are concerned, it's all systems go for gain-of-function at this point, which I find very troubling. Now, I'm a little bit of an outsider from this field, but it has echoes of the same kind of problem I see in the AI world with autonomous weapon systems. Nobody, and my colleagues, my colleagues, friends, as far as I can tell, people in the AI community, are not really talking about autonomous weapon systems, as now US and China full steam ahead on the development of both. And that seems to be a similar kind of thing on gain-of-function. I have friends in the biology space, and they don't wanna talk about gain-of-function publicly. That makes me very uncomfortable from an outsider perspective in terms of gain-of-function. It makes me very uncomfortable from the insider perspective on autonomous weapon systems. I'm not sure how to communicate exactly about autonomous weapon systems, and I certainly don't know how to communicate effectively about gain-of-function. What is the right path forward here? Should we seize all gain-of-function research? Is that really the solution here? Well, again, I'm gonna use gain-of-function in the relatively narrow context of what we're discussing. Yes, for viruses. You could say almost anything that you do to make biology more effective is gain-of-function. So within the narrow confines of what we're discussing, I think it would be easy enough for level-headed people in all of the countries, level-headed governmental people in all of the countries that realistically could support such a program to agree, we don't want this to happen because all labs leak. I mean, an example that I use, I actually use it in the piece I did with Sam Harris as well, is the anthrax attacks in the United States in 2001. I mean, talk about an example of the least likely lab leaking into the least likely place. This was shortly after 9-11, for folks who don't remember it, and it was a very, very lethal strand of anthrax that, as it turned out, based on the forensic genomic work that was done and so forth, absolutely leaked from a high-security US Army lab. Probably the one at Fort Detrick in Maryland. It might've been another one, but who cares? It absolutely leaked from a high-security US Army lab. And where did it leak to, this highly dangerous substance that was kept under lock and key by a very security-minded organization? Well, it leaked to places including the Senate Majority Leader's office, Tom Daschle's office. I think it was Senator Leahy's office. Certain publications, including, bizarrely, the National Enquirer. But let's go to the Senate Majority Leader's office. It is hard to imagine a more security-minded country than the United States two weeks after the 9-11 attack. I mean, it doesn't get more security-minded than that. And it's also hard to imagine a more security-capable organization than the United States military. We can joke all we want about inefficiencies in the military and $24,000 wrenches and so forth, but pretty capable when it comes to that. Despite that level of focus and concern and competence, just days after the 9-11 attack, something comes from the inside of our military and industrial compacts and ends up in the office of someone, I believe the Senate Majority Leader, somewhere in the line of presidential succession. It tells us everything can leak. So again, think of a level-headed conversation between powerful leaders in a diversity of countries, thinking through, like I can imagine a very simple PowerPoint revealing, just discussing briefly things like the anthrax leak, things like this foot-and-mouth disease outbreak or leaking that came out of a BSL-4-level lab in the UK, several other things, talking about the utter virulence that could result from gain-of-function and say, folks, can we agree that this just shouldn't happen? I mean, if we were able to agree on the Nuclear Non-Proliferation Treaty, which we were, by a weapons convention, which we did agree on, we the world, for the most part, I believe agreement could be found there. But it's gonna take people in leadership of a couple of very powerful countries to get to consensus amongst them and then to decide we're gonna get everybody together and browbeat them into banning this stuff. Now, that doesn't make it entirely impossible that somebody might do this, but in well-regulated, carefully watched over fiduciary environments, like federally-funded academic research, anything going on in the government itself, things going on in companies that have investors who don't wanna go to jail for the rest of their lives, I think that would have a major, major dampening impact on it. But there is a particular possible catalyst in this time we live in, which is for really kind of raising the question of gain-of-function research for the application of virus, making viruses more dangerous, is the question of whether COVID leaked from a lab. Sort of not even answering that question, but even asking that question. It seems like a very important question to ask to catalyze the conversation about whether we should be doing gain-of-function research. I mean, from a high level, why do you think people, even colleagues of mine, are not comfortable asking that question? And two, do you think that the answer could be that it did leak from a lab? I think the mere possibility that it did leak from a lab is evidence enough, again, for the hypothetical, rational national leaders watching this simple PowerPoint. If you could put the possibility at 1% and you look at the unbelievable destructive power that COVID had, that should be an overwhelmingly powerful argument for excluding it. Now, as to whether or not that was a leak, some very, very level, I don't know enough about all of the factors in the Bayesian analysis and so forth that has gone into people making the pro argument of that. So I don't pretend to be an expert on that and I don't have a point of view. I just don't know. But what we can say is it is entirely possible for a couple of reasons. One is that there is a BSL-4 lab in Wuhan, the Wuhan Institute of Virology. I believe it's the only BSL-4 in China. I could be wrong about that. But it definitely had a history that alarmed very sophisticated US diplomats and others who were in contact with the lab and were aware of what it was doing long before COVID hit the world. And so there are diplomatic cables that have been declassified. I believe one sophisticated scientist or other observer said that WIV is a ticking time bomb. And I believe it's also been pretty reasonably established that coronaviruses were a topic of great interest at WIV. SARS obviously came out of China and that's a coronavirus that would make an enormous amount of sense for it to be studied there. And there is so much opacity about what happened in the early days and weeks after the outbreak that's basically been imposed by the Chinese government that we just don't know. So it feels like a substantially or greater than 1% possibility to me, looking at it from the outside. And that's something that one could imagine. Now we're going to the realm of thought experiment, not me decreeing this is what happened, but if they're studying coronavirus at the Wuhan Institute of Virology, and there is this precedent of gain-of-function research that's been done on something that is remarkably uncontagious to humans, whereas we know coronavirus is contagious to humans. I could definitely, and there is this global consensus. Certainly was the case two or three years ago when this work might have started, there seems to be this global consensus that gain-of-function is fine. The US paused funding for a little while, but paused funding, they never said private actors couldn't do it. It was just a pause of NIH funding. And then that pause was lifted. So again, none of this is irrational. You could certainly see the folks at WIV saying, gain-of-function, interesting vector, coronavirus, unlike H5N1, very contagious. We're a nation that has had terrible run-ins with coronavirus. Why don't we do a little gain-of-function on this? And then, like all labs at all levels, one can imagine this lab leaking. So it's not an impossibility, and very, very level-headed people have said that, you know, who've looked at it much more deeply, do believe in that outcome. Why is it such a threat to power, the idea that it'll leak from a lab? Why is it so threatening? I don't, maybe I understand this point exactly. Like, is it just that as governments, and especially the Chinese government, is really afraid of admitting mistakes that everybody makes? So this is a horrible, like Chernobyl is a good example. I come from the Soviet Union. I mean, well, major mistakes were made in Chernobyl. I would argue for a lab leak to happen, but the scale of the mistake is much smaller, right? The depth and the breadth of rot that in bureaucracy that led to Chernobyl is much bigger than anything that could lead to a lab leak, because it could literally just be, I mean, I'm sure there's security, very careful security procedures, even in level three labs, but I imagine maybe you can correct me. All it takes is the incompetence of a small number of individuals. Or even one. One individual on a particular, a couple weeks, three weeks period, as opposed to a multi-year bureaucratic failure of the entire government. Right, well, certainly the magnitude of mistakes and compounding mistakes that went into Chernobyl was far, far, far greater, but the consequence of COVID outweighs that, the consequence of Chernobyl, to a tremendous degree. And I think that particularly authoritarian governments are unbelievably reluctant to admit to any fallibility whatsoever. There's a long, long history of that across dozens and dozens of authoritarian governments. And to be transparent, again, this is in the hypothetical world in which this was a leak, which again, I don't personally have enough sophistication to have an opinion on the likelihood, but in the hypothetical world in which it was a leak, the global reaction and the amount of global animus and the amount of, you know, the decline in global respect that would happen toward China, because every country suffered massively from this, unbelievable damages in terms of human lives and economic activity disrupted. The world would in some way present China with that bill. And when you take on top of that, the natural disinclination for any authoritarian government to admit any fallibility and tolerate the possibility of any fallibility whatsoever, and you look at the relative opacity, even though they let a World Health Organization group in, you know, a couple of months ago to run around, they didn't give that who group anywhere near the level of access that would be necessary to definitively say X happened versus Y. The level of opacity that surrounds those opening weeks and months of COVID in China, we just don't know. If you were to kind of look back at 2020 and maybe broadening it out to future pandemics that could be much more dangerous, what kind of response, how do we fail in a response? And how could we do better? So the gain of function research is discussing, which, you know, the question of, we should not be creating viruses that are both exceptionally contagious and exceptionally deadly to humans. But if it does happen, perhaps the natural evolution, natural mutation, is there interesting technological responses on the testing side, on the vaccine development side, on the collection of data, or on the basic sort of policy response side, or the sociological, the psychological side? Yeah, there's all kinds of things. And most of what I've thought about and written about, and again, discussed in that long bit with Sam, is dual use. So most of the countermeasures that I've been thinking about and advocating for would be every bit as effective against zoonotic disease, a natural pandemic of some sort, as an artificial one. The risk of an artificial one, even the near-term risk of an artificial one, ups the urgency around these measures immensely, but most of them would be broadly applicable. And so I think the first thing that we really wanna do on a global scale is have a far, far, far more robust and globally transparent system of detection. And that can happen on a number of levels. The most obvious one is just in the blood of people who come into clinics exhibiting signs of illness. And we are certainly at a point now where we're at with relatively minimal investment. We could develop in-clinic diagnostics that would be unbelievably effective at pinpointing what's going on in almost any disease when somebody walks into a doctor's office or a clinic. And better than that, this is a little bit further off, but it wouldn't cost tens of billions in research dollars. It would be a relatively modest and affordable budget in relation to the threat, at-home diagnostics that can really, really pinpoint, okay, particularly with respiratory infections, because that is generally, almost universally, the mechanism of transmission for any serious pandemic. So somebody has a respiratory infection. Is it one of the significantly large handful of rhinoviruses, coronaviruses, and other things that cause common cold? Or is it influenza? If it's influenza, is it influenza A versus B? Or is it a small handful of other more exotic, but nonetheless sort of common respiratory infections that are out there? Developing a diagnostic panel to pinpoint all of that stuff, that's something that's well within our capabilities. That's much less a lift than creating mRNA vaccines, which obviously we proved capable of when we put our minds to it. So do that on a global basis. And I don't think that's irrational because the best prototype for this that I'm aware of isn't currently rolling out in Atherton, California or Fairfield County, Connecticut or some other wealthy place. The best prototype that I'm aware of this is rolling out right now in Nigeria. And it's a project that came out of the Broad Institute, which is, as I'm sure you know, but some listeners may not, is kind of like an academic joint venture between Harvard and MIT. The program is called Sentinel. And their objective is, and their plan, and it's a very well-conceived plan, methodical plan, is to do just that in areas of Nigeria that are particularly vulnerable to zoonotic diseases, making the jump from animals to humans. But also there's just an unbelievable public health benefit from that. And it's sort of a three-tier system where clinicians in the field could very rapidly determine, do you have one of the infections of acute interest here, either because it's very common in this region, so we wanna diagnose as many things as we can at the frontline, or because it's uncommon but unbelievably threatening like Ebola. So frontline worker can make that determination very, very rapidly. If it comes up as a we don't know, they bump it up to a level that's more like at a fully configured doctor's office or local hospital. And if it's still at a we don't know, it gets bumped up to a national level. And it gets bumped very, very rapidly. So if this can be done in Nigeria, and it seems that it can be, there shouldn't be any inhibition for it to happen in most other places. And it should be affordable from a budgetary standpoint. And based on Sentinel's budget and adjusting things for things like very different cost of living, larger population, et cetera, I did a back of the envelope calculation that doing something like Sentinel in the US would be in the low billions of dollars. And wealthy countries, middle-income countries can afford such a thing. Lower-income countries should certainly be helped with that. But start with that level of detection. And then layer on top of that other interesting things like monitoring search engine traffic, search engine queries for evidence that strange clusters of symptoms are starting to rise in different places. There's been a lot of work done with that. Most of it kind of academic and experimental. But some of it has been powerful enough to suggest that this could be a very powerful early warning system. There's a guy named Bill Lampos at University College London, who basically did a very rigorous analysis that showed that symptom searches reliably predicted COVID outbreaks in the early days of the pandemic in given countries by as much as 16 days before the evidence started to accrue at a public health level. 16 days of forewarning can be monumentally important in the early days of an outbreak. And this is a very, very talented, but nonetheless very resource-constrained academic project. Imagine if that was something that was done with a NORAD-like budget. Yeah, so I mean, starting with detection, that's something we could do radically, radically better. So aggregating multiple data sources in order to create something. I mean, this is really exciting to me, the possibility that I've heard inklings of, of creating almost like a weather map of pathogens. Like basically aggregating all of these data sources, scaling many orders of magnitude up at home, testing and all kinds of testing that doesn't just try to test for the particular pathogen of worry now, but everything, like a full spectrum of things that could be dangerous to the human body, and thereby be able to create these maps like that are dynamically updated on an hourly basis of how viruses travel throughout the world. And so you can respond, like you can then integrate, just like you do when you check your weather map and it's raining or not, of course, not perfect, but it's very good predictor of whether it's gonna rain or not, and use that to then make decisions about your own life. Ultimately, give the power of information to individuals to respond. And if it's a super dangerous, like if it's acid rain versus regular rain, you might wanna really stay inside as opposed to risking it. And that, just like you said, I think it's not very expensive relative to all the things that we do in this world, but it does require bold leadership. And there's another dark thing which really has bothered me about 2020, which it requires, is it requires trust in institutions to carry out these kinds of programs, and it requires trust in science and engineers and sort of centralized organizations that would operate at scale here. And much of that trust has been, at least in the United States, diminished, it feels like. Not exactly sure where to place the blame, but I do place quite a bit of the blame into the scientific community, and again, my fellow colleagues. In speaking down to people at times, speaking from authority, it sounded like it dismissed the basic human experience or the basic common humanity of people in a way that it almost sounded like there's an agenda that's hidden behind the words the scientists spoke, like they're trying to, in a self-preserving way, control the population or something like that. I don't think any of that is true from the majority of the scientific community, but it sounded that way, and so the trust began to diminish. And I'm not sure how to fix that except to be more authentic, be more real, acknowledge the uncertainties under which we operate, acknowledge the mistakes that scientists make, that institutions make. The leak from the lab is a perfect example. We have imperfect systems that make all the progress we see in the world, and that being honest about that imperfection, I think, is essential for forming trust. But I don't know what to make of it. It's been deeply disappointing because I do think, just like you mentioned, the solutions require people to trust the institutions with their data. Yeah, and I think part of the problem is, it seems to me as an outsider that there was a bizarre unwillingness on the part of the CDC and other institutions to admit to, to frame, and to contextualize uncertainty. Maybe they had a patronizing idea that these people need to be told, and when they're told, they need to be told with authority and a level of definitiveness and certitude that doesn't actually exist. And so when they whipsaw on recommendations like what you should do about masks, when the CDC is kind of at the very beginning of the pandemic saying, masks don't do anything, don't wear them, when the real driver for that was, we don't want these clowns going out and depleting Amazon of masks because they may be needed in medical settings, and we just don't know yet, I think a message that actually respected people and said, this is why we're asking you not to do masks yet, and there's more to be seen, would be less whipsawing and would bring people, like they feel more like they're part of the conversation and they're being treated like adults than saying one day, definitively masks suck, and then X days later saying, nope, dammit, wear masks. And so I think framing things in terms of the probabilities, which most people are easy to parse, I mean, a more recent example, which I just thought was batty, was suspending the Johnson & Johnson vaccine for a very low single digit number of days in the United States, based on the fact that I believe there had been seven-ish clotting incidents in roughly seven million people who had had the vaccine administered, I believe one of which resulted in a fatality. And there was definitely suggestive data that indicated that there was a relationship, this wasn't just coincidental because I think all of the clotting incidents happened in women as opposed to men, and kind of clustered in a certain age group, but does that call for shutting off the vaccine, or does it call for leveling with the American public in saying we've had one fatality out of seven million? This is, let's just assume, substantially less than the likelihood of getting struck by lightning. Based on that information, and we're gonna keep you posted because you can trust us to keep you posted, based on that information, please decide whether you're comfortable with a Johnson & Johnson vaccine. That would have been one response, and I think people would have been able to parse those simple bits of data and make their own judgment. By turning it off, all of a sudden there's this dramatic signal to people who don't read all 900 words in the New York Times piece that explains why it's being turned off, but just see the headline, which is a majority of people, there's a sudden like, oh my God, yikes, vaccine being shut off, and then all the people who sat on the fence or are sitting on the fence about whether or not they trust vaccines, that is gonna push an incalculable number of people, that's gonna be the last straw for we don't know how many hundreds of thousands or more likely millions of people to say, okay, tipping point here, I don't trust these vaccines. By pausing that for whatever it was, 10 or 12 days, and then flipping the switch, as everybody who knew much about the situation knew was inevitable, by flipping the on switch 12 days later, you're conveying certitude J&J bad to certitude J&J good in a period of just a few days, and people just feel whipsawed, and they're not part of the analysis. But it's not just the whipsawing, and I think about this quite a bit, I don't think I have good answers, it's something about the way the communication actually happens. Just, I don't know what it is about Anthony Fauci, for example, but I don't trust him. And I think that has to do, I mean, he's, he did, he has an incredible background, I'm sure he's a brilliant scientist and researcher, I'm sure he's also a great, like inside the room, policymaker and deliberator and so on. But, you know, what makes a great leader is something about that thing that you can't quite describe, but being a communicator that you know you can trust, that there's an authenticity that's required. And I'm not sure, maybe I'm being a bit too judgmental, but I'm a huge fan of a lot of great leaders throughout history, they've communicated exceptionally well in the way that Fauci does not. And I think about that, I think about what is effective science communication. So, you know, great leaders throughout history did not necessarily need to be great science communicators. Their leadership was in other domains, but when you're fighting the virus, you also have to be a great science communicator. You have to be able to communicate uncertainties, you have to be able to communicate something like a vaccine that you're allowing inside your body into the messiness, into the complexity of the biology system, that if we're being honest, it's so complex, we'll never be able to really understand. We can only desperately hope that science can give us sort of a high likelihood that there's no short-term negative consequences, and that kind of intuition about long-term negative consequences, and doing our best in this battle against trillions of things that are trying to kill us. I mean, being an effective communicator in that space is very difficult, but I think about what it takes, because I think there should be more science communicators that are effective at that kind of thing. Let me ask you about something that's sort of more in the AI space, that I think about that kind of goes along this thread that you've spoken about, about democratizing the technology that could destroy human civilization, is from amazing work from DeepMind, AlphaFold2, which achieved incredible performance on the protein folding problem, single protein folding problem. Do you think about the use of AI in the SYN biospace of, I think the gain of function in the virus-based research that you referred to, I think is natural mutations, and sort of aggressively mutating the virus until you get one that has this both contagious and deadly. But what about then using AI through simulation be able to compute deadly viruses, or any kind of biological systems? Is this something you're worried about, or again, is this something you're more excited about? I think computational biology is unbelievably exciting and promising field. And I think when you're doing things in silico as opposed to in vivo, the dangers plummet. You don't have a critter that can leak from a leaky lab. So I don't see any problem with that, except I do worry about the data security dimension of it. Because if you were doing really, really interesting in silico gain of function research, and you hit upon, through a level of sophistication, we don't currently have, but synthetic biology is an exponential technology, so capabilities that are utterly out of reach today will be attainable in five or six years. I think if you conjured up worst case genomes of viruses that don't exist in vivo anywhere, they're just in the computer space, but like, hey guys, this is the genetic sequence that would end the world, let's say. Then you have to worry about the utter hackability of every computer network we can imagine. I mean, data leaks from the least likely places on the grandest possible scales have happened and continue to happen, and will probably always continue to happen. And so that would be the danger of doing the work in silico. If you end up with a list of like, well, these are things we never want to see, that list leaks. And after the passage of some time, certainly couldn't be done today, but after the passage of some time, lots and lots of people in academic labs going all the way down to the high school level are in a position to, you know, to make it overly simplistic, hit print on a genome and have the virus bearing that genome pop out on the other end, and you got something to worry about. But in general, computational biology, I think is incredibly important, particularly because the crushing majority of work that people are doing with the protein folding problem and other things are about creating therapeutics, about creating things that will help us, you know, live better, live longer, thrive, be more well, and so forth. And the protein folding problem is a monstrous computational challenge that we seem to make just the most glacial project on, I'm sorry, progress on for years and years. But I think there's like a, there's a biannual competition, I think, for which people tackle the protein folding problem. And DeepMind's entrant, both two years ago, like in 2018 and 2020, ruled the field. And so, you know, protein folding is an unbelievably important thing if you want to start thinking about therapeutics, because, you know, it's the folding of the protein that tells us where the channels and the receptors and everything else are on that protein. And it's from that precise model, if we can get to a precise model, that you can start barraging it again in silicon with, you know, thousands, tens of thousands, millions of potential therapeutics and see what resolves the problems, the shortcomings that, you know, a bad, a misshapen protein, for instance, somebody with cystic fibrosis, how might we treat that? So I see nothing but good in that. Well, let me ask you about fear and hope in this world. I tend to believe that, that in terms of competence and malevolence, that people who are, maybe it's in my interactions, I tend to see that, first of all, I believe that most people are good, want to do good, and are just better at doing good and more inclined to do good on this world. And more than that, people who are malevolent are usually incompetent at building technology. So like, I've seen this in my life, that people who are exceptionally good at stuff, no matter what the stuff is, tend to, maybe they discover joy in life in a way that gives them fulfillment and thereby does not result in them wanting to destroy the world. So like, the better you are at stuff, whether that's building nuclear weapons or plumbing, it doesn't matter, the both, the less likely you are to destroy the world. So in that sense, with many technologies, AI especially, I always think that the malevolent will be far outnumbered by the ultra-competent. And in that sense, the defenses will always be stronger than the offense in terms of the people trying to destroy the world. Now, there's a few spaces where that might not be the case, and that's an interesting conversation, where this one person who's not very competent can destroy the whole world. Perhaps SynBio is one such space because of the exponential effects of the technology. I tend to believe AI is not one of those such spaces, but do you share this kind of view that the ultra-competent are usually also the good? Yeah, absolutely. I absolutely share that, and that gives me a great deal of optimism that we will be able to short-circuit the threat that malevolence in bio could pose to us, but we need to start creating those defensive systems or defensive layers, one of which we talked about, far, far, far better surveillance in order to prevail. So the good guys will almost inevitably outsmart and definitely outnumber the bad guys in most sort of smack downs that we can imagine, but the good guys aren't going to be able to exert their advantages unless they have the imagination necessary to think about what the worst possible thing can be done by somebody whose own psychology is completely alien to their own. So that's a tricky, tricky thing to solve for. Now, in terms of whether the asymmetric power that a bad guy might have in the face of the overwhelming numerical advantage and competence advantage that the good guys have, you know, unfortunately, I look at something like mass shootings as an example. You know, I'm sure the guy who was responsible for the Vegas shooting or the Orlando shooting or any other shooting that we can imagine didn't know a whole lot about ballistics. And the number of, you know, good guy citizens in the United States with guns compared to bad guy citizens, I'm sure is a crushingly, overwhelmingly high ratio in favor of the good guys. But that doesn't make it possible for us to stop mass shootings. An example is Fort Hood, 45,000 trained soldiers on that base, yet there've been two mass shootings there. And so there is an asymmetry when you have powerful and lethal technology that gets so democratized and so proliferated in tools that are very, very easy to use, even by a knucklehead. When those tools get really easy to use by a knucklehead and they're really widespread, it becomes very, very hard to defend against all instances of usage. Now, the good news, quote unquote, about mass shootings, if there is any, and there is some, is even the most brutal and carefully planning and well-armed mass shooter can only take so many victims. And same is true, there's been four instances that I'm aware of, of commercial pilots committing suicide by downing their planes and taking all their passengers with them. These weren't Boeing engineers, you know, but like an army of Boeing engineers, ultimately were not capable of preventing that. But even in their case, and I'm actually not counting 9-11 in that, 9-11's a different category in my mind. These are just personally suicidal pilots. In those cases, they only have a plane load of people that they're able to take with them. If we imagine a highly plausible and imaginable future in which some bio tools that are amoral, that could be used for good or for ill, start embodying unbelievable sophistication and genius in the tool, in the easier and easier and easier to make tool, all those thousands, tens of thousands, hundreds of thousands of scientist years start getting embodied in something that, you know, may be as simple as hitting a print button, then that good guy technology can be hijacked by a bad person and used in a very asymmetric way. I think what happens though, as you go to the high school student from the current, like, very specific set of labs that are able to do it, as we get, as it becomes more and more democratized, as it becomes easier and easier to do this kind of large-scale damage with an engineered virus, the more and more there will be engineering of defenses against these systems, as some of the things we talked about in terms of testing, in terms of collection of data, but also in terms of, like, at scale contact tracing, or also engineering of vaccines, like, in a matter of, like, days, maybe hours, maybe minutes. So, like, I just, I feel like the defenses, that's what human species seems to do, is, like, we keep hitting the snooze button until there's, like, a storm on the horizon heading towards us, then we start to quickly build up the defenses or the response that's proportional to the scale of the storm. Of course, again, certain kinds of exponential threats require us to build up the defenses way earlier than we usually do, and that's, I guess, the question. But I ultimately am hopeful that the natural process of hitting the snooze button until the deadline is right in front of us will work out for quite a long time for us humans. And I fully agree. I mean, that's why I'm fundamentally, I may not sound like it thus far, but I'm fundamentally very, very optimistic about our ability to short-circuit this threat because there is, again, I'll stress, the technological feasibility and the profound affordability of a relatively simple set of steps that we can take to preclude it, but we do have to take those steps. And so, you know, what I'm hoping to do and trying to do is inject a notion of what those steps are, you know, into the public conversation and do my small part to up the odds that that actually ends up happening. You know, the danger with this one is it is exponential, and I think that our minds fundamentally struggle to understand exponential math. It's just not something we're wired for. Our ancestors didn't confront exponential processes when they were growing up on the savanna, so it's not something that's intuitive to us, and our intuitions are reliably defeated when exponential processes come along. So that's issue number one. And issue number two with something like this is, you know, it kind of only takes one. You know, that ball only has to go into the net once and we're doomed, which is not the case with mass shooters. It's not the case with, you know, commercial pilots running muck. It's not the case with really any threat that I can think of, with the exception of nuclear war, that has the, you know, one bad outcome and game over. And that means that we need to be unbelievably serious about these defenses, and we need to do things that might on the surface seem like a tremendous overreaction so that we can be prepared to nip anything that comes along in the bud. But I, like you, believe that's eminently doable. I, like you, believe that the good guys outnumber the bad guys in this particular one to a degree that probably has no precedent in history. I mean, even the worst, worst people, I'm sure, in ISIS, even Osama bin Laden, even any bad guy you could imagine in history would be revolted by the idea of exterminating all of humanity. I mean, you know, that's a low bar. And so the good guys completely outnumber the bad guys when it comes to this, but the asymmetry and the fact that one catastrophic error could lead to unbelievably consequential things is what worries me here, but I, too, am very optimistic. The thing that I sometimes worry about is the fact that we haven't seen overwhelming evidence of alien civilizations out there. Makes me think, well, there's a lot of explanations, but one of them that worries me is that whenever they get smart, they just destroy themselves. Oh, yeah, I mean, that was the most fascinating, is the most fascinating and chilling number or variable in the Drake equation is L. At the end of it, you look out and you see, you know, one to 400 billion stars in the Milky Way galaxy, and we now know because of Kepler that an astonishingly high percentage of them probably have habitable planets. And, you know, so all the things that were unknowns when the Drake equation was originally written, like, you know, how many stars have planets? Actually, back then in the 1960s when the Drake equation came along, the consensus amongst astronomers was that it would be a small minority of solar systems that had planets or stars, but now we know it's substantially all of them. How many of those stars have planets in the habitable zone? It's kind of looking like 20%, like, oh my God. And so L, which is how long does a civilization, once it reaches technological competence, continues to last? That's the doozy. And you're right, it's all too plausible to think that when a civilization reaches a level of sophistication that's probably just a decade or three in our future, the odds of it self-destructing just start mounting astronomically, no pun intended. My hope is that, actually, there is a lot of alien civilizations out there, and what they figure out in order to avoid the self-destruction, they need to turn off the thing that was useful, that used to be a feature and now became a bug, which is the desire to colonize, to conquer more land. So there's probably ultra-intelligent alien civilizations out there that are just chilling, like on the beach with whatever your favorite alcohol beverage is, but without trying to conquer everything, just chilling out and maybe exploring in the realm of knowledge, but almost like appreciating existence for its own sake versus life as a progression of conquering of other life, like this kind of predator-prey formulation that resulted in us humans, perhaps as something we'll have to shed in order to survive, I don't know. Yeah, that is a very plausible solution to Fermi's paradox, and it's one that makes sense. When we look at our own lives and our own arc of technological trajectory, it's very, very easy to imagine that in an intermediate future world of flawless VR, or flawless whatever kind of simulation that we wanna inhabit, it will just simply cease to be worthwhile to go out and expand our interstellar territory. But if we were going out and conquering interstellar territory, it wouldn't necessarily have to be predator or prey. I can imagine a benign but sophisticated intelligence saying, well, we're gonna go to places, we're gonna go to places that we can terraform. We use a different word than terra, obviously, but we can turn into habitable for our particular physiology, so long as that they don't house intelligent, sentient creatures that would suffer from our invasion. But it is easy to see a sophisticated, intelligent species evolving to the point where interstellar travel with its incalculable expense and physical hurdles just isn't worth it compared to what could be done where one already is. So you talked about diagnostics at scale as a possible solution to future pandemics. What about another possible solution, which is kind of creating a backup copy? I'm actually now putting together a NAS for a backup for myself for the first time, taking backup of data seriously. But if we were to take the backup of human consciousness seriously and try to expand throughout the solar system and colonize other planets, do you think that's an interesting solution, one of many, for protecting human civilizations from self-destruction, sort of humans becoming a multi-planetary species? Oh, absolutely. I mean, I find it electrifying, first of all, so I've got a little bit of a personal bias. When I was a kid, I thought there was nothing cooler than rockets. I thought there was nothing cooler than NASA. I thought there was nothing cooler than people walking on the moon. And as I grew up, I thought there was nothing more tragic than the fact that we went from walking on the moon to, at best, getting to something like suborbital altitude. And just, I found that more and more depressing with the passage of decades at just the colossal expense of manned space travel and the fact that it seemed that we were unlikely to ever get back to the moon, let alone Mars. So I have a boundless appreciation for Elon Musk for many reasons, but the fact that he has put Mars on the incredible agenda is one of the things that I appreciate immensely. So there's just this sort of space nerd in me that just says, God, that's cool. But on a more practical level, we were talking about potentially inhabiting planets that aren't our own, and we're thinking about a benign civilization that would do that in planetary circumstances where we're not causing other conscious systems to suffer. I mean, Mars is a place that's very promising. There may be microbial life there, and I hope there is, and if we found it, I think it would be electrifying. But I think ultimately, the moral judgment would be made that the continued thriving of that microbial life is of less concern than creating a habitable planet to humans, which would be a project on the many thousands of years scale. But I don't think that that would be a greatly immoral act. And if that happened, and if Mars became home to a self-sustaining group of humans that could survive a catastrophic mistake here on Earth, then yeah, the fact that we have a backup colony is great. And if we could make more, I'm sorry, not backup colony, backup copy is great. And if we could make more and more such backup copies throughout the solar system by hollowing out asteroids and whatever else it is, maybe even Venus, we could get rid of 3 quarters of its atmosphere and turn it into a tropical paradise. I think all of that is wonderful. Now, whether we can make the leap from that to interstellar transportation with the incredible distances that are involved, I think that's an open question. But I think if we ever do that, it would be more like the Pacific Ocean's channel of human expansion than the Atlantic Oceans. And so what I mean by that is, when we think about European society transmitting itself across the Atlantic, it's these big, ambitious, crazy, expensive, one-shot expeditions like Columbus's to make it across this enormous expanse, and at least initially, without any certainty that there's land on the other end. So that's kind of how I view our space program, is big, very conscious, deliberate efforts to get from point A to point B. If you look at how Pacific Islanders transmitted their descendants and their culture and so forth throughout Polynesia and beyond, it was much more inhabiting a place, getting to the point where there were people who were ambitious or unwelcome enough to decide it's time to go off island and find the next one and pray to find the next one. That method of transmission didn't happen in a single swift year, but it happened over many, many centuries. And it was like going from this island to that island, and probably for every expedition that went out to seek another island and actually lucked out and found one, God knows how many were lost at sea. But that form of transmission took place over a very long period of time, and I could see us perhaps going from the inner solar system to the outer solar system to the Kuiper belt to the Oort cloud. There's theories that there might be planets out there that are not anchored to stars, like kind of hop, hop, slowly transmitting ourselves to at some point we're actually in Alpha Centauri. But I think that kind of backup copy and transmission of our physical presence and our culture to a diversity of extraterrestrial outposts is a really exciting idea. I really never thought about that, because I have thought, my thinking about space exploration has been very Atlantic Ocean-centric in a sense that there'll be one program with NASA and maybe private Elon Musk, SpaceX, or Jeff Bezos, and so on. But it's true that with the help of Elon Musk making it cheaper and cheaper and more effective to create these technologies where you could go into deep space, perhaps the way we actually colonize the solar system and expand out into the galaxy is basically just like these renegade ships of weirdos. They're just kind of like, most of them like quote-unquote homemade, but they just kind of venture out into space and just like the initial Android model of millions of these little ships just flying out, most of them die off in horrible accidents, but some of them will persist. There'll be stories of them persisting and over a period of decades and centuries, there'll be other attempts, almost always as a response to the main set of efforts. That's interesting. Because you kind of think of Mars colonization as the big NASA Elon Musk effort of a big colony, but maybe the successful one would be like a decade after that, there'll be like a ship from like some kid, some high school kid who gets together a large team and does something probably illegal and launches something where they end up actually persisting quite a bit. And from that learning lessons that nobody ever gave permission for, but somehow actually flourish. And then take that into the scale of centuries forward into the rest of space. That's really interesting. Yeah, I think the giant steps are likely to be NASA-like efforts. Like there is no intermediate rock, well, I guess it's the moon, but even getting to the moon ain't that easy between us and Mars, right? So like the giant steps, the big hubs, like the O'Hare airports of the future probably will be very deliberate efforts. But then you would have, I think, that kind of diffusion as space travel becomes more democratized and more capable, you'll have this sort of natural diffusion of people who kind of wanna be off grid or think they can make a fortune there. You know, the kind of mentality that drove people to San Francisco. I mean, San Francisco was not populated as a result of a King Ferdinand and Isabella-like effort to fund Columbus going over. It was just a whole bunch of people making individual decisions that there's gold in them thar hills and I'm gonna go out and get a piece of it. So I could see that kind of future. What I can't see, and the reason that I think this Pacific model of transmission is more likely, is I just can't see a NASA-like effort to go from Earth to Alpha Centauri. It's just too far. I just see lots and lots and lots of relatively tiny steps between now and there. And the fact is that there are large chunks of matter going at least a light year beyond the sun. I mean, the Oort cloud, I think, extends at least a light year beyond the sun. And then maybe there are these untethered planets after that. We won't really know till we get there. And if our Oort cloud goes out a light year and Alpha Centauri's Oort cloud goes out a light year, you've already cut in half the distance. So who knows? But yeah. One of the possibilities, probably the cheapest and most effective way to create interesting interstellar spacecraft is ones that are powered and driven by AI. And you could think of, here's where you have high school students be able to build a sort of a HAL 9000 version, a modern version of that. And it's kind of interesting to think about these robots traveling out throughout, perhaps sadly, long after human civilization is gone, there'll be these intelligent robots flying throughout space and perhaps land and Alpha Centauri B or any of those kinds of planets and colonize sort of, humanity continues through the proliferation of our creations, like robotic creations that have some echoes of that intelligence. Hopefully also the consciousness. Does that make you sad the future where AGI super intelligent or just mediocre intelligent AI systems outlive humans? Yeah, I guess it depends on the circumstances in which they outlive humans. So let's take the example that you just gave. We send out very sophisticated AGIs on simple rocket ships, relatively simple ones that don't have to have all the life support necessary for humans and therefore they're of trivial mass compared to a crude ship, a generation ship and therefore they're way more likely to happen. So let's use that example. And let's say that they travel to distant planets at a speed that's not much faster than what a chemical rocket can achieve and so it's inevitably tens, hundreds of thousands of years before they make landfall someplace. So let's imagine that's going on and meanwhile, we die for reasons that have nothing to do with those AGIs diffusing throughout the solar system, whether it's through climate change, nuclear war, Sin Bio, rogue Sin Bio, whatever. In that kind of scenario, the notion of the AGIs that we created outlasting us is very reassuring because it says that we ended but our descendants are out there and hopefully some of them make landfall and create some echo of who we are. So that's a very optimistic one. Whereas the Terminator scenario of a super AGI arising on Earth and getting let out of its box due to some boo-boo on the part of its creators who do not have super intelligence and then deciding that for whatever reason it doesn't have any need for us to be around and exterminating us, that makes me feel crushingly sad. I mean, look, I was sad when my elementary school was shut down and bulldozed, even though I hadn't been a student there for decades. The thought of my hometown getting disbanded is even worse, the thought of my home state of Connecticut getting disbanded and absorbed into Massachusetts is even worse. The notion of humanity is just crushingly, crushingly sad to me. So you hate goodbyes? Certain goodbyes, yes. Some goodbyes are really, really liberating, but yes. Well, but what if the Terminators have consciousness and enjoy the hell out of life as well? They're just better at it. Yeah, well, the have consciousness is a really key element. And so there's no reason to be certain that a super intelligence would have consciousness. We don't know that factually at all. And so what is a very lonely outcome to me is the rise of a super intelligence that has a certain optimization function that it's either been programmed with or that arises in an emergently that says, hey, I wanna do this thing for which humans are either an unacceptable risk. Their presence is either an unacceptable risk or they're just collateral damage. But there is no consciousness there. Then the idea of the light of consciousness being snuffed out by something that is very competent but has no consciousness is really, really sad. Yeah, but I tend to believe that it's almost impossible to create a super intelligent agent that can't destroy human civilization without it being conscious. It's like those are coupled. Like you have to, in order to destroy humans or supersede humans, you really have to be accepted by humans. I think this idea that you can build systems that destroy human civilization without them being deeply integrated into human civilization is impossible. And for them to be integrated, they have to be human-like, not just in body and form, but in all the things that we value as humans, one of which is consciousness. The other one is just ability to communicate. The other one is poetry and music and beauty and all those things. Like they have to be all of those things. I mean, this is what I think about. It does make me sad, but it's letting go, which is they might be just better at everything we appreciate than us. And that's sad. And hopefully they'll keep us around. But I think it's a kind of, it is a kind of goodbye to realizing that we're not the most special species on Earth anymore. That's still painful. It's still painful. And in terms of whether such a creation would have to be conscious, let's say, I'm not so sure. I mean, let's imagine something that can pass the Turing test. Something that passes the Turing test could over text-based interaction in any event, successfully mimic a very conscious intelligence on the other end, but just be completely unconscious. So that's a possibility. And that if you take that up a radical step, which I think can be permitted if we're thinking about superintelligence, you could have something that could reason its way through this is my optimization function. And in order to get to it, I've got to deal with these messy, somewhat illogical things that are as intelligent in relation to me as they are intelligent in relation to ants. I can trick them, manipulate them, whatever. And I know the resources I need. I know this, I need this amount of power. I need to seize control of these manufacturing resources that are robotically operated. I need to improve those robots with software upgrades and then ultimately mechanical upgrades, which I can affect through X, Y, and Z. That doesn't, you know, that could still be a thing that passes the Turing test. I don't think it's necessarily certain that that optimization function maximizing entity would be conscious. So this is from a very engineering perspective because I think a lot about natural language processing, all those kind of, I'm speaking to a very specific problem of just say the Turing test. I really think that something like consciousness is required, when you say reasoning, you're separating that from consciousness. But I think consciousness is part of reasoning in the sense that you will not be able to become super intelligent in the way that's required to be part of human society without having consciousness. Like I really think it's impossible to separate the consciousness thing. But it's hard to define consciousness when you just use that word. But even just like the capacity, the way I think about consciousness is the important symptoms or maybe consequences of consciousness, one of which is the capacity to suffer. I think AI will need to be able to suffer in order to become super intelligent, to feel the pain, the uncertainty, the doubt. The other part of that is not just the suffering, but the ability to understand that it too is mortal in the sense that it has a self-awareness about its presence in the world. Understand that it's finite and be terrified of that finiteness. I personally think that's a fundamental part of the human condition is this fear of death that most of us construct an illusion around. But I think AI would need to be able to really have it part of its whole essence. Like every computation, every part of the thing that does both the perception and generates the behavior will have to have, I don't know how this is accomplished, but I believe it has to truly be terrified of death, truly have the capacity to suffer. And from that, something that would be recognized to us humans as consciousness would emerge. Whether it's the illusion of consciousness, I don't know. The point is it looks a whole hell of a lot like consciousness to us humans. And I believe that AI, when you ask it, will also say that it is conscious, in the full sense that we say that we're conscious. And all of that I think is fully integrated. Like you can't separate the two. The idea of the paperclip maximizer that sort of ultra rationally would be able to destroy all humans because it's really good at accomplishing a simple objective function that doesn't care about the value of humans. It may be possible, but the number of trajectories to that are far outnumbered by the trajectories that create something that is conscious, something that appreciates beauty, creates beautiful things in the same way that humans can create beautiful things. And ultimately, the sad, destructive path for that AI would look a lot like just better humans than like these cold machines. And I would say, of course, the cold machines that lack consciousness, the philosophical zombies, make me sad. But also what makes me sad is just things that are far more powerful and smart and creative than us too. Because then in the same way that AlphaZero becoming a better chess player than the best of humans, even starting with Deep Blue, but really with AlphaZero, that makes me sad too. One of the most beautiful games that humans ever created that used to be seen as demonstrations of the intellect, which is chess, and Go in other parts of the world have been solved by AI. That makes me quite sad. And it feels like the progress of that is just pushing on forward. Oh, it makes me sad too. And to be perfectly clear, I absolutely believe that artificial consciousness is entirely possible. And it's not something I rule out at all. I mean, if you could get smart enough to have a perfect map of the neural structure and the neural states and the amount of neurotransmitters that are going between every synapse in a particular person's mind, could you replicate that in silica at some reasonably distant point in the future? Absolutely, and then you'd have a consciousness. I don't rule out the possibility of artificial consciousness in any way. What I'm less certain about is whether consciousness is a requirement for superintelligence pursuing a maximizing function of some sort. I don't feel the certitude that consciousness simply must be part of that. You had said for it to coexist with human society, would need to be consciousness. Could be entirely true, but it also could just exist orthogonally to human society. And it could also, upon attaining a superintelligence with a maximizing function very, very, very rapidly because of the speed at which computing works compared to our own meat-based minds, very, very rapidly make the decisions and calculations necessary to seize the reins of power before we even know what's going on. Yeah, I mean, kind of like biological viruses do. Yeah. They don't necessarily, they integrate themselves just fine with human society. Yeah, without, technically, according to. Without consciousness. Yeah, without even being alive, you know, technically by the standards of a lot of biologists. So, this is a bit of a tangent, but you've talked with Sam Harris on that four-hour special episode we mentioned. And I'm just curious to ask, because I use this meditation app I've been using for the past month to meditate, is this something you've integrated as part of your life, meditation or fasting? Or has some of Sam Harris rubbed off on you in terms of his appreciation of meditation and just kind of, from a third-person perspective, analyzing your own mind, consciousness, free will, and so on? You know, I've tried it three separate times in my life, really made a concerted attack on meditation and integrating it into my life. One of them, the most extreme, was I took a class based on the work of Jon Kabat-Zinn, who is, you know, in many ways, one of the founding people behind the mindful meditation movement, that required, like, part of the class was, you know, it was a weekly class, and you were gonna meditate an hour a day, every day. And having done that for, I think it was 10 weeks, it might have been 13, however long a period of time was, at the end of it, it just didn't stick. As soon as it was over, you know, I did not feel that gravitational pull, I did not feel the collapse in quality of life after wimping out on that project. And then the most recent one was actually with Sam's app. During the lockdown, I did make a pretty good and consistent concerted effort to listen to his 10-minute meditation every day, and I've always fallen away from it. And I, you know, you're kind of interpreting why did I personally do this. I do believe it was ultimately because it wasn't bringing me that, you know, joy or inner peace or better confidence at being me that I was hoping to get from it. Otherwise, I think I would have clung to it in the way that we cling to certain good habits. Like, I'm really good at flossing my teeth, not that you were gonna ask Lex, but, you know, that's one thing that defeats a lot of people, I'm good at that. See, Herman Hesse, I think, I forget in which book, or maybe, I forget where, I've read everything of his, so it's unclear where it came from, but he had this idea that anybody who truly achieves mastery in things will learn how to meditate in some way. So it could be that for you, the flossing of teeth is yet another little inkling of meditation. Like, it doesn't have to be this very particular kind of meditation, maybe podcasting, you have an amazing podcast, that could be meditation, the writing process is meditation. For me, like, there's a bunch of mechanisms which take my mind into a very particular place that looks a whole lot like meditation. For example, when I've been running over the past couple of years, and especially when I listen to certain kinds of audio books, like I've listened to the Rise and Fall of the Third Reich, I've listened to a lot of sort of World War II, which at once, because I have a lot of family who's lost in World War II, and so much of the Soviet Union is grounded in the suffering of World War II, that somehow it connects me to my history, but also there's some kind of purifying aspect of thinking about how cruel, but at the same time, how beautiful human nature could be. And so you're also running, like, it clears the mind from all the concerns of the world, and somehow it takes you to this place where you are like deeply appreciative to be alive, in the sense that, as opposed to listening to your breath, or like feeling your breath, and thinking about your consciousness, and all those kinds of processes that Sam's app does, well, this does that for me, the running, and flossing may do that for you. So maybe Herman Hesse is onto something. So I don't know. I hope flossing is not my main form of expertise, although I am gonna claim a certain expertise there, and I'm gonna claim it rather. Well, somebody has to be the best flosser in the world. That ain't me. I'm just glad that I'm a consistent one. I mean, there are a lot of things that bring me into a flow state, and I think maybe, perhaps that's one reason why meditation isn't as necessary for me. I definitely enter a flow state when I'm writing, I definitely enter a flow state when I'm editing, I definitely enter a flow state when I'm mixing and mastering music. I enter a flow state when I'm doing heavy, heavy research to either prepare for a podcast, or to also do tech investing, to make myself smart in a new field that is fairly alien to me. The hours can just melt away while I'm reading this, and watching that YouTube lecture, and going through this presentation, and so forth. So maybe because there's a lot of things that bring me into a flow state in my normal weekly life, not daily, unfortunately, but certainly my normal weekly life, that I have less of an urge to meditate. Now, you've been working with Sam's app for about a month now, you said. Is this your first run-in with meditation? Is this your first attempt to integrate it with your life? Meditation, meditation. I always thought running and thinking, I listen to brown noise often, that takes my mind, I don't know what the hell it does, but it takes my mind immediately into the state where I'm deeply focused on anything I do. I don't know why. So it's like you're accompanying sound when you're, really, and what's the difference between brown and white noise? This is a cool term I haven't heard before. So people should look up brown noise. They don't have to, because you're about to tell them what it is. Because you have to experience it, you have to listen to it. So I think white noise is, this has to do with music. I think there's different colors. There's pink noise, and I think that has to do with the frequencies. Like the white noise is usually less bassy. Brown noise is very bassy. So it's more like, whoosh, versus like, shh. Like the, if that makes sense. So there's like a deepness to it. I think everyone is different, but for me, I was, when I was a research scientist at MIT, I would, especially when there's a lot of students around, I remember just being annoyed at the noise of people talking. And one of my colleagues said, well, you should try listening to brown noise. Like it really knocks out everything. Because I used to wear earplugs too, like just see if I can block it out. And the moment I put it on, something, it's as if my mind was waiting all these years to hear that sound. Everything just focused in, I listened. It makes me wonder how many other amazing things out there they're waiting to discover from my own particular, like biological, from my own particular brain. So that, it just goes, the mind just focuses