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733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | a really really great 10 person or 50 person or 100 person team that works on learning algorithms. And even if the overall brand or the overall company, you know, isn't as like, is a little bit sucky. If you manage to track down this team and if you have a job offer to join this elite team in a much bigger company, you could actually learn a lot from these people and do important work. You know, one of the things about Silicon Valley is that uh, the brand of your resume matters less and less, right? Less than never before. | 00:57:23 | 00:57:54 | 3443 | 3474 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3443s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | I mean, I guess, I think the exception of the Stanford brand, you totally want the Stanford brand in your resume but with that exception, but really you know, Silicon Valley is becoming really good. Sili- the world, right? Has become really good at evaluating people for your genuine technical skills and your genuine capability and less for your brand and so, I would recommend that instead of trying to get the best stamps of approval on your resume to go and take the positions that let you have the best learning experiences and also allows you to do | 00:57:54 | 00:58:23 | 3474 | 3503 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3474s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | the most important work and that is really shaped by the you know, 30 or 50 people you work with and not by the overall brand of the company you work with, right? So the variance across um uh-so there's a huge variance across teams within one company and that variance is actually pretty bigger or might be bigger than the variance across different companies, does that make sense? Since I would, and if a company refuses to tell you what team you would join, I would seriously consider just, you know, doing something- if you have a better option, | 00:58:23 | 00:58:54 | 3503 | 3534 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3503s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | I would, I would do something else. Um, and then finally, um, yeah and- and so really I- again I guess I don't wanna name these companies but you know think of some of the large retailers or some of the large healthcare systems or there are a lot of companies that are not well known in the AI world but that I've met their AI teams and I think they're great. And so if you're able to find those jobs and meet their people you can actually get very exciting jobs in there. All right but of course, for the giant companies with elite AI teams, | 00:58:54 | 00:59:23 | 3534 | 3563 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3534s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | you can join that elite AI team, right? That's also- that's also great. I'm a bit biased since I use to lead some of these elite AI teams. So- so I think those teams are great but the loss of some teams in a, um, ah, yeah. All right. Um, lastly, you know, just general advice, this is how I really live my life. I tend to choose the things to work on that will allow you to learn the most and you know, try to do important work, right? So, you know especially if you're relatively early in your career, whatever you learn in your career will pay off for a long time and so um, | 00:59:23 | 01:00:15 | 3563 | 3615 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3563s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | uh and so joining the teams that are working with a great set of 10 or 30 or 50 teammates will let you learn a lot, and then also, you know, hopefully, I mean, yeah and- and just don't- don't don't join a like a cigarette company and hope you know, give more people cancer or stuff like that. Just don't- don't do this. Don't- don't do stuff like that. But if you can do meaningful work that helps other people and do important work and also learn a lot on the way, hopefully you can find positions like that, right? | 01:00:15 | 01:00:47 | 3615 | 3647 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3615s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | That let you set- set yourself up for long-term success but also do work that you think matters and that, and that helps other people. All right. Um, any questions while we wrap up? Yeah. [NOISE] I have a question about important work, what are some topics that you think you would include as important [inaudible]? What's important? You know, I don't know. Um, I think one of the most meaningful things to do in life is called [inaudible]. Either advance the human condition or help other people. But the thing is, I'm nervous. | 01:00:47 | 01:01:23 | 3647 | 3683 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3647s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | I don't wanna name one or two things because the world needs a lot of people who work on a lot of different things. So, the world's not gonna function if everyone works on computational biology. I think comp-bio is great but it's actually good that, where people work on comp-bio, my Ph.D students like you know, many work on the outside to healthcare. My team at Landing AI does a lot of work on the AI applied to manufacturing, to agriculture, to some health care and some other industries. Um,uh, I actually especially