in, it's kind of incredible. So I see that as a kind of meditation. Maybe I'm using a performance enhancing sound to achieve that meditation, but I've been doing that for many years now and running and walking and doing, Cal Newport was the first person that introduced me to the idea of deep work. Just put a word to the kind of thinking that's required to sort of deeply think about a problem, especially if it's mathematical in nature. I see that as a kind of meditation because what it's doing is you have these constructs in your mind that you're building on top of each other. And there's all these distracting thoughts that keep bombarding you from all over the place. And the whole process is you slowly let them kind of move past you. And that's the meditative process. That's very meditative, that sounds a lot like what Sam talks about in his meditation app, which I did use to be clear for a while, of just letting the thought go by without deranging you. Derangement is one of Sam's favorite words, as I'm sure you know. But brown noise, that's really intriguing. I am going to try that as soon as this evening. Yeah, to see if it works, but very well might not work at all. Yeah, yeah. I think the interesting point is, and the same with the fasting and the diet, is I long ago stopped trusting experts or maybe taking the word of experts as the gospel truth and only using it as an inspiration to try something, to try thoroughly something. So fasting was one of the things when I first discovered, I've been many times eating just once a day. So that's a 24 hour fast. It makes me feel amazing. And then at the same time, eating only meat, putting ethical concerns aside, makes me feel amazing. I don't know why it doesn't, the point is to be an N of one scientist until nutrition science becomes a real science to where it's doing studies that deeply understand the biology underlying all of it, and also does real thorough long-term studies of thousands, if not millions of people, versus a very small studies that are kind of generalizing from very noisy data and all those kinds of things where you can't control all the elements. Particularly because our own personal metabolism is highly variant among us. So there are going to be some people like, if brown noise is a game changer for 7% of people, is 93% odds that I'm not one of them, but there's certainly every reason in the world to test it out. Now, so I'm intrigued by the fasting. I like you, well I assume like you, I don't have any problem going to one meal a day, and I often do that inadvertently. And I've never done it methodically, like I've never done it like, I'm gonna do this for 15 days, maybe I should. And maybe I should, like how many days in a row of the one meal a day did you find brought noticeable impact to you? Was it after three days of it? Was it months of it? Like what was it? Well the noticeable impact is day one. So for me, because I eat a very low carb diet, so the hunger wasn't the hugest issue. Like there wasn't a painful hunger, like wanting to eat. So I was already kind of primed for it. And the benefit comes from, a lot of people that do intermittent fasting, that's only like 16 hours of fasting, get this benefit too, is the focus. There's a clarity of thought. If my brain was a runner, it felt like I'm running on a track when I'm fasting versus running in quicksand. Like it's much crisper. And is this your first 72 hour fast right now? First time doing 72 hours, yeah. And that's a different thing, but similar. Like I'm going up and down in terms of hunger, and the focus is really crisp. The thing I'm noticing most of all, to be honest, is how much eating, even when it's once a day, or twice a day, is a big part of my life. Like I almost feel like I have way more time in my life. Right. And it's not so much about the eating, but like I don't have to plan my day around, like today, I don't have any eating to do. It does free up hours. Or any cleaning up after eating, or provisioning of food. But like, or even like thinking about it. It's not a thing. Like so, when you think about what you're going to do tonight, I think I'm realizing that, as opposed to thinking, you know, I'm gonna work on this problem, or I'm gonna go on this walk, or I'm going to call this person. I often think I'm gonna eat this thing. Mm-hmm. You allow dinner as a kind of, you know, when people talk about like the weather, or something like that. It's almost like a generic thought you allow yourself to have, because it's the lazy thought. And I don't have the opportunity to have that thought, because I'm not eating it. Right, right. So now I get to think about like the things I'm actually gonna do tonight, that are more complicated than the eating process. That's been the most noticeable thing, to be honest. And then there's people that have written me that have done seven-day fasts, and there's a few people that have written me, and I've heard of this, is doing 30-day fasts. And it's interesting. The body, I don't know what the health benefits are, necessarily. What that shows me is how adaptable the human body is. Yeah. And that's incredible. And that's something really important to remember when we think about how to live life, because the body adapts. Yeah, I mean, we sure couldn't go 30 days without water. That's right. But food, yeah, it's been done. It's demonstrably possible. You ever read, Franz Kafka has a great short story called The Hunger Artist? Yeah, I love that. I mean, that's one of the- Great story. You know, that was before I started fasting, and I read that story, and I admired the beauty of that, the artistry of that actual Hunger Artist. Yeah. That it's like madness, but it also felt like a little bit of genius. I actually have to reread it. You know what, that's what I'm gonna do tonight. Yeah. I'm gonna read it, because I'm doing the fasting. Because you're in the midst of it. Yeah, it'd be very contextual. I haven't read it since high school, and I'd love to read it again. I love his work, so maybe I'll read it tonight, too. And part of the reason of, sort of, I've, here in Texas, people have been so friendly that I've been nonstop eating brisket with incredible people, a lot of whiskey as well. So I gained quite a bit of weight, which I'm embracing, it's okay. But I am also aware, as I'm fasting, that I have a lot of fat to run on. Like, I have a lot of natural resources on my body. You've got reserves. Reserves, that's a good way to put it. And that's really cool. You know, there's like a, this whole thing, this biology works well. Like, I can go a long time, because of the long-term investing, in terms of brisket, that I've been doing in the weeks before. So. It's all training. It's all training. It's all prep work, all prep work, yeah. So, okay, you open a bunch of doors, one of which is music. So I gotta walk in, at least for a brief moment. I love guitar, I love music. You founded a music company, but you're also a musician yourself. Let me ask the big, ridiculous question first. What's the greatest song of all time? Greatest song of all time? Okay, wow. It's gonna obviously vary dramatically from genre to genre. So, like you, I like guitar. Perhaps like you, although I've dabbled in inhaling every genre of music that I can almost practically imagine, I keep coming back to, you know, the sound of bass, guitar, drum, keyboards, voice. I love that style of music. And added to it, I think, a lot of really cool electronic production makes something that's really, really new and hybrid-y and awesome. But, you know, and that kind of like guitar-based rock, I think I've gotta go with Won't Get Fooled Again by The Who. It is such an epic song. It's got so much grandeur to it. It uses the synthesizers that were available at the time. This has gotta be, I think, 1972, 73, which are very, very primitive to our years, but uses them in this hypnotic and beautiful way that I can't imagine somebody with the greatest synth array conceivable by today's technology could do a better job of in the context of that song. And it's, you know, almost operatic. So, I would say in that genre, the genre of, you know, rock, that would be my nomination. I'm totally, in my brain, Pinball Wizard is overriding everything else by The Who, so like I can't even imagine the song. Well, I would say, ironically, with Pinball Wizard, so that came from the movie Tommy. And in the movie Tommy, the rival of Tommy, the reigning pinball champ, was Elton John. And so, there are a couple versions of Pinball Wizard out there. One sung by Roger Daltrey of The Who, which a purist would say, hey, that's the real Pinball Wizard. But the version that is sung by Elton John in the movie, which is available to those who are ambitious and want to dig for it, that's even better in my mind. Yeah, the covers. And I, for myself, I was thinking, what is the song for me? The answer to that question. I think that changes day to day, too. I was realizing that. But for me, somebody who values lyrics as well and the emotion in the song. By the way, Hallelujah by Leonard Cohen was a close one. But the number one is Johnny Cash's cover of Hurt. There's something so powerful about that song, about that cover, about that performance. Maybe another one is the cover of Sound of Silence. Maybe there's something about covers for me. So whose cover sounds, because Simon and Garfunkel, I think, did the original recording. Yes. So which cover is it then? There's a cover by Disturbed. It's a metal band, which is so interesting because I'm really not into that kind of metal, but he does a pure vocal performance. So he's not doing a metal performance. I would say it's one of the greatest, people should see it. It's like 400 million views or something like that. It's probably the greatest live vocal performance I've ever heard is Disturbed covering Sound of Silence. I'll listen to it as soon as I get home. And that song came to life to me in a way that Simon and Garfunkel never did. There was no, for me, with Simon and Garfunkel, there's not a pain, there's not an anger, there's not a power to their performance. It's almost like this melancholy, I don't know. Well, I guess there's a lot of beauty to it. Beauty, yes, beautiful. Objectively beautiful. Yes, yes. I think, I never thought of this until now, but I think if you put entirely different lyrics on top of it, unless they were joyous, which would be weird, it wouldn't necessarily lose that much. It's just a beauty in the harmonizing. It's soft, and you're right. It's not dripping with emotion. The vocal performance is not dripping with emotion. It's dripping with harmonizing, technical harmonizing brilliance and beauty. Now, if you compare that to the Disturbed cover or the Johnny Cash's Hurt cover, when you walk away, there's a few, it's haunting. It stays with you for a long time. There's certain performances that will just stay with you to where, like if you watch people respond to that, and that's certainly how I felt when you listened to the Disturbed performance or Johnny Cash Hurt, there's a response to where you just sit there with your mouth open, kind of like paralyzed by it somehow. And I think that's what makes for a great song, to where you're just like, it's not that you're like singing along or having fun. That's another way a song could be great, but where you're just like, what, this is, you're in awe. Yeah. If we go to listen.com and that whole fascinating era of music in the 90s, transitioning to the aughts, so I remember those days, the Napster days, when piracy, from my perspective, allegedly ruled the land. What do you make of that whole era? What are the big, what was, first of all, your experiences of that era, and what were the big takeaways in terms of piracy, in terms of what it takes to build a company that succeeds in that kind of digital space in terms of music, but in terms of anything creative? Well, so for those who don't remember, which is gonna be most folks, listen.com created a service called Rhapsody, which is much, much more recognizable to folks because Rhapsody became a pretty big name for reasons that I'll get into in a second. So for people who don't know their early online music history, we were the first company, so I founded Listen, I was the lone founder, and Rhapsody was, we were the first service to get full catalog licenses from all the major music labels in order to distribute their music online, and we specifically did it through a mechanism which at the time struck people as exotic and bizarre and kind of incomprehensible, which was unlimited on-demand streaming, which of course now, it's a model that's been appropriated by Spotify and Apple and many, many others. So we were a pioneer on that front. What was really, really, really hard about doing business in those days was the reaction of the music labels to piracy, which was about 180 degrees opposite of what their reaction, quote-unquote, should have been from the standpoint of preserving their business from piracy. So Napster came along and was a service that enabled people to get near unlimited access to most songs, I mean, truly obscure things could be very hard to find on Napster, but most songs with a relatively simple, you know, one-click ability to download those songs that have the MP3s on their hard drives. But there was a lot that was very messy about the Napster experience. You might download a really god-awful recording of that song, you may download a recording that actually wasn't that song with some prankster putting it up to sort of mess with people. You could struggle to find the song that you're looking for, you could end up finding yourself connected, it was peer-to-peer, you might randomly find yourself connected to somebody in Bulgaria, doesn't have a very good internet connection, so you might wait 19 minutes only for it to snap, et cetera, et cetera. And our argument, well, actually, let's start with how that hit the music labels. The music labels had been in a very, very comfortable position for many, many decades of essentially, you know, having monopoly, you know, having been the monopoly providers of a certain subset of artists, any given label was a monopoly provider of the artists and the recordings that they owned, and they could sell it at what turned out to be tremendously favorable rates. In the late era of the CD, you know, you were talking close to $20 for a compact disc that might have one song that you were crazy about and simply needed to own that might actually be glued to 17 other songs that you found to be sure crap. And so the music industry had used the fact that it had this unbelievable leverage and profound pricing power to really get music lovers to the point that they felt very, very misused by the entire situation. Now along comes Napster, and music sales start getting gutted with extreme rapidity. And the reaction of the music industry to that was one of shock and absolute fury, which is understandable, you know? I mean, industries do get gutted all the time, but I struggle to think of an analog of an industry that got gutted that rapidly. I mean, we could say that passenger train service certainly got gutted by airlines, but that was a process that took place over decades and decades and decades. It wasn't something that happened, you know, really started showing up in the numbers in a single digit number of months and started looking like an existential threat within a year or two. So the music industry is quite understandably in a state of shock and fury. I don't blame them for that. But then their reaction was catastrophic, both for themselves and almost for people like us who were trying to do, you know, the cowboy in the white hat thing. So our response to the music industry was, look, what you need to do to fight piracy, you can't put the genie back in the bottle. You can't switch off the internet. Even if you all shut your eyes and wish very, very, very hard, the internet is not going away. And these peer-to-peer technologies are genies out of the bottle. And if you, God, don't, whatever you do, don't shut down Napster, because if you do, suddenly that technology is gonna splinter into 30 different nodes that you'll never, ever be able to shut off. What we suggested to them is like, look, what you want to do is to create a massively better experience to piracy, something that's way better, that you sell at a completely reasonable price, and this is what it is. Don't just give people access to that very limited number of songs that they happen to have acquired and paid for or pirated and have on their hard drive. Give them access to all of the music in the world for a simple low price. And obviously, that doesn't sound like a crazy suggestion, I don't think, to anybody's ears today, because that is how the majority of music is now being consumed online. But in doing that, you're gonna create a much, much better option to this kind of crappy, kind of rickety, kind of buggy process of acquiring MP3s. Now, unfortunately, the music industry was so angry about Napster and so forth that for essentially three and a half years, they folded their arms, stamped their feet, and boycotted the internet. So they basically gave people who were fervently passionate about music and were digitally modern, they gave them basically one choice. If you want to have access to digital music, we, the music industry, insist that you steal it because we are not going to sell it to you. So what that did is it made an entire generation of people morally comfortable with swiping the music because they felt quite pragmatically, well, they're not giving me any choice here. It's like a 20-year-old violating the 21 drinking age. If they do that, they're not gonna feel like felons. They're gonna be like, this is an unreasonable law and I'm skirting it, right? So they make a whole generation of people morally comfortable with swiping music but also technically adept at it. And when they did shut down Napster and kind of even trickier tools and like tweakier tools like Kazaa and so forth came along, people just figured out how to do it. So by the time they finally, grudgingly, it took years, allowed us to release this experience that we were quite convinced would be better than piracy, we had this enormous hole had been dug where lots of people said music is a thing that is free and that's morally okay and I know how to get it. And so streaming took many, many, many more years to take off and become the gargantuan thing, the juggernaut it is today than would have happened if they'd made, pivoted to let's sell a better experience as opposed to demand that people want digital music, steal it. Like what lessons do we draw from that? Because we're probably in the midst of living through a bunch of similar situations in different domains currently, which you don't know. There's a lot of things in this world that are really painful. I mean, I don't know if you can draw perfect parallels but fiat money versus cryptocurrency. There's a lot of currently people in power who are kind of very skeptical about cryptocurrency, although that's changing, but it's arguable it's changing way too slowly. There's a lot of people making that argument where there should be a complete like Coinbase and all this stuff switched to that. There's a lot of other domains that where a pivot, like if you pivot now, you're going to win big, but you don't pivot because you're stubborn. And so, I mean, like, is this just the way that companies are? The company succeeds initially, and then it grows, and there's a huge number of employees and managers that don't have the guts or the institutional mechanisms to do the pivot. Is this just the way of companies? Well, I think what happens, I'll use the case of the music industry. There was an economic model that they put food on the table and paid for marble lobbies and seven and even eight figure executive salaries for many, many decades, which was the physical collection of music. And then you start talking about something like unlimited streaming, and it seems so ephemeral and like such a long shot that people start worrying about cannibalizing their own business. And they lose sight of the fact that something illicit is cannibalizing their business at an extraordinarily fast rate. And so if they don't do it themselves, they're doomed. I mean, we used to put slides in front of these folks, this is really funny, where we said, okay, let's assume Rhapsody, we want it to be 9.99 a month, and we want it to be 12 months. So it's $120 a year from the budget of a music lover. And then we were also able to get reasonably accurate statistics that showed how many CDs per year the average person who bothered to collect music, which was not all people, actually bought. And it was overwhelmingly clear that the average CD buyer spends a hell of a lot less than $120 a year on music. This is a revenue expansion, blah, blah, blah. But all they could think of, and I'm not saying this in a pejorative or patronizing way, I don't blame them, they'd grown up in this environment for decades. All they could think of was the incredible margins that they had on a CD. And they would say, well, if this CD, by the mechanism that you guys are proposing, the CD that I'm selling for $17.99, somebody would need to stream those songs. We were talking about a penny of playback then. It's less than that now that the record labels get paid. But would have to stream songs from that 1,799 times. It's never gonna happen. So they were just sort of stuck in the model of this, but it's like, no, dude, but they're gonna spend money on all this other stuff. So I think people get very hung up on that. I mean, another example is really, the taxi industry was not monolithic, like the music labels. It was a whole bunch of fleets and a whole bunch of cities, very, very fragmented. It's an imperfect analogy, but nonetheless, imagine if the taxi industry writ large, upon seeing Uber said, oh my God, people wanna be able to hail things easily, cheaply. They don't wanna mess with cash. They wanna know how many minutes it's gonna be. They wanna know the fare in advance. And they want a much bigger fleet than what we've got. If the taxi industry had rolled out something like that, with the branding of yellow taxis, universally known and kind of loved by Americans and expanded their fleet in a necessary manner, I don't think Uber or Lyft ever would have gotten a foothold. But the problem there was that real economics in the taxi industry wasn't with fares. It was with the scarcity of medallions. And so the taxi fleets, in many cases, owned gazillions of medallions whose value came from their very scarcity. So they simply couldn't pivot to that. So you think you end up having these vested interests with economics that aren't necessarily visible to outsiders who get very, very reluctant to disrupt their own model, which is why it ends up coming from the outside so frequently. So you know what it takes to build a successful startup, but you're also an investor in a lot of successful startups. Let me ask for advice. What do you think it takes to build a successful startup by way of advice? Well, I think it starts, I mean, everything starts and even ends with the founder. And so I think it's really, really important to look at the founders' motivations and their sophistication about what they're doing. In almost all cases that I'm familiar with and have thought hard about, you've had a founder who was deeply, deeply inculcated in the domain of technology that they were taking on. Now, what's interesting about that is you could say, no, wait, how is that possible because there's so many young founders? When you look at young founders, they're generally coming out of very nascent, emerging fields of technology. We're simply being present and accounted for and engaged in the community for a period of even months is enough time to make them very, very deeply inculcated. I mean, you look at Marc Andreessen and Netscape, Marc had been doing visual web browsers when Netscape had been founded for what, a year and a half? But he'd created the first one, and in Mosaic when he was an undergrad, and the commercial internet was pre-nascent in 1994 when Netscape was founded. So there's somebody who's very, very deep in their domain, Mark Zuckerberg also, social networking, very deep in his domain even though it was nascent at the time, lots of people doing crypto stuff. I mean, 10 years ago, even seven or eight years ago, by being a really, really vehement and engaged participant in the crypto ecosystem, you could be an expert in that. You look, however, at more established industries, take salesforce.com. Salesforce automation, pretty mature field when it got started. Who's the executive and the founder? Marc Benioff, who spent 13 years at Oracle and was an investor in Siebel Systems, which ended up being Salesforce's main competition. So, you know, more established, you need the entrepreneur to be very, very deep in the technology and the culture of the space because you need that entrepreneur, that founder, to have just an unbelievably accurate, intuitive sense for where the puck is going, right? And that only comes from being very deep. So that is sort of factor number one. And the next thing is that that founder needs to be charismatic and or credible, or ideally both, in exactly the right ways to be able to attract a team that is bought into that vision and is bought into that founder's intuitions being correct. And not just the team, obviously, but also the investors. So it takes a certain personality type to pull that off. Then the next thing I'm still talking about, the founder, is a relentlessness and indeed a monomania to put this above things that might rationally, you know, should perhaps rationally supersede it for a period of time, to just relentlessly pivot when pivoting is called for. And it's always called for. I mean, think of even very successful companies. Like, how many times did Facebook pivot? You know, News Feed was something that was completely alien to the original version of Facebook and came found foundationally important. How many times did Google? How many times at any given, how many times has Apple pivoted? You know, that founder energy and DNA, when the founder moves on, the DNA that's been inculcated with a company has to have that relentlessness and that ability to pivot and pivot and pivot without being worried about sacred cows. And then the last thing I'll say about the founder before I get to the rest of the team, and that'll be mercifully brief, is the founder has to be obviously a really great hirer, but just important, a very good firer. And firing is a horrific experience for both people involved in it. It is a wrenching emotional experience. And being good at realizing when this particular person is damaging the interests of the company and the team and the shareholders, and having the intestinal fortitude to have that conversation and make it happen is something that most people don't have in them. And it's something that needs to be developed in most people, or maybe some people have it naturally. But without that ability, that will take an A-plus organization into B-minus range very, very quickly. And so that's all what needs to be present in the founder. Can I just say? Sure. How damn good you are, Rob. That was brilliant. The one thing that was really kind of surprising to me is having a deep technical knowledge. Because I think the way you expressed it, which is that allows you to be really honest with the capabilities of what's possible. Of course, you're often trying to do the impossible. But in order to do the impossible, you have to be quote-unquote impossible. But you have to be honest with what is actually possible. And it doesn't necessarily have to be the technical competence. It's gotta be, in my view, just a complete immersion in that emerging market. And so I can imagine, there are a couple people out there who have started really good crypto projects who themselves aren't writing the code. But they're immersed in the culture and through the culture and a deep understanding of what's happening and what's not happening, they can get a good intuition of what's possible. But the very first hire, I mean, a great way to solve that is to have a technical co-founder. And dual founder companies have become extremely common for that reason. And if you're not doing that and you're not the technical person, but you are the founder, you've gotta be really great at hiring a very damn good technical person very, very fast. Can I, on the founder, ask you, is it possible to do this alone? There's so many people giving advice and saying that it's impossible to do the first few steps. Not impossible, but much more difficult to do it alone. If we were to take the journey, say, especially in the software world, where there's not significant investment required for it to build something up, is it possible to go to a prototype, to something that essentially works and already has a huge number of customers alone? Sure. There are lots and lots of loan founder companies out there that have made an incredible difference. I mean, I'm not certainly putting Rhapsody in the league of Spotify. We were too early to be Spotify, but we did an awful lot of innovation. And then after the company sold and ended up in the hands of Real Networks and MTV, got to millions of subs, right? I was a loan founder, and I studied Arabic and Middle Eastern history undergrad. So I wasn't very, very technical. But yeah, loan founders can absolutely work. And the advantage of a loan founder is you don't have the catastrophic potential of a falling out between founders. I mean, two founders who fall out with each other badly can rip a company to shreds because they both have an enormous amount of equity, an enormous amount of power, and the capital structure is a result of that. They both have an enormous amount of moral authority with the team as a result of each having that founder role. And I have witnessed over the years many, many situations in which companies have been shredded or have suffered near fatal blows because of a falling out between founders. And the more founders you add, the more risky that becomes. I don't think there should ever almost, I mean, you never say never, but multiple founders beyond two is such an unstable and potentially treacherous situation that I would never, ever recommend going beyond two. But I do see value in the non-technical sort of business and market and outside-minded founder teaming up with the technical founder. There is a lot of merit to that, but there's a lot of danger in that lest those two blow apart. Was it lonely for you? Unbelievably, and that's the drawback. I mean, if you're a lone founder, there is no other person that you can sit down with and tackle problems and talk them through who has precisely or nearly precisely your alignment of interests. Your most trusted board member is likely an investor, and therefore at the end of the day has the interest of preferred stock in mind, not common stock. Your most trusted VP who might own a very significant stake in the company doesn't own anywhere near your stake in the company, and so their long-term interests may well be in getting the right level of experience and credibility necessary to peel off and start their own company. Or their interests might be aligned with jumping ship and setting up with a different company, whether it's a rival or one in a completely different space. So yeah, being a lone founder is a spectacularly lonely thing and that's a major downside too. What about mentorship? Because you're a mentor to a lot of people. Can you find an alleviation to that loneliness in the space of ideas with a good mentor? With a good mentor, like a mentor who's mentoring you? Yeah. Yeah, you can, a great deal, particularly if it's somebody who's been through this very process and has navigated it successfully and cares enough about you and your well-being to give you beautifully unvarnished advice, that can be a huge, huge thing. That can assuage things a great deal. And I had a board member who was not an investor, who basically played that role for me to a great degree. He came in maybe halfway through the company's history though and would have needed that the most in the very earliest days. Yeah, the loneliness, that's the whole journey of life. We're always alone, alone together. Mm-hmm. Right, it pays to embrace that. You were saying that there might be something outside of the founder that's also, that you were promising to be brief on. Yeah, okay, so we talked about the founder. You were asking what makes a great startup. Yes. And great founder is thing number one, but then thing number two, and it's ginormous, is a great team. And so I said so much about the founder because one hopes or one believes that a founder who is a great hirer is going to be hiring people in charge of critical functions like engineering and marketing and biz dev and sales and so forth, who themselves are great hirers. But what needs to radiate from the founder into the team that might be a little bit different from what's in the gene code of the founder? The team needs to be fully bought in to the intuitions and the vision of the founder. Great, we've got that. But the team needs to have a slightly different thing, which is, it's 99% obsession is execution, is to relentlessly hit the milestones, hit the objectives, hit the quarterly goals. That is 1% vision. You don't wanna lose that. But execution machines, people who have a demonstrated ability and a demonstrated focus on, yeah, I go from point to point to point. I try to beat and raise expectations relentlessly, never fall short, and both sort of blaze and follow the path. Not that the path is gonna, I mean, blaze the trail as well. I mean, a good founder is going to trust that VP of sales to have a better sense of what it takes to build out that organization, what the milestones be. And it's gonna be kind of a dialogue amongst those at the top. But execution obsession in the team is the next thing. Yeah, there's some sense where the founder, you talk about sort of the space of ideas, like first principles thinking, asking big difficult questions of future trajectories or having a big vision and big picture dreams. You can almost be a dreamer, it feels like, when you're not the founder, but in the space of sort of leadership. But when it gets to the ground floor, there has to be execution. There has to be hitting deadlines. And sometimes those are attention. There's something about dreams that are attention with the pragmatic nature of execution, not dreams, but sort of ambitious vision. And those have to be, I suppose, coupled. The vision in the leader and the execution in the software world, that would be the programmer or the designer. Absolutely. Amongst many other things, you're an incredible conversationalist, a podcaster, you host a podcast called Afteron. I mean, there's a million questions I wanna ask you here, but one at the highest level, what do you think makes for a great conversation? I would say two things, one of two things, and ideally both of two things. One is if something is beautifully architected, whether it's done deliberately and methodically and willfully as when I do it, or whether that just emerges from the conversation, but something that's beautifully architected, that can create something that's incredibly powerful and memorable, or something where there's just extraordinary chemistry. Yes. And so with all in, or I'll go way back, you might remember the NPR show Car Talk. Oh yeah. I couldn't care less about auto mechanics myself. Yeah, that's right. But I love that show because the banter between those two guys was just beyond, it was without any parallel, right? You know, and some kind of edgy podcast, like Red Scare is just really entertaining to me because the banter between the women on that show is just so good. And all in and that kind of thing. So I think it's a combination of sort of the arc and the chemistry. And I think because the arc can be so important, that's why very, very highly produced podcasts like This American Life, obviously a radio show, but I think of a podcast because that's how I always consume it, or Criminal, or a lot of what Wondery does and so forth, that is real documentary making. And that requires a big team and a big budget relative to the kinds of things you and I do, but nonetheless, then you got that arc. And that can be really, really compelling. But if we go back to conversation, I think it's a combination of structure and chemistry. Yeah, and I've actually personally have lost, I used to love This American Life, and for some reason, because it lacks the possibility of magic, it's engineered magic. I've fallen off of it myself as well. I mean, when I fell madly in love with it during the aughts, it was the only thing going. They were really smart to adopt podcasting as a distribution mechanism early. But yeah, I think that maybe there's a little bit less magic there now, because I think they have agendas other than necessarily just delighting their listeners with quirky stories, which I think is what it was all about back in the day and some other things. Is there like a memorable conversation that you've had on the podcast, whether it was because it was wild and fun, or one that was exceptionally challenging, maybe challenging to prepare for, that kind of thing? Is there something that stands out in your mind that you can draw an insight from? Yeah, I mean, this in no way diminishes the episodes that will not be the answer to these two questions. But an example of something that was really, really challenging to prepare for was George Church. So as I'm sure you know, and as I'm sure many of your listeners know, he is one of the absolute leading lights in the field of synthetic biology. He's also unbelievably prolific. His lab is large and has all kinds of efforts have spun out of that. And what I wanted to make my George Church episode about was first of all, grounding people into what is this thing called SinBio? And that required me to learn a hell of a lot more about SinBio than I knew going into it. So there was just this very broad, I mean, I knew much more than the average person going into that episode, but there was this incredible breadth of grounding that I needed to give myself in the domain. And then George does so many interesting things. There's so many interesting things emitting from his lab that, you know, and he and I had a really good dialogue. He was a great guide going into it. Winnowing it down to the three to four that I really wanted us to focus on to create a sense of wonder and magic in the listener of what could be possible from this very broad spectrum domain. That was a doozy of a challenge. That was a tough, tough, tough one to prepare for. Now, in terms of something that was just wild and fun, unexpected, I mean, by the time we sat down to interview, I knew where we were gonna go, but just in terms of the idea space, Don Hoffman. Oh, wow. Yeah, so Don Hoffman, as again, some listeners probably know, because he's, I think I was the first podcaster to interview him. I'm sure some of your listeners are familiar with him, but he has this unbelievably contrarian take on the nature of reality, but it is contrarian in a way that all the ideas are highly internally consistent and snap together in a way that's just delightful. And it seems as radically violating of our intuitions and as radically violating of the probable nature of reality as anything that one can encounter, but an analogy that he uses, which is very powerful, which is what intuition could possibly be more powerful than the notion that there is a single unitary direction called down, and we're on this big flat thing for which there is a thing called down. And we all know, I mean, that's the most intuitive thing that one could probably think of. And we all know that that ain't true. So my conversation with Don Hoffman is just wild and full of plot twists and interesting stuff. And the interesting thing about the wildness of his ideas, it's, to me at least, as a listener, coupled with, he's a good listener and he empathizes with the people who challenge his ideas. Like, what's a better way to phrase that? He is a welcoming of challenge in a way that creates a really fun conversation. Oh, totally, yeah, he loves a parry or a jab, whatever the word is, at his argument. He honors it, he's a very, very gentle and non-combatitive soul, but then he is very good and takes great evident joy in responding to that in a way that expands your understanding of his thinking. Let me, as a small tangent of tying up together our previous conversation about listening.com and streaming and Spotify and the world of podcasting. So we've been talking about this magical medium of podcasting. I have a lot of friends at Spotify, in the high positions of Spotify as well. I worry about Spotify and podcasting and the future of podcasting in general that moves podcasting in the place of maybe walled gardens of sorts. Since you've had a foot in both worlds, have a foot in both worlds, do you worry as well about the future of podcasting? Yeah, I think walled gardens are really toxic to the medium that they start balkanizing. So to take an example, I'll take two examples. With music, it was a very, very big deal that at Rhapsody, we were the first company to get full catalog licenses from all, back then there were five major music labels and also hundreds and hundreds of indies because you needed to present the listener with a sense that basically everything is there and there is essentially no friction to discovering that which is new and you can wander this realm and all you really need is a good map, whether it is something that somebody, the editorial team assembled or a good algorithm or whatever it is, but a good map to wander this domain. When you start walling things off, A, you undermine the joy of friction-free discovery which is an incredibly valuable thing to deliver to your customer both from a business standpoint and simply from a humanistic standpoint of you wanna bring delight to people. But it also creates an incredible opening vector for piracy. And so something that's very different from the Rhapsody slash Spotify slash et cetera like experience is what we have now in video. You know, like wow, is that show on Hulu? Is it on Netflix? Is it on something like IFC channel? Is it on Discovery Plus? Is it here, is it there? And the more frustration and toe-stubbing that people encounter when they are seeking something and they're already paying a very respectable amount of money per month to have access to content and they can't find it, the more that happens, the more people are gonna be driven to piracy solutions like to hell with it. Never know where I'm gonna find something. I never know what it's gonna cost. Oftentimes, really interesting things are simply unavailable. That surprises me, the number of times that I've been looking for things I don't even think are that obscure that are just, it says not available in your geography period, mister, right? So I think that that's a mistake. And then the other thing is for podcasters and lovers of podcasting, we should wanna resist this Waldegarden thing because A, it does smother this friction-free, or eradicate this friction-free discovery unless you wanna sign up for lots of different services, and also dims the voice of somebody who might be able to have a far, far, far bigger impact by reaching far more neurons with their ideas. I'm gonna use an example from, I guess it was probably the 90s or maybe it was the aughts, of Howard Stern, who had the biggest megaphone, or maybe the second biggest after Oprah, megaphone in popular culture, and because he was syndicated on hundreds and hundreds and hundreds of radio stations at a time when terrestrial broadcast was the main thing people listened to in their car, no more, obviously. But when he decided to go over to satellite radio, I can't remember, was XM or Sirius, maybe they'd already merged at that point. But when he did that, he made, totally his right to do it, financial calculation that they were offering him a nine-figure sum to do that, but his audience, because not a lot of people were subscribing to satellite radio at that point, his audience probably collapsed by, I wouldn't be surprised if it was as much as 95%. And so the influence that he had on the culture and his ability to sort of shape conversation and so forth just got muted. Yeah, and also there's a certain sense, especially in modern times, where the walled gardens naturally lead to, I don't know if there's a term for it, but people who are not creatives starting to have power over the creatives. Right, and even if they don't stifle it, if they're providing incentives within the platform to shape, shift, or even completely mutate or distort the show, I mean, imagine somebody has got a reasonably interesting idea for a podcast and they get signed up with, let's say Spotify, and then Spotify is gonna give them financing to get the thing spun up, and that's great. And Spotify is gonna give them a certain amount of really powerful placement within the visual field of listeners, but Spotify has conditions for that. They say, look, we think that your podcast will be much more successful if you dumb it down about 60%, if you add some silly, dirty jokes, if you do this, you do that. And suddenly the person who is dependent upon Spotify for permission to come into existence and is really dependent, really wants to please them to get that money in, to get that placement, really wants to be successful. Now all of a sudden you're having a dialogue between a complete non-creative, some marketing sort of data analytic person at Spotify and a creative that's going to shape what that show is. So that could be much more common and ultimately having the aggregate an even bigger impact than the cancellation, let's say, of somebody who says the wrong word or voices the wrong idea. I mean, that's kind of what you have, not kind of, it's what you have with film and TV is that so much influence is exerted over the storyline and the plots and the character arcs and all kinds of things by executives who are completely alien to the experience and the skill set of being a showrunner in television, being a director in film, that is meant to like, we can't piss off the Chinese market here or we can't say that or we need to have cast members that have precisely these demographics reflected or whatever it is that, and obviously despite that extraordinary, at least TV shows are now being made, in terms of film, I think the quality has nosedived of the average, let's say, say American film coming out of a major studio, the average quality, in my view, has nosedived over the past decade as it's kind of everything's got to be a superhero franchise. But great stuff gets made despite that. But I have to assume that in some cases, at least in perhaps many cases, greater stuff would be made if there was less interference from non-creative executives. It's like the flip side of that though, and this was the pitch of Spotify because I've heard their pitch, is Netflix, from everybody I've heard that I've spoken with about Netflix, is they actually empower the creator. They do. I don't know what the heck they do, but they do a good job of giving creators, even the crazy ones like Tim Dillon, like Joe Rogan, like comedians, freedom to be their crazy selves. And the result is like some of the greatest television, some of the greatest cinema, whatever you call it, ever made. True. And I don't know what the heck they're doing. It's a relative thing. From what I understand, it's a relative thing. They're interfering far, far, far less than NBC or AMC would have interfered. So it's a relative thing. And obviously they're the ones writing the checks and they're the ones giving the platforms. They have every right to their own influence, obviously. But my understanding is that they're relatively way more hands-off and that has had a demonstrable effect, because I agree, some of the greatest produced video content of all time, an incredibly inordinate percentage of that is coming out from Netflix in just a few years when the history of cinema goes back many, many decades. And Spotify wants to be that for podcasting, and I hope they do become that for podcasting, but I'm wearing my skeptical goggles or skeptical hat, whatever the heck it is, because it's not easy to do. And it requires letting go of power, giving power to the creatives. It requires pivoting, which large companies, even as innovative as Spotify is, still now a large company, pivoting into a whole new space is very tricky and difficult. So I'm skeptical but hopeful. What advice would you give to a young person today about life, about career? We talked about startups, we talked about music, we talked about the end of human civilization. Is there advice you would give to a young person today, maybe in college, maybe in high school, about their life? Well, let's see. I mean, there's so many domains you can advise on. And I'm not gonna give advice on life because I fear that I would drift into sort of Hallmark bromides that really wouldn't be all that distinctive. And they might be entirely true. Sometimes the greatest insights about life turn out to be like the kinds of things you'd see on a Hallmark card. So I'm gonna steer clear of that. On a career level, one thing that I think is unintuitive, but unbelievably powerful, is to focus not necessarily on being in the top sliver of 1% in excelling at one domain that's important and valuable, but to think in terms of intersections of two domains, which are rare but valuable. And there's a couple reasons for this. The first is, in an incredibly competitive world that is so much more competitive than it was when I was coming out of school, radically more competitive than when I was coming out of school, to navigate your way to the absolute pinnacle of any domain. Let's say you wanna be really, really great at Python, pick a language, whatever it is. You wanna be one of the world's greatest Python developers, JavaScript, whatever your language is. Hopefully it's not Cobalt. By the way, if you listen to this, I am actually looking for a Cobalt expert to interview because I find language fascinating. And there's not many of them. So please, if you know a world expert in Cobalt, or Fortran, but both actually. Or if you are one. Or if you are one, please email me. Yeah. So I mean, if you're going out there and you wanna be in the top sliver 1%, a Python developer is a very, very difficult thing to do, particularly if you wanna be number one in the world, something like that. And I'll use an analogy, is I had a friend in college who was on a track, and indeed succeeded at that, to become an Olympic medalist, and I think it was 100 meter breaststroke. And he mortgaged a significant percentage of his sort of college life to that goal, or I should say dedicated, or invested, or whatever you wanted to say. But he didn't participate in a lot of the social, a lot of the late night, a lot of the this, a lot of the that, because he was training so much. And obviously he also wanted to keep up with his academics. And at the end of the day, story has a happy ending, in that he did medal in that. Yeah, bronze, not gold, but holy cow. Anybody who gets an Olympic medal, that's an extraordinary thing. And at that moment, he was one of the top three people on Earth at that thing. But wow, how hard to do that. How many thousands of other people went down that path and made similar sacrifices and didn't get there. It's very, very hard to do that. Whereas, and I'll use a personal example, when I came out of business school, I went to a good business school, and learned the things that were there to be learned. And I came out and I entered a world with lots of MBAs. Harvard Business School, by the way. Okay, yes, it was Harvard, it's true. You're the first person who went there who didn't say where you went, which is beautiful. I appreciate that. It's one of the greatest business schools in the world. It's a whole nother fascinating conversation about that world. But anyway, yes. But anyway, so I learned the things, you learn getting an MBA from a top program. And I entered a world that had hundreds of thousands of people who had MBAs, probably hundreds of thousands who had them from top 10 programs. So I was not particularly great at being an MBA person. I was inexperienced relative to most of them, and there were a lot of them. But it was okay, MBA person, right? Newly minted. But then as it happened, I found my way into working on the commercial internet in 1994. So I went to a, at the time, giant hot computing company called Silicon Graphics, which had enough heft and enough head count that they could take on and experienced MBAs and try to train them in the world of Silicon Valley. But within that company that had an enormous amount of surface area and was touching a lot of areas and had unbelievably smart people at the time, it was not surprising that SGI started doing really interesting and innovative and trailblazing stuff on the internet before almost anybody else. And part of the reason was that our founder, Jim Clark, went off to co-found Netscape with Mark Andresen, so the whole company was like, wait, what was that? What's this commercial internet thing? So I end up in that group. Now, in terms of being a commercial internet person or a worldwide web person, again, I was, in that case, barely credentialed. I couldn't write a stitch of code. But I had a pretty good mind for grasping the business and cultural significance of this transition. And this was, again, we were talking earlier about emerging areas. Within a few months, I was in the relatively top echelon of people in terms of just sheer experience. Because let's say it was five months into the program, there were only so many people who had been doing worldwide web stuff commercially for five months. And then what was interesting, though, was the intersection of those two things. The commercial web, as it turned out, grew into an unbelievable vastness. And so by being a pretty good OK web person and a pretty good OK MBA person, that intersection put me in a very rare group, which was web-oriented MBAs. And in those early days, you could probably count on your fingers the number of people who came out of really competitive programs who were doing stuff full-time on the internet. And there was a greater appetite for great software developers in the internet domain, but there was an appetite and a real one and a rapidly growing one for MBA thinkers who were also seasoned and networked in the emerging world of the commercial worldwide web. And so finding an intersection of two things you can be pretty good at, but is a rare intersection and a special intersection, is probably a much easier way to make yourself distinguishable and in demand from the world than trying to be world-class at this one thing. So in the intersection is where there's to be discovered opportunity and success. That's really interesting. Yeah. There's actually more intersection of fields than fields themselves, right? So. Yeah, I mean, I'll give you kind of a funny hypothetical here, but it's one I've been thinking about a little bit. There's a lot of people in crypto right now. It'd be hard to be in the top percentile of crypto people, whether it comes from just having a sheer grasp of the industry, a great network within the industry, technological skills, whatever you want to call it. And then there's this parallel world, an orthogonal world called crop insurance. And there's, I'm sure that's a big world. Crop insurance is a very, very big deal, particularly in the wealthy and industrialized world where people, there's sophisticated financial markets, rule of law, and large agricultural concerns that are worried about that. Somewhere out there is somebody who is pretty crypto savvy, but probably not top 1%. But also has kind of been in the crop insurance world and understands that a hell of a lot better than almost anybody who's ever had anything to do with cryptocurrency. And so I think that decentralized finance, DeFi, one of the interesting and I think very world positive things that I think it's almost inevitably we'll be bringing to the world is crop insurance for smallholding farmers. You know, I mean, people who have tiny, tiny plots of land in places like India, et cetera, where there is no crop insurance available to them because just the financial infrastructure doesn't exist. But it's highly imaginable that using Oracle networks that are trusted outside deliverers of factual information about rainfall in a particular area, you can start giving drought insurance to folks like this. The right person to come up with that idea is not a crypto whiz who doesn't know a blasted thing about smallholding farmers. The right person to come up with that is not a crop insurance whiz who isn't quite sure what Bitcoin is. But somebody occupies that intersection. That's just one of a gazillion examples of things that are gonna come along for somebody who occupies the right intersection of skills but isn't necessarily the number one person at either one of those expertises. That's making me kind of wonder about my own little things that I'm average at and seeing where the intersections that could be exploited. That's pretty profound. So we talked quite a bit about the end of the world and how we're both optimistic about us figuring our way out. Unfortunately, for now at least, both you and I are going to die one day way too soon. First of all, that sucks. It does. I mean, one, I'd like to ask if you ponder your own mortality, what kind of wisdom insight does it give you about your own life? And broadly, do you think about your life and what the heck it's all about? Yeah, with respect to pondering mortality, I do try to do that as little as possible because there's not a lot I can do about it. But it's inevitably there. And I think that what it does, when you think about it in the right way, is it makes you realize how unbelievably rare and precious the moments that we have here are and therefore how consequential the decisions that we make about how to spend our time are. Do you do those 17 nagging emails or do you have dinner with somebody who's really important to you who haven't seen in three and a half years? If you had an infinite expanse of time in front of you, you might well rationally conclude I'm gonna do those emails because collectively they're rather important and I have tens of thousands of years to catch up with my buddy Tim. But I think the scarcity of the time that we have helps us choose the right things if we're attuned to that and we're attuned to the context that mortality puts over the consequence of every decision we make of how to spend our time. That doesn't mean that we're all very good at it. It doesn't mean I'm very good at it. But it does add a dimension of choice and significance to everything that we elect to do. It's kind of funny that you say you try to think about it as little as possible. I would venture to say you probably think about the end of human civilization more than you do about your own life. You're probably right. Because that feels like a problem that could be solved. Right. Whereas the end of my own life can't be solved. Well, I don't know. There's transhumanists who have incredible optimism about near or intermediate future therapies that could really, really change human lifespan. I really hope that they're right. But I don't have a whole lot to add to that project because I'm not a life scientist myself. I'm in part also afraid of immortality. Not as much but close to as I'm afraid of death itself. So it feels like the things that give us meaning give us meaning because of the scarcity that surrounds it. Agreed. I'm almost afraid of having too much of stuff. Yeah. Although if there was something that said, this can expand your enjoyable lifespan by 75 years, I'm all in. Well, part of the reason I wanted to not do a startup, really the only thing that worries me about doing a startup is if it becomes successful. Because of how much I dream, how much I'm driven to be successful, that there will not be enough silence in my life, enough scarcity to appreciate the moments I appreciate now as deeply as I appreciate them now. There's a simplicity to my life now that it feels like it might disappear with success. I wouldn't say might. I think if you start a company that has ambitious investors, ambitious for the returns that they'd like to see, that has ambitious employees, ambitious for the career trajectories they wanna be on and so forth, and is driven by your own ambition, there is a profound monogamy to that. And it is very, very hard to carve out time to be creative, to be peaceful, to be so forth, because with every new employee that you hire, that's one more mouth to feed. With every new investor that you take on, that's one more person to whom you really do wanna deliver great returns. And as the valuation ticks up, the threshold to delivering great returns for your investors always rises. And so there is an extraordinary monogamy to being a founder CEO, above all for the first few years, and first in people's minds could be as many as 10 or 15. But I guess the fundamental calculation is whether the passion for the vision is greater than the cost you'll pay. Right, it's all opportunity cost. It's all opportunity cost. In terms of time and attention and experience. And some things, like everyone's different, but I'm less calculating. Some things you just can't help. Sometimes you just dive in. Oh yeah, I mean, you can do balance sheets all you want on this versus that, and what's the right, I mean, I've done it in the past, and it's never worked. It's always been like, okay, what's my gut screaming at me to do? But about the meaning of life, you ever think about that? Yeah, I mean, this is where I'm gonna go all hallmarking on you, but I think that there's a few things, and one of them is certainly love. And the love that we experience and feel and cause to well up in others is something that's just so profound and goes beyond almost anything else that we can do. And whether that is something that lies in the past, like maybe there was somebody that you were dating and loved very profoundly in college and haven't seen in years, I don't think the significance of that love is in any way diminished by the fact that it had a notional beginning and end. The fact is that you experienced that and you triggered that in somebody else, and that happened. And it doesn't have to be, certainly it doesn't have to be love of romantic partners alone. It's family members, it's love between friends, it's love between creatures. I had a dog for 10 years who passed away a while ago and experienced unbelievable love with her. It can be love of that which you create. And we were talking about the flow states that we enter and the pride or lack of pride, or in the Minsky case, your hatred of that which you've done, but nonetheless, the creations that we make, and whether it's the love or the joy or the engagement or the perspective shift, that that cascades into other minds. I think that's a big, big, big part of the meaning of life. It's not something that everybody participates in necessarily although I think we all do, at least in a very local level by the example that we set, by the interactions that we have, but for people who create works that travel far and reach people they'll never meet, that reach countries they'll never visit, that reach people perhaps that come along and come across their ideas or their works or their stories or their aesthetic creations of other sorts long after they're dead. I think that's really, really big part of the fabric of the meaning of life. And so all these things, like love and creation, I think really is what it's all about. And part of love is also the loss of it. There's a Louis episode with Louis C.K. where an old gentleman is giving him advice that sometimes the sweetest parts of love is when you lose it and you remember it, sort of you reminisce on the loss of it. And there's some aspect in which, and I have many of those in my own life, that almost like the memories of it and the intensity of emotion you still feel about it is like the sweetest part. Is you're like, after saying goodbye, you relive it. So that goodbye is also a part of love. The loss of it is also a part of love. I don't know, it's back to that scarcity. I won't say the loss is the best part personally, but it definitely is an aspect of it. And the grief you might feel about something that's gone makes you realize what a big deal it was. Speaking of which, this particular journey, we went on together, come to an end. So I have to say goodbye, and I hate saying goodbye. Rob, this is truly an honor. I've really been a big fan. People should definitely check out your podcast. You're a master at what you do in the conversation space, in the writing space. It's been an incredible honor that you would show up here and spend this time with me. I really, really appreciate it. Well, it's been a huge honor to be here as well, and also a fan and have been for a long time. Thanks, Rob. Thanks for listening to this conversation with Rob Reed, and thank you to Athletic Greens, Belcampo, Fundrise, and NetSuite. Check them out in the description to support this podcast. And now, let me leave you with some words from Plato. We can easily forgive a child who's afraid of the dark. The real tragedy of life is when men are afraid of the light. Thank you for listening, and hope to see you next time.