the California fire is burning you know, | 01:01:23 | 01:01:53 | 3683 | 3713 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3683s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | I actually think that there's important work to be done in AI and climate change, uh, um, but I think that there's a lot of important work in a lot of industries. Right, I actually think that, you know, I should think that the next wave of AI, excuse me I should say machine learning, is we've already um, transformed a lot of the tech world, right? So, you know, yeah, I mean we've already helped a lot of the Silicon Valley tech world become good at AI and that's great, right? Helped build a couple of the teams that wound up doing this, right? | 01:01:53 | 01:02:26 | 3713 | 3746 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3713s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | Google Brain, how Google become good at deep learning, the Baidu I grew up with, hope I do become, you know, good at one of the greatest AI companies in the world, certainly in China, and I'm very happy that between me and some of my friends in the industry we've made a lot of good AI companies. I think part of the next phase for the evolution of machine learning is for it to go into not just the tech companies like the, you know, like the Google and Baidu which I helped as well as Facebook, Microsoft which I had nothing to do with as well | 01:02:26 | 01:02:55 | 3746 | 3775 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3746s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | as what else AirBnB, Pinterest, Uber, right? All these are great companies. I hope they'll all embrace AI. But I think some of the most exciting work to be done still has also looked outside the tech industry and to look at all the sometimes called traditional industries that do not have shiny tech things because I think the value creation there as surprise you could implement there may be even bigger than if you, you know, uh, uh yeah. I'll mention one interesting thing, one thing I noticed is a lot of large tech companies all work on the same problems, right? | 01:02:55 | 01:03:28 | 3775 | 3808 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3775s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | So everyone works on machine translation, everyone works on speech recognition, face detection, and click-through rate and part of me feels like this is great because it means there's a lot of progress in machine translation and that's great. We do want progress in machine translation. Though sometimes when you look at other industries. Um, so, you know, when you look at manufacturing or um, some of the medical devices that you're looking at or sometimes on on these farms hanging out with farmers on, on, on. | 01:03:28 | 01:03:55 | 3808 | 3835 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3808s | |
733m6qBH-jI | Stanford CS230: Deep Learning | Autumn 2018 | Lecture 8 - Career Advice / Reading Research Papers | If you like, in my own work with my teams where sometimes we're stumbling across brand new research problems that the big tech companies do not see and have not yet learned to frame. So, I find one of the most exciting challenges is actually to be constantly on the cutting edge. Looking at these types of problems there's a different cutting edge than the cutting edge of the big tech companies. So, I think some of you will join the big tech companies and that's great. We need more AI in the big companies, in the tech companies, | 01:03:55 | 01:04:21 | 3835 | 3861 | https://www.youtube.com/watch?v=733m6qBH-jI&t=3835s | |
5QaOt56cWhg | John Searle - What is Belief? | John I believe a lot of things everything I believe I think is true but if I stop to think about it what do I mean by a belief what is the nature of belief yeah well I think as you know the mind is a biological phenomenon so belief is part of the biology of the mind and you won't understand belief unless you see it in relation to other parts of the biology of the mind now I have to introduce an ugly word here intentionality and that sounds like it's a fancy thing it just means the capacity by which the mind represents objects and | 00:00:00 | 00:00:29 | 0 | 29 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=0s | |
5QaOt56cWhg | John Searle - What is Belief? | states of affairs so beliefs and hopes and fears and desires and love and hate and lust and discussion those are all intentional now that suggests they've got something to with intending but that's just an accident of history we got this word from the Germans and like most of our confused words in philosophy I and in German intentionality doesn't sound like a position that's the word for intention so forget about the connection with intending and just think there is this capacity that the mind has to represent and it does that in a | 00:00:29 | 00:00:57 | 29 | 57 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=29s | |
5QaOt56cWhg | John Searle - What is Belief? | variety of ways and belief is one of the most important a belief in desire are kind of matching concepts here because with belief we represent how things are or how we think they are and that has the mind to world direction of v am I supposed to fit the world but with desires we represent not how we think things are but how we want them to be and that desire has the world to mind direction of it the world is supposed to change to match the mind now how then does all of this work as a totality all of these intentional States well I can't | 00:00:57 | 00:01:32 | 57 | 92 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=57s | |