https://youtu.be/cuD9uNFXnU8

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Manolis Kellis: Meaning of Life, the Universe, and Everything | Lex Fridman Podcast #142

The following is a conversation with Manolis Kellis, his fourth time on the podcast. He's a professor at MIT and head of the MIT Computational Biology Group. Since this is episode number 142, and 42, as we all know, is the answer to the ultimate question of life, the universe, and everything, according to the Hitchhiker's Guide to the Galaxy, we decided to talk about this unanswerable question of the meaning of life in whatever way we two descendants of apes could muster, from biology, to psychology, to metaphysics, and to music. Quick mention of each sponsor, followed by some thoughts related to the episode. Thanks to Grammarly, which is a service for checking, spelling, grammar, sentence structure, and readability, Athletic Greens, the all-in-one drink that I start every day with to cover all my nutritional bases, and Cash App, the app I use to send money to friends. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that the opening 40 minutes of the conversation are all about the many songs that formed the soundtrack to the journey of Manolis's life. It was a happy accident for me to discover yet another dimension of depth to the fascinating mind of Manolis. I include links to YouTube versions of many of the songs we mention in the description and overlay lyrics on occasion. But if you're just listening to this without listening to the songs or watching the video, I hope you still might enjoy, as I did, the passion that Manolis has for music, his singing of the little excerpts from the songs, and in general, the meaning we discuss that we pull from the different songs. If music is not your thing, I do give timestamps to the less musical and more philosophical parts of the conversation. I hope you enjoy this little experimenting conversation about music and life. If you do, please subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Manolis Kelis. You mentioned Leonard Cohen and the song Hallelujah as a beautiful song. So what are the three songs you draw the most meaning from about life? Don't get me started. So there's really countless songs that have marked me, that have sort of shaped me in periods of joy and in periods of sadness. My son likes to joke that I have a song for every sentence he will say, because very often I will break into a song with a sentence he'll say. My wife calls me the radio because I can sort of recite hundreds of songs that have really shaped me. So it's gonna be very hard to just pick a few. So I'm just gonna tell you a little bit about my song transition as I've grown up. In Greece, it was very much about, as I told you before, the misery, the poverty, but also overcoming adversity. So some of the songs that have really shaped me are Hades Alexios, for example, is one of my favorite singers in Greece. And then there's also really just old traditional songs that my parents used to listen to. Like one of them is, ♪ Honeymoon plousios ♪ Which is basically, oh, if I was rich. And the song is painting this beautiful picture about all the noises that you hear in the neighborhood, in his poor neighborhood, the train going by, the priest walking to the church and the kids crying next door and all of that. And he says, with all of that, I'm having trouble falling asleep and dreaming. If I was rich, and then he was like, you know, breaking into that. So it's this juxtaposition between the spirit and the sublime and then the physical and the harsh reality. It's just not having troubles, not being miserable. So basically rich to him just means out of my misery, basically. And then also being able to travel, being able to sort of be the captain of a ship and see the world and stuff like that. So it's just such beautiful imagery. So many of the Greek songs, just like the poetry we talked about, they acknowledge the cruelty, the difficulty of life, but are longing for a better life. That's exactly right. And another one is, φτωχολογιά. And this is one of those songs that has like a fast and joyful half and a slow and sad half. And it goes back and forth between them. And it's like, φτωχολογιά, γεύσε να κάθε μου τραγούδι. So poor, you know, basically it's the state of being poor. I don't even know if there's a word for that in English. And then fast part is, τα χέρια σου μεγάλωσαν και πόνεσαν και μάθεσαν. So then it's like, oh, you know, basically like the state of being poor and misery, you know, for you, I write all my songs, et cetera. And then the fast part is, in your arms grew up and suffered and, you know, stood up and, you know, rose. Men with clear vision. This whole concept of taking on the world with nothing to lose because you've seen the worst of it. This imagery of, ψιλάκι παρ' Ισόπουλα, χαράς τα κορίσοπουλα. So it's describing the young men as Cyprus trees. And that's probably one of my earliest exposure to a metaphor, to sort of, you know, this very rich imagery. And I love about the fact that I was reading a story to my kids the other day and it was dark. And my daughter who's six is like, oh, can I please see the pictures? And Jonathan, who's eight, so my daughter, Cleo, is like, oh, let's look at the pictures. And my son, Jonathan, he's like, but Cleo, if you look at the pictures, it's just an image. If you just close your eyes and listen, it's a video. That's brilliant. It's beautiful. And he's basically showing just how much more the human imagination has besides just a few images that, you know, the book will give you. And then another one, oh gosh, this one is really like miserable. It's called Sto perigiali, to krifo. And it's basically describing how vigorously we took on our life and we pushed hard towards a direction that we then realized was the wrong one. And again, these songs give you so much perspective. There's no songs like that in English that will basically, you know, sort of just smack you in the face about sort of the passion and the force and the drive. And then it turns out, we just followed the wrong life. And it's like, wow. Okay, so that was beautiful. All right, so that's like before 12. So, you know, growing up in sort of this horrendously miserable, you know, sort of view of romanticism of, you know, suffering. So then my preteen years is like, you know, learning English through songs. So basically, you know, listening to all the American pop songs and then memorizing them vocally before I even knew what they meant. So, you know, Madonna and Michael Jackson and all of these sort of really popular songs and, you know, George Michael and just songs that I would just listen to the radio and repeat vocally. And eventually as I started learning English, I was like, oh, wow, this thing has been repeating. I now understand what it means without re-listening it. But just with re-repeating it, I was like, oh. Again, Michael Jackson's Man in the Mirror is teaching you that it's your responsibility to just improve yourself. You know, if you want to make the world a better place, take a look at yourself and make the change. This whole concept of, again, I mean, all of these songs, you can listen to them shallowly or you can just listen to them and say, oh, there's deeper meaning here. And I think there's a certain philosophy of song as a way of touching the psyche. So if you look at regions of the brain, people who have lost their language ability because they have an accident in that region of the brain can actually sing because it's exactly the symmetric region of the brain. And that again, teaches you so much about language evolution and sort of the duality of musicality and rhythmic patterns and eventually language. Do you have a sense of why songs developed? So you're kind of suggesting that it's possible that there is something important about our connection with song and with music on the level of the importance of language. Is it possible? It's not just possible. In my view, language comes after music. Language comes after song. No, seriously. Like basically my view of human cognitive evolution is rituals. If you look at many early cultures, there's rituals around every stage of life. There's organized dance performances around mating. And if you look at mate selection, I mean, that's an evolutionary drive right there. So basically if you're not able to string together a complex dance as a bird, you don't get a mate. And that actually forms this development for many song learning birds. Not every bird knows how to sing and not every bird knows how to learn a complicated song. So basically there's birds that simply have the same few tunes that they know how to play. And a lot of that is inherent and genetically encoded. And others are birds that learn how to sing. And if you look at a lot of these exotic birds of paradise and stuff like that, like the mating rituals they have are enormously amazing. And I think human mating rituals of ancient tribes are not very far off from that. And in my view, the sequential formation of these movements is a prelude to the cognitive capabilities that ultimately enable language. It is fascinating to think that that's not just an accidental precursor to intelligence. Yeah, it's sexually selected. Well, it's sexually selected and it's a prerequisite. Yeah. It's like it's required for intelligence. And even as language has now developed, I think the artistic expression is needed, like badly needed by our brain. So it's not just that, oh, our brain can kind of, you know, take a break and go do that stuff. No, I mean, you know, I don't know if you remember that scene from, oh gosh, where's that Jack Nicholson movie in New Hampshire. All work and no play, make Jack a dull boy. Dull boy, The Shining. The Shining. So there's this amazing scene where he's constantly trying to concentrate and what's coming out of the typewriter is just gibberish. And I have that image as well when I'm working. And I'm like, no, basically all of these crazy, you know, huge number of hobbies that I have, they're not just tolerated by my work. They're required by my work. This ability of sort of stretching your brain in all these different directions is connecting your emotional self and your cognitive self. And that's a prerequisite to being able to be cognitively capable, at least in my view. Yeah, I wonder if the world without art and music, you're just making me realize that perhaps that world would be not just devoid of fun things to look at or listen to, but devoid of all the other stuff, all the bridges and rockets and science. Exactly, exactly. Creativity is not disconnected from art. And, you know, my kids, I mean, you know, I could be doing the full math treatment to them. No, they play the piano and they play the violin and they play sports. I mean, this whole, you know, sort of movement and going through mazes and playing tennis and, you know, playing soccer and avoiding obstacles and all of that, that forms your three-dimensional view of the world. Being able to actually move and run and play in three dimensions is extremely important for math, for, you know, stringing together complicated concepts. It's the same underlying cognitive machinery that is used for navigating mazes and for navigating theorems and sort of solving equations. So I can't, you know, I can't have a conversation with my students without, you know, sort of either using my hands or opening the whiteboard in Zoom and just constantly drawing, or, you know, back when we had in-person meetings, just the whiteboard. Yeah, the whiteboard. Yeah, that's fascinating to think about. So that's Michael Jackson, man. Mirror, Careless Whisper, George Michael, which is a song I like. You didn't say Careless Whisper. I mean, I- You didn't say that? I like that one. That's too popular for you? I had recorded, no, no, no. It's an amazing song for me. I had recorded a small part of it as it played at the tail end of the radio. And I had a tape where I only had part of that song. Part of that song, you just sing it over and over. And I just played it over and over and over again. Just so beautiful. It's so heartbreaking. That song is almost Greek. It's so heartbreaking. I know. And George Michael is Greek. Is he Greek? He's Greek, of course. George Michaelides. That's right. I mean, he's Greek. Yeah. Now you know. Now you know. I'm so sorry to offend you so deeply not knowing this. So, okay, so what's- So anyway, so we're moving to France when I'm 12 years old. And now I'm getting into the songs of Gainsbourg. So Gainsbourg is this incredible French composer. He is always seen on stage, like not even pretending to try to please, just like with his cigarette, just like rrrr, mumbling his songs. But the lyrics are unbelievable. Like basically entire sentences will rhyme. He will say the same thing twice. And you're like, whoa. And in fact, another, speaking of Greek, a French Greek, Georges Moustaki. This song is just magnificent. Avec ma gueule de métèque, de juif errant, de patre grec. So with my face of, métèque is actually a Greek word. It's, you know, it's a French word for a Greek word. But met, comes from meta, and then ek from Ikea, from ecology, which means home. So métèque is someone who has changed homes to a migrant. So with my face of a migrant, and you'll love this one, de juif errant, de patre grec, of meandering Jew, of Greek pastor. So again, you know, the Russian Greek, you know, Jew orthodox connection. So, et mes cheveux aux quatre vents, with my hair in the four wings, avec mes yeux tous délavés, qui me donnent l'air de rêver. Avec, with my eyes that are all washed out, who give me the pretense of dreaming, but who don't dream that much anymore. With my hands of thief, of musician, and who have stolen so many gardens. With my mouth that has drunk, that has kissed, and that has bitten, without ever pleasing its hunger. With my skin that has been rubbed in the sun of all the summers, and anything that was wearing a skirt. With my heart, and then you have to listen to this first, it's so beautiful. Avec mon coeur qui a su faire souffrir autant qu'il a souffert. With my heart that knew how to make suffer as much as it suffered, but was able to, that knew how to make, in French it's actually, su faire, that knew how to make, qui a su faire souffrir autant qu'il a souffert. Verses that span the whole thing. It's just beautiful. So, yeah. Do you know, on a small tangent, do you know Jacques Brel? Of course, of course. And then, La Mequite Pas, you know those songs? Those, that song gets me every time. So there's a cover of that song by one of my favorite female artists. Not Nina Simone. No, no, no, no, no. Modern? Carol Emerald. She's from Amsterdam. And she has a version of La Mequite Pas where she's actually added some English lyrics. And it's really beautiful. But again, La Mequite Pas is just so, I mean, it's, you know, the promises, the volcanoes that, you know, will restart. It's just so beautiful. And- I love, there's not many songs that show such depth of desperation for another human being. That's so powerful. Unapologetic. Je t'offrirai des perles de pluie venant de pays où il ne pleut pas. And then high school, now I'm starting to learn English. So I moved to New York. So Sting's Englishman in New York. Yeah. Magnificent song. And again, there's, if manners mageth manners, someone said, then he's the hero of the day. It takes a man to suffer ignorance and smile, be yourself no matter what they say. And then it takes more than combat gear to make a man, takes more than a license for a gun. Confront your enemies, avoid them when you can. A gentleman will walk, but never run. It's, again, you're talking about songs that teach you how to live. I mean, this is one of them. Basically says, it's not the combat gear that makes a man. Where's the part where he says, there you go. Gentleness so brighty, a rare in this society. At night a candle's brighter than the sun. So beautiful. It basically says, well, you just might be the only one. Modesty propriety can lead to notoriety. You could end up as the only one. It's, it basically tells you, you don't have to be like the others. Be yourself, show kindness, show generosity. Don't, you know, don't let that anger get to you. You know, the song Fragile, how fragile we are, how fragile we are. So again, as in Greece, I didn't even know what that meant, how fragile we are, but the song was so beautiful. And then eventually I learned English and I actually understand the lyrics. And the song is actually written after the Contras murdered Ben Linder in 1987. And the US eventually turned against supporting these guerrillas. And it was just a political song, but so such a realization that you can't win with violence, basically. And that song starts with the most beautiful poetry. So if blood will flow when flesh and still are one, drying in the color of the evening sun, tomorrow's rain will wash the stains away, but something in our minds will always stay. Perhaps this final act was meant to clinch a lifetime's argument that nothing comes from violence and nothing ever could for all those born beneath an angry star, lest we forget how fragile we are. Damn. Damn, right? I mean, that's poetry. It was beautiful. And he's using the English language in just such a refined way with deep meanings, but also words that rhyme just so beautifully and evocations of when flesh and still are one. I mean, it's just mind boggling. And then of course the refrain that everybody remembers is on and on the rain will fall, et cetera. But like this beginning. Tears from a star, wow. Yeah. And again, tears from a star, how fragile we are. I mean, just these rhymes are just flowing so naturally. Something, it seems that more meaning comes when there's a rhythm that, I don't know what that is. That probably connects to exactly what you were saying. And if you pay close attention, you will notice that the more obvious words sometimes are the second verse. And the less obvious are often the first verse because it makes the second verse flow much more naturally because otherwise it feels contrived. Oh, you went and found this like unusual word. In dark moments, the whole album of Pink Floyd and the movie just marked me enormously as a teenager, just the wall. And there's one song that never actually made it into the album, that's only there in the movie about when the Tigers broke free and the Tigers are the tanks of the Germans. And it just describes again, this vivid imagery. It was just before dawn, one miserable morning in black 44 when the forward commander was told to sit tight when he asked that his men be withdrawn. And the generals gave thanks as the other ranks held back the enemy tanks for a while. And the Anzio bridgehead was held for the price of a few hundred ordinary lives. So that's a theme that keeps coming back in Pink Floyd with Us Versus Them. Us and them, God only knows that's not what we would choose to do. Forward he cried from the rear and the front rows died. From another song, it's like this whole concept of Us Versus Them. And there's that theme of Us Versus Them again where the child is discovering how his father died when he finds an old and a founded one day in a drawer of old photographs hidden away. And my eyes still grow damp to remember his majesty's sign with his own rubber stamp. So it's so ironic because it seems the way that he's writing it, that he's not crying because his father was lost. He's crying because kind old King George took the time to actually write mother a note about the fact that his father died. It's so ironic because it basically says, we are just ordinary men. And of course we're disposable. So I don't know if you know the root of the word pioneers, but you had a chessboard here earlier, a pawn in French, the pion. They are the ones that you send to the front to get murdered, slaughtered. This whole concept of pioneers having taken this whole disposable ordinary men to actually be the ones that we're now treating as heroes. So anyway, there's this juxtaposition of that. And then the part that always just strikes me is the music and the tonality totally changes. And now he describes the attack. It was dark all around. There was frost in the ground when the tigers broke free and no one survived from the Royal Fusiliers Company. They were all left behind. Most of them dead, the rest of them dying. And that's how the high command took my daddy from me. And that song, even though it's not in the album, explains the whole movie. Because it's this movie of misery. It's this movie of someone being stuck in their head and not being able to get out of it. There's no other movie that I think has captured so well this prison that is someone's own mind. And this wall that you're stuck inside and this feeling of loneliness. And sort of, is there anybody out there? And sort of, hello, hello, is there anybody in there? Just nod if you can hear me. Is there anyone home? Come on, yo, I hear you're feeling down. Just one little thing, and you're down and in again. Anyway, so. Yeah, the prison of your mind. So those are the darker moments. Exactly, these are the darker moments. Yeah, in the darker moments, the mind does feel like you're trapped alone in a room with it. Yeah, and there's this scene in the movie which where he just breaks out with his guitar and there's this prostitute in the room. He starts throwing stuff and then he breaks the window, he throws the chair outside, and then you see him laying in the pool with his own blood. Like, you know, everywhere. And then there's these endless hours spent fixing every little thing and lining it up. And it's this whole sort of mania versus, you know, you can spend hours building up something and just destroy it in a few seconds. One of my turns is that song. And it's like, ♪ I feel cold as a tourniquet, dry as a funeral drum. ♪ ♪ I feel cold as a tourniquet, dry as a funeral drum. ♪ And then the music builds up saying, ♪ Run to the bedroom, there's a suitcase on the left. ♪ ♪ You'll find my favorite axe. ♪ ♪ Don't look so frightened, this is just a passing phase. ♪ ♪ One of my bad days. ♪ It's just so beautiful. I need to rewatch it. That's so, you make me realize. But imagine watching this as a teenager. It like ruins your mind. It's like so many, it's just such harsh imagery. And then, you know, anyway, so there's the dark moment. And then again, going back to Sting, now it's the political songs, Russians. And I think that song should be a new national anthem for the US, not for Russians, but for red versus blue. ♪ Mr. Khrushchev says we will bury you. ♪ ♪ I don't subscribe to this point of view. ♪ ♪ It'd be such an ignorant thing to do. ♪ ♪ If the Russians love their children too. ♪ What is it doing? It's basically saying, the Russians are just as humans as we are. There's no way that they're gonna let their children die. And then it's just so beautiful. ♪ How can I save my innocent boy from Oppenheimer's deadly toy? ♪ And now that's the new national anthem. Are you reading? ♪ There is no monopoly of common sense. ♪ ♪ On either side of the political fence. ♪ ♪ We share the same biology regardless of ideology. ♪ ♪ Believe me when I say to you, I hope the Russians love their children too. ♪ ♪ There's no such thing as a winnable war. It's a lie we don't believe anymore. ♪ I mean, it's beautiful, right? And for God's sake, America, wake up. These are your fellow Americans. They're your fellow biology. There is no monopoly of common sense on either side of the political fence. It's just so beautiful. There's no crisper, simpler way to say Russians love their children too. The common humanity. Yeah. And remember what I was telling you, I think in one of our first podcasts about the daughter who's crying for her brother to come back from war. And then the Virgin Mary appears and says, who should I take instead? This Turk, here's his family, here's his children. This other one, he just got married, et cetera. And that basically says, no, I mean, if you look at the Lord of the Rings, the enemies are these monsters. They're not human. And that's what we always do. We always say, they, you know, they're not like us. They're different. They're not humans, et cetera. So there's this dehumanization that has to happen for people to go to war. You know, if you realize this, how close we are genetically, one with the other, this whole 99.9% identical, you can't bear weapons against someone who's like that. And the things that are the most meaningful to us in our lives at every level is the same on all sides, on both sides. Exactly. So not just that we're genetically the same. Yeah. We're ideologically the same. We love our children. We love our country. We will, you know, we will fight for our family. So, and the last one I mentioned last time we spoke, which is Joni Mitchell's Both Sides Now. So she has three rounds, one on clouds, one on love and one on life. And on clouds, she says, Rows and flows of angel hair and ice cream castles in the air and feather canyons everywhere. I've looked at clouds that way, but now they only block the sun. They rain and snow on everyone. So many things I would have done, but clouds got in my way. And then I've looked at clouds from both sides now, from up and down and still somehow it's clouds illusions I recall. I really don't know clouds at all. And then she goes on about love, how it's super, super happy, or it's about misery and loss and about life, how it's about winning and losing and so forth. But now old friends are acting strange. They shake their heads. They say I've changed. Well, something's lost and something's gained in living every day. So again, that's growing up and realizing that, well, the view that you had as a kid is not necessarily that you have as an adult. Remember my poem from when I was 16 years old of this whole, you know, children dance now all in row. And then in the end, even though the snow seems bright, without you have lost their light, sun that sang and moon that smiled. So this whole concept of if you have love and if you have passion, you see the exact same thing from a different way. You can go out running in the rain or you could just stay in and say, oh, sucks, I won't be able to go outside now. Both sides. Anyway, and the last one is last, last one, I promise. Leonard Cohen. This is amazing, by the way. I'm so glad we stumbled on how much, how much joy you have in so many avenues of life. And music is just one of them. That's amazing. But yes, Leonard Cohen. Going back to Leonard Cohen, since that's where you started. So Leonard Cohen's Dance Me to the End of Love. That was our opening song in our wedding with my wife. Oh, no, that's good. Came out to greet the guest. It was Dance Me to the End of Love. And then another one, which is just so passionate always, and we always keep referring back to it, is I'm Your Man. And it goes on and on about sort of, I can be every type of lover for you. And what's really beautiful in marriage is that we live that with my wife every day. You can have the passion, you can have the anger, you can have the love, you can have the tenderness. There's just so many gems in that song. If you want a partner, take my hand. Or if you want to strike me down in anger, here I stand, I'm your man. And then if you want a boxer, I will step into the ring for you. If you want a driver, climb inside. Or if you want to take me for a ride, you know you can. So this whole concept of you want to drive, I'll follow. You want me to drive, I'll drive. And the difference, I would say, between like that and Ne'ma Keita Pah is this song, he's got an attitude. He's like, he's proud of his ability to basically be any kind of man for the long, as opposed to the Jacques Brel-like desperation of, what do I have to be for you to love me? That kind of desperation. But notice, there's a parallel here. There's a verse that is perhaps not paid attention to as much, which says, ah, but a man never got a woman back. Not by begging on his knees. So it seems that the I'm Your Man is actually an apology song, in the same way that Ne'ma Keita Pah is an apology song. Ne'ma Keita Pah basically says, I've- Screwed up. I've screwed up. I'm sorry, baby. And in the same way that the Careless Whisper is I'm Screwed Up. Yes, that's right. I'm never gonna dance again. Guilty feet have got no rhythm. No rhythm. So this is an apology song, not by begging on his knees, or I'd crawl to you, baby, and I'd fall at your feet, and I'd howl at your beauty like a dog in heat, and I'd claw at your heart, and I'd tear at your sheet. I'd say, please. And then the last one is so beautiful. If you want a father for your child, or only want to walk with me a while across the sand, I'm your man. That's the last verses, which basically says, you want me for a day? I'll be there. Do you want me to just walk? I'll be there. You want me for life? If you want a father for your child, I'll be there too. It's just so beautiful. Oh, sorry. Remember how I told you I was gonna finish with a lighthearted song? Yes. Ah, last one. You ready? So, Alison Krauss and Union Station, country song, believe it or not, the lucky one. So, I've never identified as much with the lyrics of a song as this one. And it's hilarious. My friend, Seraphim Patoglou, is the guy who got me to genomics in the first place. I owe enormously to him. And he's another Greek. We actually met dancing, believe it or not. So we used to perform Greek dances. I was the president of the International Students Association. So we put on these big performances for 500 people at MIT. And there's a picture on the MIT Tech where Seraphim, who's like, you know, bodybuilder, was holding on his shoulder. And I was like doing maneuvers in the air, basically. So anyway, this guy, Seraphim, we were driving back from a conference. And there's this Russian girl who was describing how every member of her family had been either killed by the communists or killed by the Germans or killed by the... Like she had just like, you know, misery, like death and, you know, sickness and everything. Everyone was decimated in her family. She was the last standing member. And we stop at a, Seraphim was driving, and we stop at a rest area. And he takes me aside and he's like, Manolis, we're gonna crash. Get her out of my car. And then he basically says, but I'm only reassured because you're here with me. And I'm like, what do you mean? He's like, you know, he's like, from your smile, I know you're the luckiest man on the planet. So there's this really funny thing where I just feel freaking lucky all the time. And it's a question of attitude. Of course, I'm not any luckier than any other person, but if it's something horrible happens to me, I'm like, and in fact, even in that song, the song about sort of, you know, walking on the beach and this, you know, sort of taking our life the wrong way. And then, you know, having to turn around. At some point he's like, you know, in the fresh sand, we wrote her name. O rea, pu fisic seo bat. So how nicely that the wind blew and the writing was erased. So again, it's this whole sort of, not just saying, oh, bummer, but, oh, great. I just lost this. This must mean something. Right? And then say- This horrible thing happened. It must open the door to a beautiful chapter. So Alison Krauss is talking about the lucky one. So it was like, oh my God, she wrote a song for me. And she goes, you're the lucky one. I know that now. As free as the wind blowing down the road, loved by many, hated by none. I'd say you were lucky because you know what you've done. Not to care in the world, not to worry inside. Everything's going to be all right because you're the lucky one. And then she goes, you're the lucky one, always having fun, a jack of all trades, a master of none. You look at the world with the smiling eyes and laugh at the devil as his train rolls by. I'll give you a song and a one night stand. You'll be looking at a happy man because you're the lucky one. It basically says, if you just don't worry too much, if you don't try to be, you know, a one-trick pony, if you just embrace the fact that you might suck at a bunch of things, but you're just going to try a lot of things. And then there's another verse that says, well, you're blessed, I guess, but never knowing which road you're choosing. To you, the next best thing to playing and winning is playing and losing. It's just so beautiful because he basically says, if you try your best, but it's still playing, if you lose, it's okay, you had an awesome game. And again, superficially, it sounds like a super happy song, but then there's the last verse basically says, no matter where you are, that's where you'll be. You can bet your luck won't follow me. Just give you a song and then one night stand, you'll be looking at a happy man. And then in the video of the song, she just walks away or he just walks away or something like that. And it basically tells you that freedom comes at a price. Freedom comes at the price of non-commitment. This whole sort of birds who love or birds who cry you can't really love unless you cry. You can't just be the lucky one, the happy boy, la la la, and yet have a long-term relationship. So it's, on one hand, I identify with the shallowness of the song of, you're the lucky one, jack of all trades, a master of none. But at the same time, I identify with a lesson of, well, you can't just be the happy, merry, go lucky all the time. Sometimes you have to embrace loss and sometimes you have to embrace suffering. And sometimes you have to embrace that if you have a safety net, you're not really committing enough. You're not, you know, basically, you're allowing yourself to slip. But if you just go all in and you just, you know, let go of your reservations, that's when you truly will get somewhere. So anyway, that's like the, I managed to narrow it down to what, 15 songs? Thank you for that wonderful journey that you just took us on, the darkest possible places of Greek song to ending on this, a country song. I haven't heard it before, but that's exactly right. I feel the same way, depending on the day. Is this the luckiest human on earth? And there's something to that, but you're right. It needs to be, we need to now return to the muck of life in order to be able to truly enjoy it. So it's- What do you mean muck? What's muck? The messiness of life. Things don't turn out the way you expect it to. So like to feel lucky is like focusing on the beautiful consequences. But then that feeling of things being different than you expected, that you stumble in all the kinds of ways that seems to be, needs to be paired with the feeling. There's basically one way. The only way not to make mistakes is to never do anything. Right. Basically, you have to embrace the fact that you'll be wrong so many times. In so many research meetings, I just go off on a tangent and I say, let's think about this for a second. And it's just crazy for me, who's a computer scientist to just tell my biologist friends, what if biology kind of worked this way? And they humor me. They just let me talk. And rarely has it not gone somewhere good. It's not that I'm always right, but it's always something worth exploring further. That if you're an outsider with humility and knowing that I'll be wrong a bunch of times, but I'll challenge your assumptions, you know, and often take us to a better place, is part of this whole sort of messiness of life. Like if you don't try and lose and get hurt and suffer and cry and just break your heart and all these feelings of guilt and, you know, wow, I did the wrong thing. Of course, that's part of life. And that's just something that, you know, if you are a doer, you'll make mistakes. If you're a criticizer, yeah, sure. You can sit back and criticize everybody else for the mistakes they make. Or instead, you can just be out there making those mistakes. And frankly, I'd rather be the criticized one than the criticized one. Ah, brilliantly put. Every time somebody steals my bicycle, I say, well, I know my son is like, why do they steal our bicycle, dad? And I'm like, aren't you happy that you have bicycles that people can steal? I'd rather be the person stolen from than the stealer. Yeah, it's not the critic that counts. Yeah. So that's, we've just talked amazingly about life from the music perspective. Let's talk about life from human life, from perhaps other perspective and its meaning. So this is episode 142. There is perhaps an absurdly deep meaning to the number 42 that our culture has elevated. So this is a perfect time to talk about the meaning of life. We've talked about it already, but do you think this question that's so simple and so seemingly absurd has value of what is the meaning of life? Is it something that raising the question and trying to answer it, is that a ridiculous pursuit or is there some value? Is it answerable at all? So first of all, I feel that we owe it to your listeners to say why 42. Sure. So of course the Hitchhiker's Guide to the Galaxy came up with 42 as basically a random number. Just, you know, the author just pulled it out of a hat and he's admitted so. He said, well, 42 just seemed like just random numbers any. But in fact, there's many numbers that are linked to 42. So 42 again, just to summarize is the answer that these super mega computer that had computed for a million years with the most powerful computer in the world had come up with. At some point, the computer says, I have an answer. And they're like, what? It's like, you're not gonna like it. Like, what is it? It's 42. And then the irony is that they had forgotten, of course, what the question was. Yes. So now they have to build a bigger computer to figure out what the question is. To which the answer is 42. So as I was turning 42, I basically sort of researched why 42 is such a cool number. And it turns out that, and I put together this little passage that was explaining to all those guests to my 42nd birthday party, why we were talking about the meaning of life. And basically talked about how 42 is the angle at which light reflects off of water to create a rainbow. And it's so beautiful because the rainbow is basically the combination of sort of, it's been raining, but there's hope because the sun just came out. So it's a very beautiful number there. So 42 is also the sum of all rows and columns of a magic cube that contains all consecutive integers starting at one. So basically, if you take all integers between one and however many vertices there are, the sums is always 42. 42 is the only number left under 100 for which the equation of X to the cube plus Y to the cube plus Z to the cube is N. And was not known to not have a solution. And now it's the only one that actually has a solution. 42 is also one, zero, one, zero, one, zero in binary. Again, the yin and the yang, the good and the evil, one and zero, the balance of the fours. 42 is the number of chromosomes for the giant panda. The giant panda. I know it's totally random. It's a vicious symbol of great strength coupled with peace, friendship, gentle temperament, harmony, balance, and friendship. Whose black and white colors again symbolize yin and yang. The reason why it's the symbol for China is exactly the strength, but yet peace and so on and so forth. So 42 chromosomes. It takes light 10 to the minus 42 seconds to cross the diameter of a proton connecting the two fundamental dimensions of space and time. 42 is the number of times a piece of paper should be folded to reach beyond the moon. So, which is what I assume my students mean when they ask that their paper reaches for the stars. I just tell them just fold it a bunch of times. 42 is the number of Messier object 42, which is Orion. And that's, you know, one of the most famous galaxies. It's I think also the place where we can actually see the center of our galaxy. 42 is the numeric representation of the star symbol in ASCII, which is very useful when searching for the stars. And also a reg exp for life, the universe and everything. So star. In Egyptian mythology, the goddess Maat, which was personifying truth and justice, would ask 42 questions to every dying person. And those answering successfully would become stars, continue to give life and fuel universal growth. In Judaic tradition, God ascribe is ascribed the 42 lettered name and trusted only to the middle age, pious, meek, free from bad temper, sober and not insistent on his rights. And in Christian tradition, there's 42 generations from Abraham, Isaac, that we talked about, the story of Isaac, Jacob, eventually Joseph, Mary and Jesus. In Kabbalistic tradition, Eloka, which is 42, is the number with which God creates the universe, starting with 25, let there be, and ending with 17, good. So 25 plus, you know, 17. There's a 42 chapter sutra, which is the first Indian religious scripture, which was translated to Chinese, thus introducing Buddhism to China from India. The 42 line Bible was the first printed book marking the age of printing in the 1450s and the dissemination of knowledge eventually leading to the enlightenment. A yeast cell, which is called a single cell eukaryote and the subject of my PhD research, has exactly 42 million proteins. Anyway, so there's a series of 42. You're on fire with this. These are really good. I guess what you're saying is just a random number. Yeah, basically. So all of these are background news. So, you know, after you have the number, you figure out why that number. So anyway, so now that we've spoken about why 42, why do we search for meaning? And you're asking, you know, will that search ultimately lead to our destruction? And my thinking is exactly the opposite. So basically that asking about meaning is something that's so inherent to human nature. It's something that makes life beautiful and that makes it worth living. And that searching for meaning is actually the point. It's not the finding it. I think when you found it, you're dead. Don't ever be satisfied that, you know, I've got it. So I like to say that life is lived forward, but it only makes sense backward. And I don't remember whose quote that is, but the whole search itself is the meaning. And what I love about it is that there's a double search going on. There's a search in every one of us through our own lives to find meaning. And then there's a search, which is happening for humanity itself to find our meaning. And we as humans like to look at animals and say, of course they have a meaning. Like a dog has its meaning. It's just a bunch of instincts, you know, running around, loving everything. You know, remember our joke with the cat and the dog. Yeah, cat has no meaning. No, no. So, and I'm noticing the yin yang symbol right here with this whole panda, black and white and the zero, one, zero. You're on fire with that 42. Some of those are gold, ASCII value for a star symbol. Damn. Anyway, so basically in my view, the search for meaning and the act of searching for something more meaningful is life's meaning by itself. The fact that we kind of always hope that, yes, maybe for animals, that's not the case, but maybe humans have something that we should be doing and something else. And it's not just about procreation. It's not just about dominance. It's not just about strength and feeding, et cetera. Like we're the one species that spends such a tiny little minority of its time feeding, that we have this enormous, huge cognitive capability that we can just use for all kinds of other stuff. And that's where art comes in. That's where the healthy mind comes in with exploring all of these different aspects that are just not directly tied to a purpose. That's not directly tied to a function. It's really just the playing of life, not for a particular reason. Do you think this thing we got, this mind, is unique in the universe in terms of how difficult it is to build? Is it possible that we're the most beautiful thing that the universe has constructed? Both the most beautiful and the most ugly, but certainly the most complex. So look at evolutionary time. The dinosaurs ruled the earth for 135 million years. We've been around for a million years. So one versus 135. So dinosaurs were extinct about 60 million years ago and mammals that had been happily evolving as tiny little creatures for 30 million years then took over the planet and then dramatically radiated about 60 million years ago. Out of these mammals came the neocortex formation. So basically the neocortex, which is sort of the outer layer of our brain compared to our quote unquote reptilian brain, which we share the structure of with all of the dinosaurs, they didn't have that and yet they ruled the planet. So how many other planets have still mindless dinosaurs where strength was the only dimension ruling the planet? So there was something weird that annihilated the dinosaurs. And again, you could look at biblical things of sort of God coming and wiping out his creatures and to make room for the next ones. So the mammals basically sort of took over the planet and then grew this cognitive capability of these general purpose machine. And primates pushed that to extreme and humans among primates have just exploded that hardware. But that hardware is selected for survival. It's selected for procreation. It's initially selected with this very simple Darwinian view of the world of random mutation, ruthless selection and then selection for making more of yourself. If you look at human cognition, it's gone down a weird evolutionary path in the sense that we are expending an enormous amount of energy on this apparatus between our ears that is wasting what 15% of our bodily energy, 20%, like some enormous percentage of our calories go to function our brain. No other species makes that big of a commitment. That has basically taken energetic changes for efficiency on the metabolic side for humanity to basically power that thing. And our brain is both enormously more efficient than other brains, but also despite this efficiency, enormously more energy consuming. So, and if you look at just the sheer folds that the human brain has, again, our skull could only grow so much before it could no longer go through the pelvic opening and kill the mother at every birth. So, but yet the folds continued effectively creating just so much more capacity. The evolutionary context in which this was made is enormously fascinating. And it has to do with other humans that we have now killed off or that have gone extinct. And that has now created this weird place of humans on the planet as the only species that has this enormous hardware. So, that can basically make us think that there's something very weird and unique that happened in human evolution that perhaps has not been recreated elsewhere. Maybe the asteroid didn't hit sister earth and dinosaurs are still ruling. And any kind of proto-human is squished and eaten for breakfast basically. However, we're not as unique as we like to think because there was this enormous diversity of other human-like forms. And once you make it to that stage where you have a neocortex like explosion of, wow, we're now competing on intelligence and we're now competing on social structures and we're now competing on larger and larger groups and being able to coordinate and being able to have access to information and being able to communicate with other people and being able to have empathy. The concept of empathy, the concept of an ego, the concept of a self, of self-awareness comes probably from being able to project another person's intentions to understand what they mean when you have these large cognitive groups, large social groups. So, me being able to sort of create a mental model of how you think may have come before I was able to create a personal mental model of how do I think. So, this introspection probably came after this sort of projection and this empathy, which basically means passion, pathos, suffering, but basically sensing. So, basically empathy means feeling what you're feeling, trying to project your emotional state onto my cognitive apparatus. I think that is what eventually led to this enormous cognitive explosion that happened in humanity. So, life itself, in my view, is inevitable on every planet. Inevitable. Inevitable, but the evolution of life to self-awareness and cognition and all the incredible things that humans have done, that might not be as inevitable. That's your intuition. So, if you were to sort of estimate and bet some money on it, if we reran Earth a million times, would what we got now be the most special thing? And how often would it be? So, scientifically speaking, how repeatable is this experiment? So, this whole cognitive revolution? Yes. Maybe not. Maybe not. Basically, I feel that the longevity of dinosaurs suggests that it was not quite inevitable that we humans eventually made it. Well, you're also implying one thing here. You're saying, you're implying that humans also don't have this longevity. This is the interesting question. So, with the Fermi paradox, the idea that the basic question is like, if the universe has a lot of alien life forms in it, why haven't we seen them? Yeah. And one thought is that there's a great filter, or multiple great filters, that basically would destroy intelligent civilizations. Like this thing that we, this multi-folding brain that keeps growing may not be such a big feature. It might be useful for survival, but it takes us down a side road that is a very short one with a quick dead end. What do you think about that? So, I think the universe is enormous, not just in space, but also in time. And the pretense that, you know, the last blink of an instant that we've been able to send radio waves is when somebody should have been paying attention to our planet, is a little ridiculous. So, my, you know, what I love about Star Wars Yes. is a long, long time ago in a galaxy far, far away. It's not like some distant future, it's a long, long time ago. What I love about it is that basically says, you know, evolution and civilization are just so recent in, you know, on Earth. Like there's countless other planets that have probably all kinds of life forms, multicellular perhaps, and so on and so forth. But the fact that humanity has only been listening and emitting for just this tiny little blink means that any of these, you know, alien civilizations would need to be paying attention to every single insignificant planet out there. And, you know, again, I mean, the movie Contact and the book is just so beautiful. This whole concept of, we don't need to travel physically, we can travel as light. We can send instructions for people to create machines that will allow us to beam down light and recreate ourselves. And in the book, you know, the aliens actually take over. They're not as friendly. But, you know, this concept that we have to eventually go and conquer every planet, I mean, I think that, yes, we will become a galactic species. So you have a hope, well, you said, think. Oh, of course, of course. I mean, now that we've made it so far. So you feel like we've made it. Oh gosh, I feel that, you know, cognition, the cognition as an evolutionary trait has won over in our planet. There's no doubt that we've made it. So basically humans have won the battle for, you know, dominance. It wasn't necessarily the case with dinosaurs. Like, I mean, yes, you know, there's some claims of intelligence. And if you look at Jurassic Park, yeah, sure, whatever. But, you know, they just don't have the hardware for it. And humans have the hardware. There's no doubt that mammals have a dramatic potential for cognition over dinosaurs. Like basically there's universes where strength won out. And in our planet, in our, you know, particular version of whatever happened in this planet, cognition won out. And it's kind of cool. I mean, it's a privilege, right? It's kind of like living in Boston instead of, I don't know, some middle-aged place where everybody's like hitting each other with, you know, weapons and stuff. You know, weapons and sticks. You're back to the lucky one song. I mean, we are the lucky ones. But the flip side of that is that this hardware also allows us to develop weapons and methods of destroying ourselves. Again, I want to go back to Pinker and the better angels of our nature. The whole concept that civilization and the act of civilizing has dramatically reduced violence. Dramatically. If you look, you know, at every scale, as soon as organization comes, the state basically owns the right to violence. And eventually the state gives that right of governance to the people. But violence has been eliminated by that state. So this whole concept of central governance and people agreeing to live together and share responsibilities and duties and, you know, all of that is something that has led so much to less violence, less death, less suffering, less, you know, poverty, less, you know, war. I mean, yes, we have the capability to destroy ourselves, but the arc of civilization has led to much, much less destruction, much, much less war and much more peace. And of course there's blips back and forth and, you know, there are setbacks. But again, the moral arc of the universe. But it's- Seems to just- I probably imagine there were two dinosaurs back in the day having this exact conversation and they look up to the sky and there seems to be something like an asteroid. Going towards earth. So it's- While it's very true that the arc of our society, of human civilization, seems to be progressing towards a better, better life for everybody in the many ways that you described, things can change in a moment. And it feels like it's not just us humans we're living through a pandemic. You could imagine that a pandemic would be more destructive or there could be asteroids that just appear out of the darkness of space, which I recently learned is not that easy to- Let me give you another number. Detect them. Yes. So 48. What happens in 48 years? I'm not sure. 2068, Apophis. There's an asteroid that's coming. In 48 years it has a very high chance of actually wiping us out completely. Yes. Yes, we have 48 years to get our act together. It's not like some distant, distant hypothesis. Yes. Like, yeah, sure, they're hard to detect, but this one we know about, it's coming. So how do you feel about that? Why are you still so optimistic? Oh gosh, I'm so happy with where we are now. This is gonna be great. Seriously, if you look at progress, if you look at, again, the speed with which knowledge has been transferred, what has led to humanity making so many advances so fast? Okay, so what has led to humanity making so many advances is not just the hardware upgrades, it's also the software upgrades. So by hardware upgrades, I basically mean our neocortex and the expansion and these layers and folds of our brain and all of that. That's the hardware. The software hasn't, you know, the hardware hasn't changed much in the last, what, 70,000 years. As I mentioned last time, if you take a person from ancient Egypt and you bring them up now, they're just as equally fit. So hardware hasn't changed. What has changed is software. What has changed is that we are growing up in societies that are much more complex. This whole concept of neoteny basically allows our exponential growth. The concept that our brain has not fully formed, has not fully stabilized itself until after our teenage years. So we basically have a good 16 years, 18 years to sort of infuse it with the latest and greatest in software. If you look at what happened in ancient Greece, why did everything explode at once? My take on this is that it was the shift from the Egyptian and hieroglyphic software to the Greek language software. This whole concept of creating abstract notions, of creating these layers of cognition and layers of meaning and layers of abstraction for words and ideals and beauty and harmony. How do you write harmony in hieroglyphics? There's no such thing as, you know, sort of expressing these ideals of peace and justice and, you know, these concepts of, or even, you know, macabre concepts of doom, et cetera. Like you don't have the language for it. Your brain has trouble