5QaOt56cWhg | John Searle - What is Belief? | ask that question briefly it's too big a question but I can tell you some features beliefs are characteristically I justified beliefs required justification in a way that desires and hunches don't and beliefs are currently justified by their position within a network of other beliefs and other intentional states and above all a network that contains perception so you see that the dog is in the living room and that is a kind of a boring belief but you come to the believing the dog is in the living room so you have beliefs | 00:01:32 | 00:02:06 | 92 | 126 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=92s | |
5QaOt56cWhg | John Searle - What is Belief? | that are both related to your perceptions and also many of your beliefs are derived related to other beliefs I believe that Barack Obama is active in the government because I also believe he's president the United States but now the remarkable thing is that with beliefs there's a peculiar rational constraint in that the belief is not only caused by perception which is often the case but the belief is itself subject to rational assessment depending on not just what you've seen but what you've read and what you know | 00:02:06 | 00:02:44 | 126 | 164 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=126s | |
5QaOt56cWhg | John Searle - What is Belief? | otherwise and what seems reasonable and what evidence you have so now I have to introduce another piece of jargon the belief only exists in a big network of other beliefs and other mental states and one part of the network such as my belief were in the United States that only makes sense in relation to the whole network I'd have to believe the United States is a country that if it's on the surface of the earth and so on so belief is not belief it looks like it's pretty simple on the surface truth I got this belief I believe I'm an American | 00:02:44 | 00:03:14 | 164 | 194 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=164s | |
5QaOt56cWhg | John Searle - What is Belief? | but in fact it's part of a vast network of intentionality and you can really only understand it by seeing how the network works and how its constrained by rationality and by perception are there different categories of beliefs such that the belief that you saw your dog in your living room or the belief that you do not believe in God yeah those are two things I'd use the word believe but one is kind of a direct perception and the other is kind of an analysis of reality yeah but but I have they're both beliefs | 00:03:14 | 00:03:49 | 194 | 229 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=194s | |
5QaOt56cWhg | John Searle - What is Belief? | yeah I think that you're right to say that we have to make a categorization of our beliefs in this or so so to speak different degrees of centrality but in fact there's some of my beliefs I think it is misleading to describe as beliefs and I think they are presuppositions that enable me to cope with a world do I believe that there is a real world out there independently of my representation see I'm gonna get on an airplane now when I call up the airline when I get on the computer to find out is the plane on time I don't then have to | 00:03:49 | 00:04:26 | 229 | 266 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=229s | |
5QaOt56cWhg | John Searle - What is Belief? | as oh and by the way does reality exist I that's not something I can find out by even looking on the net because all of these activities presuppose the existence of reality so there are some beliefs I that are so fundamental that is probably not a good idea to construe them as beliefs and I mentioned earlier that Network these are part of something in addition to the network these are what I call the background the whole system works against a background of what we take for granted we take for granted that entities are related to | 00:04:26 | 00:05:03 | 266 | 303 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=266s | |
5QaOt56cWhg | John Searle - What is Belief? | each other by cause and effect relation so we want to know what's the cause of cancer and it won't do to say well cancer is just one of those things it doesn't have any causes we won't accept that because our background presupposition is things need a causal explanation and the background presupposition that makes sense of true belief is the idea that there's a way that things are that's independent of how we represent and how they are now sometimes that's not the case sometimes our beliefs are so enjoyed they're so | 00:05:03 | 00:05:33 | 303 | 333 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=303s | |
5QaOt56cWhg | John Searle - What is Belief? | ill formed we don't really know but for beliefs that really matter to us we assume that there is a reality that corresponds to the belief but that belief in that reality is not just another belief it's a presupposition of making sense of the first belief some people say that when they believe in God that that is the most sure thing that they know yet many people know I think a lot of people for them the belief in God is the kind of background presupposition they make sense of their lives only on the presupposition that there is a | 00:05:33 | 00:06:06 | 333 | 366 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=333s | |