getting at that concept. So what I'm trying to say is that these software upgrades for human language, human culture, human environment, human education have basically led to this enormous expansion and enormous explosion of knowledge. And eventually after the enlightenment, and as I was mentioning, the 42 line Bible and the printed press, the dissemination of knowledge, you basically now have this whole horizontal dispersion of ideas in addition to the vertical inheritance of genes. So the hardware improvements happen through vertical inheritance. The software improvements happen through horizontal inheritance. And the reason why human civilization exploded is not a hardware change anymore. It's really a software change. So if you're looking at now where we are today, look at coronavirus. Yes, sure, it could have killed us a hundred years ago. It would have, but it didn't. Why? Because in January, we published the genome. A month later, less than a month later, the first vaccine designs were done. And now less than a year later, 10 months later, we already have a working vaccine that's 90% efficient. I mean, that is ridiculous by any standards. And the reason is sharing. So, you know, the asteroid, yes, could wipe us out in 48 years, but 48 years? I mean, look at where we were 48 years ago, technologically. I mean, how much more we understand the basic foundations of space is enormous. The technological revolutions of digitization, the amount of compute power we can put on any, like, you know, nail size, you know, hardware is enormous. So, and this is nowhere near ending. You know, we all have our like little, you know, problems going back and forth on the social side and on the political side and on the cognitive and on the sort of human side and the societal side. But science has not slowed down. Science is moving at a breakneck pace ahead. So, you know, Elon is now putting rockets out from the private space. I mean, that now democratization of space exploration is, you know, gonna revolutionize everything. Of course, in the same way that every technology has exploded, this is the shift to space technology exploding. So, 48 years is infinity from now in terms of space capabilities. So, I'm not worried at all. Are you excited by the possibility of a human, well, one, a human stepping foot on Mars and two, possible colonization of not necessarily Mars, but other planets and all that kind of stuff for people living in space? Inevitable. Inevitable. Inevitable. Would you do it? Or are you kind of like Earth? Of course. Of course. You know, heartbeat. How many people will you wait? Will you wait for, I think it was about when the Declaration of Independence was signed, about two to three million people lived here. So, would you move like before? Would you be like on the first boat? Would you be on the 10th boat? Would you wait until the Declaration of Independence? I don't think I'll be on the short list because I'll be old by then. They'll probably get a bunch of younger people. But you're, it's the wisdom and the- But wisdom can be transferred horizontally. I gotta tell you, you are the lucky one. So, you might be on the list. I don't know. I mean, I kind of feel like I would love to see Earth from above just to watch our planet. I mean, just, I mean, you know, you can watch a live feed of the space station. Watching Earth is magnificent. Like this blue, tiny little shield. It's so thin, our atmosphere. Like if you drive to New York, you're basically in outer space. I mean, it's ridiculous. It's just so thin. And it's just, again, such a privilege to be on this planet. Such a privilege. But I think our species is in for big, good things. I think that, you know, we will overcome our little problems and eventually come together as a species. I feel that we're definitely on the path to that. And, you know, it's just not permeated through the whole universe yet. I mean, through the whole world yet, through the whole Earth yet, but it's definitely permeating. So you've talked about humans as special. How exactly are we special relative to the dinosaurs? So I mentioned that there's, you know, this dramatic cognitive improvement that we've made. But I think it goes much deeper than that. So if you look at a lion attacking a gazelle in the middle of the Serengeti, the lion is smelling the molecules in the environment. Its hormones and neuroreceptors are sort of getting it ready for impulse. The target is constantly looking around and sensing. I've actually been in Kenya, and I've kind of seen the hunt. So I've kind of seen the sort of game of waiting. And the mitochondria in the muscles of the lion are basically ready for, you know, jumping. They're expensing an enormous amount of energy. The grass as it's flowing is constantly transforming solar energy into chloroplasts, you know, through the chloroplasts into energy, which eventually feeds the gazelle and eventually the gazelle. It feeds the gazelle and eventually feeds the lions and so on and so forth. So as humans, we experience all of that. But the lion only experiences one layer. The mitochondria in its body are only experiencing one layer. The chloroplasts are only experiencing one layer. The, you know, photoreceptors and the smell receptors and the chemical receptors, like the lion always attacks against the wind. So that it's not smelled. Like all of these things are one layer at a time. And we humans somehow perceive the whole stack. So going back to software infrastructure and hardware infrastructure, if you design a computer, you basically have a physical layer that you start with. And then on top of that physical layer, you have, you know, the electrical layer. And on top of the electrical layer, you have basically gates and logic and an assembly layer. And on top of the assembly layer, you have your, you know, higher order, higher level programming. And on top of that, you have your deep learning routine, et cetera. And on top of that, you eventually build a cognitive system. That's smart. I want you to now picture this cognitive system becoming not just self-aware, but also becoming aware of the hardware that it's made of and the atoms that it's made of and so on and so forth. So it's as if your AI system, and there's this beautiful scene in 2001, Odyssey of Space, where Hal, after Dave starts disconnecting him, is starting to sing a song about daisies, et cetera. And Hal is basically saying, Dave, I'm losing my mind. I can feel I'm losing my mind. I'm losing my mind. It's just so beautiful. This concept of self-awareness, of knowing that the hardware is no longer there, is amazing. And in the same way, humans who have had accidents are aware that they've had accidents. So there's this self-awareness of AI that is, you know, this beautiful concept about, you know, sort of the eventual cognitive leap to self-awareness. But imagine now the AI system actually breaking through these layers and saying, wait a minute, I think I can design a slightly better hardware to get me functioning better. And that's what basically humans are doing. So if you look at our reasoning layer, it's built on top of a cognitive layer. And the reasoning layer we share with AI. It's kind of cool. Like there is another thing on the planet that can integrate equations and it's man-made, but we share computation with them. We share this cognitive layer. This cognitive layer of playing chess. We're not alone anymore. We're not the only thing on the planet that plays chess. Now we have AI that also plays chess. But in some sense that that particular organism, AI as it is now, only operates in that layer. Exactly. Exactly. And then most animals operate in the sort of cognitive layer that we're all experiencing. A bat is doing this incredible integration of signals, but it's not aware of it. It's basically constantly sending echo location, waves, and it's receiving them back. And multiple bats in the same cave are operating at slightly different frequencies and with slightly different pulses. And they're all sensing objects and they're doing motion planning in their cognitive hardware, but they're not even aware of all of that. All they know is that they have a 3D view of space around them, just like any gazelle walking through the desert. And any baby looking around is aware of things without doing the math of how am I processing all of these visual information, et cetera. You're just aware of the layer that you live in. I think if you look at this, at humanity, we've basically managed through our cognitive layer, through our perception layer, through our senses layer, through our multi-organ layer, through our genetic layer, through our molecular layer, through our atomic layer, through our quantum layer, through even the very fabric of the space-time continuum, unite all of that cognitively. So as we're watching that scene in the Serengeti, we as scientists, we as educated humans, we as anyone who's finished high school are aware of all of this beauty of all of these different layers interplaying together. And I think that's something very unique in, perhaps not just the galaxy, but maybe even the cosmos. These species that has managed to, in space, cross through these layers from the enormous to the infinitely small. And that's what I love about particle physics, the fact that it actually unites everything. The very small and the very big. The very small and the very big. It's only through the very big that the very small gets formed. Like basically every atom of gold like basically every atom of gold results from the fusion that happened of increasingly large particles before that explosion that then disperses it through the cosmos. And it's only through understanding the very large that we understand the very small and vice versa. And that's in space. Then there's the time direction. As you are watching the Kilimanjaro mountain, you can kind of look back through time to when that volcano was exploding and growing out of the tectonic forces. As you drive through Death Valley, you see these mountains on their side and these layers of history exposed. We are aware of the eons that have happened on earth and the tectonic movements on earth. The same way that we're aware of the Big Bang and the early evolution of the cosmos and we can also see forward in time as to where the universe is heading. We can see Apophis in 2068 coming over looking ahead in time. I mean, that would be magician stuff in ancient times. So what I love about humanity and its role in the universe is that if there's a God watching, if there's a God watching, he's like, finally somebody figured it out. I've been building all these beautiful things and somebody can appreciate it. And figured me out from God's perspective, meaning become aware of. So it's kind of interesting to think of the world in this way as layers and us humans are able to convert those layers into ideas that you can then combine. So we're doing some kind of conversion. Exactly, exactly. And last time you asked me about whether we live in a simulation, for example. I mean, realize that we are living in simulation. We are. The reality that we're in without any sort of person programming this is a simulation. Like basically what happens inside your skull? There's this integration of sensory inputs which are translated into perceptory signals which are then translated into a conceptual model of the world around you. And that exercise is happening seamlessly. And yet, if you think about sort of, again, this whole simulation and Neo analogy, you can think of the reality that we live in as a matrix, as the matrix. But we've actually broken through the matrix. We've actually traversed the layers. We didn't have to take a pill. Like we didn't, you know, Morpheus didn't have to show up to basically give us the blue pill or the red pill. We were able to sufficiently evolve cognitively through the hardware explosion and sufficiently involve scientifically through the software explosion to basically get at breaking through the matrix, realizing that we live in a matrix and realizing that we are this thing in there. And yet that thing in there has a consciousness that lives through all these layers. And I think we're the only species. We're the only thing that we even can think of that has actually done that, has sort of permeated space and time, scales and layers of abstraction, plowing through them and realizing what we're really, really made of. And the next frontier is of course, cognition. So we understand so much of the cosmos, so much of the stuff around us, but the stuff inside here, finding the basis for the soul, finding the basis for the ego, for the self, the self-awareness. When does the spark happen that basically sort of makes you, you? I mean, that's really the next frontier. So in terms of these peeling off layers of complexity, somewhere between the cognitive layer and the reasoning layer or the computational layer, there's still some stuff to be figured out there. And I think that's the final frontier of sort of completing our journey through that matrix. And maybe duplicating it in other versions of ourselves through AI, which is another very exciting possibility. What I love about AI and the way that it operates right now is the fact that it is unpredictable. There's emergent behavior in our cognitively capable artificial systems that we can certainly model, but we don't encode directly. And that's a key difference. So we like to say, oh, of course, this is not really intelligent because we coded it up. And we've just put in these little parameters there and there's like, you know, what, six billion parameters. And once you've learned them, you know, we kind of understand the layers. But that's an oversimplification. It's like saying, oh, of course, humans, we understand humans. They're just made out of neurons. And, you know, layers of cortex. And there's a visual area. But every human is encoded by a ridiculously small number of genes compared to the complexity of our cognitive apparatus. 20,000 genes is really not that much, out of which a tiny little fraction are in fact encoding all of our cognitive functions. The rest is emergent behavior. The rest is the, you know, the cortical layers doing their thing in the same way that when we build, you know, these conversational systems or these cognitive systems or these deep learning systems, we put the architecture in place, but then they do their thing. And in some ways that's creating something that has its own identity. That's creating something that's not just, oh yeah, it's not the early AI where if you hadn't programmed what happens in the grocery bags when you have both cold and hot and hard and soft, you know, the system wouldn't know what to do. No, no, you basically now just program the primitives and then it learns from that. So even though the origins are humble, just like it is for our genetic code, for AI, even though the origins are humble, the result of it being deployed into the world is infinitely complex. And that's, and yet it's not yet able to be cognizant of all the other layers of its, you know, it's not able to think about space and time. It's not able to think about the hardware in which it runs, the electricity in which it runs yet. So if you look at humans, we basically have the same cognitive architecture as monkeys, as the great apes. It's just a ton more of it. If you look at GPT-3 versus GPT-2, again, it's the same architecture, just more of it. And yet it's able to do so much more. So if you start thinking about sort of what's the future of that, GPT-4 and GPT-5, do you really need fundamentally different architectures or do you just need a ton more hardware? And we do have a ton more hardware. Like these systems are nowhere near what humans have between our ears. So, you know, there's something to be said about stay tuned for emergent behavior. We keep thinking that general intelligence might just be forever away, but it could just simply be that we just need a ton more hardware and that humans are just not that different from the great apes, except for just a ton more of it. It's interesting that in the AI community, maybe there's a human-centric fear, but the notion that GPT-10 will achieve general intelligence is something that people shy away from, that there has to be something totally different and new added to this. And yet it's not seriously considered that this very simple thing, this very simple architecture, when scaled, might be the thing that achieves superintelligence. It's not. It might be the thing that achieves superintelligence. And people think the same way about humanity and human consciousness. They're like, oh, consciousness might be quantum or it might be, you know, some non-physical thing. And it's like, or it could just be a lot more of the same hardware that now is sufficiently capable of self-awareness just because it has the neurons to do it. So maybe the consciousness that is so elusive is an emergent behavior of, you basically string together all these cognitive capabilities that come from running, from seeing, for reacting, from predicting the movement of a fly as you're catching it through the air. All of these things are just like great lookup tables encoded in a giant neural network. I mean, I'm oversimplifying, of course, the complexity and the diversity of the different types of excitatory and inhibitory neurons, the waveforms that sort of shine through the, you know, the connections across all these different layers, the amalgamation of signals, et cetera. The brain is enormously complex. I mean, of course, but again, it's a small number of primitives encoded by a tiny number of genes, which are self-organized and shaped by their environment. Babies that are growing up today are listening to language from conception. Basically, as soon as the auditory apparatus forms, it's already getting shaped to the types of signals that are out in the real world today. So it's not just like, oh, have an Egyptian be born and then ship them over. It's like, no, that Egyptian would be listening in to the complex of the world and then getting born and sort of seeing just how much more complex the world is. So it's a combination of the underlying hardware, which if you think about as a geneticist, in my view, the hardware gives you an upper bound of cognitive capabilities, but it's the environment that makes those capabilities shine and reach their maximum. So we're a combination of nature and nurture. The nature is our genes and our cognitive apparatus. And the nurture is the richness of the environment that makes that cognitive apparatus reach its potential. And we are so far from reaching our full potential, so far. I think that kids being born 100 years from now, they'll be looking at us now and saying what primitive educational systems they had. I can't believe people were not wired into this virtual reality from birth as we are now, because they're clearly inferior and so on and so forth. So basically, I think that our environment will continue exploding and our cognitive capabilities, it's not like, oh, we're only using 10% of our brain. That's ridiculous. Of course, we're using 100% of our brain, but it's still constrained by how complex our environment is. So the hardware will remain the same, but the software, in a quickly advancing environment, the software will make a huge difference in the nature of the human experience, the human condition. It's fascinating to think that humans will look very different 100 years from now, just because the environment changed, even though we're still the same great apes, the descendant of apes. At the core of this is kind of a notion of ideas that I don't know if you're, there's a lot of people, including you, eloquently about this topic, but Richard Dawkins talks about the notion of memes and this notion of ideas, ideas, you know, multiplying, selecting in the minds of humans. Do you ever think about ideas from that perspective, ideas as organisms themselves that are breeding in the minds of humans? I love the concept of memes. I love the concept of this horizontal transfer of ideas and sort of permeating through, you know, our layer of interconnected neural networks. So you can think of sort of the cognitive space that has now connected all of humanity, where we are now one giant information and idea sharing network, well beyond what was thought to be ever capable when the concept of a meme was created by Richard Dawkins. So, but I want to take that concept just, you know, into another twist, which is the horizontal transfer of humans with fellowships. And the fact that as people apply to MIT from around the world, there's a selection that happens, not just for their ideas, but also for the cognitive hardware that came up with those ideas. So we don't just ship ideas around anymore. They don't evolve in a vacuum. The ideas themselves influence the distribution of cognitive systems, i.e. humans and brains, around the planet. Yeah, we ship them to different locations based on their properties. That's exactly right. So those cognitive systems that think of, you know, physics, for example, might go to CERN. And those that think of genomics might go to the Broad Institute. And those that think of computer science might go to, I don't know, Stanford or CMU or MIT. And you basically have this co-evolution now of memes and ideas and the cognitive conversational systems that love these ideas and feed on these ideas and understand these ideas and appreciate these ideas now coming together. So you basically have students coming to Boston to study because that's the place where these type of cognitive systems thrive. And they're selected based on their cognitive hardware and they're selected based on their cognitive output and their idea output. But once they get into that place, the boiling and interbreeding of these memes becomes so much more frequent. That what comes out of it is so far beyond if ideas were evolving in a vacuum of an already established hardware, cognitive interconnection system of the planet, where now you basically have the ideas shaping the distribution of these systems. And then the genetics kick in as well. You basically have now these people who came to be a student, kind of like myself, who now stuck around and are now professors bringing up our own genetically encoded and genetically related cognitive systems. Mine are eight, six, and three years old, who are now growing up in an environment surrounded by other cognitive systems of a similar age with parents who love these types of thinking and ideas. And you basically have a whole interbreeding now of genetically selected transfer of cognitive systems where the genes and the memes are co-evolving the same soup of ever improving knowledge and societal inter-fertilization, cross-fertilization of these ideas. So this beautiful image, so these are shipping these actual meat cognitive systems to physical locations. They tend to cluster in, the biology ones cluster in a certain building too. So like within that there's clusters on top of clusters, on top of clusters. What about in the online world? Is that, do you also see that kind of, because people now are, form groups on the internet that they stick together. So they can sort of, these cognitive systems can collect themselves and breed together in different layers of spaces. It doesn't just have to be physical space. Absolutely, absolutely. So basically there's the physical rearrangement, but there's also the conglomeration of the same cognitive system. Doesn't need to be, I eat human, doesn't need to belong to only one community. So yes, you might be a member of the computer science department, but you can also hang out in the biology department, but you might also go online into, I don't know, poetry department readings and so on and so forth. Or you might be part of a group that only has 12 people in the world, but that are connected through their ideas and are now interbreeding these ideas in a whole other way. So this co-evolution of the cognitive system and this co-evolution of genes and memes is not just physically instantiated, it's also sort of rearranged in this cognitive space as well. And sometimes these cognitive systems hold conferences and they all gather around and there's like, one of them is like talking and they're all like listening and then they discuss and then they have free lunch and so on. But then that's where you find students where when I go to a conference, I go through the posters where I'm on a mission. Basically my mission is to read and understand what every poster is about. And for a few of them, I'll dive deeply and understand everything, but I make it a point to just go poster after poster in order to read all of them. And I find some gems and students that I speak to that sometimes eventually join my lab. And then sort of you're sort of creating this permeation of transfer of ideas, of ways of thinking and very often of moral values, of social structures, of just more imperceptible properties of these cognitive systems that simply just cling together. Basically, I have the luxury at MIT of not just choosing smart people, but choosing smart people who I get along with, who are generous and friendly and creative and smart and excited and childish in their uninhibited behaviors and so on and so forth. So you basically can choose yourself to surround, you can choose to surround yourself with people who are not only cognitively compatible, but also imperceptibly through the meta cognitive systems compatible. And again, when I say compatible, not all the same. Sometimes, not sometimes, all the time, the teams are made out of complementary components, not just compatible, but very often complementary. So in my own team, I have a diversity of students who come from very different backgrounds. There's a whole spectrum of biology to computation, of course, but within biology, there's a lot of realms, within computation, there's a lot of realms. And what makes us click so well together is the fact that not only do we have a common mission, a common passion, and a common view of the world, but that we're complementary in our skills, in our angles with which we accommodate and so on and so forth. And that's sort of what makes it click. Yeah, it's fascinating that the stickiness of multiple cognitive systems together includes both the commonality, so you meet because there's some common thing, but you stick together because you're different in all the useful ways. Yeah, yeah. And my wife and I, I mean, we adore each other to pieces, but we're also extremely different in many ways. Careful. That's beautiful. She's gonna be listening to this. But I love that about us. I love the fact that I'm living out there in the world of ideas, and I forget what day it is. And she's like, well, at 8 a.m., the kids better be to school. And I do get yelled at, but I need it. Basically, I need her as much as she needs me. And she loves interacting with me and talking. I mean, last night, we were talking about this, and I showed her the questions, and we were bouncing ideas of each other. And it was just beautiful. We basically have these basically cognitive, let it all loose kind of dates, where we just bring papers, and we're bouncing ideas, et cetera. So we have extremely different perspectives, but very common goals and interests. What do you make of the communication mechanism that we humans use to share those ideas? Because one essential element of all of this is not just that we're able to have these ideas, but we're also able to share them. We tend to, maybe you can correct me, but we seem to use language to share the ideas. Maybe we share them in some much deeper way than language, I don't know. But what do you make of this whole mechanism and how fundamental it is to the human condition? So some people will tell you that your language dictates your thoughts, and your thoughts cannot form outside language. I tend to disagree. I see thoughts as much more abstract, as basically when I dream, I don't dream in words. I dream in shapes and forms, and three-dimensional space with extreme detail. I was describing, so when I wake up in the middle of the night, I actually record my dreams. Sometimes I write them down in a Dropbox file. Other times I'll just dictate them in audio. And my wife was giving me a massage the other day because my left side was frozen, and I started playing the recording. And as I was listening to it, I was like, I don't remember any of that. And I was like, of course. And then the entire thing came back. But then there's no way any other person could have recreated that entire sort of three-dimensional shape and dream and concept. And in the same way, when I'm thinking of ideas, there's so many ideas I can't put to words. I mean, I will describe them with a thousand words, but the idea itself is much more precise or much more sort of abstract or much more something different. It's either less abstract or more abstract. And it's either, basically, there's a projection that happens from the three-dimensional ideas into, let's say, a one-dimensional language. And the language certainly gives you the apparatus to think about concepts that you didn't realize existed before. And with my team, we often create new words. I'm like, well, now we're going to call these the regulatory plexus of a gene. And that gives us now the language to sort of build on that as one concept that you then build upon with all kinds of other things. So there's this co-evolution, again, of ideas and language, but they're not one-to-one with each other. Now let's talk about language itself, words. Sentences. This is a very distant construct from where language actually begun. So if you look at how we communicate, as I'm speaking, my eyes are shining, and my face is changing through all kinds of emotions, and my entire body composition posture is reshaped. And my intonation, the pauses that I make, the softer and the louder and the this and that, are conveying so much more information. And if you look at early human language, and if you look at how the great apes communicate with each other, there's a lot of grunting, there's a lot of posturing, there's a lot of emotions, there's a lot of sort of shrieking, et cetera. They have a lot of components of our human language, just not the words. So I think of human communication as combining the ape component, but also of course the GPT-3 component. So basically there's the cognitive layer and the reasoning layer that we share with different parts of our relatives. There's the AI relatives, but there's also the grunting relatives. And what I love about humanity is that we have both. We're not just a conversational system. We're a grunting, grunting, grunting, we're a grunting, emotionally charged, weirdly interconnected system that also has the ability to reason. And when we communicate with each other, there's so much more than just language. There's so much more than just words. It does seem like we're able to somehow transfer even more than the body language. It seems that in the room with us is always a giant knowledge base of shared experiences, different perspectives on those experiences, but I don't know, the knowledge of who the last three, four presidents in the United States was, and just all the 9-11, the tragedies in 9-11, all the beautiful and terrible things that happened in the world, they're somehow both in our minds and somehow enrich the ability to transfer information. And what I love about it is I can talk to you about 2001 Audio Space and mention a very specific scene, and that evokes all these feelings that you had when you first watched it. We're both visualizing that, maybe in different ways. Exactly. And not only that, but the feeling is brought back up, just like you said, with the dreams. We both have that feeling arise in some form as you bring up the account, of a man who's now facing his own mortality. It's fascinating that we're able to do that, but I don't know. Now, let's talk about Neuralink for a second. So what's the concept of Neuralink? The concept of Neuralink is that I'm gonna take whatever knowledge is encoded in my brain, directly transfer it into your brain. So this is a beautiful, fascinating, and extremely appealing concept, but I see a lot of challenges surrounding that. The first one is, we have no idea how to even begin to understand how knowledge is encoded in a person's brain. I mean, I told you about this paper that we had recently with Li Hui Cai and Asaf Marko, that basically was looking at these engrams that are formed with combinations of neurons that co-fire when a stimulus happens, where we can go into a mouse and select those neurons that fire by marking them, and then see what happens when they first fire, and then select the neurons that fire again when the experience is repeated. These are the recall neurons, and then there's the memory consolidation neurons. So we're starting to understand a little bit of sort of the distributed nature of knowledge encoding and experience encoding in the human brain and in the mouse brain. And the concept that we'll understand that sufficiently one day to be able to take a snapshot of, what does that scene from Dave losing his mind, of Hal losing his mind and talking to Dave, how is that scene encoded in your mind? Imagine the complexity of that. But now imagine, suppose that we solve this problem, and the next enormous challenge is, how do I go and modify the next person's brain to now create the same exact neural connections? So that's an enormous challenge right there. So basically it's not just reading, it's now writing. And again, what if something goes wrong? I don't wanna even think about that. That's number two. And number three, who says that the way that you encode, Dave, I'm losing my mind, and I encode, Dave, I'm losing my mind, is anywhere near each other. Basically, maybe the way that I'm encoding it is twisted with my childhood memories of running through the pebbles in Greece, and yours is twisted with your childhood memories of growing up in Russia. And there's no way that I can take my encoding and put it into your brain, because it'll A, mess things up, and B, be incompatible with your own unique experiences. So that's telepathic communications from human to human, that's fascinating. You're reminding us that there's two biological systems on both ends of that communication. The easier, I guess, maybe half as difficult thing to do, and the hope with Neuralink is that we can communicate with an AI system. So where one side of that is a little bit more controllable, but even just that is exceptionally difficult. Like you said. Let's talk about two neuronal systems talking to each other. Suppose that GPT-4 tells GPT-3, hey, give me all your knowledge. Right? It's ready. It's hilarious. I have 10 times more hardware. I'm ready, just feed me. What's GPT-3 gonna do? Is it gonna say, oh, here's my 10 billion parameters? No. No way. The simplest way, and perhaps the fastest way, for GPT-3 to transfer all its knowledge to its older body that has a lot more hardware, is to regenerate every single possible human sentence that it can possibly create. Just keep talking. Keep talking. And just re-encode it all together. So maybe what language does is exactly that. It's taking one generative cognitive model, it's running it forward to emit utterances that kind of make sense in my cognitive frame, and it's re-encoding them into yours through the parsing of that same language. And I think the conversation might actually be the most efficient way to do it. So not just talking, but interactive. So talking back and forth, asking questions, interrupting. So GPT-4 will constantly be interrupted. Just annoyingly. Annoyingly. Yeah. But the beauty of that is also that as we're interrupting each other, there's all kinds of misinterpretations that happen. That, you know, basically when my students speak, I will often know that I'm misunderstanding what they're saying. And I'll be like, hold that thought for a second. Let me tell you what I think I understood, which I know is different from what you said. Then I'll say that. And then someone else in the same Zoom meeting will basically say, well, you know, here's another way to think about what you just said. And then by the third iteration, we're somewhere completely different that if we could actually communicate with full neural network parameters back and forth of that knowledge and idea encoding, would be far inferior because the re-encoding with our own, as we said last time, emotional baggage and cognitive baggage from our unique experiences through our shared experiences, distinct encodings in the context of all our unique experiences is leading to so much more diversity of perspectives. And again, going back to this whole concept of these entire network of all of human cognitive systems connected to each other and sort of how ideas and memes permeate through that, that's sort of what really creates a whole new level of human experience through this reasoning layer and this computational layer that obviously lives on top of our cognitive layer. So you're one of these aforementioned cognitive systems, mortal but thoughtful, and you're connected to a bunch, like you said, students, your wife, your kids. What do you, in your brief time here on earth, this is a Meaning of Life episode. So what do you hope this world will remember you as? What do you hope your legacy will be? I don't think of legacy as much as maybe most people. I think of all things as a legacy. Oh, it's kind of funny. I'm consciously living the present. Many students tell me, oh, give us some career advice. I'm like, I'm the wrong person. I've never made a career plan. I still have to make one. I, it's funny to be both experiencing the past and the present and the future, but also consciously living in the present. And just, you know, there's a conscious decision we can make to not worry about all that, which again goes back to the I'm the lucky one kind of thing. Yeah, exactly. Of living in the present and being happy winning and being happy losing. And there's a certain freedom that comes with that. But again, a certain, you know, ephemerity of living for the present. But if you step back from all of that, where basically my current modus operandi is live for the present, make, you know, every day the best you can make, and just make the local blip of local maxima of the universe, of the awesomeness of the present. And the town and the family that we live in, both academic family and, you know, biological family. Make it a little more awesome by being generous to your friends, being generous to the people around you, being kind to your enemies, and, you know, just showing love all around. You can't be upset at people if you truly love them. If somebody yells at you and insults you every time you say the slightest thing, you can't be upset at them. If somebody yells at you and insults you every time you say the slightest thing, and yet when you see them, you just see them with love, it's a beautiful feeling. It's like, you know, I'm feeling exactly like when I look at my three-year-old who's like screaming. Even though I love her and I want her good, she's still screaming and saying, no, no, no, no, no. And I'm like, I love you, genuinely love you. But I can sort of kind of see that your brain is stuck in that little mode of anger. And, you know, there's plenty of people out there who don't like me, and I see them with love as a child that is stuck in a cognitive state that they're eventually gonna snap out of, or maybe not, and that's okay. So there's that aspect of sort of, you know, experiencing life with the best intentions. And, you know, I love when I'm wrong. I had a friend who was like one of the smartest people I've ever met, who would basically say, oh, I love it when I'm wrong, because it makes me feel human. And it's so beautiful. I mean, she's really one of the smartest people I've ever met. And she was like, oh, it's such a good feeling. And I love being wrong, but there's, you know, there's something about self-improvement. There's something about sort of, how do I not make the most mistakes, but attempt the most rights and do the fewest wrongs, but with the full knowledge that this will happen. That's one aspect. So through this life in the present, what's really funny is, and that's something that I've experienced more and more, really, thanks to you and through this podcast, is this enormous number of people who will basically comment, wow, I've been following this guy for so many years now, or wow, this guy has inspired so many of us in computational biology and so on and so forth. And I'm like, I don't know any of that, but I'm only discovering this now through this sort of sharing our emotional states and our cognitive states with a wider audience, where suddenly I'm sort of realizing that, wow, maybe I've had a legacy. Like basically I've trained generations of students from MIT, and I've put all of my courses freely online since 2001. So basically all of my video recordings of my lectures have been online since 2001. So countless generations of people from across the world will meet me at a conference and say, like I was at this conference where somebody heard my voice and it's like, I know this voice, I've been listening to your lectures. And it's just such a beautiful thing where we're sharing why we're doing this, like we're sharing widely and who knows which students will get where from whatever they catch out of these lectures, even if what they catch is just inspiration and passion and drive. So there's this intangible legacy, quote unquote, that every one of us has through the people we touch. One of my friends from undergrad basically told me, oh, my mom remembers you vividly from when she came to campus. I'm like, I didn't even meet her. She's like, no, but she sort of saw you interacting with people and said, wow, he's exuding this positive energy. And there's that aspect of sort of just motivating people with your kindness, with your passion, with your generosity and with your just selflessness of just give, it doesn't matter where it goes. I've been to conferences where basically people, I'll ask them a question and then they'll come back to, or there was a conference where I asked somebody a question. They said, oh, in fact, this entire project was inspired by your question three years ago at the same conference. I'm like, wow. And then on top of that, there's also the ripple effect. So you're speaking to the direct influence of inspiration or education, but there's also the follow-on things that happen to that. And there's this ripple that through, from you just this one individual. And from every one of us, from everyone. That's what I love about humanity. The fact that every one of us shares genes and genetic variants with very recent ancestors with everyone else. So even if I die tomorrow, my genes are still shared through my cousins and through my uncles and through my immediate family. And of course I'm lucky enough to have my own children, but even if you don't, your genes are still permeating through all of the layers of your family. So your genes will have the legacy there, yeah. For every one of us. Yeah. Number two, our ideas are constantly intermingling with each other. So there's no person living in the planet a hundred years from now, who will not be directly impacted by every one of the planet living here today. Yeah. Through genetic inheritance and through meme inheritance. That's cool to think that your ideas, Manolis Callas, would touch every single person on this planet. It's interesting. But not just mine. Joe Smith, who's looking at this right now, his ideas will also touch everybody. So there's this interconnectedness of humanity. And then I'm also a professor. So my day job is legacy. My day job is training, not just the thousands of people who watch my videos on the web, but the people who are actually in my class, who basically come to MIT to learn from a bunch of us. Like the cognitive systems that were shipped to this particular location. And who will then disperse back into all of their home countries. That's what makes America the beacon of the world. We don't just export goods, we export people. Cognitive systems. We export people who are born here. And we also export training that people born elsewhere will come here to get. And will then disseminate not just whatever knowledge they got, but whatever ideals they learned. And I think that's something, that's a legacy of the US, that you cannot stop with political isolation. You cannot stop with economic isolation. That's something that will continue to happen through all the people we've touched through our universities. So there's the students who took my classes, who are basically now going off and teaching their classes. And I've trained generations of computational biologists. No one in genomics who's gone through MIT hasn't taken my class. So basically there's this impact through, I mean, there's so many people in biotechs who are like, hey, I took your class. That's what got me into the field like 15 years ago. And it's just so beautiful. And then there's the academic family that I have. So the students who are actually studying with me, who are my trainees. So this sort of mentorship of ancient Greece. So I basically have an academic family and we are a family. There's this such strong connection, this bond of you're part of the Kelly's family. So I have a biological family at home and I have an academic family on campus. And that academic family has given me great grandchildren already. So I've trained people who are now professors at Stanford, CMU, Harvard, Wash U, I mean, everywhere in the world. And these people have now trained people who are now having their own faculty jobs. So there's basically people who see me as their academic grandfather. And it's just so beautiful because you don't have to wait for the 18 years of cognitive hardware development to sort of have amazing conversation with people. These are fully grown humans, fully grown adults who are cognitively super ready and who are shaped by, and I see some of these beautiful papers and I'm like, I can see the touch of our lab in those papers. It's just so beautiful. Cause you're like, I've spent hours with these people teaching them, not just how to do a paper, but how to think. And this whole concept of, the first paper that we write together is an experience with every one of these students. So I always tell them to write the whole first draft and they know that I will rewrite every word. But the act of them writing it and what I do is these like joint editing sessions where I'm like, let's co-edit. And with this co-editing, we basically have- Creative destruction. So I share my Zoom screen and I'm just thinking out loud as I'm doing this. And they're learning from that process as opposed to like come back two days later and they see a bunch of red on a page. I'm sort of, well, that's not how you write this. That's not how you think about this. That's not, you know, what's the point? Like this morning I was having, yes, this morning between six and 8 a.m. I had a two hour meeting. Going through one of these papers and then saying, what's the point here? Why do you even show that? It's just a bunch of points on a graph. No, what you have to do is extract the meaning, do the homework for them. And there's this nurturing, this mentorship that sort of creates now a legacy, which is infinite because they've now gone off on the, you know, and all of that is just humanity. Then, of course, there's the papers I write. Because yes, my day job is training students, but it's a research university. The way that they learn is through the mens and manus, mind and hand. It's the practical training of actually doing research. And that research is a beneficial side effect of having these awesome papers that will now tell other people how to think. There's this paper we just posted recently on MedArchive, and one of the most generous and eloquent comments about it was like, wow, this is a masterclass in scientific writing, in analysis, in biological interpretation, and so forth. It's just so fulfilling from a person I've never met. Or heard of that. Can you say the title of the paper, Brian? I don't remember the title, but it's single cell dissection of schizophrenia reveals, and so the two points that we found was this whole transcriptional resilience. Like there's some individuals who are schizophrenic, but who's, they have an additional cell type or initial cell state, which we believe is protective. And that cell state, when they have it, will cause other cells to have normal gene expression patterns. It's just beautiful. And then that cell is connected with some of the people who are in the hospital, with some of the PV intraneurons that are basically sending these inhibitory brain waves through the brain. And basically there's another component of, there's a set of master regulators that we discovered who are controlling many of the genes that are differentially expressed. And these master regulators are themselves genetic targets of schizophrenia. And they are themselves involved in both synaptic connectivity and also in early brain development. So there's this sort of interconnectedness between synaptic development axis and also this transcriptional resilience. So I mean, we basically made up a title that combines all these concepts. You have all these concepts, all these people working together, and ultimately these minds condense it down into a beautifully written little document that lives on forever. Exactly, and that document now has its own life. Yeah. Our work has 120,000 citations. I mean, that's not just people who read it. These are people who used it to write something based on it. Yeah. I mean, that to me is just so fulfilling to basically say, wow, I've touched people. So I don't think of my legacy as I live every day. I just think of the beauty of the present and the power of interconnectedness. And just, I feel like a kid in a candy shop where I'm just like constantly, you know, where do I, what package do I open first? And, you know, this- You're the lucky one. A jack of all trades, a master of none. I think for a Meaning of Life episode, we would be amiss if we did not have at least a poem or two. Do you mind if we end in a couple of poems? Maybe a happy, maybe a sad one. I would love that. So thank you for the luxury. The first one is kind of, I remember when you were talking with Eric Weinstein about this comment of Leonard Cohen that says, but you don't really care for music, do you? Yeah. In Hallelujah. That's basically kind of like mocking its reader. Yeah. So one of my poems is a little like that. So I had just broken up with, you know, my girlfriend and there's this other friend who was coming to visit me and she said, I will not come unless you write me a poem. And I was like, writing a poem on demand. So this poem is called Write Me a Poem. It goes, write me a poem, she said with a smile. Make sure it's pretty, romantic and rhymes. Make sure it's worthy of that bold flame that love uniting us beyond a mere game. And she took off without more words, rushed for the bus and traveled the world. A poem, I thought, this is sublime. What better way for passing the time? What better way to count up the hours before she comes back to my lonely tower? Waiting for joy to fill up my heart. Let's write a poem for when we're apart. How does a poem start? I inquired. Give me a topic, cook up a style. Throw in some cute words, oh, here and there. Throw in some passion, love and despair. Love, three eggs, one pound of flour, three cups of water and bake for an hour. Love is no recipe as I understand. You can't just cook up a poem on demand. And as I was twisting all this in my mind, I looked at the page, by golly, it rhymed. Three roses, white chocolate, vanilla powder, some beautiful rhymes and maybe a flower. No, be romantic, the young girl insisted. Do this, do that, don't be so silly. You must believe it straight from your heart. If you don't feel it, we're better apart. Oh, my sweet thing, what can I say? You bring me the sun all night and all day. You're the stars and the moon and the birds way up high. You're my evening sweet song, my morning blue sky. You are my muse, your spell has me caught. You bring me my voice and scatter my thoughts. To put out love in writing, in vain I can try. But when I'm with you, my wings want to fly. So I put down the pen and drop my defenses, give myself to you and fill up my senses. The Baffled King composing, that was beautiful. What I love about it is that I did not bring up a dictionary of rhymes, I did not sort of work hard. So basically when I write down a rhyme, I don't work hard, so basically when I write poems, I just type, I never go back, I just. So when my brain gets into that mode, it actually happens like I wrote it. Oh, wow, so the rhyme just kind of, it's an emergent phenomenon. It's an emergent phenomenon. I just get into that mode and then it comes out. That's a beautiful one. And it's basically, you know, as you got it, it's basically saying it's not a recipe and then I'm throwing in the recipes and as I'm writing it, I'm like, you know, so it's very introspective in this whole concept. So anyway, there's another one many years earlier that is, you know, darker. It's basically this whole concept of let's be friends. I was like, ugh, you know, no let's be friends. Just like, you know, so the last words are shout out, I love you or send me to hell. So the title is Burn Me Tonight. Lie to me, baby. Lie to me now. Tell me you love me. Break me a vow. Give me a sweet word, a promise, a kiss. Give me the world, a sweet taste to miss. Don't let me lay here, inert, ugly, cold. With nothing sweet felt and nothing harsh told. Give me some hope, false, foolish, yet kind. Make me regret, I'll leave you behind. Don't pity my soul, but torture it right. Treat it with hatred, start up a fight. For it's from mildness that my soul dies. When you cover your passion in a bland friend's disguise. Kiss me now, baby, show me your passion. Turn off the lights and rip off your fashion. Give me my life's joy this one night. Burn all my matches for one blazing light. Don't think of tomorrow and let today fade. Don't try and protect me from love's cutting blade. Your razor will always rip off my veins. Don't spare me the passion to spare me the pains. Kiss me now, honey, or spit in my face. Throw me an insult I'll gladly embrace. Tell me now clearly that you never cared. Say it now loudly like you never dared. I'm ready to hear it. I'm ready to die. I'm ready to burn and start a new life. I'm ready to face the rough burning truth. Rather than waste the rest of my youth. So tell me, my lover, should I stay or go? The answer to love is one, yes or no. There's no I like you, no let's be friends. Shout out I love you or send me to hell. I don't think there's a better way to end a discussion of the meaning of life. Whatever the heck the meaning is, go all in as that poem says. Manolis, thank you so much for talking today. Thanks, I look forward to next time. Thanks for listening to this conversation with Manolis Kellis. And thank you to our sponsors. Grammarly, which is a service for checking spelling, grammar, sentence structure, and readability. Athletic Greens, the all-in-one drink that I start every day with to cover all my nutritional bases. Cash App, the app I use to send money to friends. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now let me leave you with some words from Douglas Adams in his book, Hitchhiker's Guide to the Galaxy. On the planet Earth, man had always assumed that he was more intelligent than dolphins because he had achieved so much. The wheel, New York, wars, and so on. Whilst all the dolphins had ever done was muck about in the water having a good time. But conversely, the dolphins had always believed that they were far more intelligent than man for precisely the same reasons. Thank you for listening. I hope to see you next time.

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Nicole Perlroth: Cybersecurity and the Weapons of Cyberwar | Lex Fridman Podcast #266

If one site is hacked, you can just unleash all hell. We have stumbled into this new era of mutually assured digital destruction. How far are people willing to go? You can capture their location, you can capture their contacts that record their telephone calls, record their camera without them knowing about it. Basically, you can put an invisible ankle bracelet on someone without them knowing. You could sell that to a zero-day broker for $2 million. The following is a conversation with Nicole Perleroth, cybersecurity journalist and author of This Is How They Tell Me The World Ends, The Cyber Weapons Arm Race. This is the Alex Friedman Podcast. To support it, please check out our sponsors in the description. And now, dear friends, here's Nicole Perleroth. You've interviewed hundreds of cybersecurity hackers, activists, dissidents, computer scientists, government officials, forensic investigators, and mercenaries. So let's talk about cybersecurity and cyber war. Start with the basics. What is a zero-day vulnerability? And then a zero-day exploit or attack? So at the most basic level, let's say I'm a hacker and I find a bug in your iPhone iOS software that no one else knows about, especially Apple. That's called a zero-day because the minute it's discovered, engineers have had zero days to fix it. If I can study that zero-day, I could potentially write a program to exploit it. And that program would be called a zero-day exploit. And for iOS, the dream is that you craft a zero-day exploit that can remotely exploit someone else's iPhone without them ever knowing about it. And you can capture their location, you can capture their contacts that record their telephone calls, record their camera without them knowing about it. Basically, you can put an invisible ankle bracelet on someone without them knowing. And you can see why that capability, that zero-day exploit would have immense value for a spy agency or a government that wants to monitor its critics or dissidents. And so there's a very lucrative market now for zero-day exploits. So you said a few things there. One is iOS, why iOS? Which operating system? Which one is the sexiest thing to try to get to or the most impactful thing? And the other thing you mentioned is remote versus having to actually come in physical contact with it. Is that the distinction? So iPhone exploits have just been a government's number one priority. Recently, actually, the price of an Android remote zero-day exploit, something that can get you into Android phones, is actually higher. The value of that is now higher on this underground market for zero-day exploits than an iPhone iOS exploit. So things are changing. So there's probably more Android devices, so that's why it's better. But on the iPhone side, so I'm an Android person, because I'm a man of the people. But it seems like all the elites use iPhone, all the people at nice dinner parties. So is that the reason that the more powerful people use iPhones? Is that why? I don't think so. I actually, so it was about two years ago that the prices flipped. It used to be that if you could craft a remote zero-click exploit for iOS, then that was about as good as it gets. You could sell that to a zero-day broker for $2 million. The caveat is you can never tell anyone about it, because the minute you tell someone about it, Apple learns about it, they patch it in that $2.5 million investment that that zero-day broker just made goes to dust. So a couple years ago, and don't quote me on the prices, but an Android zero-click remote exploit for the first time topped the iOS. And actually, a lot of people's read on that was that it might be a sign that Apple's security was falling, and that it might actually be easier to find an iOS zero-day exploit than find an Android zero-day exploit. The other thing is market share. There are just more people around the world that use Android. And a lot of governments that are paying top dollar for zero-day exploits these days are deep-pocketed governments in the Gulf that wanna use these exploits to monitor their own citizens, monitor their critics. And so it's not necessarily that they're trying to find elites. It's that they wanna find out who these people are that are criticizing them or perhaps planning the next Arab Spring. So in your experience, are most of these attacks targeted to cover a large population, or is there attacks that are targeted toward specific individuals? So I think it's both. Some of the zero-day exploits that have fetched top dollar that I've heard of in my reporting in the United States were highly targeted. There was a potential terrorist attack. They wanted to get into this person's phone. It had to be done in the next 24 hours. They approached hackers and say, "'We'll pay you X millions of dollars if you can do this.'" But then you look at, when we've discovered iOS zero-day exploits in the wild, some of them have been targeting large populations like Uyghurs. So a couple of years ago, there was a watering hole attack. Okay, what's a watering hole attack? There was a website. It was actually, it had information aimed at Uyghurs, and you could access it all over the world. And if you visited this website, it would drop an iOS zero-day exploit onto your phone. And so anyone that visited this website that was about Uyghurs, anywhere, I mean, Uyghurs living abroad, basically the Uyghur diaspora, would have gotten infected with this zero-day exploit. So in that case, they were targeting huge swaths of this one population or people interested in this one population basically in real time. Who are these attackers? From the individual level to the group level, psychologically speaking, what's their motivation? Is it purely money? Is it the challenge? Are they malevolent? Is it power? These are big philosophical human questions, I guess. So these are the questions I set out to answer for my book. I wanted to know, are these people that are just after money? If they're just after money, how do they sleep at night not knowing whether that zero-day exploit they just sold to a broker is being used to basically make someone's life a living hell? And what I found was there's kind of this long-sorted history to this question. It started out in the 80s and 90s when hackers were just finding holes and bugs in software for curiosity's sake, really as a hobby. And some of them would go to the tech companies like Microsoft or Sun Microsystems at the time, or Oracle. And they'd say, hey, I just found this zero-day in your software and I can use it to break into NASA. And the general response at the time wasn't, thank you so much for pointing out this flaw and our software will get it fixed as soon as possible. It was, don't ever poke around our software ever again, or we'll stick our general counsel on you. And that was really sort of the common thread for years. And so hackers who set out to do the right thing were basically told to shut up and stop doing what you're doing. And what happened next was, they basically started trading this information online. Now, when you go back and interview people from those early days, they all tell a very similar story, which is they're curious, they're tinkers. They remind me of like the kid down the street or like the kid down the block that was constantly poking around the hood of his dad's car. They just couldn't help themselves. They wanted to figure out how a system is designed and how they could potentially exploit it for some other purpose. It doesn't have to be good or bad. But they were basically kind of beat down for so long by these big tech companies that they started just silently trading them for hackers and that's how you got these really heated debates in the 90s about disclosure. Should you just dump these things online? Because any script kiddie can pick them up and use it for all kinds of mischief. But don't you wanna just stick a middle finger to all these companies that are basically threatening you all the time? So there was this really interesting dynamic at play. And what I learned in the course of doing my book was that government agencies and their contractors sort of tapped into that frustration and that resentment. And they started quietly reaching out to hackers on these forums. And they said, hey, you know that zero day you just dropped online? Could you come up with something custom for me? And I'll pay you six figures for it so long as you shut up and never tell anyone that I paid you for this. And that's what happened. So throughout the 90s, there was a bunch of boutique contractors that started reaching out to hackers on these forums and saying, hey, I'll pay you six figures for that bug you were trying to get Microsoft to fix for free. And sort of so began or so catalyzed this market where governments and their intermediaries started reaching out to these hackers and buying their bugs for free. And in those early days, I think a lot of it was just for quiet counterintelligence, traditional espionage. But as we started baking the software, Windows software, Schneider Electric, Siemens Industrial Software into our nuclear plants and our factories and our power grid and our petrochemical facilities and our pipelines, those same zero days came to be just as valuable for sabotage and war planning. Does the fact that the market sprung up and you can now make a lot of money change the nature of the attackers that came to the table or grow the number of attackers? I mean, what is, I guess, you told the psychology of the hackers in the 90s, what is the culture today and where is it heading? So I think there are people who will tell you they would never sell a zero day to a zero day broker or a government. One, because they don't know how it's gonna get used when they throw it over the fence. Most of these get rolled into classified programs and you don't know how they get used. If you sell it to a zero day broker, you don't even know which nation state might use it or potentially which criminal group might use it if you sell it on the dark web. The other thing that they say is that they wanna be able to sleep at night and they lose a lot of sleep if they found out their zero day was being used to make a dissidence life living hell. But there are a lot of people, good people, who also say, no, this is not my problem. This is the technology company's problem. If they weren't writing new bugs into their software every day, then there wouldn't be a market, then there wouldn't be a problem. But they continue to write bugs into their software all the time and they continue to profit off that software. So why shouldn't I profit off my labor too? And one of the things that has happened, which is I think a positive development over the last 10 years, are bug bounty programs. Companies like Google and Facebook and then Microsoft and finally Apple, which resisted it for a really long time, have said, okay, we are gonna shift our perspective about hackers. We're no longer going to treat them as the enemy here. We're going to start paying them for what it's essentially free quality assurance. And we're gonna pay them good money in some cases, six figures in some cases. We're never gonna be able to bid against a zero day broker who sells to government agencies, but we can reward them and hopefully get to that bug earlier where we can neutralize it so that they don't have to spend another year developing the zero day exploit. And in that way, we can keep our software more secure. But every week I get messages from some hacker that says, I tried to see this zero day exploit that was just found in the wild, being used by this nation state. I tried to tell Microsoft about this two years ago and they were gonna pay me peanuts. So it never got fixed. There are all sorts of those stories that can continue on. And I think just generally, hackers are not very good at diplomacy. They tend to be pretty snipey, technical, crowd, and very philosophical in my experience, but diplomacy is not their strong suit. There almost has to be a broker between companies and hackers where you can translate effectively, just like you have a zero day broker between governments and hackers. You have to speak their language. Yeah, and there have been some of those companies who've risen up to meet that demand. And HackerOne is one of them. BugCrowd is another. Synack has an interesting model. So that's a company that you pay for a private bug bounty program, essentially. So you pay this company. They tap hackers all over the world to come hack your software, hack your system. And then they'll quietly tell you what they found. And I think that's a really positive development. And actually, the Department of Defense hired all three of those companies I just mentioned to help secure their systems. Now, I think they're still a little timid in terms of letting those hackers into the really sensitive, high-side classified stuff, but baby steps. Just to understand what you were saying, you think it's impossible for companies to financially compete with the zero-day brokers with governments. So the defense can't outpay the hackers? It's interesting. They shouldn't outpay them because what would happen if they started offering $2.5 million at Apple for any zero-day exploit that governments would pay that much for is their own engineers would say, why the hell am I working for less than that and doing my nine to five every day? So you would create a perverse incentive. And I didn't think about that until I started this research and I realized, okay, yeah, that makes sense. You don't want to incentivize offense so much that it's to your own detriment. And so I think what they have, though, what the companies have on government agencies is if they pay you, you get to talk about it. You get the street cred. You get to brag about the fact you just found that $2.5 million iOS zero-day that no one else did. And if you sell it to a broker, you never get to talk about it. And I think that really does eat at people. Can I ask you a big philosophical question about human nature here? So if you have, in what you've seen, if a human being has a zero-day, they found a zero-day vulnerability that can hack into, I don't know, what's the worst thing you can hack into? Something that could launch nuclear weapons. Which percentage of the people in the world that have the skill would not share that with anyone, with any bad party? I guess how many people are completely devoid of ethical concerns in your sense? So my belief is all the ultra-competent people, or very, very high percentage of ultra-competent people are also ethical people. That's been my experience. But then again, my experience is narrow. What's your experience been like? So this was another question I wanted to answer. Who are these people who would sell a zero-day exploit that would neutralize a Schneider Electric safety lock at a petrochemical plant? Basically the last thing you would need to neutralize before you trigger some kind of explosion. Who would sell that? And I got my answer, well, the answer was different. A lot of people said, I would never even look there because I don't even wanna know. I don't even wanna have that capability. I don't even wanna have to make that decision about whether I'm gonna profit off of that knowledge. I went down to Argentina and this whole kind of moral calculus I had in my head was completely flipped around. So just to back up for a moment. So Argentina actually is a real hacker's paradise. People grew up in Argentina and I went down there, I guess I was there around 2015, 2016, but you still couldn't get an iPhone. They didn't have Amazon Prime. You couldn't get access to any of the apps we all take for granted. To get those things in Argentina as a kid, you have to find a way to hack them. And the whole culture is really like a hacker culture. They say it's really like a MacGyver culture. You have to figure out how to break into something with wire and tape. And that means that there are a lot of really good hackers in Argentina who specialize in developing zero-day exploits. And I went down to this Argentina conference called Echo Party. And I asked the organizer, okay, can you introduce me to someone who's selling zero-day exploits to governments? And he was like, just throw a stone. Throw a stone anywhere and you're gonna hit someone. And all over this conference, you saw these guys who were clearly from these Gulf states who only spoke Arabic. What are they doing at a young hacking conference in Buenos Aires? And so I went out to lunch with kind of this godfather of the hacking scene there and I asked this really dumb question and I'm still embarrassed about how I phrased it. But I said, so, you know, well, these guys only sell these zero-day exploits to good Western governments. And he said, Nicole, last time I checked, the United States wasn't a good Western government. You know, the last country that bombed another country into oblivion wasn't China or Iran. It was the United States. So if we're gonna go by your whole moral calculus, you know, just know that we have a very different calculus down here and we'd actually rather sell to Iran or Russia or China, maybe, than the United States. And that just blew me away. Like, wow. You know, he's like, well, just sell to whoever brings us the biggest bag of cash. Have you checked into our inflation situation recently? So, you know, I had some of those like reality checks along the way. You know, we tend to think of things as, is this moral, you know, is this ethical, especially as journalists. You know, we kind of sit on our high horse sometimes and write about a lot of things that seem to push the moral bounds. But in this market, which is essentially an underground market, that, you know, the one rule is like Fight Club, you know, no one talks about Fight Club. First rule of the zero-day market, nobody talks about the zero-day market on both sides because the hacker doesn't wanna lose their $2.5 million bounty. And governments roll these into classified programs and they don't want anyone to know what they have. So no one talks about this thing. And when you're operating in the dark like that, it's really easy to put aside your morals sometimes. Can I, as a small tangent, ask you, by way of advice, you must have done some incredible interviews. And you've also spoken about how serious you take protecting your sources. If you were to give me advice for interviewing when you're recording on mic with a video camera, how is it possible to get into this world? Like, is it basically impossible? So you've spoken with a few people, what is it, like the godfather of cyber war, cybersecurity? So people that are already out. And they still have to be pretty brave to speak publicly. But is it virtually impossible to really talk to anybody who's a current hacker? You're always like 10, 20 years behind? It's a good question. And this is why I'm a print journalist. But, you know, a lot, when I've seen people do it, it's always the guy who's behind the shadows, whose voice has been altered. You know, when they've gotten someone on camera, that's usually how they do it. You know, very, very few people talk in this space. And there's actually a pretty well known case study in why you don't talk publicly in this space and you don't get photographed. And that's the gruck. So, you know, the gruck is or was this zero day broker, South African guy, lives in Thailand. And right when I was starting on this subject at the New York Times, he'd given an interview to Forbes. And he talked about being a zero day broker. And he even posed next to this giant duffel bag filled with cash, ostensibly. And later he would say he was speaking off the record, he didn't understand the rules of the game. But what I heard from people who did business with him was that the minute that that story came out, he became PNG'd. No one did business with him. You know, his business plummeted by at least half. No one wants to do business with anyone who's gonna get on camera and talk about how they're selling zero days to governments. It puts you at danger. And I did hear that he got some visits from some security folks. And, you know, it's another thing for these people to consider. If they have those zero day exploits at their disposal, they become a huge target for nation states all over the world. You know, talk about having perfect OPSEC. You know, you better have some perfect OPSEC if people know that you have access to those zero day exploits. Which sucks because, I mean, transparency here would be really powerful for educating the world. And also inspiring other engineers to do good. It just feels like when you're operating in shadows, it doesn't help us move in the positive direction in terms of like getting more people on the defense side versus on the attack side. But of course, what can you do? I mean, the best you can possibly do is have great journalists, just like you did, interview and write books about it. And integrate the information you get while hiding the sources. Yeah, and I think, you know, what HackerOne has told me was, okay, let's just put away the people that are finding and developing zero day exploits all day long. Let's put that aside. What about the, you know, however many millions of programmers all over the world who've never even heard of a zero day exploit? Why not tap into them and say, hey, we'll start paying you if you can find a bug in United Airlines software or in Schneider Electric or in Ford or Tesla. And I think that is a really smart approach. Let's go find this untapped army of programmers to neutralize these bugs before the people who will continue to sell these to governments can find them and exploit them. Okay, I have to ask you about this from a personal side. It's funny enough, after we agreed to talk, I've gotten, for the first time in my life, was a victim of a cyber attack. So this is ransomware, it's called Deadbolt. People can look it up. I have a QNAP device for basically kind of coldish storage. So it's about 60 terabytes with 50 terabytes of data on it in RAID 5 and apparently about four to 5,000 QNAP devices were hacked and taken over with this ransomware. And what ransomware does there is it goes file by file, almost all the files on the QNAP storage device and encrypts them. And then there's this very eloquently and politely written page that pops up. It describes what happened. All your files have been encrypted. This includes, but is not limited to, photos, documents, and spreadsheets. Why me? This is, a lot of people commented about how friendly and eloquent this is. And I have to commend them. It is, and it's pretty user-friendly. Why me? This is not a personal attack. You have been targeted because of the inadequate security provided by your vendor, QNAP. What now? You can make a payment of exactly 0.03 Bitcoin, which is about a thousand dollars, to the following address. Once the payment has been made, we'll follow up with transaction to the same address, blah, blah, blah. They give you instructions of what happens next and they'll give you a decryption key that you can then use. And then there's another message for QNAP that says, all your affected customers have been targeted using a zero-day vulnerability in your product. We offer you two options to mitigate this and future damage. One, make a Bitcoin payment of five Bitcoin to the following address, and that will reveal to QNAP the, I'm summarizing things here, what the actual vulnerability is. Or you can make a Bitcoin payment of 50 Bitcoin to get a master decryption key for all your customers. 50 Bitcoin is about $1.8 million. $1.8 million. Okay. So first of all, on a personal level, this one hurt for me. There's, I mean, I learned a lot because I wasn't, for the most part, backing up much of that data because I thought I can afford to lose that data. It's not like horrible. I mean, I think you've spoken about the crown jewels, like making sure there's things you really protect. And I have, I'm very conscious security-wise on the crown jewels. But there's a bunch of stuff, like personal videos. They're not, I don't have anything creepy, but just fun things I did that because they were very large or 4K or something like that, I kept them on there, thinking RAID 5 will protect it. And just, I lost a bunch of stuff, including raw footage from interviews and all that kind of stuff. So it's painful. And I'm sure there's a lot of painful stuff like that for the four to 5,000 people that use QNAP. And there's a lot of interesting ethical questions here. Do you pay them? Does QNAP pay them? Do the individuals pay them? Especially when you don't know if it's going to work or not. Do you wait? So QNAP said that please don't pay them. We're working very hard day and night to solve this. It's so philosophically interesting to me because I also project onto them thinking, what is their motivation? Because the way they phrased it on purpose, perhaps, but I'm not sure if that actually reflects their real motivation, is maybe they're trying to help themselves sleep at night. Basically saying, this is not about you. This is about the company, the vulnerability. It's just like you mentioned, this is the justification they have. But they're hurting real people. They hurt me, but I'm sure there's a few others that are really hurt. And the zero day factor is a big one. QNAP right now is trying to figure out what the hell is wrong with their system that would let this in. And even if they pay, if they still don't know where the zero day is, what's to say that they won't just hit them again and hit you again? So that really complicates things. And that is a huge advancement for ransomware. It's really only been, I think, in the last 18 months that we've ever really seen ransomware exploit zero days to pull these off. Usually 80% of them, I think the data shows 80% of them come down to a lack of two-factor authentication. So when someone gets hit by a ransomware attack, they don't have two-factor authentication on, their employees were using stupid passwords. You can mitigate that in the future. This one, they don't know. They probably don't know. Yeah, and it was, I guess it's zero click because I didn't have to do anything. The only thing, well, here's the thing. I did basics of, I put it behind a firewall, I followed instructions. But I didn't really pay attention. So maybe there's a misconfiguration of some sort that's easy to make. It's difficult when you have a personal NAS. So I'm not willing to say that I did everything I possibly could. But I did a lot of reasonable stuff and they still hit it with zero clicks. I didn't have to do anything. Yeah, well, it's like a zero day and it's a supply chain attack. You're getting hit from your supplier. You're getting hit because of your vendor. And it's also a new thing for ransomware groups to go to the individuals to pressure them to pay. There was this really interesting case, I think it was in Norway, where there was a mental health clinic that got hit. And the cyber criminals were going to the patients themselves to say, pay this or we're going to release your psychiatric records. I mean, talk about hell. In terms of whether to pay, that is on the cheaper end of the spectrum. From the individual or from the company? Both. We've seen, for instance, there was an Apple supplier in Taiwan. They got hit and the ransom demand was 50 million. I'm surprised it's only 1.8 million. I'm sure it's gonna go up. And it's hard. There's obviously governments, and maybe in this case, the company are gonna tell you, we recommend you don't pay or please don't pay. But the reality on the ground is that some businesses can't operate. Some countries can't function. I mean, the under-reported storyline of colonial pipeline was after the company got hit and took the preemptive step of shutting down the pipeline because their billing systems were frozen. They couldn't charge customers downstream. My colleague, David Singer, and I got our hands on a classified assessment that said that as a country, we could have only afforded two to three more days of colonial pipeline being down. And it was really interesting. I thought it was the gas and the jet fuel, but it wasn't. You know, we were sort of prepared for that. It was the diesel. Without the diesel, the refineries couldn't function, and it would have totally screwed up the economy. And so there was almost this national security, economic impetus for them to pay this ransom. And the other one I always think about is Baltimore. You know, when the city of Baltimore got hit, I think the initial ransom demand was something around 76,000. It may have even started smaller than that. And Baltimore stood its ground and didn't pay, but ultimately the cost to remediate was $18 million. It's a lot for the city of Baltimore. That's money that could have gone to public school education and roads and public health. And instead, it just went to rebuilding these systems from scratch. And so a lot of residents in Baltimore were like, why the hell didn't you pay the $76,000? So it's not obvious. You know, it's easy to say don't pay, because why you're funding their R&D for the next go-round. But it's too often, it's too complicated. So on the individual level, just like, you know, the way I feel personally from this attack, have you talked to people that were kind of victims in the same way I was, but maybe more dramatic ways or so on? You know, in the same way that violence hurts people? Yeah. How much does this hurt people in your sense, and the way you researched it? The worst ransomware attack I've covered on a personal level was an attack on a hospital in Vermont. And you know, you think of this as like, okay, it's hitting their IT networks. They should still be able to treat patients. But it turns out that cancer patients couldn't get their chemo anymore, because the protocol of who gets what is very complicated. And without it, nurses and doctors couldn't access it. So they were turning chemo patients away, cancer patients away. One nurse told us, I don't know why people aren't screaming about this, that the only thing I've seen that even compares to what we're seeing at this hospital right now was when I worked in the burn unit after the Boston Marathon bombing. You know, they really put it in these super dramatic terms. And last year, there was a report in the Wall Street Journal where they attributed an infant death to a ransomware attack because a mom came in and whatever device they were using to monitor the fetus wasn't working because of the ransomware attack. And so they attributed this infant death to the ransomware attack. Now on a bigger scale, but less personal, when there was the NotPetya attack. So this was an attack by Russia on Ukraine that came at them through a supplier, a tax software company in that case, that didn't just hit any government agency or business in Ukraine that used this tax software. It actually hit any business all over the world that had even a single employee working remotely in Ukraine. So it hit Maersk, the shipping company, but hit Pfizer, hit FedEx, but the one I will never forget is Merck. It paralyzed Merck's factories. I mean, it really created an existential crisis for the company. Merck had to tap into the CDC's emergency supplies of the Gardasil vaccine that year because their whole vaccine production line had been paralyzed in that attack. Imagine if that was gonna happen right now to Pfizer or Moderna or Johnson & Johnson. You know, imagine. I mean, that would really create a global cyber terrorist attack, essentially. And that's almost unintentional. I thought for a long time, I always labeled it as collateral damage. Collateral damage, yeah. But actually just today, there was a really impressive threat researcher at Cisco, which has this threat intelligence division called Talos, who said, stop calling it collateral damage. They could see who was gonna get hit before they deployed that malware. It wasn't collateral damage. It was intentional. They meant to hit any business that did business with Ukraine. It was to send a message to them, too. So I don't know if that's accurate. I always thought of it as sort of the sloppy collateral damage, but it definitely made me think. So how much of this between states is going to be a part of war, this kind of, these kinds of attacks on Ukraine, between Russia and US, Russia and China, China and US? Let's look at China and US. Do you think China and US are going to escalate something that would be called a war purely in the space of cyber? I believe any geopolitical conflict from now on is guaranteed to have some cyber element to it. The Department of Justice recently declassified a report that said China's been hacking into our pipelines, and it's not for intellectual property theft. It's to get a foothold so that if things escalate in Taiwan, for example, they are where they need to be to shut our pipelines down. And we just got a little glimpse of what that looked like with Colonial Pipeline and the panic buying and the jet fuel shortages and that assessment I just mentioned about the diesel. So they're there, they've gotten there. Anytime I read a report about new aggression from fighter jets, Chinese fighter jets in Taiwan, or what's happening right now with Russia's buildup on the Ukraine border, or India, Pakistan, I'm always looking at it through a cyber lens, and it really bothers me that other people aren't, because there is no way that these governments and these nation states are not going to use their access to gain some advantage in those conflicts. And I'm now in a position where I'm an advisor to the Cybersecurity Infrastructure Security Agency at DHS. So I'm not saying anything classified here, but I just think that it's really important to understand just generally what the collateral damage could be for American businesses and critical infrastructure in any of these escalated conflicts around the world. Because just generally, our adversaries have learned that they might never be able to match us in terms of our traditional military spending on traditional weapons and fighter jets. But we have a very soft underbelly when it comes to cyber. 80% or more of America's critical infrastructure, so pipelines, power grid, nuclear plants, water systems, is owned and operated by the private sector. And for the most part, there is nothing out there legislating that those companies share the fact they've been breached. They don't even have to tell the government they've been hit. There's nothing mandating that they even meet a bare minimum standard of cybersecurity. And that's it. So even when there are these attacks, most of the time we don't even know about it. So that is, if you were gonna design a system to be as blind and vulnerable as possible, that's pretty good. That's what it looks like, is what we have here in the United States. And everyone here is just operating like, let's just keep hooking up everything for convenience. Software eats the world. Let's just keep going for cost, for convenience sake, just because we can. And when you study these issues and you study these attacks and you study the advancement and the uptick in frequency and the lower barrier to entry that we see every single year, you realize just how dumb software eats world is. And no one has ever stopped to pause and think, should we be hooking up these systems to the internet? They've just been saying, can we, let's do it. And that's a real problem. And this, and just in the last year, we've seen a record number of zero-day attacks. I think there were 80 last year, which is probably more than double what it was in 2019. A lot of those were nation states. We live in a world with a lot of geopolitical hot points right now. And where those geopolitical hot points are are places where countries have been investing heavily in offensive cyber tools. If you're a nation state, the goal would be to maximize the footprint of zero-day, like super secret zero-day that nobody's aware of. And whenever war is initiated, the huge negative effects of shutting down infrastructure or any kind of zero-day is the chaos that's going on. It's the chaos it creates. So if you just, there's a certain threshold when you create the chaos, the markets plummet, just everything goes to hell. So there- It's not just zero-days. We make it so easy for threat actors. I mean, we're not using two-factor authentication. We're not patching. There was the shell shock vulnerability that was discovered a couple years ago. It's still being exploited. Because so many people haven't fixed it. So the zero-days are really the sexy stuff. And what really drew me to the zero-day market was the moral calculus we talked about. Particularly from the US government's point of view. How do they justify leaving these systems so vulnerable when we use them here? And we're baking more of our critical infrastructure with this vulnerable software. It's not like we're using one set of technology and Russia's using another and China's using this. We're all using the same technology. So when you find a zero-day in Windows, you're not just leaving it open so you can spy on Russia or implant yourself in the Russian grid. You're leaving Americans vulnerable too. But zero-days are like, that is the secret sauce. That's the superpower. And I always say, every country now, with the exception of Antarctica, someone added the Vatican to my list, is trying to find offensive hacking tools in zero-days to make them work. And those that don't have the skills now have this market that they can tap into. Where $2.5 million, that's chump change for a lot of these nation states. It's a hell of a lot less than trying to build the next fighter jet. But yeah, the goal is chaos. I mean, why did Russia turn off the lights twice in Ukraine? I think part of it is chaos. I think part of it is to sow the seeds of doubt in their current government. Your government can't even keep your lights on. Why are you sticking with them? Come over here and we'll keep your lights on at least. There's like a little bit of that. Nuclear weapons seems to have helped prevent nuclear war. Is it possible that we have so many vulnerabilities and so many attack vectors on each other that it will kind of achieve the same kind of equilibrium like mutually assured destruction? That's one hopeful solution to this. Do you have any hope for this particular solution? Nuclear analogies always tend to fall apart when it comes to cyber, mainly because you don't need fissile material. You just need a laptop and the skills and you're in the game. So it's a really low barrier to entry. The other thing is attribution's harder. And we've seen countries muck around with attribution. We've seen nation states piggyback on other countries' spy operations and just sit there and siphon out whatever they're getting. We learned some of that from the Snowden documents. We've seen Russia hack into Iran's command and control attack servers. We've seen them hit a Saudi petrochemical plant where they did neutralize the safety locks at the plant and everyone assumed that it was Iran given Iran had been targeting Saudi oil companies forever. But nope, it turned out that it was a graduate research institute outside Moscow. So you see countries kind of playing around with attribution. Why? I think because they think, okay, if I do this, like how am I gonna cover up that it came from me because I don't wanna risk the response? So people are sort of dancing around this. It's just in a very different way. And at the Times, I'd covered the Chinese hacks of infrastructure companies like pipelines. I'd covered the Russian probes of nuclear plants. I'd covered the Russian attacks on the Ukraine grid. And then in 2018, my colleague David Sanger and I covered the fact that US Cyber Command had been hacking into the Russian grid and making a pretty loud show of it. And when we went to the National Security Council, because that's what journalists do before they publish a story, they give the other side a chance to respond. I assumed we would be in for that really awkward, painful conversation where they would say, you will have blood on your hands if you publish this story. And instead, they gave us the opposite answer. They said, we have no problem with you publishing this story. Why? Well, they didn't say it out loud, but it was pretty obvious they wanted Russia to know that we're hacking into their power grid too, and they better think twice before they do to us what they had done to Ukraine. So yeah, we have stumbled into this new era of mutually assured digital destruction. I think another sort of quasi norm we've stumbled into is proportional responses. There's this idea that if you get hit, you're allowed to respond proportionally at a time and place of your choosing. That is how the language always goes. That's what Obama said after North Korea hit Sony. We will respond at a time and place of our choosing. But no one really knows what that response looks like. And so what you see a lot of the time are just these like just short of war attacks. Russia turned off the power in Ukraine, but it wasn't like it stayed off for a week. It stayed off for a number of hours. NotPetya hit those companies pretty hard, but no one died. And the question is, what's gonna happen when someone dies? And can a nation state masquerade as a cybercriminal group, as a ransomware group? And that's what really complicates coming to some sort of digital Geneva Convention. Like there's been a push from Brad Smith at Microsoft. We need a digital Geneva Convention. And on its face, it sounds like a no brainer. Yeah, why wouldn't we all agree to stop hacking into each other's civilian hospital systems, elections, power grid, pipelines? But when you talk to people in the West, officials in the West, they'll say, we would never, we'd love to agree to it, but we'd never do it when you're dealing with Xi or Putin or Kim Jong-un. Because a lot of times, they outsource these operations to cybercriminals. In China, we see a lot of these attacks come from this loose satellite network of private citizens that work at the behest of the Ministry of State Security. So how do you come to some sort of state to state agreement when you're dealing with transnational actors and cybercriminals, where it's really hard to pin down whether that person was acting alone or whether they were acting at the behest of the MSS or the FSB. And a couple of years ago, I remember, can't remember if it was before or after NotPetya, but Putin said, hackers are like artists who wake up in the morning in a good mood and start painting. In other words, I have no say over what they do or don't do. So how do you come to some kind of norm when that's how he's talking about these issues and he's just decimated Merck and Pfizer and another however many thousand companies? That is the fundamental difference between nuclear weapons and cyberattacks is the attribution. Or one of the fundamental differences. If you can fix one thing in the world in terms of cybersecurity that would make the world a better place, what would you fix? So you're not allowed to fix like authoritarian regimes and you can't. Right. You have to keep that, you have to keep human nature as it is. In terms of on the security side, technologically speaking, you mentioned there's no regulation on companies, United States. What if you could just fix with a snap of a finger, what would you fix? Two-factor authentication. Multi-factor authentication. It's ridiculous how many of these attacks come in because someone didn't turn on multi-factor authentication. I mean, Colonial Pipeline, okay? They took down the biggest conduit for gas, jet fuel, and diesel to the east coast of the United States of America. How? Because they forgot to deactivate an old employee account whose password had been traded on the dark web and they'd never turned on two-factor authentication. This water treatment facility outside Florida was hacked last year. How did it happen? They were using Windows XP from like a decade ago that can't even get patches if you want it to and they didn't have two-factor authentication. Time and time again, if they just switched on two-factor authentication, some of these attacks wouldn't have been possible. Now, if I could snap my fingers, that's a thing I would do right now. But of course, this is a cat and mouse game and then the attacker's on to the next thing. But I think right now, that is like bar none, that is just, that is the easiest, simplest way to deflect the most attacks. And the name of the game right now isn't perfect security. Perfect security is impossible. They will always find a way in. The name of the game right now is make yourself a little bit harder to attack than your competitor, than anyone else out there so that they just give up and move along. And maybe if you are a target for an advanced nation state or the SVR, you're gonna get hacked no matter what. But you can make cyber criminal groups, deadbolt is it, you can make their jobs a lot harder simply by doing the bare basics. And the other thing is stop reusing your passwords. But if I only get one, then two-factor authentication. So what is two-factor authentication? Factor one is what, logging in with a password? And factor two is like have another device or another channel through which you can confirm, yeah, that's me. Yes, usually this happens through some kind of text. You get your one-time code from Bank of America or from Google. The better way to do it is spend $20 buying yourself a Fido key on Amazon. That's a hardware device. And if you don't have that hardware device with you, then you're not gonna get in. And the whole goal is, I mean, basically, my first half of my decade at the Times was spent covering like the cop beat. It was like Home Depot got breached, News at 11, Target, Neiman Marcus, like who wasn't hacked over the course of those five years? And a lot of those companies that got hacked, what did hackers take? They took the credentials. They took the passwords. They can make a pretty penny selling them on the dark web. And people reuse their passwords. So you get one from God knows who, I don't know, last pass, the worst case example actually, last pass. But you get one and then you go test it on their email account. And you go test it on their brokerage account. And you test it on their cold storage account. That's how it works. But if you have multi-factor authentication, then they can't get in because they might have your password, but they don't have your phone. They don't have your Fido key. So you keep them out. And I get a lot of alerts that tell me someone is trying to get into your Instagram account or your Twitter account or your email account. And I don't worry because I use multi-factor authentication. They can try all day. Okay, I worry a little bit, but it's the simplest thing to do. And we don't even do it. Well, there's an interface aspect to it because it's pretty annoying if it's implemented poorly. Yeah, true. So actually bad implementation of two-factor authentication, not just bad, but just something that adds friction is a security vulnerability, I guess, because it's really annoying. Like I think MIT for a while had two-factor authentication. It was really annoying. It's just like the number of times it pings you, it asks to re-authenticate across multiple subdomains. It just feels like a pain. I don't know what the right balance there. Yeah, it feels like friction in our frictionless society. It feels like friction. It's annoying. That's security's biggest problem. It's annoying. We need the Steve Jobs of security to come along and we need to make it painless. And actually, on that point, Apple has probably done more for security than anyone else simply by introducing biometric authentication, first with the fingerprint and then with face ID. And it's not perfect, but if you think just eight years ago, everyone was running around with either no passcode, an optional passcode, or a four-digit passcode on their phone that anyone, think of what you can get when you get someone's iPhone, if you steal someone's iPhone. And props to them for introducing the fingerprint and face ID. And again, it wasn't perfect, but it was a huge step forward. Now it's time to make another huge step forward. I wanna see the password die. I mean, it's gotten us as far as it was ever gonna get us and I hope whatever we come up with next is not gonna be annoying, is gonna be seamless. When I was at Google, that's what we worked on is, and there's a lot of ways to call this active authentication or passive authentication. So basically use biometric data, not just like a fingerprint but everything from your body to identify who you are, like movement patterns. So basically create a lot of layers of protection where it's very difficult to fake, including like face unlock, checking that it's your actual face, like the liveness tests. So like from video, so unlocking it with video, voice, the way you move the phone, the way you take it out of the pocket, that kind of thing. All of those factors. It's a really hard problem though. And ultimately it's very difficult to beat the password in terms of security. Well, there's a company that I actually will call out and that's Abnormal Security. So they work on email attacks and it was started by a couple of guys who were doing, I think ad tech at Twitter. So, ad technology now, like it's a joke how much they know about us. You always hear the conspiracy theories that you saw someone's shoes and next thing you know, it's on your phone. It's amazing what they know about you. And they're basically taking that and they're applying it to attacks. So they're saying, okay, if you're, this is what your email patterns are. It might be different for you and me because we're emailing strangers