5QaOt56cWhg | John Searle - What is Belief? | divine force I and there was a period in my life a rather long time ago when I accepted something like that when I was a small child but it later on it came to see me there's no rational ground for that whatever it's sad that there's no rational ground for it and a lot of people think well who the hell needs a rational ground I have it on faith well okay but faith is not a reason a faith is not a ground for accepting something so I I think you're absolutely right that there are a lot of people for whom a certain metaphysical vision the | 00:06:06 | 00:06:39 | 366 | 399 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=366s | |
5QaOt56cWhg | John Searle - What is Belief? | existence of or the existence of spirituality or the existence of a certain spiritual nature of the universe that all of those are background presuppositions of their whole being and a whole mode of life but I I don't share any of that I think it's all for the I think it's almost all hot air that they don't have any ground for these and many of them would admit they don't have any ground but for me that's a reason for not accepting it whereas I can my acceptance that there is a world that exists independently of me that | 00:06:39 | 00:07:08 | 399 | 428 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=399s | |
5QaOt56cWhg | John Searle - What is Belief? | seems to me not at all like the belief in God it's not specific to this or that view it just says if when you investigate how things are there's a way that they are that enables you to investigate but to understand the nature of belief you're feeling the reality of the external world and the person who really believes in God as a fundamental basic belief in terms of just understanding belief not understanding reality it's kind of the same thing yeah no I don't think it is and I'll tell you why the belief in God presupposes the | 00:07:08 | 00:07:42 | 428 | 462 | https://www.youtube.com/watch?v=5QaOt56cWhg&t=428s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | Translator: Michele Gianella Reviewer: Saeed Hosseinzadeh When I was a boy, I wanted to maximise my impact on the world, and I was smart enough to realise that I am not very smart. And that I have to build a machine that learns to become much smarter than myself, such that it can solve all the problems that I cannot solve myself, and I can retire. And my first publication on that dates back 30 years: 1987. My diploma thesis, where I already try to solve the grand problem of AI, not only build a machine that learns a little bit here, learns a little bit there, | 00:00:00 | 00:00:53 | 0 | 53 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=0s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | but also learns to improve the learning algorithm itself. And the way it learns, the way it learns, and so on recursively, without any limits except the limits of logics and physics. And, I'm still working on the same old thing, and I'm still pretty much saying the same thing, except that now more people are listening. Because the learning algorithms that we have developed on the way to this goal, they are now on 3.000 million smartphones. And all of you have them in your pockets. What you see here are the five most valuable companies of the Western world: | 00:00:53 | 00:01:45 | 53 | 105 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=53s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | Apple, Google, Facebook, Microsoft and Amazon. And all of them are emphasising that AI, artificial intelligence, is central to what they are doing. And all of them are using heavily the deep learning methods that my team has developed since the early nineties, in Munich and in Switzerland. Especially something which is called: "the long short-term memory". Has anybody in this room ever heard of the long short-term memory, or the LSTM? Hands up, anybody ever heard of that? Okay. Has anybody never heard of the LSTM? | 00:01:45 | 00:02:33 | 105 | 153 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=105s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | Okay. I see we have a third group in this room: [those] who didn't understand the question. (Laughter) The LSTM is a little bit like your brain: it's an artificial neural network which also has neurons, and in your brain, you've got about 100 billion neurons. And each of them is connected to roughly 10,000 other neurons on average, Which means that you have got a million billion connections. And each of these connections has a "strength" which says how much does this neuron over here influence that one over there at the next time step. | 00:02:33 | 00:03:25 | 153 | 205 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=153s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | And in the beginning, all these connections are random and the system knows nothing; but then, through a smart learning algorithm, it learns from lots of examples to translate the incoming data, such as video through the cameras, or audio through the microphones, or pain signals through the pain sensors. It learns to translate that into output actions, because some of these neurons are output neurons, that control speech muscles and finger muscles. And only through experience, it can learn to solve all kinds of interesting problems, | 00:03:25 | 00:04:04 | 205 | 244 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=205s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | such as driving a car or do the speech recognition on your smartphone. Because whenever you take out your smartphone, an Android phone, for example, and you speak to it, and you say: "Ok Google, show me the shortest way to Milano." Then it understands your speech. Because there is a LSTM in there which has learned to understand speech. Every ten milliseconds, 100 times a second, new inputs are coming from the microphone, and then are translated, after thinking, into letters which are then questioned to the search engine. | 00:04:04 | 00:04:48 | 244 | 288 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=244s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | And it has learned to do that by listening to lots of speech from women, from men, all kinds of people. And that's how, since 2015, Google speech recognition is now much better than it used to be. The basic LSTM cell looks like that: I don't have the time to explain that, but at least I can list the names of the brilliant students in my lab who made that possible. And what are the big companies doing with that? Well, speech recognition is only one example; if you are on Facebook - is anybody on Facebook? Are you sometimes clicking at the translate button? | 00:04:48 | 00:05:30 | 288 | 330 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=288s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | because somebody sent you something in a foreign language and then you can translate it. Is anybody doing that? Yeah. Whenever you do that, you are waking up, again, a long short term memory, an LSTM, which has learned to translate text in one language into translated text. And Facebook is doing that four billion times a day, so every second 50,000 sentences are being translated by an LSTM working for Facebook; and another 50,000 in the second; then another 50,000. And to see how much this thing is now permitting the modern world, | 00:05:30 | 00:06:13 | 330 | 373 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=330s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | just note that almost 30 percent of the awesome computational power for inference and all these Google Data Centers, all these data centers of Google, all over the world, is used for LSTM. Almost 30 percent. If you have an Amazon Echo, you can ask a question and it answers you. And the voice that you hear it's not a recording; it's an LSTM network which has learned from training examples to sound like a female voice. If you have an iPhone, and you're using the quick type, it's trying to predict what you want to do next | 00:06:13 | 00:06:57 | 373 | 417 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=373s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | given all the previous context of what you did so far. Again, that's an LSTM which has learned to do that, so it's on a billion iPhones. You are a large audience, by my standards: but when we started this work, decades ago, in the early '90s, only few people were interested in that, because computers were so slow and you couldn't do so much with it. And I remember I gave a talk at a conference, and there was just one single person in the audience, a young lady. I said, young lady, it's very embarrassing, but apparently today I'm going to give this talk just to you. | 00:06:57 | 00:07:42 | 417 | 462 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=417s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | And she said, "OK, but please hurry: I am the next speaker!" (Laughter) Since then, we have greatly profited from the fact that every five years computers are getting ten times cheaper, which is an old trend that has held since 1941 at least. Since this man, Konrad Zuse, built the first working program controlled computer in Berlin and he could do, roughly, one operation per second. One! And then ten years later, for the same price, one could do 100 operations: 30 years later, 1 million operations for the same price; | 00:07:42 | 00:08:27 | 462 | 507 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=462s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | and today, after 75 years, we can do a million billion times as much for the same price. And the trend is not about to stop, because the physical limits are much further out there. Rather soon, and not so many years or decades, we will for the first time have little computational devices that can compute as much as a human brain; and that's a trend that doesn't break. 