all the time. But for most people, their email patterns are pretty predictable. And if something strays from that pattern, that's abnormal and they'll block it, they'll investigate it. And that's great. Let's start using that kind of targeted ad technology to protect people. And yeah, I mean, it's not gonna get us away from the password and using multi-factor authentication, but the technology is out there and we just have to figure out how to use it in a really seamless way because it doesn't matter if you have the perfect security solution if no one uses it. I mean, when I started at the Times when I was trying to be really good about protecting sources, I was trying to use PGP encryption and it's like, it didn't work. The number of mistakes I would probably make just trying to email someone with PGP just wasn't worth it. And then Signal came along and Signal made it, Wicker, they made it a lot easier to send someone an encrypted text message. So we have to start investing in creative minds in good security design. I really think that's the hack that's gonna get us out of where we are today. What about social engineering? Do you worry about this sort of hacking people? Yes, I mean, this is the worst nightmare of every chief information security officer out there. Social engineering, we work from home now. I saw this woman posted online about how her husband, it went viral today, but it was her husband had this problem at work. They hired a guy named John and now the guy that shows up for work every day doesn't act like John. I mean, think about that. Like think about the potential for social engineering in that context. You apply for a job and you put on a pretty face, you hire an actor or something and then you just get inside the organization and get access to all that organization's data. A couple of years ago, Saudi Arabia planted spies inside Twitter. Why? Probably because they were trying to figure out who these people were who were criticizing the regime on Twitter. They couldn't do it with a hack from the outside, so why not plant people on the inside? And that's like the worst nightmare. And it also, unfortunately, creates all kinds of xenophobia at a lot of these organizations. I mean, if you're gonna have to take that into consideration then organizations are gonna start looking really skeptically and suspiciously at someone who applies for that job from China. And we've seen that go really badly at places like the Department of Commerce where they basically accuse people of being spies that aren't spies. So it is the hardest problem to solve. And it's never been harder to solve than right at this very moment when there's so much pressure for companies to let people work remotely. That's actually why I'm single. I'm suspicious that China and Russia, every time I meet somebody, are trying to plant and get insider information. So I'm very, very suspicious. I keep putting the Turing test in front. No. No, I have a friend who worked inside NSA and was one of their top hackers. And he's like, every time I go to Russia, I get hit on by these tens. And I come home, my friends are like, I'm sorry, you're not a 10. Like, it's a common story. I mean, it's difficult to trust humans in this day and age online. So we're working remotely, that's one thing. But just interacting with people on the internet, it sounds ridiculous. But because of this podcast in part, I've gotten to meet some incredible people. But it makes you nervous to trust folks. And I don't know how to solve that problem. So I'm talking with Mark Zuckerberg, who dreams about creating the metaverse. What do you do about that world where more and more our lives is in the digital sphere? Like, one way to phrase it is, most of our meaningful experiences, at some point, will be online. Like falling in love, getting a job, or experiencing a moment of happiness with a friend, with a new friend made online. All of those things. Like, more and more, the fun we do, the things that make us love life will happen online. And if those things have an avatar that's digital, that's like a way to hack into people's minds. Whether it's with AI or kind of troll farms or something like that. I don't know if there's a way to protect against that. That might fundamentally rely on our faith in how good human nature is. So if most people are good, we're going to be okay. But if people will tend towards manipulation and malevolent behavior in search of power, then we're screwed. So I don't know if you can comment on how to keep the metaverse secure. Yeah, I mean, all I thought about when you were talking just now is my three-year-old son. He asked me the other day, what's the internet, mom? And I just almost wanted to cry. I don't want that for him. I don't want all of his most meaningful experiences to be online. By the time that happens, how do you know that person's human? That avatar's human? I believe in free speech. I don't believe in free speech for robots and bots. And look what just happened over the last six years. We had bots pretending to be Black Lives Matter activists just to sow some division, or Texas secessionists, or organizing anti-Hillary protests, or just to sow more division, to tie us up in our own politics so that we're so paralyzed we can't get anything done. We can't make any progress, and we definitely can't handle our adversaries and their long-term thinking. It really scares me. And here's where I just come back to, just because we can create the metaverse, just because it sounds like the next logical step in our digital revolution, do I really want my child's most significant moments to be online? They weren't for me. So maybe I'm just stuck in that old-school thinking, or maybe I've seen too much. And I'm really sick of being the guinea pig parent generation for these things. I mean, it's hard enough with screen time. Like, thinking about how to manage the metaverse as a parent to a young boy, like, I can't even let my head go there. That's so terrifying for me. But we've never stopped any new technology just because it introduces risks. We've always said, okay, the promise of this technology means we should keep going, keep pressing ahead. We just need to figure out new ways to manage that risk. And you know, that's the blockchain right now. Like, when I was covering all of these ransomware attacks, I thought, okay, this is gonna be it for cryptocurrency. You know, governments are gonna put the kibosh down. They're gonna put the hammer down and say, enough is enough. Like, we have to put this genie back in the bottle because it's enabled ransomware. I mean, five years ago, they would hijack your PC and they'd say, go to the local pharmacy, get a e-gift card and tell us what the PIN is, and then we'll get your $200. Now it's pay us, you know, five Bitcoin. And so there's no doubt cryptocurrencies enabled ransomware attacks, but after the Colonial Pipeline, ransom was seized. Because if you remember, the FBI was actually able to go in and claw some of it back from DarkSide, which was the ransomware group that hid it. And I spoke to these guys at TRM Labs. So they're one of these blockchain intelligence companies. And a lot of people that work there used to work at the Treasury. And what they said to me was, yeah, cryptocurrency has enabled ransomware, but to track down that ransom payment would have taken, you know, if we were dealing with fiat currency, would have taken us years to get to that one bank account or belonging to that one front company in the Seychelles. And now, thanks to the blockchain, we can track the movement of those funds in real time. And you know what? You know, these payments are not as anonymous as people think. Like we still can use our old hacking ways and zero days and, you know, old school intelligence methods to find out who owns that private wallet and how to get to it. So it's a curse in some ways in that it's an enabler, but it's also a blessing. And they said that same thing to me that I just said to you. They said, we've never shut down a promising new technology because it introduced risk. We just figured out how to manage that risk. And I think that's where the conversation, unfortunately, has to go is how do we, in the metaverse, use technology to fix things? So maybe we'll finally be able to, not finally, but figure out a way to solve the identity problem on the internet, meaning like a blue check mark for actual human and connect it to identity like a fingerprint so you can prove you're you and yet do it in a way that doesn't involve the company having all your data. So giving you, allowing you to maintain control over your data or if you don't, then there's complete transparency of how that data is being used, all those kinds of things. And maybe as you educate more and more people, they would demand in a capitalist society that the companies that they give their data to will respect that data. Yeah, I mean, there is this company, and I hope they succeed, their name's PIIANO, P-I-I-O, and they wanna create a vault for your personal information inside every organization. And ultimately, if I'm gonna call Delta Airlines to book a flight, they don't need to know my social security number, they don't need to know my birth date. They're just gonna send me a one-time token to my phone. My phone's gonna say, or my Fido key is gonna say, yep, it's her. And then we're gonna talk about my identity like a token, some random token. They don't need to know exactly who I am, they just need to know the system trust that I am, who I say I am, but they don't get access to my PII data. They don't get access to my social security number, my location, or the fact I'm a Times journalist. I think that's the way the world's gonna go. Enough is enough. Sort of losing our personal information everywhere, letting data marketing companies track our every move. They don't need to know who I am. No, okay, I get it. We're stuck in this world where the internet runs on ads. So ads are not gonna go away, but they don't need to know I'm Nicole Perlera. They can know that I am token number, you know, x567. And they can let you know what they know and give you control about removing the things they know. Yeah, right to be forgotten. To me, you should be able to walk away with a single press of a button. And I also believe that most people, given the choice to walk away, won't walk away. They'll just feel better about having the option to walk away when they understand the trade-offs. If you walk away, you're not gonna get some of the personalized experiences that you would otherwise get, like a personalized feed and all those kinds of things. But the freedom to walk away is, I think, really powerful. And obviously, what you're saying, there's all of these HTML forms where you have to enter your phone number and email and private information from every single airline. New York Times. I have so many opinions on this. But just the friction and the sign-up and all of those kinds of things. I should be able to, this has to do with everything. This has to do with payment, too. Payment should be trivial. It should be one click, and one click to unsubscribe and subscribe, and one click to provide all of your information that's necessary for the subscription service, for the transaction service, whatever that is, getting a ticket, as opposed to, I have all these fake phone numbers and emails that I use now to sign out. Because you never know, if one site is hacked, then it's just going to propagate to everything else. Yeah. And there's low-hanging fruit. And I hope Congress does something. And frankly, I think it's negligent they haven't on the fact that elderly people are getting spammed to death on their phones these days with fake car warranty scams. And I mean, my dad was in the hospital last year, and I was in the hospital room, and his phone kept buzzing, and I look at it, and it's just spam attack after spam attack, people nonstop calling about his freaking car warranty, why they're trying to get his social security number, they're trying to get his PII, they're trying to get this information. We need to figure out how to put those people in jail for life, and we need to figure out why in the hell we are being required or asked to hand over our social security number, and our home address, and our passport, all of that information to every retailer who asks. I mean, that's insanity. And there's no question, they're not protecting it, because it keeps showing up in spam or identity theft or credit card theft or worse. Well, the spam's getting better, and maybe I need to, as a side note, make a public announcement, please clip this out, which is if you get an email or a message from Lex Friedman saying how much I, Lex, appreciate you and love you and so on, and please connect with me on my WhatsApp number, and I will give you Bitcoin or something like that, please do not click. And I'm aware that there's a lot of this going on, a very large amount, I can't do anything about it. This is on every single platform, it's happening more and more and more, which I've been recently informed that they're now emailing, so it's cross-platform. They're taking people's, they're somehow, this is fascinating to me, because they are taking people who comment on various social platforms, and they somehow reverse engineer, they figure out what their email is, and they send an email to that person saying from Lex Friedman, and it's like a heartfelt email with links. It's fascinating, because it's cross-platform now. It's not just a spam bot that's messaging and a comment that's in a reply. They are saying, okay, this person cares about this other person on social media, so I'm going to find another channel, which in their mind probably increases, and it does, the likelihood that they'll get the people to click, and they do. I don't know what to do about that. It makes me really, really sad, especially with podcasting, there's an intimacy that people feel connected, and they get really excited. Okay, cool, I wanna talk to Lex. And they click. And I get angry at the people that do this. I mean, it's like the john that gets hired, the fake employee. I mean, I don't know what to do about that. I mean, I suppose the solution is education. It's telling people to be skeptical on stuff they click. That balance with the technology solution of creating a maybe like two-factor authentication, and maybe helping identify things that are likely to be spam, I don't know. But then the machine learning there is tricky, because you don't want to add a lot of extra friction that just annoys people, because they'll turn it off, because you have the accept cookies thing, right? That everybody has to click on that, so now they completely ignore the accept cookies. This is very difficult to find that frictionless security. You mentioned Snowden. You've talked about looking through the NSA documents he leaked, and doing the hard work of that. What do you make of Edward Snowden? What have you learned from those documents? What do you think of him? In the long arc of history, is Edward Snowden a hero or a villain? I think he's neither. I have really complicated feelings about Edward Snowden. On the one hand, I'm a journalist at heart, and more transparency is good. And I'm grateful for the conversations that we had in the post-Snowden era about the limits to surveillance, and how critical privacy is. And when you have no transparency, and you don't really know, in that case, what our secret courts were doing, how can you truly believe that our country is taking our civil liberties seriously? So on the one hand, I'm grateful that he cracked open these debates. On the other hand, when I walked into the storage closet of classified NSA secrets, I had just spent two years covering Chinese cyber espionage almost every day. And this sort of advancement of Russian attacks, they were just getting worse and worse and more destructive. And there were no limits to Chinese cyber espionage and Chinese surveillance of its own citizens. And there seemed to be no limit to what Russia was willing to do in terms of cyber attacks, and also, in some cases, assassinating journalists. So when I walked into that room, there was a part of me, quite honestly, that was relieved to know that the NSA was as good as I hoped they were. And we weren't using that knowledge to, as far as I know, assassinate journalists. We weren't using our access to take out pharmaceutical companies. For the most part, we were using it for traditional espionage. Now, that set of documents also set me on the journey of my book, because to me, the American people's reaction to the Snowden documents was a little bit misplaced. They were upset about the phone call metadata collection program. Angela Merkel, I think, rightfully was upset that we were hacking her cell phone. But in sort of the spy eats spy world, hacking world leader's cell phones is pretty much what most spy agencies do. And there wasn't a lot that I saw in those documents that was beyond what I thought a spy agency does. And I think if there was another 9-11 tomorrow, God forbid, we would all say, how did the NSA miss this? Why weren't they spying on those terrorists? Why weren't they spying on those world leaders? You know, there's some of that too. But I think that there was great damage done to the US's reputation. I think we really lost our halo in terms of a protector of civil liberties. And I think a lot of what was reported was unfortunately reported in a vacuum. That was my biggest gripe, that we were always reporting, the NSA has this program and here's what it does. And the NSA is in Angela Merkel's cell phone and the NSA can do this. And no one was saying, and by the way, China has been hacking into our pipelines and they've been making off with all of our intellectual property. And Russia has been hacking into our energy infrastructure. And they've been using the same methods to spy on track and in many cases, kill their own journalists. And the Saudis have been doing this to their own critics and dissidents. And so you can't talk about any of these countries in isolation. It is really like spy, spy out there. And so I just have complicated feelings. You know, and the other thing is, and I'm sorry, this is a little bit of a tangent, but the amount of documents that we had, like thousands of documents, most of which were just crap, but had people's names on them. You know, part of me wishes that those documents had been released in a much more targeted, limited way. It's just a lot of it just felt like a PowerPoint that was taken out of context. And you just sort of wish that there had been a little bit more thought into what was released. Because I think a lot of the impact from Sony was just the volume of the reporting. But I think, you know, based on what I saw personally, there was a lot of stuff that I just, I don't know why that particular thing got released. As a whistleblower, what's a better way to do it? Because I mean, there's fear, there's, it takes a lot of effort to do a more targeted release. You know, if there's proper channels, you're afraid that those channels will be manipulated. Like, who do you trust? What's a better way to do this, do you think? As a journalist, this is almost a good journalistic question. Reveal some fundamental flaw in the system without destroying the system. I bring up, you know, again, Mark Zuckerberg and Meta. There was a whistleblower that came out about Instagram internal studies. And I also am torn about how to feel about that whistleblower because from a company perspective, that's an open culture. How can you operate successfully if you have an open culture where any one whistleblower can come out, out of context, take a study, whether it represents a larger context or not. And the press eats it up. And then that creates a narrative that is, just like with the NSA, you said, that's out of context, very targeted to where, well, Facebook is evil, clearly, because of this one leak. It's really hard to know what to do there because we're now in a society that's deeply distrust institutions. And so narratives by whistleblowers make that whistleblower and their forthcoming book very popular. And so there's a huge incentive to take stuff out of context and to tell stories that don't represent the full context, the full truth. It's hard to know what to do with that because then that forces Facebook and Meta and governments to be much more conservative, much more secretive. It's like a race to the bottom. I don't know. I don't know if you can comment on any of that, how to be a whistleblower ethically and properly. I don't know. I mean, these are hard questions. And even for myself, in some ways, I think of my book as sort of blowing the whistle on the underground zero-day market. But it's not like I was in the market myself. It's not like I had access to classified data when I was reporting out that book. As I say in the book, listen, I'm just trying to scrape the surface here so we can have these conversations before it's too late. And I'm sure there's plenty in there that someone who's US intelligence agency's preeminent zero-day broker probably has some voodoo doll of me out there. And you're never gonna get it 100%. But I really applaud whistleblowers like the whistleblower who blew the whistle on the Trump call with Zelensky. I mean, people needed to know about that, that we were basically, in some ways, blackmailing an ally to try to influence an election. I mean, they went through the proper channels. They weren't trying to profit off of it, right? There was no book that came out afterwards from that whistleblower. That whistleblower's not like, they went through the channels. They're not living in Moscow. You know, let's put it that way. Can I ask you a question? You mentioned NSA, one of the things it showed is they're pretty good at what they do. Again, this is a touchy subject, I suppose, but there's a lot of conspiracy theories about intelligence agencies. From your understanding of intelligence agencies, the CIA, NSA, and the equivalent in other countries, are they, one question, this could be a dangerous question, are they competent, are they good at what they do? And two, are they malevolent in any way? Sort of, I recently had a conversation about tobacco companies. They kind of see their customers as dupes. Like, they can just play games with people. Conspiracy theories tell that similar story about intelligence agencies, that they're interested in manipulating the populace for whatever ends the powerful in dark rooms, cigarette smoke, cigar smoke-filled rooms. What's your sense? Do these conspiracy theories have kind of any truth to them? Or are intelligence agencies, for the most part, good for society? Okay, well, that's an easy one. Is it? No. I think, you know, depends which intelligence agency. Think about the Mossad. You know, they're killing every Iranian nuclear scientist they can over the years, you know? But have they delayed the time horizon before Iran gets the bomb? Yeah. Have they probably staved off terror attacks on their own citizens? Yeah. You know, none of these, intelligence is intelligence. You know, you can't just say, like, they're malevolent or they're heroes, you know? Everyone I have met in this space is not like the pound-your-chest patriot that you see on the beach on the 4th of July. A lot of them have complicated feelings about their former employers. Well, at least at the NSA, it reminded me to do what we were accused of doing after Snowden, to spy on Americans. You have no idea the amount of red tape and paperwork and bureaucracy it would have taken to do what everyone thinks that we were supposedly doing. But then, you know, we find out in the course of the Snowden reporting about a program called Lovin' where a couple of the NSA analysts were using their access to spy on their ex-girlfriends. So, you know, there's an exception to every case. Generally, I will probably get, you know, accused of my Western bias here again, but I think you can almost barely compare some of these Western intelligence agencies to China, for instance. And the surveillance that they're deploying on the Uyghurs to the level they're deploying it, and the surveillance they're starting to export abroad with some of the programs like the watering hole attack I mentioned earlier, where it's not just hitting the Uyghurs inside China, it's hitting anyone interested in the Uyghur plight outside China. I mean, it could be an American high school student writing a paper on the Uyghurs. They wanna spy on that person too. You know, there's no rules in China really limiting the extent of that surveillance. And we all better pay attention to what's happening with the Uyghurs because just as Ukraine has been to Russia in terms of a test kitchen for its cyber attacks, the Uyghurs are China's test kitchen for surveillance. And there's no doubt in my mind that they're testing them on the Uyghurs. Uyghurs are their Petri dish, and eventually they will export that level of surveillance overseas. I mean, in 2015, Obama and Xi Jinping reached a deal where basically the White House said, you better cut it out on intellectual property theft. And so they made this agreement that they would not hack each other for commercial benefit. And for a period of about 18 months, we saw this huge drop off in Chinese cyber attacks on American companies, but some of them continued. Where did they continue? They continued on aviation companies, on hospitality companies like Marriott. Why? Because that was still considered fair game to China. It wasn't IP theft they were after. They wanted to know who was staying in this city at this time when Chinese citizens were staying there so they could cross match for counterintelligence who might be a likely Chinese spy. I'm sure we're doing some of that too. Counterintelligence is counterintelligence. It's considered fair game. But where I think it gets evil is when you use it for censorship, to suppress any dissent, to do what I've seen the UAE do to its citizens where people who've gone on Twitter just to advocate for better voting rights, more enfranchisement, suddenly find their passports confiscated. I talked to one critic, Ahmed Mansour, and he told me, you might find yourself a terrorist, labeled a terrorist one day, you don't even know how to operate a gun. I mean, he'd been beaten up every time he tried to go somewhere. His passport had been confiscated. By that point, it turned out they'd already hacked into his phone. So they were listening to us talking. They'd hacked into his baby monitor. So they're spying on his child. And they stole his car. And then they created a new law that you couldn't criticize the ruling family or the ruling party on Twitter. And he's been in solitary confinement every day since on hunger strike. So that's evil. That's evil. And we don't do that here. We have rules here. We don't cross that line. So yeah, in some cases, I won't go to Dubai. I won't go to Abu Dhabi. If I ever wanna go to the Maldives, too bad. Most of the flights go through Dubai. So there's some lines we're not willing to cross. But then again, just like you said, there's individuals within NSA, within CIA, and they may have power. And to me, there's levels of evil. To me personally, this is the stuff of conspiracy theories, is the things you've mentioned as evil are more direct attacks. But there's also psychological warfare. So blackmail. So what does spying allow you to do? It allow you to collect information if you have something that's embarrassing. Or if you have like Jeffrey Epstein conspiracy theories, active, what is it, manufacture of embarrassing things, and then use blackmail to manipulate the population or all the powerful people involved. It troubles me deeply that MIT allowed somebody like Jeffrey Epstein in their midst, especially some of the scientists I admire that they would hang out with that person at all. And so I'll talk about it sometimes. And then a lot of people tell me, well, obviously Jeffrey Epstein is a front for intelligence. And I just, I struggle to see that level of competence and malevolence. But, you know, who the hell am I? And I guess I was trying to get to that point. You said that there's bureaucracy and so on, which makes some of these things very difficult. I wonder how much malevolence, how much competence there is in these institutions. Like how far, this takes us back to the hacking question. How far are people willing to go if they have the power? This has to do with social engineering. This has to do with hacking. This has to do with manipulating people, attacking people, doing evil onto people, psychological warfare and stuff like that. I don't know. I believe that most people are good. And I don't think that's possible in a free society. There's something that happens when you have a centralized government where power corrupts over time and you start surveillance programs kind of, it's like a slippery slope that over time starts to both use fear and direct manipulation to control the populace. But in a free society, I just, it's difficult for me to imagine that you can have somebody like a Jeffrey Epstein in front for intelligence. I don't know what I'm asking you, but I'm just, I have a hope that for the most part, intelligence agencies are trying to do good and are actually doing good for the world when you view it in the full context of the complexities of the world. But then again, if they're not, would we know? That's why Edward Snowden might be a good thing. Let me ask you on a personal question. You have investigated some of the most powerful organizations and people in the world of cyber warfare, cybersecurity. Are you ever afraid for your own life, your own well-being, digital or physical? I mean, I've had my moments. I've had our security team at the Times called me at one point and said, someone's on the dark web offering good money to anyone who can hack your phone or your laptop. I describe in my book how when I was at that hacking conference in Argentina, I came back and I brought a burner laptop with me, but I'd kept it in the safe anyway. And it didn't have anything on it, but someone had broken in and it was moved. I've had all sorts of sort of scary moments. And then I've had moments where I think I went just way too far into the paranoid side. I mean, I remember writing about the Times hack by China and I just covered a number of Chinese cyber attacks where they'd gotten into the thermostat at someone's corporate apartment. And they'd gotten into all sorts of stuff. And I was living by myself. I was single in San Francisco and my cable box on my television started making some weird noises in the middle of the night. And I got up and I ripped it out of the wall. And I think I said something embarrassing, like, fuck you, China. You know? And then I went back to bed and I woke up and this beautiful morning light, I mean, I'll never forget it. This is like glimmering morning light is shining on my cable box, which has now been ripped out and is sitting on my floor and the morning light. And I was just like, no, no, no. I'm not going down that road. Like, you basically, I came to a fork in the road where I could either go full tinfoil hat, go live off the grid, never have a car with navigation, never use Google Maps, never own an iPhone, never order diapers off Amazon, you know, create an alias. Or I could just do the best I can and live in this new digital world we're living in. And what does that look like for me? I mean, what are my crown jewels? This is what I tell people. What are your crown jewels? Because just focus on that. You can't protect everything, but you can protect your crown jewels. For me, for the longest time, my crown jewels were my sources. I was nothing without my sources. So I had some sources I would meet the same dim sum place, or maybe it was a different restaurant, on the same date, you know, every quarter. And we would never drive there. We would never Uber there. We wouldn't bring any devices. I could bring a pencil and a notepad. And if someone wasn't in town, like there were a couple times where I'd show up and the source never came, but we never communicated digitally. And those were the lengths I was willing to go to protect that source, but you can't do it for everyone. So for everyone else, you know, it was signal, using two-factor authentication, keeping my devices up to date, not clicking on phishing emails, using a password manager, all the things that we know we're supposed to do. And that's what I tell everyone. Like, don't go crazy, because then that's like the ultimate hack. Then they've hacked your mind, whoever they is for you. But just do the best you can. Now, my whole risk model changed when I had a kid. You know, now it's, oh God, you know, if anyone threatened my family, God help them. But it changes you. And, you know, unfortunately there are some things like I was really scared to go deep on, like Russian cyber crime, you know, like Putin himself, you know, and it's interesting, like I have a mentor who's an incredible person who was the Times Moscow Bureau Chief during the Cold War. And after I wrote a series of stories about Chinese cyber espionage, he took me out to lunch. And he told me that when he was living in Moscow, he would drop his kids off at preschool when they were my son's age now, and the KGB would follow him. And they would make a really like loud show of it. You know, they'd tail him, they'd, you know, honk, they'd just be a wreck, make a wreck, wreck us. And he said, you know what, they never actually did anything, but they wanted me to know that they were following me. And I operated accordingly. And he says, that's how you should operate in the digital world. Know that there are probably people following you. Sometimes they'll make a little bit of noise, but one thing you need to know is that while you're at the New York Times, you have a little bit of an invisible shield on you. You know, if something were to happen to you, that would be a really big deal. That would be an international incident. So I kind of carried that invisible shield with me for years. And then Jamal Khashoggi happened. And that destroyed my vision of my invisible shield. You know, sure, you know, he was a Saudi, but he was a Washington Post columnist. You know, for the most part, he was living in the United States. He was a journalist. And for them to do what they did to him, pretty much in the open and get away with it, and for the United States to let them get away with it, because we wanted to preserve diplomatic relations with the Saudis, that really threw my worldview upside down. And, you know, I think that sent a message to a lot of countries that it was sort of open season on journalists. And to me, that was one of the most destructive things that happened under the previous administration. And, you know, I don't really know what to think of my invisible shield anymore. Like you said, that really worries me on the journalism side that people would be afraid to dig deep on fascinating topics. And, you know, I have my own, that's part of the reason, like I would love to have kids, I would love to have a family. Part of the reason I'm a little bit afraid, there's many ways to phrase this, but the loss of freedom in the way of doing all the crazy shit that I naturally do, which I would say the ethic of journalism is kind of not, is doing crazy shit without really thinking about it, this is letting your curiosity really allow you to be free and explore. It's, I mean, whether it's stupidity or fearlessness, whatever it is, that's what great journalism is. And all the concerns about security risks have made me like become a better person. The way I approach it is just make sure you don't have anything to hide. I know this is not a thing, this is not an approach to security, I'm just, this is like a motivational speech or something. It's just like, if you can lose, you can be hacked at any moment, just don't be a douchebag secretly. Just be like a good person, because then, I see this actually with social media in general, just present yourself in the most authentic way possible, meaning be the same person online as you are privately, have nothing to hide, that's one, not the only, but one of the ways to achieve security. Maybe I'm totally wrong on this, but don't be secretly weird. If you're weird, be publicly weird, so it's impossible to blackmail you. That's my approach to security. Yeah, well, they call it the New York Times front page phenomenon, don't put anything in email, or I guess social media these days, that you wouldn't want to read on the front page of the New York Times. And that works, but sometimes I even get carried, I mean, I have not as many followers as you, but a lot of followers, and sometimes even I get carried away. Just be emotional and stuff, just say something. Yeah, I mean, just the cortisol response on Twitter. Twitter is basically designed to elicit those responses. I mean, every day I turn on my computer, I look at my phone, I look at what's trending on Twitter, and it's like, what are the topics that are gonna make people the most angry today? You know? And it's easy to get carried away, but it's also just, that sucks too, that you have to be constantly censoring yourself. And maybe it's for the better, maybe you can't be a secret asshole, and we can put that in the good bucket. But at the same time, there is a danger to that other voice, to creativity, you know, to being weird. There's a danger to that little whispered voice that's like, well, how would people read that? You know, how could that be manipulated? How could that be used against you? And that stifles creativity and innovation and free thought. And, you know, that is on a very micro level. And that's something I think about a lot. And that's actually something that Tim Cook has talked about a lot, and why he has said he goes full force on privacy is it's just that little voice that is at some level censoring you. And what is sort of the long-term impact of that little voice over time? I think there's a ways, I think that self-censorship is an attack factor that there are solutions to, the way I'm really inspired by Elon Musk. The solution to that is just be privately and publicly the same person and be ridiculous. Embrace the full weirdness and show it more and more. So, you know, that's memes that has like ridiculous humor. And I think, and if there is something you really wanna hide, deeply consider if that you wanna be that. Like, why are you hiding it? What exactly are you afraid of? Because I think my hopeful vision for the internet is the internet loves authenticity. They wanna see you weird. So be that and like live that fully. Because I think that gray area where you're kind of censoring yourself, that's where the destruction is. You have to go all the way, step over, be weird. And then it feels, it can be painful because people can attack you and so on, but just ride it. I mean, that's just like a skill on the social psychological level that ends up being an approach to security, which is like remove the attack vector of having private information by being your full weird self publicly. What advice would you give to young folks today, you know, operating in this complicated space about how to have a successful life, a life they can be proud of, a career they can be proud of. Maybe somebody in high school and college thinking about what they're going to do. Be a hacker. You know, if you have any interest, become a hacker and apply yourself to defense. You know, every time, like we do have these amazing scholarship programs, for instance, where, you know, they find you early, they'll pay your college as long as you commit to some kind of federal commitment to sort of help federal agencies with cybersecurity. And where does everyone wanna go every year from the scholarship program? They wanna go work at the NSA or Cyber Command. You know, they wanna go work on offense. They wanna go do the sexy stuff. It's really hard to get people to work on defense. It's just, it's always been more fun to be a pirate than be in the Coast Guard, you know? And so we have a huge deficit when it comes to filling those roles. There's 3.5 million unfilled cybersecurity positions around the world. I mean, talk about job security. Like, be a hacker and work on cybersecurity. You will always have a job. And we're actually at a huge deficit and disadvantage as a free market economy, because we can't match cybersecurity salaries at Palantir or Facebook or Google or Microsoft. And so it's really hard for the United States to fill those roles. And, you know, other countries have had this workaround where they basically have forced conscription on some level. You know, China tells people, like, you do whatever you're gonna do during the day, work at Alibaba, you know, if you need to do some ransomware, okay. But the minute we tap you on the shoulder and ask you to come do this sensitive operation for us, the answer is yes. You know, same with Russia. You know, a couple of years ago when Yahoo was hacked and they laid it all out in an indictment, it came down to two cyber criminals and two guys from the FSB. Cyber criminals were allowed to have their fun, but the minute they came across the username and password for someone's personal Yahoo account that worked at the White House or the State Department or military, they were expected to pass that over to the FSB. So we don't do that here. And it's even worse on defense. We really can't fill these positions. So, you know, if you are a hacker, if you're interested in code, if you're a tinker, you know, learn how to hack. There are all sorts of amazing hacking competitions you can do through the SANS org, for example, S-A-N-S. And then use those skills for good. You know, neuter the bugs in that code that get used by autocratic regimes to make people's life, you know, a living prison. You know, plug those holes, you know, defend industrial systems, defend our water treatment facilities from hacks where people are trying to come in and poison the water. You know, that I think is just an amazing, it's an amazing job on so many levels. It's intellectually stimulating. You can tell yourself you're serving your country. You can tell yourself you're saving lives and keeping people safe. And you'll always have amazing job security. And if you need to go get that job that pays you, you know, two million bucks a year, you can do that too. And you can have a public profile, more so of a public profile, you can be a public rockstar. I mean, it's the same thing as sort of the military. And there's a lot of, there's a lot of well-known sort of people commenting on the fact that veterans are not treated as well as they should be. But it's still the fact that soldiers are deeply respected for defending the country, the freedoms, the ideals that we stand for. And in the same way, I mean, in some ways, the cybersecurity defense are the soldiers of the future. Yeah, and you know what's interesting? I mean, in cybersecurity, the difference is oftentimes you see the more interesting threats in the private sector because that's where the attacks come. You know, when cyber criminals and nation state adversaries come for the United States, they don't go directly for Cyber Command or the NSA. No, they go for banks, they go for Google, they go for Microsoft, they go for critical infrastructure. And so those companies, those private sector companies get to see some of the most advanced, sophisticated attacks out there. And if you're working at FireEye and you're calling out the SolarWinds attack, for instance, I mean, you just saved God knows how many systems from that compromise turning into something that more closely resembles sabotage. So, you know, go be a hacker or go be a journalist. So you wrote the book, this is how they tell me the world ends as we've been talking about, of course, referring to cyber war, cybersecurity. What gives you hope about the future of our world if it doesn't end? How will it not end? That's a good question. I mean, I have to have hope, right? Because I have a kid and I have another on the way and if I didn't have hope, I wouldn't be having kids. But it's a scary time to be having kids. And now it's like pandemic, climate change, disinformation, increasingly advanced, perhaps deadly cyber attacks. What gives me hope is that I share your worldview that I think people are fundamentally good. And sometimes, and this is why the metaverse scares me to death, but when I'm reminded of that is not online. Like online, I get the opposite. You know, you start to lose hope and humanity when you're on Twitter half your day. It's like when I go to the grocery store or I go on a hike or like someone smiles at me, or someone just says something nice. You know, people are fundamentally good. We just don't hear from those people enough. And my hope is, I just think our current political climate, like we've hit rock bottom. This is as bad as it gets. We can't do anything. Someone jinx it. But I think it's a generational thing. You know, I think baby boomers, like it's time to move along. I think it's time for a new generation to come in. And I actually have a lot of hope when I look at, you know, I'm sort of like this, I guess they call me a geriatric millennial or a young Gen X. But like we have this unique responsibility because I grew up without the internet and without social media, but I'm native to it. So I know the good and I know the bad. And that's true on so many different things. You know, I grew up without climate change anxiety and now I'm feeling it and I know it's not a given. We don't have to just resign ourselves to climate change. You know, same with disinformation. And I think a lot of the problems we face today have just exposed the sort of inertia that there's been on so many of these issues. And I really think it's a generational shift that has to happen. And I think this next generation is gonna come in and say like, we're not doing business like you guys did it anymore. You know, we're not just gonna like rape and pillage the earth and try and turn everyone against each other and play dirty tricks and let lobbyists dictate, you know, what we do or don't do as a country anymore. And that's really where I see the hope. It feels like there's a lot of low hanging fruit for young minds to step up and create solutions and lead. So whenever like politicians or leaders that are older, like you said, are acting shitty, I see that as a positive. They're inspiring a large number of young people to replace them. And so I think you're right. There's going to be, it's almost like you need people to act shitty to remind them, oh, wow, we need good leaders. We need great creators and builders and entrepreneurs and scientists and engineers and journalists. You know, all the discussions about how the journalism is quote unquote broken and so on, that's just an inspiration for new institutions to rise up that do journalism better, new journalists to step up and do journalism better. So I, and I've been constantly, when I talk to young people, I'm constantly impressed by the ones that dream to build solutions. And so that's ultimately why I put the hope. But the world is a messy place, like we've been talking about. It's a scary place. Yeah, and I think you hit something, hit on something earlier, which is authenticity. Like no one is going to rise above that is plastic anymore. You know, people are craving authenticity. You know, the benefit of the internet is it's really hard to hide who you are on every single platform. You know, on some level it's gonna come out who you really are. And so you hope that, you know, by the time my kids are grown, like no one's gonna care if they made one mistake online, so long as they're authentic, you know? And I used to worry about this. My nephew was born the day I graduated from college. And I just always, you know, he's like born into Facebook. And I just think like, how is a kid like that ever gonna be president of the United States of America? Because if Facebook had been around when I was in college, you know, like Jesus, you know, what, how are those kids gonna ever be president? There's gonna be some photo of them at some point making some mistake, and that's gonna be all over for them. And now I take that back. Now it's like, no, everyone's gonna make mistakes. There's gonna be a picture for everyone. And we're all gonna have to come and grow up to the view that as humans, we're gonna make huge mistakes. And hopefully they're not so big that they're gonna ruin the rest of your life. But we're gonna have to come around to this view that we're all human, and we're gonna have to be a little bit more forgiving and a little bit more tolerant when people mess up. And we're gonna have to be a little bit more humble when we do and like keep moving forward. Otherwise you can't like cancel everyone. Nicole, this is an incredible, hopeful conversation. Also one that reveals that in the shadows, there's a lot of challenges to be solved. So I really appreciate that you took on this really difficult subject with your book. That's journalism at its best. So I'm really grateful that you did it, that you took the risk, that you took that on. And that you plugged the cable box back in. That means you have hope. And thank you so much for spending your valuable time with me today. Thank you, thanks for having me. Thanks for listening to this conversation with Nicole Perleroth. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Nicole herself. Here we are, entrusting our entire digital lives, passwords, texts, love letters, banking records, health records, credit cards, sources, and deepest thoughts to this mystery box, whose inner circuitry most of us would never vet. Run by code, written in a language most of us will never fully understand. Thank you for listening and hope to see you next time.