50 years later, there will be a little computational device, for the same price, that can compute as much as all 10 billion human brains taken together. | 00:08:27 | 00:09:08 | 507 | 548 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=507s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | and there will not only be one, of those devices, but many many many. Everything is going to change. Already in 2011, computers were fast enough such that our deep learning methods for the first time could achieve a superhuman pattern-recognition result. It was the first superhuman result in the history of computer vision. And back then, computers were 20 times more expensive than today. So today, for the same price, we can do 20 times as much. And just five years ago, when computers were 10 times more expensive than today, | 00:09:08 | 00:09:46 | 548 | 586 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=548s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | we already could win, for the first time, medical imaging competitions. What you see behind me is a slice through the female breast and the tissue that you see there has all kinds of cells; and normally you need a trained doctor, a trained histologist who is able to detect the dangerous cancer cells, or pre-cancer cells. Now, our stupid network knows nothing about cancer, knows nothing about vision. It knows nothing in the beginning: but we can train it to imitate the human teacher, the doctor. And it became as good, or better, than the best competitors. | 00:09:46 | 00:10:26 | 586 | 626 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=586s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | And very soon, all of medical diagnosis is going to be superhuman. And it's going to be mandatory, because it's going to be so much better than the doctors. After this, all kinds of medical imaging startups were founded focusing just on this, because it's so important. We can also use LSTM to train robots. One important thing I want to say is, that we not only have systems that slavishly imitate what humans show them; no, we also have AIs that set themselves their own goals. And like little babies, invent their own experiment | 00:10:26 | 00:11:12 | 626 | 672 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=626s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | to explore the world and to figure out what you can do in the world. Without a teacher. And becoming more and more general problem solvers in the process, by learning new skills on top of old skills. And this is going to scale: we call that "Artificial Curiosity". Or a recent buzzword is "power plane". Learning to become a more and more general problem solvers by learning to invent, like a scientist, one new interesting goal after another. And it's going to scale. And I think, in not so many years from now, for the first time, | 00:11:12 | 00:11:50 | 672 | 710 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=672s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | we are going to have an animal-like AI - we don't have that yet. On the level of a little crow, which already can learn to use tools, for example, or a little monkey. And once we have that, it may take just a few decades to do the final step towards human level intelligence. Because technological evolution is about a million times faster than biological evolution, and biological evolution needed 3.5 billion years to evolve a monkey from scratch. But then, it took just a few tens of millions of years afterwards | 00:11:50 | 00:12:35 | 710 | 755 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=710s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | to evolve human level intelligence. We have a company which is called Nnaisense like birth in [French], "Naissance", but spelled in a different way, which is trying to make this a reality and build the first true general-purpose AI. At the moment, almost all research in AI is very human centric, and it's all about making human lives longer and healthier and easier and making humans more addicted to their smartphones. But in the long run, AIs are going to - especially the smart ones - are going to set themselves their own goals. | 00:12:35 | 00:13:16 | 755 | 796 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=755s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | And I have no doubt, in my mind, that they are going to become much smarter than we are. And what are they going to do? Of course they are going to realize what we have realized a long time ago; namely, that most of the resources, in the solar system or in general, are not in our little biosphere. They are out there in space. And so, of course, they are going to emigrate. And of course they are going to use trillions of self-replicating robot factories to expand in form of a growing AI bubble which within a few hundred thousand years | 00:13:16 | 00:14:00 | 796 | 840 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=796s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | is going to cover the entire galaxy by senders and receivers such that AIs can travel the way they are already traveling in my lab: by radio, from sender to receiver. Wireless. So what we are witnessing now is much more than just another Industrial Revolution. This is something that transcends humankind, and even life itself. The last time something so important has happened was maybe 3.5 billion years ago, when life was invented. A new type of life is going to emerge from our little planet and it's going to colonize and transform the entire universe. | 00:14:00 | 00:14:48 | 840 | 888 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=840s | |
-Y7PLaxXUrs | True Artificial Intelligence will change everything | Juergen Schmidhuber | TEDxLakeComo | The universe is still young: it's only 13.8 billion years old, it's going to become much older than that, many times older than that. So there's plenty of time to reach all of it, or all of the visible parts, totally within the limits of light speed and physics. A new type of life is going to make the universe intelligent. Now, of course, we are not going to remain the crown of creation, of course not. But there is still beauty in seeing yourself as part of a grander process that leads the cosmos from low complexity towards higher complexity. | 00:14:48 | 00:15:33 | 888 | 933 | https://www.youtube.com/watch?v=-Y7PLaxXUrs&t=888s | |