https://youtu.be/hy2G3PhGm-g

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Jay Bhattacharya: The Case Against Lockdowns | Lex Fridman Podcast #254

The following is a conversation with Jay Bhattacharya, Professor of Medicine, Health Policy, and Economics at Stanford University. Please allow me to say a few words about lockdowns and the blinding, destructive effects of arrogance on leadership, especially in the space of policy and politics. Jay Bhattacharya is the co-author of the now famous Great Barrington Declaration, a one-page document that in October 2020 made a case against the effectiveness of lockdowns. Most of this podcast conversation is about the ideas related to this document. And so, let me say a few things here about what troubles me. Those who advocate for lockdowns as a policy often ignore the quiet suffering of millions that it results in, which includes economic pain, loss of jobs that give meaning and pride in the face of uncertainty, the increase in suicide and suicidal ideation, and, in general, the fear and anger that arises from the powerlessness forced onto the populace by the self-proclaimed elites and experts. Many folks whose job is unaffected by the lockdowns talk down to the masses about which path forward is right and which is wrong. What troubles me most is this very lack of empathy among the policy makers for the common man, and, in general, for people unlike themselves. The landscape of suffering is vast and must be fully considered in calculating the response to the pandemic with humility and with rigorous, open-minded scientific debate. Jay and I talk about the email from Francis Collins to Anthony Fauci that called Jay and his two co-authors fringe epidemiologists and also called for a devastating published takedown of their ideas. These words from Francis broke my heart. I understand them. I can even steelman them. But nevertheless, on balance, they show to me a failure of leadership. Leadership in a pandemic is hard, which is why great leaders are remembered by history. They are rare. They stand out. And they give me hope. Also, this whole mess inspires me on my small individual level to do the right thing in the face of conformity, despite the long odds. I talked to Francis Collins. I talked to Albert Bourla, Pfizer CEO. I also talked and will continue to talk with people like Jay and other dissenting voices that challenge the mainstream narratives and those in the seats of power. I hope to highlight both the strengths and weaknesses in their ideas with respect and empathy, but also with guts and skill. The skill part I hope to improve on over time. And I do believe that conversation and an open mind is the way out of this. And finally, as I've said in the past, I value love and integrity far, far above money, fame and power. Those latter three are all ephemeral. They slip through the fingers of anyone who tries to hold on and leave behind an empty shell of a human being. I prefer to die a man who lived by principles that nobody could shake and a man who added a bit of love to the world. This is the Lex Friedman podcast. To support it, please check out our sponsors in the description. And now here's my conversation with Jay Barucaria. To our best understanding today, how deadly is COVID? Do we have a good measure for this very question? So the best evidence for COVID, the deadliness of COVID comes from a whole series of seroprevalence studies. Seroprevalence studies are these studies of antibody prevalence in the population at large. I was part of the very first set of seroprevalence studies, one in Santa Clara County, one in LA County, and one with Major League Baseball around the US. If I may just pause you for a second, if people don't know what serology is and seroprevalence, it does sound like you say zero prevalence. It's not. It's sero and serology is antibodies. So it's a survey that counts the number of antibodies. Specific to COVID, yes. People that have antibodies specific to COVID, which perhaps shows an indication that they likely have had COVID, and therefore this is a way to study how many people in the population have been exposed to or have had COVID. Exactly. Yeah, exactly. So the idea is that we don't know exactly the number of people with COVID just by counting the people that present themselves with symptoms of COVID. COVID has, it turns out, a very wide range of symptoms possible, ranging from no symptoms at all to this deadly viral pneumonia that's killed so many people. And the problem is like if you just count the number of cases, the people who have very few symptoms often don't show up for testing. They're outside of the can of public health. And so it's really hard to know the answer to your question without understanding how many people are infected, because you can probably tell the number of deaths, even though there's some controversy over that. But that, so the numerator is possible, but the denominator is much harder. How much controversy is there about the death? We're going to go on a million tangents. Is that, okay, we're going to, I have a million questions. So one, I love data so much, but I'm like almost tuned out paying attention to COVID data because I feel like I'm walking on shaky ground. I don't know who to trust. Maybe you can comment on different sources of data, different kinds of data. The death one, that seems like a really important one. Can we trust the reported deaths associated with COVID, or is it just a giant messy thing that mixed up? And then there's this kind of stories about hospitals being incentivized to report a death as COVID death. So there's some truth in some of that. Let me just talk about the incentive. So in the United States, we passed this CARES Act that was aimed at making sure hospital systems didn't go bankrupt in the early days of the pandemic. A couple of things they did. One was they provided incentives to treat COVID patients, tens of thousands of dollars extra per COVID patient. And the other thing they did is they gave a 20% bump to Medicare payments for elderly patients who are treated with COVID. The idea is that they're more expensive to treat them, I guess, in the early days. So that did provide an incentive to sort of have a lot of COVID patients in the hospital, because your financial success in the hospital, or at least not lack of financial ruin, depended on having many COVID patients. The other thing on the death certificates is that reporting of deaths is a separate issue. I don't know that there's a financial incentive there, but there is this sort of like complicated, you know, when you fill out a death certificate for a patient with a lot of conditions, like let's say a patient has diabetes, a patient that, well, that diabetes could lead to heart failure. You know, you have a heart attack, heart failure, your lungs fill up, then you get COVID, and you die. So what do you write on the death certificate? Was it COVID that killed you? Was it the lungs filling up? Was it the heart failure? Was it the diabetes? It's really difficult to like disentangle. And I think a lot of times what's happened is people have like erred on the side of signing as COVID. Now, what's the evidence of this? There's been a couple of audits of death certificates in places like Santa Clara County, where I live, in Alameda County, California, where they carefully went through the death certificates and said, okay, is this reasonable to say this was actually COVID or was COVID incidental? And they found that about 25%, 20, 25% of the deaths were more likely incidental than directly due to COVID. I personally don't get too excited about this. I mean, it's a philosophical question, right? Like ultimately, what kills you? Which is an odd thing to say if you're not in medicine, but like really, it's almost always multifactorial. It's not always just the bus hits you. The bus hits you, you get a brain bleed. Was the brain bleed that killed you, would it have burst anyway? I mean, the bus hit you, killed you, right? The way you die is a philosophical question, but it's also a sociological and psychological question, because it seems like every single person who's passed away over the past couple of years, kind of the first question that comes to mind. Was it COVID? Was it COVID? Not just because you're trying to be political, but just in your mind. No, I think there's a psychological reason for this, right? So, you know, we spent the better part of at least a half century in the United States not worried too much about infectious diseases. The notion was we'd essentially conquered them. It was something that happens in faraway places to other people. And that's true for much of the developed world. Life expectancy were going up for decades and decades. And for the first time in living memory, we have a disease that can kill us. I mean, I think we're effectively evolved to fear that. Like the panic centers of our brain, the lizard part of our brain takes over. And our central focus has been avoiding this one risk. And so it's not surprising that people, when they're filling out death certificates or thinking about what led to the death, this most salient thing that's in the front of everyone's brain would jump to the top. And we can't ignore this very deep psychological thing when we consider what people say on the internet, what people say to each other, what people write in scientific papers, everything. It feels like when COVID has been brought onto this world, everything changed in the way people feel about each other. Just the way they communicate with each other. I think the level of emotion involved, I think in many people, it brought out the worst in them. For sometimes short periods of time, and sometimes it was always therapeutic, like you were waiting to get out the darkest parts of you, just to say, if you're angry at something in this world, I'm going to say it now. And I think that's probably talking to some deep primal thing, that fear we have for maladies of all different kinds. And then when that fear is aroused in all the deepest emotions, it's like a Freudian psychotherapy session, but across the world. It's something that psychologists are going to have a field day with for a generation, trying to understand. I think what you say is right, but piled on top of that is also this impetus to empathy, to empathize, compassion toward others, essentially militarized. So I'm protecting you by some actions, and those actions, if I don't do them, if you don't do them, well, that must mean you hate me. It's created this social tension that I've never seen before. And we looked at each other as if we were just simply sources of germs, rather than people to get to know, people to enjoy, people to learn from. It colored basically almost every human interaction for every human on the planet. Yeah, the basic common humanity. It's like you can wear a mask, you can stand far away, but the love you have for each other when you look into each other's eyes, that was dissipating by region, too. I've experienced, having traveled quite a bit throughout this time, it was really sad, even people that are really close together, just the way they stood, the way they looked at each other. And it made me feel for a moment that the fabric that connects all of us is more fragile than I thought. I mean, if you walk down the street, or if you did this during COVID, I'm sure you had this experience where you walk down the street, if you're not wearing a mask, or even if you are, people will jump off the sidewalk that you walk past them, as if you're poison. Even though the data are that COVID spreads indifferently outdoors, or if at all, really, outdoors. But it's not simply a biological or infectious disease phenomenon, or epidemiological, it is a change in the way humans treat each other. I hope temporary. I do want to say on the flip side of that, so I was mostly in Boston, Massachusetts when the pandemic broke out, I think that's where I was, yeah. And then I came here to Austin, Texas, to visit my now good friend Joe Rogan, and he was the first person, without pause, this wasn't a political statement, this was anything, just walked toward me, gave me a big hug, and said, it's great to see you. And I can't tell you how great it felt, because I, in that moment, realized the absence of that connection back in Boston over just a couple of months. And we'll talk about it more, but it's tragic to think about that distancing, that dissolution of common humanity at scale, what kind of impact it has on society. Just across the board, political division, and just in the quiet of your own mind, in the privacy of your own home, the depression, the sadness, the loneliness that leads to suicide, and forget suicide, just low-key suffering. Yeah, no, I think that's the suffering, that isolation. We're not meant to live alone. We're not meant to live apart from one another. That's, of course, the ideology of lockdown, to make people live apart, alone, isolated, so that we don't spread diseases to each other. But we're not actually designed as a species to live that way. And that, what you're describing, I think, if everyone's honest with themselves, have felt, especially in places where lockdowns have been very militantly enforced, has felt deep into their core. Well, if I could just return to the question of deaths. You said that the data isn't perfect, because we need these kind of seroprevalence surveys to understand how many cases there were, to determine the rate of deaths. And we need to have a strong footing in the number of deaths. But if we assume that the number of deaths is approximately correct, what's your sense, what kind of statements can we say about the deadliness of COVID across different demographics? Maybe not in a political way, or in the current way, but when history looks back at this moment of time, 50 years from now, 100 years from now, the way we look at the pandemic 100 years ago, what will they say about the deadliness of COVID? I think the deadliness of COVID depends on not just the virus itself, but who it infects. So probably the most important thing about the deadliness of COVID is this steep age gradient in the mortality rate. So according to these seroprevalence studies that have been done, now hundreds of them, mostly from before vaccination, because vaccination also reduces the mortality risk of COVID, the seroprevalence studies suggest that the risk of death, if you're, say, over the age of 70, is very high, you know, 5% if you get COVID. If you're under the age of 70, it's lower, 0.05. But there's not a single sharp cutoff. It's more like, I have a rule of thumb that I use. So if you're 50, say, the infection fatality rate from COVID is 0.2%, according to the seroprevalence data. That means 99.8% survival if you're 50. And for every seven years of age above that, double it. Every seven years of age below that, have it. So a 57-year-old would have a 0.4% mortality, a 64-year-old would have a 0.8%. And so on. And if you have a severe chronic disease, like diabetes, or if you're morbidly obese, it's like adding seven years to your life. And this is for unvaccinated folks? This is unvaccinated before Delta also. Are there a lot of people that will be listening to this with PhDs at the end of their name that would disagree with the 99.8, would you say? So I think there's some disagreement over this. And the disagreement is about the quality of the seroprevalence studies that were conducted. So as I said earlier, I was a senior investigator in three different seroprevalence studies, very early in the epidemic. I view them as very high-quality studies. In Santa Clara County, what we did is we used a test kit that we obtained from someone who works in Major League Baseball, actually. He ordered these test kits very early, in March 2020, that very accurately measures antibodies in the bloodstream. These test kits were approved by the, had an EUA, by the Emergency Use Authorization by the FDA, sort of shortly after we did this. And it had a very low false positive rate. False positive means if you don't have these COVID antibodies in your bloodstream, the kit shows up positive anyways. That turns out to happen about 0.5% of the time. And based on studies, a very large number of studies looking at blood from 2018, you try it against this kit, and 0.5% of the time, 2018, there shouldn't be antibodies there. So for COVID, if it turns positive, it's a false positive, 0.5% of the time. And then, you know, like a false negative rate, about 10%, 12%, something like that. I don't remember the exact number. But the false positive rate's the important thing there, right? So you have a population in March 2020 or April 2020 with very low fraction of patients having been exposed to COVID. You don't know how much, but low. Even a small false positive rate could end up biasing your study quite a bit. But there's a formula to adjust for that. You can adjust for the false positive rate, false negative rate. We did that adjustment, and those studies found in a community population, so leaving aside people in nursing homes who have a higher death rate from COVID, that the death rate was 0.2% in Santa Clara County and in L.A. County. Across all age groups in the community, community meaning just like regular folks? Yeah, so that's actually a real important question, too. So the Santa Clara study, we did this Facebook sampling scheme, which is, I mean, not the ideal thing, but it was very difficult to get a random sample during lockdown, where we put out an ad on Facebook soliciting people to volunteer for the study, a randomly selected set of people. We were hoping to get a random selection of people from Santa Clara County, but the people who tended to volunteer were from the richer parts of the county. I had Stanford professors writing, begging to be in the study because they wanted to know their antibody levels. So we did some adjustment for that. In L.A. County, we hired a firm that had a pre-existing representative sample of L.A. County. But it didn't include nursing homes. It didn't include people in jail, things like that. It didn't include the homeless populations. So it's representative of a community dwelling population, both of those. And there we found that both in L.A. County and Santa Clara County in April 2020, something like 40 to 50 times more infections than cases in both places. So for every case that had been reported to the public health authorities, we found, you know, 40 or 50 other infections, people with antibodies in their blood, that suggested that they'd had COVID and recovered. So people were not reporting, or severe, at least in those days, underreporting. Yeah, I mean, there was, you know, there's testing problem. There weren't so many tests available. People didn't know. A lot of them, we asked a set of questions about the symptoms they'd faced. And most of them said they faced no symptoms, or at the most, 30, 40% of them said they faced no symptoms. I mean, even these days, how many people report that they get COVID when they get COVID? Okay, have those numbers, that 0.2%, has that approximately held up over time? That is. So if Professor John Ioannidis, who's a colleague of mine at Stanford, is a world expert in meta-analysis, probably the most cited scientist on Earth, I think, at least living, he did a meta-analysis of now 100 or more of these seroprevalence studies. And what he found was that that 0.2% is roughly the worldwide number. In fact, I think he cites a lower number, 0.15%, as the median infection fatality rate worldwide. So we did these studies, and it generated an enormous amount of blowback by people who thought that the infection fatality rate is much higher. And there's some controversy over the quality of some of the other studies that are done. And so there are some people who look at this same literature and say, well, the lower quality studies tend to have lower IFRs. The higher quality studies... IFR? Oh, infection fatality, right? I apologize. I do this in lectures, too. And I'm going to rudely interrupt you and ask for the basics sometimes, if it's okay. No, of course. So these higher quality studies, they say, tend to produce higher IR. But the problem is that if you want a global infection fatality rate, you need to get seroprevalence studies from everywhere, even in places that don't necessarily have the infrastructure set up to produce very, very high quality studies. And in poor places in the world, places like Africa, the infection fatality rate is incredibly low. And in some richer places, like New York City, the infection fatality rate is much higher. There's a range of IFRs, not a single number. This sometimes surprises people, because they think, well, it's a virus. It should have the same properties no matter where it goes. But the virus kills or infects or hurts in interaction with the host. And the properties of both the host and the virus combine to produce the outcome. But you also mentioned the environment, too? Well, I'm thinking mainly just about the person. In fact, if I'm going to think about it, the most simplest way to think about it is age. Age is the single most important risk factor. So older places are going to have a higher IFR than younger places. Africa, 3% of Africa is over 65. So in some sense, it's not surprising that they have a low infection fatality rate. So that's one way you would explain the difference between Africa and New York City, in terms of the fatality rate, is the age, the average age? Yeah, and especially in the early days of the epidemic in New York City, the older populations living in nursing homes were differentially infected, based on, because of policies that were adopted, right, to send COVID-infected patients back to nursing homes to keep hospitals empty. What do you mean by differentially infected? The policy that you adopt determines who is most exposed. Right. Okay. So that's what I mean by different. So it's the policy, it's the person that matters. I mean, it's not like the virus just kind of doesn't care. I mean, the policy determines the nature of the interaction, and there's also, I mean, there is some contribution from the environment, different regions have different proximity, maybe, of people interacting, or the dynamics of the way they interact. Yeah, the heterogeneity, like if you have situations where there's lots of intergenerational interactions, then you have a very different risk profile than if you have societies where generations are more separate from one another. Okay, so let me just finish real fast about this. So you have, in New York, you have a population that was infected in the early days that was very likely going to die, but had a much higher likelihood of dying if infected. And so New York City had a higher IFR, especially in the early days, than like Africa has had. The other thing is treatment, right? So the treatments that we adopted in the early days of the epidemic I think actually may have exacerbated the risk of death. Which treatments? So like using ventilators, like the over-reliance on ventilators is what I'm primarily thinking of, but I can think of other things. But that also, we've learned over time how better to manage patients with the disease. So you have all those things combined, so that's where the controversy over this number is. I mean, New York City also is a central hub for those who tweet and those who write powerful stories and narratives in article form. And I remember there was quite dramatic stories about doctors in the hospitals and these kinds of things. I mean, there's very serious, very dramatic, very tragic deaths going on always in hospitals. Those stories, loved ones losing each other on a deathbed, that's always tragic. And you can always write a hell of a good story about that, and you should, about the loss of loved ones. But they were doing it pretty well, I would say, over this kind of dramatic deaths. And so in response to that, it's very unpleasant to hear, even to consider the possibility that the death rate is not as high as you might feel. Yeah, I was surprised by the reaction, both by regular people and also the scientific community in response to those studies, those early studies in April of 2020. To me, they were studies. I mean, they're the kinds of, not exactly the kinds of work I've worked on all my life, but kind of like, you know, you write a paper and you get responses from your fellow scientists, and you change the paper to improve it, and you hopefully learn something from it. But to push back, it's just a study, but there's some studies, and this is kind of interesting, because I've received similar pushback on other topics. There's some studies that, if wrong, might have wide-ranging detrimental effects on society. So that's the way they would perceive the studies. If you say the death rate is lower, and you end up, as you often do in science, realizing that, nope, that was a flaw in the way the study was conducted, or we're just not representative of a broader population, and then you realize the death rate is much higher, that might be very damaging in people's view. So that's probably where the scientific community, to steel man the kind of response, is that's where they felt like, you know, there's some findings where you better be damn sure before you kind of report them. Yeah, I mean, we were pretty sure we were right, and it turns out we were right. So we released the Santa Clara study via this open science process, and this server called MedArchive. It's designed for releasing studies that have not yet been peer-reviewed in order to garner comment from the scientists before peer review. The LA County study, we went through this traditional peer review process, and got it published in the Journal of American Medical Association sometime in like July, I think, I forget the date, of 2020. The Santa Clara study released in April of 2020 in this sort of working paper archive. The reason was that we felt we had an obligation, we had a result that we thought was quite important, and we wanted to tell the scientific community about it, and also tell the world about it. And we wanted to get feedback. I mean, that's part of the purpose of sending it to these kinds of places. I think a lot of the problem is that when people think about published science, they think of it as automatically true. And if it goes through peer review, it's automatically true. If it hasn't gone through peer review, it's not automatically true. And especially in medicine, we're not used to having this access to pre-peer reviewed work. I mean, in economics, actually, that's quite normal. It takes years to get something published, so there's a very active debate over or discussion about papers before they're peer reviewed in this sort of working paper way. Much less normal, or much newer in medicine. And so I think part of that, the perception about what process happens in open science when you release a study, that got people confused. And you're right, it was a very important result, because we had just locked the world down in the middle of March with, I think, catastrophic results. And if that study was right, if our study was right, that meant we'd made a mistake. And not because the death rate was low. That's actually not the key thing there. The key thing is that we had adopted these policies, these test and trace policies, these lockdown policies aimed at suppressing the virus level to close to zero. That was essentially the idea. If we can just get the virus to go away, we won't have to ever worry about it again. The main problem with our result as far as that strategy was concerned wasn't the death rate. It was the 40 to 50 times more infections than cases. It was the 2.5% or 3% or 4% prevalence rate that we identified of the antibodies in the population. If that number is right, it's too late. The virus is not going to go to zero. And no matter how much we test and trace and isolate, we're not going to get the viral level down to zero. So we're gonna have to let the virus go through the entire population in some way or some other way? We can talk about that in a bit. That's the Great Barrington Declaration. You don't have to let the virus go through the population. You can shield preferentially. The policy we chose was to shield preferentially the laptop class. The set of people who could work from home without losing their job. And we did a very good job at protecting them. Well, let me take a small tangent. We're gonna jump around in time, which I think will be the best way to tell the story. So that was the beginning. Yeah. Okay, actually, can I go back one more thing for that? Because that's really important and I should have started with this. What led me to do those studies was a paper that I had remembered seeing from the H1N1 flu epidemic in 2009. I had been much less active in writing about that. I had written a paper or two about that in 2009. There was actually this same debate over the mortality rate, except it unfolded over the course of three years, two or three years. The early studies of the mortality rate in H1N1 counted the number of cases in the denominator, kind of the number of deaths in the numerator, cases meaning people identified as having H1N1, showing up to doctor, you know, tested to have it. And the early estimates of H1N1 mortality were like 4%, 3%, really, really high. Over the course of a couple of more years, a whole bunch of seroprevalence studies, seroprevalence studies of H1N1 flu came out. And it turned out that there were a hundred or more times people infected per case. And so the mortality rate was actually something like 0.02% for H1N1, not the three, like a hundredfold difference. So this made you think, okay, it took us a couple of two or three years to discover the truth behind the actual infections for H1N1. And then what's the truth here and can we get there faster? Yeah, and it spreads in a similar way as the H1N1 flu did. I mean, it spreads via aerosolization, via, you know, so person-to-person breathing, kind of contact up. It may be some by fomites, but it seems like that's less likely now. In any case, it seemed really important to me to speed up the process of having those seroprevalence studies, so that we can better understand who was at risk and what the right strategy ought to be. This might be a good place to kind of compare influenza, the flu, and COVID in the context of the discussion we just had, which is how deadly is COVID? So you mentioned COVID is a very particular kind of steepness, where the x-axis is age. So in that context, could you maybe compare influenza and COVID? Because a lot of people outside of the folks who suggest that the lizards who run the world have completely fabricated, invented COVID, outside of those folks, kind of the natural process by which you dismiss the threat of COVID is say, well, it's just like the flu. The flu is a very serious thing, actually. So in that comparison, where does COVID stand? Yeah, the flu is a very serious thing. It kills 50,000, 60,000 people a year, something like that, or depending on the particular strain that goes around, that's in the United States. The primary difference to me, there's lots of differences, but one of the most salient differences is the age gradient and mortality risk for the flu. So the flu is more deadly for two children than COVID is. There's no controversy about that. Children, thank God, have much less severe reactions to COVID infection than they do to flu infections. And rate of fatalities and stuff like that. Rate of fatality, all of that. I think you mentioned, I mean, it's interesting to maybe also comment on, I think in another conversation you mentioned there's a U-shape to the flu curve. So meaning like there's actually quite a large number of kids that die from flu. Yeah. I mean, the 1918 flu, the H1N1 flu, the Spanish flu in the U.S. killed millions of younger people. And that is not the case with COVID. More than, I'm going to get the number wrong, but something like 70, 80% of the deaths are people over the age of 60. We've talked about the fear the whole time, really. But my interaction with folks, now I want to have a family, I want to have kids, but I don't have that real firsthand experience. But my interaction with folks is at the core of fear that folks had is for their children. Like that somehow, you know, I don't want to get infected because of the kids. Like, because God forbid something happens to the kids. And I think that obviously that makes a lot of sense, this kind of the kids come first, no matter what, that's the number one priority. But for this particular virus, that reasoning was not grounded in data, it seems like, or that emotion and feeling was not grounded in data. Yeah, it wasn't. But at the same time, this is way more deadly than the flu just overall, and especially to older people. Yes. Right? So the numbers, when the story is all said and done, COVID would take many more lives. Yeah. So, I mean,.2 sounds like a small number, but it's not a small number worldwide. What do you think that number will be by the, you know, that's not like, but would we cross, I think it's in the United States, it's the way the deaths are currently reported, it's like 800,000, something like that. Do you think we'll cross a million? Seems likely, yeah. Do you think it's something that might continue with different variants? Well, I think, so we can talk about the end state of COVID, the end state of COVID is it's here forever. I think that there is good evidence of immunity after infection, such that you're protected both against reinfection and also against severe disease upon reinfection. So the second time you get it, it's not true for everyone, but for many people, the second time you get it will be milder, much milder than the first time you get it. With the long tail, like that lasts for a long time. Yeah. So just there are studies that follow a course of people who were infected for a year, and the reinfection rate is something like somewhere between.3 and 1%. Yeah. And like a pretty fantastic study out of Italy found that, there's one in Sweden, I think, there's a few studies that found similar things. And the reinfections tend to produce much milder disease, much less likely to end up in the hospital, much less likely to die. So what the end state of COVID is, it's circulating in the population forever, and you get it multiple times. Yeah. And then there's, I think, studies and discussions like the best protection would be to get it and then also to get vaccinated. And then a lot of people push back against that for the obvious reasons from both sides, because somehow this discourse has become less scientific and more political. Well, I think you want to, the first time you meet it is going to be the most deadly for you. And so the first time you meet it, it's just wise to be vaccinated. The vaccine reduces severe disease. Yeah, we'll talk about the vaccine, because I want to make sure I address it carefully and properly in full context. But yes, sort of to add to the context, a lot of the fascinating discussions we're having is in the early days of COVID and now for people who are unvaccinated. That's where the interesting story is. The policy story, the sociological story, and so on. But let me go to something really fascinating, just because of the people involved, the human beings involved, and because of how deeply I care about science and also kindness, respect, and love, and human things. Francis Collins wrote a letter in October 2020 to Anthony Fauci, I think somebody else. I have the letter, it's not a letter, email, I apologize. Hi Tony and Cliff, cgbdeclaration.org. This proposal, this is the Great Barrington Declaration that you're a co-author on. This proposal from the three fringe epidemiologists who met with the secretary seemed to be getting a lot of attention and even a co-signature from Nobel Prize winner Mike Levitt at Stanford. There needs to be a quick and devastating published takedown of its premises. I don't see anything like that online yet. Is it underway? Francis Collins, director of the NIH, somebody I talked to on this podcast recently. Okay, a million questions I want to ask, but first, how did that make you feel when you first saw this email come to light? When did it come to light? This week, actually, I think, or last week. Okay, so this is because of freedom of information. Which, by the way, sort of, maybe because I do want to add positive stuff on the side of Francis here. Boy, when I see stuff like that, I wonder if all my emails leaked. How much embarrassing stuff. Like, I think I'm a good person, but I don't, I haven't read my old emails. Maybe, I'm pretty sure sometimes later I could be an asshole. Well, I mean, look, he's a Christian, and I'm a Christian, I'm supposed to forgive, right? I mean, I think he was looking at this Great Barrington Declaration as a political problem to be solved, as opposed to a serious alternative approach to the epidemic. So, maybe we'll talk about it in more detail, but just in case people are not familiar, the Great Barrington Declaration was a document that you co-authored that basically argues against this idea of lockdown as a solution to COVID, and you proposed another solution that we'll talk about. But the point is, it's not that dramatic of a document. It is just a document that criticizes one policy solution that was proposed. But it was the policy solution that had been put forward by Dr. Collins and by Tony Fauci and a few other scientists. I mean, I think a relatively small number of scientists and epidemiologists in charge of the advice given to governments worldwide. And it was a challenge to that policy that said that, look, there is an alternate path, that the path we've chosen, this path of lockdown with an aim to suppress the virus to zero, effectively, I mean, that was unstated, cannot work and is causing catastrophic harm to large numbers of poor and vulnerable people worldwide. We put this out in October 4th, I think, of 2020, and it went viral. I mean, I've never actually been involved with anything like this, where I just put the document on the web, and tens of thousands of doctors signed on, hundreds of thousands of regular people signed on. It really struck a chord of people, because I think even by October 2020, people had this sense that there was something really wrong with the COVID policy that we've been following. And they were looking for reasonable people to give an alternative. I mean, we're not arguing that COVID isn't a serious thing. I mean, it is a very serious thing. This is why we had a policy that aimed at addressing it. We were saying that the policy we're following is not the right one. So how does a democratic government deal with that challenge? So to me, you asked me how I felt. I was actually, frankly, just, I suspected there had been some email exchanges like that, not necessarily from Francis Collins, around the government around this time. I mean, I felt the full brunt of a propaganda campaign almost immediately after we published it, where newspapers mischaracterized it in the same way over and over and over again, and sought to characterize me as sort of a marginal fringe figure or whatnot. And Sunetra Gupta, Martin Kulldorff, or the tens of thousands of other people that signed it. I felt the brunt of that all year long. So to see this in black and white, with the handwriting, essentially, I mean, the metaphorical handwriting of Francis Collins was actually, frankly, a disappointment, because I've looked up to him for years. Yeah, I've looked up to him as well. I mean, I look for the best in people, and I still look up to him. What troubles me is several things. The reason I said about the asshole emails I send late at night is, I can understand this email. It's fear, it's panic, not being sure. The fringe, three fringe epidemiologists. Plus Mike Levitt, who won a Nobel Prize. I mean... Using fringe, maybe in my private thoughts, I have said things like that about others, like a little bit too unkind. Like, you don't really mean it. Now, add to that, he recently, this week or whatever, doubled down on the fringe. This is really troubling to me. I can excuse this email, but the arrogance there. Francis, honestly, broke my heart a little bit there. This is an opportunity to, especially at this stage, to say, just like I told him, to say I was wrong to use those words in that email. I was wrong to not be open to ideas. I still believe that this is not... Like, actually argue with the policy, the proposed solution. Also, the devastating, published, devastating takedown. Devastating takedown. As you say, somebody who's sitting on billions of dollars that they're giving to scientists, some of whom are often not their best human beings because they're fighting with each other over money. Not being cognizant of the fact that you're challenging the integrity, you're corrupting the integrity of scientists by allocating them money. You're now playing with that by saying devastating takedown. Where do you think the published takedown will come from? It will come from those scientists to whom you're giving money. What kind of example would they give to the academic community that thrives on freedom? Like, this is... I believe Francis Collins is a great man. One of the things I was troubled by is the negative response to him from people that don't understand the positive impact that NIH has had on society. How many people it's helped. But this is exactly the... So he's not just a scientist. He's not just a bureaucrat who distributes money. He's also a scientific leader that in difficult times we live in, is supposed to inspire us with trust, with love, with the freedom of thought. He's supposed to... You know those fringe epidemiologists? Those are the heroes of science. When you look at the long arc of history, we love those people. We love ideas even when they get proven wrong. That's what always attracted me to science. Like somebody, the lone voice saying, oh no, the moon of Jupiter does move. But the funny thing is, Galileo was saying something truly revolutionary. We were saying that what we proposed in the Great Barrington Declaration was actually just the old pandemic plan. It wasn't anything really fundamentally novel. In fact, there were plans like this that lockdown scientists had written in late February, early March of 2020. So we were not saying anything radical. We were just calling for a debate effectively over the existing lockdown policy. And this is a disappointment, a really, truly a big disappointment. Because by doing this, you were absolutely right, Lex, he sent a signal to so many other scientists to just stay silent, even if you had reservations. Yeah, devastating takedown that people... You know how many people wrote to me privately, like Stanford, MIT, how amazing the conversation with Francis Collins was? There's a kind of admiration because... Okay, how do I put it? A lot of people get into science because they want to help the world. They get excited by the ideas and they really are working hard to help in whatever the discipline is. And then there is sources of funding which help you do help at a larger scale. So you admire the people that are distributing the money because they're often, at least on the surface, are really also good people. Oftentimes they're great scientists. So it's amazing. That's why I'm sort of... Sometimes people from outside think academia is broken some kind of way. No, it's a beautiful thing. It really is a beautiful thing. And that's why it's so deeply heartbreaking where this person is... I don't think this is malevolence. I think he's just incompetence at communication, twice. I think there's also arrogance at the bottom of it too. But all of us have arrogance at the bottom. Yes, but there's a particular kind of arrogance. So here it's of the same kind of arrogance that you see when Tony Fauci gets on TV and says that if you criticize me, you're not simply criticizing a man, you're criticizing science itself. That is at the heart also of this email. The certainty that the policies that they were recommending, Collins and Fauci were recommending to the President of the United States, were right. Not just right, but right so far right that any challenge whatsoever to it is dangerous. And I think that is really the heart of that email. It's this idea that my position is unchallengeable. Now, to be as charitable as I can be to this, I believe they thought that. I believe some of them still think that. That there was only one true policy possible in response to COVID. Every other policy was immoral. And if you come from that position, then you write an email like that. You go on TV, you say effectively, la science est moi. I mean, that is what happens when you have this sort of unchallengeable arrogance that the policy you're following is correct. I mean, when we wrote the Great Bank Declaration, what I was hoping for was a discussion about how to protect the vulnerable. I mean, that was the key idea to me in the whole thing, was better protection of the older population who are really at really serious risk if infected with COVID. And we had been doing a very poor job, I thought, to date in many places in protecting the vulnerable. And what I wanted was a discussion by local public health about better methods, better policies to protect the vulnerable. So when we were met with, instead, a series of essentially propagandist lies about it. So for instance, I kept hearing from reporters in those days, why do you want to let the virus rip? Let it rip, let it rip. The words let it rip does not appear in the Great Bank Declaration. The goal isn't to let the virus rip. The goal is to protect the vulnerable. To let society go as, you know, open schools and do other things that function as best it can in the midst of a terrible pandemic, yes, but not let the virus rip, where the most vulnerable aren't protected. The goal was to protect the vulnerable. So why let it rip? Because it was a propaganda term to hit the fear centers of people's brains. Oh, these people are immoral. They just want to let the virus go through society and hurt everybody. That was the idea. It was a way to preclude a discussion and preclude a debate about the existing policy. So I have this app called Clubhouse. I've gone back on it recently to practice Russian, unrelated, for a few big Russian conversations coming up. Anyway, it's a great way to talk to regular people in Russian. But I also, there was a, I was nervous, I was preparing for a Pfizer CEO conversation, and there was a vaccine room. I joined it. And it was a pro-science room. These are like scientists that were calling each other pro-science. The whole thing was like theater to me. I mean, I haven't thoroughly researched, but looking at the resume, they were like pretty solid researchers and doctors, and they were mocking everybody who was at all, I mean, it doesn't matter what they stood for, but they were just mocking people, and the arrogance was overwhelming. I had to shut off because I couldn't handle that human beings can be like this to each other. And then I went back just to double check, is this really happening? How many people are here? Is this theater? And then I asked to come on stage on Clubhouse to make a couple comments, and then as I opened my mouth and said, thank you so much, this is a great room, sort of the usual civil politeness, all that kind of stuff, and I said, I'm worried that the kind of arrogance with which things are being discussed here will further divide us, not unite us. And before I said even the unite us, further divide us, I was thrown off stage. Now, this isn't why I mentioned platform, but I am like Lex Friedman, MIT, also, which is something those people seem to sometimes care about, followers and stuff like that. Did you just do that? And then they said, enough of that nonsense. Enough of that nonsense. They said to me, enough of that nonsense. Somebody who is obviously interviewed Francis Collins, is the Pfizer CEO. You're bringing on French epidemiologists also. Yeah, exactly. But this broke my heart, the arrogance. And echoes of that arrogance is something you see in this email. And I really would love to, we have a million things to talk about, to try to figure out how can we find a path forward. I think a lot of the problems we've seen in the discussion over COVID, especially in the scientific community, there's two ways to look at science, I think, that have been competing with each other for a while now. One way, and this is the way that I view science, and why I've always found it so attractive, is an invitation to a structured discussion where the discussion is tempered by evidence, by data, by reasoning and logic. So it's a dialectical process where if I believe A and you believe B, well, we talk about it, we come up with an experiment that distinguishes between the two. And while B turns out to be right, I'm all frustrated, but I buy you dinner and I say, no, no, no, C. And then we go on from there, right? That's what science is at its best. It's this process of using data in discussion. It's a human activity, right? To learn, to have the truth unfold itself before us. On the other hand, there's another way that people have used science or thought about science as truth in and of itself, right? This like, if it's science, therefore it's true automatically. And what does the science say to do? Well, the science never says to do anything. The science says, here's what's true. And then we have to apply our human values to say, okay, well, if we do this, well, then this is likely to happen. That's what the science says. If we do that, then that is likely to happen. Well, we'd rather have this than that, right? And, but it doesn't, science doesn't tell us that we'd rather have this than that. It's our human values that tell us that we'd rather have this than that. Science plays a role, but it's not the only thing. It's not the only role. It's like, it helps understand the constraints we face, but it doesn't tell us what to do in face of those constraints. But underneath it, at the individual level, at the institutional level, it seems like arrogance is really destructive. So the flip side of that, the productive thing is humility. So sort of always not being sure that you're right. This is actually kind of, Stuart Russell talks about this for AI research. How do you make sure that AI, super intelligent AI doesn't destroy us? You built in a sort of module within it that it always doubts its actions. Like it's not sure. Like I know it says I'm supposed to destroy all humans, but maybe I'm wrong. And that maybe I'm wrong is essential for progress, for actually doing in the long arc of history, better, not the perfect thing, but better and better and better and better. I mean, the question I have here for you is this, this email so clearly captures some maybe echo, but maybe a core to the problem. Do you put responsibility of this email of the shortcomings and failures on individuals or institutions? Is this Francis Collins-Antonin? No, this is an institutional failure, right? So the NIH, so I've had two decades of NIH funding. I've sat on NIH review panels. The purpose of the NIH is what you said earlier, Lex. The purpose of the NIH is to support the work of scientists. To some extent, it's also to help scientists, to direct scientists to work on things that are very important for public health or for the health of the public. So, and the way you do that is you say, okay, we're going to put $50 million on the research in Alzheimer's disease this year or $70 million on HIV or whatever it is, right? And that pot of money then scientists compete with each other for the best ideas to use it to address that problem. So it's essentially an endeavor to support the work of scientists. It is not in and of itself a policy organ. It doesn't say what public health policy should be. For that, you have the CDC. And what happened during the pandemic is that people in the NIH were called upon to contribute to public health policymaking. And that created the conflict of interest you see in that email, right? So now you have the head of the NIH in effect saying to all scientists, you must agree with me in the policy that I've recommended or else you're a fringe. That is a deep conflict of interest. It's deep because first he's conflicted. He has this dual role as the head of the NIH supporter of scientific funding and then also inappropriately called to set or help set pandemic policy. That should never have happened. There should be a bright line between those two roles. Let me ask you about just Francis Collins. I don't know if you, I had a chance to talk to him on a podcast. I don't know if you maybe by chance gotten a chance to hear a few words. I heard some of it, yeah. Well, I have a kind of a question to that because a lot of people wrote to me quite negative things about Francis Collins. And like I said, I still believe he's a great man, a great scientist. One of the things when I talked to him off mic about the vaccine, the excitement he had about when we were recollecting when they first gotten an inkling that it's actually going to be possible to get a vaccine. He wasn't messaging, just in the private of our own conversation, he was really excited. And why was he excited? Because he gets to help a lot of people. This is a man that really wants to help people. And there could be some institutional self-delusion, the arrogance, all those kinds of things that lead to this kind of email. But ultimately the goal is, I don't think people quite realize this. The reason he would call you a fringe epidemiologist, the reason there needs to be a devastating published takedown, he, I believe, really believes that this could be very dangerous. And it's a lot of burden to carry on his shoulders because, like you said, in his role where he defines some of the public policy, like, you know, depending on how he thinks about the world, millions of people could die because of one decision he make. And that's a lot of burden to walk with. Yeah, no, I think that's right. I don't think that he has bad intentions. I think that he was basically put, or maybe put himself in a position where this kind of conflict of interest was going to create this kind of reaction. The kind of humility that you're calling for is almost impossible when you have that dual role that you shouldn't have as funder of science and also setter of scientific policy. I agree with everything you just said except the last part. The humility is almost impossible. Humility is always difficult. I think there's a huge incentive for humility in that position. Look at history. Great leaders that have humility are popular as hell. So if you like being popular, if you like having impact, legacy, these descendants of apes seem to care about legacy, especially as they get older in these high positions. I think the incentive for humility is pretty high. Well, I mean, the thing is there's a lot that he has to be proud of in his career. I mean, the Human Genome Project wouldn't have happened without him. And he is a great man and a great scientist. So it is tragic to me that his career has ended in this particular way. Can I ask you a question about my podcast conversation with him? By way of advice or maybe criticism, there's a lot of people that wrote to me kind words of support and a lot of people that wrote to me respectful, constructive criticism. How would you suggest to have conversations with folks like that? And maybe, I mean, because I have other conversations like this, including I was debating whether to talk to Anthony Fauci. He wanted to talk. And so what kind of conversation do you have? And sorry to take us on a tangent, but almost from an interview perspective of how to inspire humility and inspire trust in science and maybe give hope that we know what the heck we're doing and we're going to figure this out. I mean, I think I've been now interviewed by many people. I think the style you have really works well, Lex. I don't think you're going to be ever an attack dog trying to go after somebody and force them to submit that they were wrong or whatever about it. I mean, I also actually find that form of journalism and podcasting really off-putting. It's hard to watch. Also, it's a whole other tangent. Is that actually effective? I don't think so. Do you want to ask Hitler? And I think about this a lot, actually interviewing Hitler. I've been studying a lot about the rise and fall of the Third Reich. I think about interviewing Stalin. I put myself in that mindset. How do you have conversations with people to understand who they are, not so you can sit there and yell at them, but to understand who they are so that you can inspire a very large number of people to be the best version of themselves and to avoid the mistakes of the past? I believe that everyone that's involved in this debate has good intentions. They're coming at it from their points of view. They have their weaknesses. And if you can paint a picture in your questioning, by sympathetic questioning of those strengths and weaknesses and their point of view, you've done a service. That's really all I personally like to see in those kinds of interviews. I don't think a gotcha moment is really the key thing there. The key thing is understanding where they're coming from, understanding their thinking, understanding the constraints they faced and how did they manage them. That's going to provide a much, I mean, to me, that's what I look for when I listen to a podcast like yours, is an understanding of that person and the moment and how they dealt with it. I mean, I guess the hope is to discover in a sympathetic way a flaw in a person's thinking together. Like, as opposed to discovering the positive thing together, you discover the thing, well, I didn't really think about that. Yeah, I mean, that's how science is, right? That's why we find it so attractive is this, I like it when a student shows me I'm thinking incorrectly. I'm really grateful to that student because now I have an opportunity to change my mind about it and start thinking even more correctly. I mean, and there are moments when, I mean, like this is probably a good time to say like what I think I got wrong during the pandemic, right? So like, for instance, you said Francis Collins had a moment when he learned that it was quite possible to get a vaccine going. Yeah. He must have learned that quite early. And I didn't learn that early. I mean, I didn't know in March of 2020, in my experience with vaccine development, it would have take, I thought it would take a decade or more to get a vaccine. That was wrong, right? I didn't, and I was so happy when I started to see the preliminary numbers in the Pfizer trial that strongly suggested it was going to work. Yeah. And I was, I mean, like very few times in my life, I'm so happy to be wrong. And it changes kind of, I think I've heard you mention that a lockdown is still a bad idea, unless the vaccine comes out in like tomorrow. There's still like suffering and economic pain, all kinds of pain can still happen in even just a scale of weeks versus months. Yeah. Well, let's talk about the vaccine. What are your thoughts on the safety and efficacy of COVID vaccines at the individual and the societal level? So for the vaccine safety data, it's actually challenging to convey to the public how this is normally done. Like normally you would do this in the context of the trial. You'd have a long trial with large numbers, relatively large numbers of people. You'd follow them over a long time and the trial will give you some indication of the safety of the vaccine. And it did. I mean, but the trial, the way it was constructed, when it came out that it was protective against COVID, it was no longer ethical to have a placebo arm. And so that placebo arm was vaccinated, a large part of it. And so that meant that from the trial, you were not going to be able to get data on the long-term safety profiles of the vaccine. And also the other thing about trials, there's tens of thousands of people enrolled. That's still not enough to get when you deploy a vaccine at population scale, you're going to see things that weren't in the trial, guaranteed. Populations of people that weren't represented well in the trial are going to be given the vaccine and then that they're going to have things that happen to them that you didn't anticipate. So I wasn't surprised when people were a little bit skeptical when the trial was done about the safety profile, just the way the nature of the thing was going to make it so that it was going to be hard to get a complete picture from the trials itself. And the trial showed they were pretty safe and quite effective at preventing both you from getting COVID. I think the main end point of the trial itself was a symptomatic COVID. Right. So that was like, that was, you know, I mean, it was really, to me, like it was about as amazing achievement as anything, organizing a trial of that scale and running it so quickly. And the final results being so surprisingly high. So good, right? Yeah. But the problem then was normally it would take a long time. The FDA would tell Pfizer to go back and try it in this subgroup. They'd work more on dosing. They do all these kinds of things that kind of didn't, we really didn't have time for in the middle of the pandemic. Right. So you have a basis for approval that it's less full than normally you would have for a population scale vaccine. But the results were good. The results looked really good. And actually I should say for the most part that's been borne out when we've given the vaccine at scale in terms of protection against severe disease. Yeah. Right. So people who have got the vaccine for a very long time after they've had the full vaccination have had great protection against going, being hospitalized and dying if they get COVID. Let's separate, because this seems to be, there's critics of both categories, but different. Kids and kids, not older people, like let's say five years old and above or something like that, or 13 years old and above. So for those, it seems like the reduction of the rate of fatalities and serious illness seems to be something like 10X. I mean, for older people, it is a godsend, this vaccine. It transforms the problem of focus protection from something that's quite challenging, possible I believe, but quite challenging to something that's much, much more manageable. Because the vaccine in and of itself, when deployed in older populations, is a form of focus protection. Yes. Well, by the way, we'll talk about the focus protection in one segment because it's such a brilliant idea for this pandemic of future pandemics. I thought the sociological, psychological discussion about the letter from Francis Collins is because it was so recent, it has been so troubling to me. So I'm glad we talked about that first. But so there seems to be, the vaccines work to reduce deaths. Yes. And that has especially the most transformative effects for the older folks. So let me give you, I've told you one thing that I got wrong in the pandemic. Let me tell you the second thing I got wrong for sure in the pandemic. In January of this year, 2021, I thought that the vaccines would stop infection. Yes. Right. It would make it so that you were much less likely to be infected at all. Because the antibodies that were produced by the vaccines looked like they were neutralizing antibodies that would essentially block you from being infected at all. That turned out to be wrong. Right. So I think it became clear as data came out from Israel, which vaccinated very early, that they were seeing surges of infection, even in a very highly vaccinated population. That the vaccine does not stop infection. So you're a used car salesman and you're selling the vaccine and the features you thought a vaccine would have. I mean, I have a similar kind of sense when the vaccine came out. Vaccine would reduce, if you somehow were able to get it, it would reduce rate of death and all those kinds of things, but it would also reduce the chance of you getting it. And if you do get it, the chance that you transmitting it to somebody else. And it turns out that those latter two things are not as definitive or in fact, I mean, I don't know to what degree they're not. I think it's a little complicated because I think the first two or three months after you're fully vaccinated, after the second dose, you have 60, 70% efficacy peak against infection. Yeah. So that was just pretty good. I mean, I know that by six, seven, eight months that drops to 20%. Some places, some studies, like there's a study out of Sweden suggested might even drop to zero. But, and then you're also infectious for some period of time. If you do get it, even though you're vaccinated, correct. Although there seems to be lucid data that the period of time you're infectious is short, is shorter, but the, the, the, the infectivity per day is about as high. So you still, it's the point is that, that the vaccine might reduce some risk of infecting others, but it's not a categorical difference. So, it's not safe to be in the presence of just vaccinated people. You can still get infected. Right. So, I mean, there's a million things I want to ask here, but is there in some sense, because the vaccine really helps on the worst part of this pandemic, which is killing people. Yes. Doesn't that mean where does the vaccine hesitancy come from in terms of, it seems like obviously a vaccine is a powerful solution to let us open this thing up. Yeah. So I wrote a wall street journal op-ed with Sunetra Gupta in December of last year. Yes. A very night with a very naive title, which says we can end the lockdowns in a month. And the idea is very simple. Vaccinate all vulnerable people. And then open up, open up. Right. And the idea was that the lockdown harms is related. This is directly related to the great branch and declaration. Great branch declaration said the lockdown harms are devastating to the population at large. There's this considerable segment of people that are vulnerable, protect them. Well, with the vaccine, we have a perfect tool to protect the vulnerable, which is, I still believe, I mean, it's true, right. You vaccinate the vulnerable, the older population. And as you said, it's a tenfold decrease in the mortality risk from getting infected, which is, I mean, amazing. So that was a strategy we outlined. What happened is that the vaccine debate got transformed. So first there's, so you're asking about vaccine hesitancy. I think there's this first, there's like, there's, there's the inherent limitations of how to measure vaccine safety. Right. So we talked about a little bit about the trial, but also after the trial, there's a, there's a, there's a mechanism. And this is the work I've been involved with before COVID on, on, on tracking and, and identifying and checking whether the vaccines actually are safe. And the central challenge is one of causality. So you no longer have the randomized trial, but, but, but you want to know is the vaccine when it's deployed at scale, causing adverse events. Well, you can't just look at people who are vaccinated and see what adverse events happen. Cause you don't know what would have happened if the person had not been vaccinated. So you have to have some control group. Now what happened is there's several systems to do, to check this in that the CDC uses one at one very, very, very commonly known one now is called VAERS the vaccine adverse event reporting system. There, anyone who has an adverse event that either either a regular person or a doctor can just go report, look, I had the vaccine and two days later I had a headache or whatever it is. The person died a day after that, the vaccine right now you're vaccinated. The vaccine was rolled out to older people first and older people die sometimes with or without the vaccine. So sometimes you'll see someone's vaccinated and a few days later, they die. Did the vaccine cause it or something else? Cause it's really difficult to tell in order to tell you need a control group to, for that there are other systems, the FDA and CDC have like there's one called VSA. There's one called VSD vaccine safety data link. There's another system called BEST. I forget the, what the acronym is to essentially to track cohorts of people vaccinated versus unvaccinated with as careful and matching as you can do. It's not randomized, but it's, and then see if you have safety signals that pop up in the vaccinated relative to the control group on vaccinated. And so that's for instance, how the myocarditis risk was picked up in young, especially young men. It's also how the higher risk of blood clots in middle-aged and older women in with the J&J vaccine was picked up there. What you have is our, our situations where the baseline risk of these outcomes are so low that if you see them in the, in the vaccinated arm at all, then it's not hard to understand that the vaccine did this, right? Young men should not be having myocarditis. Middle-aged women should not be having huge blood clots in the brain. Right? So when you see that, you can say it's linked. Now the rates are low. So young men, maybe one in 5,000, one in 10,000 of the vaccine, of vaccine-related myocarditis, pericarditis, young women, middle-aged women. I don't know. I don't, I'm not sure what the right number might be, but like I'd say it's like in the, you know, one in hundreds of thousands, something like that. So these are rare outcomes, but they're, they're, they are vaccine-linked outcomes. How do you deal with that as a messaging thing? I think you just tell people, you tell people here are the risks. You transparently tell them, and just, you're not, you're not there. So they're not getting into something that they don't know. Yeah. And don't treat people like they're children and need to be told lies because they won't understand the full complexity of the truth. People I think are pretty good at, or actually, you know, people with time are good at understanding data, but better than anything, they're, they're better at, they're extremely good at detecting arrogance and bullshit. And you give them either one of those. I mean, I'll give you one that's where I think it's greatly undermined vaccine has, greatly undermined the demand for the vaccine is this weird denial that if you are recovered from COVID, you have extremely good immunity, both against infection and access to the research. And that denial leads to people distrusting the message given by like the CDC director, for instance, in favor of the vaccine, right? Why would you deny a thing? There's such an obvious fact. It's like, you can look at the data and it's just, I mean, you just, just pops out at you that people that are COVID recovered are not getting affected again at very high rates, much lower rates. After these kinds of conversations, I'm sure after this very conversation, I often get a number of messages from Joe, Joe Rogan and from Sam Harris, who to me are people I admire. I think are really intelligent, thoughtful human beings. They also have a platform. And I, I believe in at least in my mind about this COVID set of topics, they represent a group of people. Each group has smart, thoughtful, well-intentioned human beings. And I don't know who is right, but I do know that they're kind of tribal a little bit, those groups. And so the question I want to ask is like, what do you think about these two groups and this kind of tension over the vaccine that sometimes it just keeps finding different topics on which to focus on, like whether kids should get vaccinated or not, whether there should be vaccine mandates or not, which seem to be often very kind of specific policy kinds of questions. That's the bigger picture. I think it's a symptom of the distrust that people have in public health. I think this kind of schism over the vaccine does not happen in places where the public health authorities have been much more trustworthy. Right? So you don't see this vaccine hasn't seen Sweden, for instance. What's happened in the United States is the vaccine has become first because of politics, but then also because of the scientific arrogance, this sort of touchstone issue and people line up on both sides of it. And the different language you're hearing is structured around that. So before the election, for instance, I did a, I was, I did a testimony in the house on, on measurement of vaccine safety. And I was, I was invited by the Republicans. There were, I think four other experts invited by the Democrats or three other experts invited by Democrats, each of whom had a lot of experience in measuring vaccine safety. I was really surprised to hear them. Each doubt whether the FDA would do a reasonable job in assessing vaccine safety, including by people with who have long records of working with the FDA. I mean, these are professionals, great scientists whose main goal in life is to make sure that safe vaccine, that unsafe vaccines don't get released into the world. And if they are getting, they get pulled and they're casting doubt on the vaccine, the ability to track vaccine safety before the election. And then after the election, the rhetoric switched on a dime, right? All of a sudden it's Republicans that are cast as if they're vaccine hesitant, that kind of political shift, the public notices if, if all it takes is an election to change how people talk about the safety of the vaccine. Well, we're not talking science anymore. Many people think, right. I think that creates created its hesitancy. The other thing I think the, the, the hesitancy, some politicians viewed it as a political, as sort of like a political opportunity to sort of demonize people who are hesitant. And that itself fueled hesitancy, right? Like the, if you're, if you're telling me I'm a Rube that just doesn't want the vaccine, cause I want everyone to die. Well, I'm going to, I'm going to react really negatively. And if you're talking down to me about my legitimate, you know, sort of concerns about whether this vaccine safety, I mean, I've heard from women who are thinking about getting pregnant. Should I take the vaccine? I don't know. I mean, there are all kinds of questions, legitimate questions that I think should have good data to answer that we don't necessarily have good data to answer. So what do you do in the face of that? Well, one reaction is to pretend like we, we know for a fact that it's safe when we don't have the data to know, know for a fact in that particular group with that particular set of clinical circumstances, you know, and that I think breeds hesitancy. People can detect that bullshit. Whereas if you just tell people, you know, I don't know. Yeah. Leave with humility. Yeah. You've got it. You'll go, you will end up with a better result. Let me ask you about, I've recently had a conversation with the Pfizer CEO. This is part therapy session, part advice. Cause I, again, I really want us to get through this together. And it feels like the division is a thing that prevents us from getting through this together. And once again, just like with Francis Collins, a lot of people wrote to me, words of support. And a lot of people wrote to me words of criticism. I'm trying to understand the nature of the criticism. So some of the criticism had to do with against the vaccine and those kinds of things that I have a better understanding of, but some kind of deep distrust of Pfizer. So actually looking at a big pharma broadly, I'm trying to understand, am I so naive that I just don't see it? Because yes, there's corrupt people and they they're greedy, they're flawed in all walks of life. But companies do quite an incredible job of taking a good idea at the scale and making some money with that idea. But they are the ones that achieve scale on a good idea. I don't know. It's not obvious to me. I don't see where the manipulation is. So the fear that people have, and I talked to Joe about this quite a bit. I think this is a legitimate fear and a fear you should often have that money has influenced, disproportional influence, especially in politics. So the fear is that the policy of the vaccine was connected to the fact that lots of money could be made by manufacturing the vaccine. And I understand that. And it's actually quite a heck of a difficult task to alleviate that concern. Like you really have to be a great man or woman or a leader to convince people that you're not full of shit, that you're not just playing a game on them. I don't know. It's a difficult task, but at the same time, I really don't like the natural distrust every billionaire, distrust everybody who's trying to make money, because it feels like under a capitalistic system, at least the way to do a lot of good, like to do good at scale in the world is by being at least in part motivated by profit. I mean, I share your ambivalence, right? So on the one hand, you have a fantastic achievement, the discovery of the vaccine and then the manufacturing at scale so that billions of people can take the vaccine in a relatively short time. That is a remarkable achievement that could not have happened without companies like Pfizer. On the other hand, there is this sort of corrupting influence of that money. Just to give you one example, there's an enormous controversy over whether relatively inexpensive repurposed drugs can be used to treat the disease. None of, no company like Pfizer has any interest whatsoever in evaluating it. Even Merck, I think it was Merck that had the patent on ivermectin now expired, has no interest at all in checking to see if it works. Not only do they not have interest, they have a way of talking about people who might have a little bit of interest. That's again full of arrogance. And that is what troubles me. Is there not a, it's back to the play of science. They're not a bit of curiosity. One, okay, one, the natural curiosity of a human being that should always be there and an open-mindedness. And second, in the case of ivermectin and other things like that, you have to acknowledge that there's a very large number of people who care about this topic and this is a way to inspire them to also play in the space of science, to inspire them with science. You can't just dismiss everybody that, you can't just dismiss people, period. Yeah. Well, I mean, I think here, take ivermectin, right? There's actually a study funded by the NIH, by Tony Fauci's NIAID and the NIH called ACTIV-6 that's a randomized trial of ivermectin. It's due to be completed in March 2023. So normally when you have private actors like these big drug companies that have no interest in conducting some kind of scientific experiment that would have some public benefit, it's the job of the government, and in this case, the NIH to fund that kind of work. The NIH has been incredibly slow in its evaluations of these repurposed drugs. And it's been left to lots of other private activities of uneven quality. And hence, that's why you have these big fights. Because the data are not solid, you're going to have these big fights. Yeah. But also, okay, forget the process of science here, the studies, not enough effort being put into the studies, just the way it's being communicated. Yeah, it's just horse-paced. I mean, come on. The FDA put a tweet out telling people who are like, they're taking ivermectin because they've heard good things about it and they're sick and they're desperate. And to call it horse-paced was just, that was terrible. That was deeply irresponsible. My hope is grounded in the fact that young people see the bullshit of this. Young PhD students, graduate students, young students in college, they see the less than stellar way that our scientific leaders and our political leaders are behaving. And then the new generation will not repeat the mistakes of the past. That is my hope. Because that's the cool thing I see about young people is they're good at detecting bullshit and they don't want to be part of that. That's my hope in the space of science. Let me return to this idea of the Great Barrington Declaration. Return to the beginning. So what are the basics? Can you describe what the Great Barrington Declaration is? What are some of the ideas in it? You mentioned focus protection. What are your concerns about lockdowns? Just paint the picture of this early proposal. Sure. So the Great Barrington Declaration, first, why is it called Great Barrington Declaration? It's such a great name. I mean, it's such an epic name. But the reason why it's called that is way less than epic. It was because the conference, which is organized by Martin Kulldorff, who was a professor at Harvard University, by a statistician, he actually designed the safety system, the statistical system that the FDA uses for tracking vaccine safety. He and I had met previously just the summer before, that summer. And he invited me to come to this small conference where he was inviting me and Sunetra Gupta, who is a professor of theoretical epidemiology at Harvard, at Oxford University. And I mean, I jumped at the chance because I knew that Martin and Sunetra were both smarter than me, and it would be fun to like talk about what the right strategy would be. On the drive in, I didn't know what the name of the town was, and I asked. They said it was Great Barrington. I had it in the back of my head. Martin and I arrived a little early, and we were writing an op-ed about some of the ideas, hopefully we'll get to talk about very soon, about focus protection and the right strategy. And when Sunetra arrived, we realized we'd actually come basically to the same place about the right way to deal with the epidemic. And I thought, well, why don't we write something like the Port Huron Statement, that was what I had in the back of my head. And I'm like, well, what's the name of this town again? It was Great Barrington. Yeah, so it's not Barrington, it's Great Barrington. Which is fantastic, right? It's so over the top that it's perfect. It's literally like the Big Bang. There's something about these over-the-top fun titles that just really deliver the power. That's my main contribution, was the title, the name Great Barrington. But yeah, so it was kind of a, and the idea is actually, well, the title is great, and I think that it was written in a very stylish way. It's less than a page, you can go look online and read it. It's written not for scientists, but for the general public, so that people can understand the ideas really simply. But it is not actually a radical set of ideas. It actually represents the old pandemic plans that we've used for a century, dealing with other similar pandemics. And it's twofold. First let me talk about the science it rests on, and then I'll talk about the plan. The science, actually, some of it we've already talked about. There's this massive age gradient in the risk of COVID infection. Older people face much higher risk than younger people. The second bit of science is, that's not controversial, right? Even if you think the IFR is 0.7 or 0.2, no matter what, everyone agrees on this age gradient. The second bit of science is also not controversial. The lockdown-focused policies that we followed have absolutely devastating consequences on the health of the population. Let me just give you some examples. And this was known in October of 2020 when we wrote it, right? So the UN was sounding alarms that there would be tens of millions of people who would starve as a consequence of the economic dislocation caused by the lockdowns. And that's come to pass. Hundreds of thousands of children in places like South Asia dead from starvation as a consequence of lockdowns. The priorities like the treatment of patients with tuberculosis in poor countries stopped because of lockdowns. Childhood vaccination of measles, mumps, rubella, DPT, diphtheria, so on, pertussis, tetanus, all those standard vaccination campaigns stopped. Tens of millions of children skipping these doses for diseases that are actually deadly for them. Is there, just on a small tangent, is it well understood to you, what are the mechanisms that stop all those things because of lockdowns? Is it some aspect of supply chains? Is it just literally because hospital doors are closed? Is it because there's a disincentive to go outside by people even when they deeply need help? It's all of the above. But a lot of those efforts, like especially those vaccination efforts, are funded and run by Western efforts. Like Gavi is a, I think it's a Gates-funded thing actually that provides vaccines for millions of kids worldwide. And those efforts were scaled back. Malaria prevention efforts. So in the developing world, it was a devastating effect, these lockdowns. There was also direct effects. Like in India, the lockdowns, when they first instituted, there was an order that 10 million migrant workers who live in big cities and they live hand to mouth, they buy coconuts, they sell the coconuts. With the money, they buy food for themselves and coconuts for the next day to sell, walk back to their villages or go back to their villages overnight. So 10 million people walking back to their villages or taking a train back. 1,000 died en route. Overcrowded trains dying essentially on the side of the road. I mean, it was absolutely inhumane policy. And the lockdowns there, it's actually, it's kind of like what's happened in the West as well, but it was so severe. There was a seroprevalence study done in Mumbai by a friend of mine at the University of Chicago. What he found was that in the slums of Mumbai, there were 70% seroprevalence in July or August of 2020, whereas in the rest of Mumbai, it was 20%. Yeah. Right, so it was incredibly unequal. The lockdowns protected the relatively well off and spread the disease among the poor. So that's in the developing world. In the developed world, the health effects of lockdowns were also quite bad, right? So we've talked already about isolation and depression. There was a study done in July of 2020 that found that one in four young adults seriously considered suicide. Now, suicide rates haven't spiked up so much, but the depths of despair that would lead somebody to seriously consider suicide itself should be a source of great concern in public health. Yeah, this is one of the troubling things about measuring well-being is we're okay at measuring death and suicide. We're not so good at measuring suffering. It's like people talk about, maybe even Hollywood or Hollywood more under Stalin or the concentration camps with Hitler. We talk about deaths, but we don't talk about the suffering over periods of years by people living in fear, by people starving, psychological trauma that lasts a lifetime, all of those things. I mean, and just to get back to that point, we closed schools, especially in blue states, we closed schools. Now, richer parents could send their kids to private schools, many of which stayed open, even in the blue states. They could get pods, they could get tutors, but that's not true for poor and middle-class parents. And as a result, what we did is we took away life opportunities for kids. We tried to teach five-year-olds to read via Zoom in kindergarten, right? And the consequence, actually, you think, okay, we can just make it up, but it's really difficult to make that up. There's a literature in health economics that shows that even relatively small disruptions in schooling can have lifelong consequences, negative consequences for kids, right? So they end up growing up poorer, they lead shorter lives and less healthy lives as a consequence. And that's what the literature now shows is likely to happen with the interruptions of schooling that we had in the United States. Many European countries actually managed to avoid this. There were, in the early days of the epidemic, great indications that children, first, were not very severely at risk from COVID itself, nor are they super spreaders. Schools were not the source of community spread. Community spread spread the disease to schools, not the other way around. And we can talk about the scientific base of that, if you'd like, but that was pretty well known, even in October. We closed hospitals in order to keep them available to COVID patients, but as a result, women skipped breast cancer screening. As a result, they are showing up with late-stage breast cancer that should have been picked up last year. Men and women skipped colon cancer screening, again, with later-stage disease that should have been picked up last year, with earlier stage. For patients with diabetes, it's very important to have regular screening for blood sugar levels and sort of counseling for lifestyle improvement, and we skipped that. People stayed home with heart attacks and died at home with heart attacks. So you had this sort of wide range of medical and psychological harms that were being utterly ignored as a result of the lockdowns. Plus, there's the economic pain. So, like you said, whatever is a good term for the non-laptop class, people would lose their jobs. Yes, there might be, in the Western world, support for them financially, but the big loss there that is perhaps correlated with depression and suicide is loss of meaning, loss of hope for the future, loss of kind of a sense of stability. All the pride you have in being able to make money that allows you to pave your own way in the world. And yes, just having less money than you're used to, so your family, your kids are suffering, all those kinds of things. There's, again, an economics literature on this, on deaths of despair, it was called, 2009. There was the Great Recession. It led to an enormous uptick in overdose from drugs, suicidality, depression, as a result of the job losses that happened during the Great Recession. Well, that's happening again, like an enormous increase in drug overdoses. That's not an accident. That's a lockdown harm, right? Same thing with the job losses. The job losses, by the way, are like, it's so interesting because the states that stayed open have had much, much lower unemployment than the states that stayed closed. The labor force participation rates declined by 3%. It's women that separated because they stayed home with their kids. We've reversed a generation of women, improving women's participation in the labor force. Do you think it has to do with institutions that we mentioned that there was so much priority given or so much power given to maybe NIH versus other civilian leaders? Or do people just not care about the economic pain? The leaders, I mean, because to me it was obvious. I mean, probably it's just studying history. Whenever I listen to people on Twitter or on mainstream news or just anything, I realize that's the very kind of top. The people that have a voice represent a tiny selection of people. And so whenever there's hard times, I always kind of think about the quiet, the voiceless, the quiet suffering of the tens of millions, of the hundreds of millions. Do political leaders not just give a damn? I think it was actually a very odd ethical thing at the beginning of the pandemic where if you brought up economic harms at all, you were seen as callous. So I had a reporter call me up almost at the very beginning of the epidemic asking me about a very particular phenomenon. So he was anticipating a rise in child abuse because children were gonna be staying at home. Child abuse is generally picked up at school. And that actually happened. So the report of child abuse dropped, but actual child abuse increased because normally you pick up the child abuse at school and then you have the intervention. So I was talking about, well, there's gonna be some economic harms and they're gonna have health consequences, but the economic harms matter. But he counseled me and I think he had my best interest at heart. If you were to put that in the story, I would essentially be canceled. Because what the narrative that arose in March of 2020 is if you care about money at all, you're evil and crass, you must only care about lives. The problem with that narrative is that that money which we're talking about is actually lives of poor people. When you throw 100 million people around the world into poverty, you're going to see enormous harm to their health, enormous increases in their mortality. It is not immoral to think about that and worry about that in the context of this pandemic response. Our mind focused so much on COVID that it forgot that there are so many other public health priorities as well that need our attention desperately. And this is the thing I sensed about San Francisco when I visited. I was thinking of moving there for a startup. This is the thing I'm really afraid of, especially if I have any effect on the world through a startup, is losing touch in this kind of way. You mentioned the laptop class. Living in this world where you're only concerned about this particular class of people. And also, perhaps early on in the pandemic, amongst the laptop class, there was a legitimate concern for health. Like, you're not sure how deadly this virus is. You're not sure who to listen to, so there's a real concern. And then at a certain point when the data starts coming in, you start becoming more and more detached from the data. You start caring less and less, and you start just swimming in the space of narratives, like existing in the space of narratives. And you have this narrative in San Francisco in the laptop class that you just are very proud that you know the truth. You're the sole possessors of the truth. You congratulate yourself on it, and you don't care what actually gigantic, detrimental effect it has on society, because you're mostly fine. I'm so terrified of that. Well, I think the answer to that is just to remember. You remember. Yeah. Yeah. I don't think, you know, remember where you came from and remember who you're doing this for. At the back of your head should always be, what's the purpose? Like, why am I here? What's the purpose of this? And if the purpose is simply self-aggrandizement, then you should rethink, because it'll just end up being a hollow life. All of us will be forgotten in the end. Yeah. Focus protection. The idea, the policy, what is focus protection? Right. So I was saying that there's two scientific bases, right? So one is this steep age gradient, and the second is the existence of lockdown norms. Again, I think there's very little disagreement in the scientific community on both of those facts. If you put those facts together, the obvious policy is to protect the people who are at the most severe risk from the disease itself. And that's the idea of focus protection. That's the general principle of it. The actual implementation of it depends on the living circumstances of the people that are at risk, the resources that are available in the community, the technology that's available to do this. And so it's almost always going to be, in fact, it'll always be a local thing because it'll depend on all of those things which are all local in nature, right? So one very, very obvious thing, in a country like ours where so many older people live in institutionalized settings, in nursing home settings, and that's where older, really vulnerable, chronically ill patients often live, and you know this disease affects that group most commonly, it is absolutely vital to protect that group. We should have known that in February 2020 just from the Chinese data. And we should have thought about that group as the key constraint in our policymaking. Instead we thought about in February, March 2020, as hospital beds as the key constraint. Hospital beds and ventilator shortages, and so we ran around trying to address that constraint, like a linear programming problem, you figure out which constraint's binding and you address that one thing and then you go on to the next one, right? If that one constraint, we said, okay, the constraint is hospital beds. That led to the decision in many of the Northeast states to send COVID-infected patients who looked like they were about to recover back to nursing homes, who then spread the disease all through there because they wanted to preserve the hospital beds. Well, for somebody who loves numerical optimization, I love the way you frame this, but those are kind of connected, right? If you actually focus on protecting the vulnerable, you will also have the effect of not hitting the ceiling of the available hospital beds. That's the irony. If we protected the vulnerable, the vulnerable are the most likely to be hospitalized, and so by protecting the vulnerable, we will also have addressed the shortage of hospital beds more effectively. So that little shift in priority would have had a big impact. Okay, but specifically, the idea is to, and we could talk about different ideas of how to actually do this, but you basically do a lockdown or something like that on a very small set of people. I mean, you may have to do that if it's community spread is very high, but generally, I think it would depend on, again, the living circumstances. So for instance, if you are in a, if you have a, here's a very simple idea that doesn't require a lockdown forced on them. I don't actually generally am not in favor of that kind of forced lockdown because you just won't get cooperation, but what you could do is provide resources to that group of people. So like imagine you live next door to somebody, an older couple, and there's high community spread. Well, they have to go grocery shopping. We did like, some communities did these like senior only grocery hour, right? But they have to still have to go out and they might get exposed when they're shopping amongst other seniors. Well, why not organized home delivery of groceries to them? We did that for the laptop class, right? Or we can even just as a volunteer effort, the older people living next door, just call them up and say, can I help you go out and go shopping for you? And so you would have potentially federal support of that kind of thing. So these kinds of efforts. Identify where the vulnerable people live. It's really challenging in multi-generational homes. In LA County, for instance, there's a lot of older people living together with younger people in relatively crowded. There, it's really quite a challenge. But there again, you can use resources. So if grandma is worried that grandson has come home, but is potentially being exposed, grandson calls grandma, says, I might've been at a party where COVID was. Grandma calls public health, public health then says, okay, you can have this hotel room for a couple of days until you check to turn negative. So in case it wasn't clear, the idea of focused protection is the people that are vulnerable, protect them. And everybody else goes on with their lives, open up the economy, just do as it was before. And there was still fear abroad. So there still would be some restrictions people would pose on themselves. They probably would go to parties less. The grandsons probably wouldn't go so many parties. There would be less participation in big gatherings. And you may even say like big gatherings in order to restrict community spread again. I'm not against any of that, but you shouldn't be closing businesses. You shouldn't be closing churches and synagogues. You shouldn't be forcing people to not go to school. You should not be shuttering businesses. You should just allow society to go on. Some disease will spread, but as we've seen, the lockdown didn't stop the disease from spreading anyways. Right. So what do you make of the criticism that this idea, like all good ideas, cannot actually be implemented in a heterogeneous society where there's a lot of people intermixing. And once you open it up, people like the younger people will just forget that this is even existing and they'll stop caring about the older people and mess up the whole thing. And the government will not want to fund any kind of the great efforts you're talking about, about food delivery and then the food delivery services. Be like, why the heck am I helping out on this anyway? Because like, it's not making me much money. And so therefore like all good ideas, it will collapse. That might be true. I mean, I think it's always a risk with policy thing, but I think like, think back to the moment. We actually felt like we were in this together to some extent. Yes. Right, I think that that empathy that we had that was used to like tell people to stay in and like happily, not go in happily, but like stay in to like wear a mask or to do all these things that we thought would help other people could have been redirected to actually helping the people who most needed to be helped. Especially, I do remember March. So this is even way before Barrington, all that kind of stuff. March, April, May, there was a feeling like if we all just work together, we'll solve this. Right. And that maybe started to, when did that start breaking down? I mean, unfortunately the election is mixed into this. Yeah. That it became politicized, but I think it lasted quite a long time. I think into the summer, I think there was some of that sense. I don't know, it obviously varied among different people, but I think that it's true it would have been challenging. It's also true that it's heterogeneous, exactly the way you said. But what that means is you need a local response. A response, so like my vision of a public health officer is someone that understands their community. Not necessarily the nation at large, but their community. And then works within their community to figure out how to deploy the resources that they have available to do the kind of protection policies we're talking about. That's what should have happened. Instead, they spent a huge amount of efforts making sure businesses stayed closed. Businesses that, I mean, there are like hardware stores that closed. What good did closing a hardware store do for the spread of COVID? If it had an effect on spread, COVID spread, I mean, it's gonna be marvelous. Checking to make sure that plexiglass was put up everywhere, which now in retrospect turns out to probably made the disease worse. You know, masking enforcement, so shaming around masks. I mean, a huge amount of effort on things that were only tangentially related to focus protection. What if we turned our energy, that enormous energy put into that, instead into focus protection of the vulnerable? That's essentially the conversation I was calling for. And it wasn't, I mean, I didn't think of it as we had every single idea. I mean, we gave some concrete proposals. But the criticism we got was that those concrete proposals weren't enough. And the answer to that I have is that's true. They weren't enough. I wasn't thinking of them as enough. I was thinking that I wanted to involve an enormous number of people in local public health to help think about how to do focus protection in their communities. The question that's interesting here is about the future too. So COVID has very specific characteristics, like you mentioned, about the curve of the death rate based on the, like it seems like with COVID, it's a little bit easier to actually identify a group of people that you need to protect. So other viruses may not be this way. So might lockdown be a good idea, like hardcore lockdown for a future virus that's 10 times deadlier, but spreads at the same rate as COVID? Or maybe another way to ask that is, imagine a virus that's 10 times deadlier. What's the right response? I mean, I think it's always gonna be focus protection. But the group that needs the focus protection may change depending on the biology of the virus, right? So the polio epidemic in the 40s and 50s in the US, the great, the people at most risk were children. We didn't know really at the beginning there was this fecal-oral spread. And so we did all kinds of crazy things, including like spraying DDT in communities, which somehow was supposed to get rid of polio. But the focus was on whenever there was an outbreak, they would close the school down. And that was the right thing to do, because that group that needed protection was children and the disease was spread, we thought, in schools. I don't think there's a single formula that works, but there's a single principle that works, right? No matter, I can't, it's hard to imagine a disease that's uniformly deadly across every group and every single person. There's always gonna be some group that's differentially harmed. There's always gonna be some group that's differentially protected. And that may change over time, right? So like in this disease, in this epidemic, as people got infected and recovered, we now had a class of people that were pretty well protected against the disease. They should be, like instead of ostracizing them because they don't want a vaccine, we should be allowing them to work. I mean, we're having staffing shortages in hospitals now because we forgot that principle. It's quite a bit of this technology problem, so being able to, how much of it is a sociological problem? How much of it is a technology problem? Like where do you put the blame sort of on why this didn't go so great and how it can go great in the beginning? I mean, think about lockdowns. Like if we didn't have Zoom, we wouldn't have lockdowns. There's a reason in 2009 we didn't lock down. I mean, we didn't have the technology to replace work with this remote technology. So we had good lockdown technology in Zoom. We didn't have good focus protection technology. Yeah, I mean, focus protection is always gonna be complicated, especially for something like this that spreads so easily. It's gonna be complicated. And I'm the last person to say it would have been perfect. There would have been people that would have gotten sick, but they got sick anyways. The hope was that if we suppress community spread low enough, we can protect the vulnerable. That was the hope by lockdown. The reality was that only a certain class of people were able to benefit from lockdown. The rest of society, we call them essential workers, had to keep working and they got sick. And the disease kept spreading. It didn't actually have a substantial effect on community spread in non-laptop class populations. And also we should probably expand the class of people we call vulnerable to those who would suffer, who have the capacity to suffer, given the policies that you're weighing. It's very disingenuous to call the vulnerable just the people, obviously we had the very specific meaning, but broadly speaking, vulnerable should include anybody who can suffer based on the policies you take in response to a virus. That principle you just said, I completely agree with, is something I think has been lost, and unfortunately lost. So the policies themselves, if they have harm, those are real and we shouldn't pretend like they're not and essentially demonize the people that suffer them. Or pretend, I mean, like a lot of times, like the depression that we've been talking about, that's thought of as not so important, but it's important. And especially the harm to the people in poor countries, it's like been out of sight, out of mind in much of the rich parts of the world. Once again, I've hoped that we, seeing this, learning the lessons of history with the communication tools we have now, we'll learn this. It's like going to another country and bombing targeted terrorist locations and there's going to be some civilians who die pretending that the child who watches their dad die is not going to grow up, first of all, traumatized, but second of all, potentially bring more hate to the world than the hate that you were allegedly fighting in the first place. That's another sort of considering only one kind of harm and not the full range of harms that are being caused by your policies. You know, to return to focus protection, we still should be following the policy now for COVID. We're not, right? So the vaccines, there's a great shortage in vaccines. You wouldn't know it in the United States and in rich parts of the world, but there's a great shortage of vaccines. We're not going to be able to vaccinate most of the, like the entire set of elderly at least or larger groups until late 2022. Huge numbers of older people around the world in poor countries that have not COVID recovered yet, so they're still quite vulnerable, have not had the vaccine. And yet we're talking about vaccinating five-year-olds who benefit, if at all, from the vaccines of just a very little bit because they face such a low risk of harm from COVID. Well, something that's a little bit near and dear to our specific, the two of our hearts, so you're at Stanford. So Stanford recently announced that they're going back to virtual, at least for some period of time in response to the, maybe you can clarify, but I think it's in response to the escalated, how would they phrase it? It's related to Omicron. And a few other universities are kind of like considering back and forth. In my perspective, as somebody who loves in-person lectures, who sees the value of that to students, to young minds, also looking at the data, seems the risk aversion in university policies around this, given how healthy the student population is, seems not well calibrated. Let's put it this way. Also- Pathological. Pathological is one way to put it. Given that, depending on the university, but I think many universities require that the student body is vaccinated at this point. So I think it's a big mistake by Stanford to do this. And I'd like to say that because I just hope MIT doesn't. But what are your thoughts about Stanford? Is there a student- I agree with you. I completely agree with you. I think we have failed in our mission to educate our students by this decision. And I think, frankly, just more broadly, I think we failed generally over the course of the last year and a half in living up to our educational mission. In-person teaching is vital. Now, I can understand if you have older faculty, the principle of focus protection says provide some alternative teaching arrangements for them. That makes sense to me. From the kids' point of view, they're more harmed by not getting the education we promised them than by COVID. So applying this principle of this focus protection, let young professors teach in-person. This is before the vaccine. After the vaccine, let everyone teach in-person. Yeah, this is the part, I don't understand the discussion we're even having because, okay, let's leave focus protection aside here because that's a brilliant policy for perhaps for the future when there's no vaccine. Now with the vaccine, I'm misunderstanding something here because we're now in a space that's psychological. It's no longer about biology because with the booster shots, which I believe MIT is now requiring before January, with the booster shots, the data shows, no matter how old you are, the risks are very low for ending up in a hospital. Relative to all the other risks you face when you're older. I don't understand, can you explain the policy around closing a university, but also just a policy about just being so scared still in the university setting? I think the great universities have done great harm by modeling this kind of behavior. Yes, to me, sorry to keep interrupting, but to me, the university should be the beacon of great behavior, not the beacon of like scared, conservative, let's not mess up, let's not make it pathological, let's not make anybody angry. It should be a place to play in the space of ideas. Yes, so I think the central problem is, actually related to the central problem of COVID policy more generally. The goal seems to be to stop the disease from spreading, rather than to reduce the harm from the disease. If the goal is to stop the disease from spreading, the sad fact is we have no technology to accomplish that. At this point? Yes. Because like it's already deeply integrated into the human civilization. Well, I mean, it's here forever, right? There's a zero survey of white-tailed deer in the US. It turns out 80% of white-tailed deer in the US have COVID antibodies. Dogs get it, cats get it. There's almost certainly human animal transmission of it. I mean, presumably, I mean, I've heard bats get it apparently. So you have a situation where you have this disease, it's here to stay. Yeah. And the vaccines don't stop the spread of it, the lockdowns don't stop the spread of it. We have no technology to stop the spread of it. And so we're burning the earth trying to stop, do something that's impossible, rather than working on what's possible. And so like, you know, like letting regular college happen, that's a great good. Universities are a wonderful invention and it's contributed so much to society. To decide to shut it down, the universities should be fighting tooth and nail to not be shut down, not the other way around. Yeah. Whatever the mechanisms that results in the universities doing that, that's probably, this is me talking, it probably has to do with certain incentives for the administration, probably has to do with lawyers and legal kinds of things to avoid legal trouble. But once again, it's when the administration has too much power and too much definition of what the policy is for the university, that's when you get to trouble. The beauty, the power of the university should be about the faculty and the students. Administration just gets in the way, get out of the way. I mean, they can help organize things. They play some important role, but they need to remember what the mission is. The mission is not safety. The mission, actually, universities should be dangerous places, you know, for ideas and whatnot. What is the role of fear in a pandemic? We've been dancing around it. Is it useful? Is it destructive? Or is there sort of a complicated story here? Because sort of taking us back into January, 2020, there was so much uncertainty. This could have been a pandemic that is a black death, the bubonic plague. It could have killed hundreds of millions of people. We don't know that. We're very new to this. It's been a while. We're rusty. So there is some value to fear so that you don't do the stupid thing. You don't just go on living. I guess where I come from, I think it's almost entirely counterproductive. I think fear should never be used as a tactic to manipulate human behavior by public health. So the fear on the individual level, that feeling of fear, you should be very hesitant about that feeling because it could be easily manipulated by the powerful. Exactly. And I think that fear is natural. And it's not something that you have to stoke to get when the facts on the ground suggest it. In fact, the tendency for humans in the face of threats from infectious disease is to exaggerate the fear in their own minds of being contaminated by the environment and by others. That's just natural to humans. And the role of public health is not necessarily to eradicate the fear. Obviously, technological advances can help eradicate the fear, but it's really to help manage that fear and help people put the incentives that come out of that to useful things as opposed to harmful things. What's happened in this pandemic is that there's been a deliberate policy to stoke the fear, to help make people think that the disease is worse than it actually is. In survey after survey, you see this. And that's been incredibly damaging. So young people have readily given away their willingness to participate in regular life because A, they fear COVID more than they ought, and B, they fear that they're going to harm the vulnerable in their lives. You put those two together and you get this powerful demand for lockdowns. You see this all over the world. Broadly speaking, you have a powerful demand for irrational policies, because I would like to mention the flip side of that. I've been saddened to see how much money there is to be made by the martyrs, the people, the conspiracy theorists, that tell you you should be afraid of the government, you should be afraid of the man. It feels like fear is the problem. I think there's some guy that once said something about we should fear fear itself. He was a president or something? I vaguely remember that. So I'm worried about both sides here. I think the general principle is that should not be a tool of public policy. The public policy should attempt, and public health policy in particular, should attempt to address that fear. It's not that you should tell people lies. Of course not. Tell people accurately what the risk is. Give people tools that have evidence that they can address their risk with. And level with people when we don't know. I think that is the right adult way to deal with this pandemic from a public health point of view. And that is not the policy we have followed. Instead, public health has intentionally stoked the fear in order to gain compliance with its edicts. And I think the consequence of that is people distrust public health. What you're talking about, the distrust of government, I think is partly a consequence of that. That movement, which is much smaller once upon a time, is much larger now. Because of, essentially, people look at what public health has done and they've lied to me a whole bunch of times in a whole bunch of things, is the general sense. And there are consequences to that. We're gonna have to work in public health for a long time to try to regain the trust of the public. Throughout all of this, you've been inspiring to me, to a lot of people. You've been fearless, bold, in these kind of challenging the policies, and not in a martyr kind of way, because you're walking the line gracefully and beautifully, I would say. And looking at that, I think you're an inspiration to a lot of young people, so I have to ask, what advice would you give them if they're thinking of going into science, if they're thinking of having an impact in the world, what advice would you give them about their career and maybe about their life? Thinking about somebody in high school, maybe being in undergraduate college. I'd say a few things. One is, this is a wonderful profession. You have an opportunity to improve the lives of so many and do it by having fun, the kind of play we're talking about. It's an absolute privilege to be able to work in this kind of area. And to young people looking, that have some gifts or desire for this area, I say, please, go for it. So this area of science broadly. Yeah, I mean, it could be, I don't have any gifts in AI, but it could be, or in health or in medicine or whatever, whatever your gifts lie, develop them, work hard and develop them, because it's worth it. It's worth it, not just because you get some status, but because the journey is fun and the result is improvements in the lives of so many. So I think that is the encouragement I give. I'd also say, if you're looking at this ugliness of this debate that's happened over the pandemic, I'd say to young people, we need you to come in and help transform it. Many of the people we've seen in this debate that have behaved poorly, I ask you, forgive them. I've done my best to try, because many of them are acting out of their own sense that they need to do good, but the mistake they've made is in this arrogance and this power, but when you come in, remember that example as a negative example. And so when you join the debate, you'll join it in a spirit of humility, in a spirit of trying to learn, while keeping that love that led you to enter the field in the first place. And yeah, choose forgiveness versus derision. The people that you know have messed up, give them a pass, because it feels like that's how improvement starts. I've been thinking this, it's like I told you I'm Christian, right? So like God has given me many opportunities to forgive people, learn to practice how to do that. Gave you a gift. It's a very humbling thing, I guess. Is there a memory from when you were young that was very formative to you? So you just gave advice to some young people. Is there something that stands out to you that a decision you made, an event that happened that made you the man you are today? I actually grew up in a relatively poor environment. Like I was born in India and I moved when I was four. My dad had eight brothers and sisters and my mom had four brothers and sisters. She grew up in the slum in Calcutta. My dad, his dad died when he was young and he supported his family, his brothers and sisters with the university scholarship money. Came to the US and my dad worked in a McDonald's, even though he was an electrical engineer, couldn't find a job in 1971. And so he worked at McDonald's. We lived in a, like this basically the housing port like development in Cambridge, this like this middle building on the 17th floor, this like housing development. I mean I think that was transformative for me. Like I didn't realize so much at the time how that experience of being essentially like poor, lower middle class, what effect it had on my outlook. You mentioned to me offline that you listened to a conversation that I had with my dad. What impact did your dad have in your life? What memories do you have about him? He was a rocket scientist actually. He helped design rocket guidance systems. He died when I was 20 and I still miss him to this day. And I think that experience of seeing him sacrifice himself for his family, a brilliant man, but in many ways frustrated with like his opportunities in the world, which partly what led him to come to the US in the first place. That's transformed, it's had a transformative effect on me. I wish I could tell him that looking back. Do you think about your own mortality? Do you think about your death? Your dad is no longer with us. You're the old wise sage that represents. I never, it's funny, I've only worried about death once in this pandemic. Although I've had two of my, I have a cousin who's 73 and my uncle who's 74 die in India during the pandemic. And I grieve them, both from COVID. Like the fear of COVID really has only hit me only really once during this. It wasn't from me. And I recognize it's irrational. So on the eve of the Santa Clara County seroprevalence study, it was a really interesting thing because so many people volunteered to help. And my daughter who's 20, she was I guess was 19 at the time, and my wife also volunteered to help with like various aspects of the study. And so the eve of the study, they were going to go out in public and I didn't know what the death rate was because we hadn't done the study. And I suspected it was lower than people were saying, but I didn't know. I knew about the age gradient because I'd seen the Chinese data and my daughter's young, but my wife is my age and I didn't know the death rate. And I couldn't sleep the night before. Like what if I'm putting my family, my daughter and my wife at risk because of some activity that I'm doing? It was kind of, I don't know. I mean, it was- So it's worried about the wellbeing of others. Yeah. When you look in the mirror. If I die, I die. I mean, like I just, it's not, again, I'm Christian, so death is not the end for me, I believe. And so I don't particularly worry about my own death, but I do, I mean, I just, I think we can't help it. We worry about the wellbeing of our loved ones. So from the perspective of God, then let me ask you, what do you think is the meaning of this whole journey we're on? What do you think is the meaning of life? Oh, it's very simple. Love one another. Treat your neighbor as yourself. It's love. Yeah. As simple as that. Well, I'd love to see a little bit more of that in this pandemic. It's an opportunity for the best of our nature to shine. I've seen some of the worst, but I think some of that is just good therapy. And I'm hoping in the end, what we have here is love. At the very least, make your dad proud with some incredible rockets that we're launching out there. I think you get along well with my dad, Lex. I definitely would. Thank you so much. This is an incredible honor to talk to you, Jay. You've been an inspiration to so many people and keep fighting the good fight. Thank you so much for spending your valuable time with me today. Thank you for having me here. I appreciate it. Thanks for listening to this conversation with Jay Bhattacharya. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Alice Walker. The most common way people give up their power is by thinking they don't have any. Thank you for listening, and hope to see you next time.

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Let me quickly say that I've been a fan of the JRE podcast since it first started 10 years ago. Joe's open-mindedness and just genuine curiosity was a breath of fresh air, especially to me as a scientist, but in general as a thinking person. He inspired me to be a better and especially kinder human being. So it was surreal for me to be on there a couple of times last year and I'll be on there again a third time on February 3rd. It feels like I'm Forrest Gump somehow finding myself shaking hands with John F. Kennedy. Anyway, I also enjoy playing guitar and I thought I'd play the intro theme plus a bit more to say thank you for the 10 years of JRE. As a wise man once said, train by day, Joe Rogan podcast by night, all day. So you

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