zoa2pKYp_fk | Active Learning Overview | well active learning is the idea that students to really learn something to really understand something have to be actively involved and that just sitting passively and listening to a lecture really doesn't help students develop the higher order cognitive processes that they need to really really understand something so you can listen to something you can watch a movie you can watch TV and you can generally get the plot but if you're asked to to recall specific details or to to even explain a particular nuance associated with the TV | 00:00:00 | 00:00:41 | 0 | 41 | https://www.youtube.com/watch?v=zoa2pKYp_fk&t=0s | |
zoa2pKYp_fk | Active Learning Overview | show or movie you can't really do it and that's what happens often in the lecture is that students will sit in the lecture though write down what's being said but they're not really engaged with the material so active learning is this idea of people say minds on always hands-on sometimes those students have to to be actively with their mind thinking about the material applying what's being said and given opportunities within the lecture to apply what's being taught or what's being the topic at hand and then active learning | 00:00:41 | 00:01:16 | 41 | 76 | https://www.youtube.com/watch?v=zoa2pKYp_fk&t=41s | |
zoa2pKYp_fk | Active Learning Overview | strictly speaking means that you just you're just one a particular individual is active interactive we tend to parse that a little bit and say interactive learning would mean the student has been active in his or her own mind in thinking about the material but then is also interacting with others peers or potentially the faculty member or TA in order to to further develop understanding construct meaning for for the topic I always start maybe the second session of the class the second class meeting is a discussion of what we | 00:01:16 | 00:01:52 | 76 | 112 | https://www.youtube.com/watch?v=zoa2pKYp_fk&t=76s | |
zoa2pKYp_fk | Active Learning Overview | know about how people learn so a discussion of the literature and the research on human cognition and learning and and if you take a constructivist point of view or constructionist point of view which really says that as I said before to understand people have to make meaning of a topic they have to construct their own meaning and we show the research that really shows that this is true for a higher level of processes people have to be actively engaged and there's research to show that we also show the classroom based | 00:01:52 | 00:02:25 | 112 | 145 | https://www.youtube.com/watch?v=zoa2pKYp_fk&t=112s | |
zoa2pKYp_fk | Active Learning Overview | research so Freeman's 2014 paper that was a meta-analysis of 225 other studies that showed that in courses in college-level courses with we're active learning was used there was a 12% decrease in the failure rate and they normalized it to all of the important factors that they should be normalized to the experience of the instructor the size of the class the type of the institution the the situation the way the position that the class is situated within the larger curriculum and and across the board it was shown that there | 00:02:25 | 00:03:01 | 145 | 181 | https://www.youtube.com/watch?v=zoa2pKYp_fk&t=145s | |
zoa2pKYp_fk | Active Learning Overview | was a 12% decrease on average of the failure rate and they make a comment in the paper that if that had been a clinical trial of a drug and 12% of the people on the drug head showed marked improvement they would have had to stop the trial and and give everyone the drug so this idea that there's a 12% decrease in the failure rate in courses that use active learning to me is pretty compelling that we should all be using active learning so whenever possible because we have an MIT our students our MIT students we use data we use the | 00:03:01 | 00:03:36 | 181 | 216 | https://www.youtube.com/watch?v=zoa2pKYp_fk&t=181s | |
zoa2pKYp_fk | Active Learning Overview | research and we we try to find really good research solid research that shows the the way people learn and then how to support that with specific Act classroom practices so many of the students haven't had the experience of being in a class where active learning was used so they don't really understand it so when we start to talk about it as a way of teaching they may not really get it so throughout the course from the first the first class all the way through we I try to use several different types of active | 00:03:36 | 00:04:07 | 216 | 247 | https://www.youtube.com/watch?v=zoa2pKYp_fk&t=216s | |
zoa2pKYp_fk | Active Learning Overview | learning exercises each class so the students themselves are actively engaged with the material from the first day so I may have them break into pairs and discuss a particular topic or identify something they didn't they didn't understand from the pre class readings and then after three minutes week they can either share their comments with someone else or maybe we just report out to the larger group that that if they just report if they just write down and then report back that's a pretty good example of active learning it's a pretty | 00:04:07 | 00:04:36 | 247 | 276 | https://www.youtube.com/watch?v=zoa2pKYp_fk&t=247s |