This Canadian Genius Created Modern AI

This Canadian Genius Created Modern AI


(playful music) This is Geoff Hinton. Because of a back condition,
he hasn’t been able to sit down for more than 12 years. I hate standing, I would
much rather sit down, but if I sit down I have
a disc that comes out. So.
Okay. Well, at least now standing
desks are fashionable and– Yeah, but I was ahead. (laughs) I was standing when they
weren’t fashionable. Since he can’t sit in a car or on a bus, Hinton walks everywhere. (playful music) The walk says a lot about
Hinton and his resolve. For nearly 40 years,
Hinton has been trying to get computers to learn like people do. A quest almost everyone thought was crazy, or at least hopeless. Right up until the moment
it revolutionized the field. Google thinks this is the
future of the company. Amazon thinks this is the
future of the company. Apple thinks it’s future of the company. My own department thinks this
stuff’s probably nonsense and we shouldn’t be doing any more of it. (laughs) So, I talked everybody into
it except my own department. (playful music) You obviously grew up in the UK, and you had this very prestigious family full of famous
mathematicians and economists and, I was curious what
that was like for you. Yeah, there was a lot of pressure. I think by the time I was about seven, I realized I was gonna have to get a Ph.D. (laughing) Did you rebel against that? Or you went along with it? I dropped out every so often. I became a carpenter for a while. Geoff Hinton pretty
early on became obsessed with this idea of figuring
out how the mind works. He started off getting into physiology, the anatomy of how the brain works, then he got into psychology,
and then finally, he settled on more of a
computer science approach to modeling the brain, and got
into artificial intelligence. My feeling is, if you want to understand a really complicated device like a brain, you should build one. I mean, you can look at cars, and you could think you
could understand cars. When you try to build a
car, you suddenly discover then there’s this stuff that
has to go under the hood, otherwise it doesn’t work. Yeah. (laughs) As Geoff was starting to
think about these ideas, he got inspired by some AI
researchers across the pond. Specifically, this guy: Frank Rosenblatt. Rosenblatt, in the the late 1950s, developed what he called a perceptron, and it was a neural
network, a computing system that would mimic the brain. The basic idea is a collection of small units, called neurons. These are little computing units, but they’re actually modeled on the way that the human brain
does it’s computation. They take their incoming data
like we do from our senses, and they actually learn, so the neural net can learn to make decisions over time. Rosenblatts’s hope was that you could feed a neural network a bunch of data, like pictures of men and women, and it would eventually
learn how to tell them apart. Just like humans do. There was just one problem:
it didn’t work very well. Rosenblatt, his neural
network was the single layer of neurons, and it was
limited in what it could do. Extremely limited. And a colleague of his
wrote a book in the late 60s that showed these limitations. And, it kind of put the
whole area of research into a deep freeze for a good 10 years. No one wanted to work in this area. They were sure it would never work. Well, almost no one. It was just obvious to me that everything was about ready to go. The brain’s a big neural network, and so, it has to be that
stuff like this can work, because it works in our brains. There’s just never any doubt about that. And what do you think
that it was inside of you that kept you wanting to pursue this when everyone else was giving up? Just, that you thought it was
the right direction to go? No, that everyone else was wrong. Okay. (laughs) (upbeat music) Hinton decides he’s got an idea of how these neural nets might work, and he’s going to pursue
it no matter what. For a little while, he’s bouncing around research institutions in the US. He kind of gets fed up that most of them were funded by the Defense Department, and he starts looking for
somewhere else he can go. I didn’t want to take
Defense Department money. I sort of didn’t like
the idea that this stuff was going to be used for purposes that I didn’t think were good. He suddenly hears that
Canada might be interested in funding artificial intelligence. And that was very attractive, that I could go off to
this civilized town, and just get on with it. So I came to the University of Toronto. And then in the mid-80s, we discovered how to make more complicated neural nets so they could solve those problems that the simple ones couldn’t solve. He and his collaborators developed a multi-layered neural
network, a deep neural network. And this started to work in a lot of ways. Using a neural network, a guy named Dean Pomerleau built a
self-driving car in the late 80s. And it drove on public roads. Yann LeCun, in the 90s, built a system that could recognize handwritten digits, and this ended up being used commercially. But again, they hit a ceiling. (upbeat music) It didn’t work quite well enough, because we didn’t have enough data, we didn’t have enough compute power. And people in AI and computer science, decided that neural networks were wishful thinking, basically. So, it was a big disappointment. Through the 90s, into the 2000s, Geoff was one of only a
handful of people on the planet who were still pursuing this technology. He would show up at academic conferences and be banished to the back rooms, he was treated as, really like a pariah. Was there like a time when you thought this just wasn’t going to work? And you had some self-doubt? I mean there were many
times when I thought, “I’m not going to make this work.” (laughs) But Geoff was consumed by
this and couldn’t stop. He just kept pursuing the idea that computers could learn. Until about 2006, when
the world catches up to Hinton’s ideas. (upbeat music) Computers are now a lot faster. And now, it’s behaving like I thought it would behave in the mid-80s. It’s solving everything. The arrival of super-fast chips, and the massive amounts of
data produced on the internet gave Hinton’s algorithms a magical boost. Suddenly, computers could
identify what was in an image. Then, they could recognize speech and translate from one
language to another. By 2012, words like neural
nets and machine learning were popping up on the front page of the New York Times. You have to go all these years, and then all of a sudden, in
a the span of a few months, it just takes off. Did it finally feel like aha, the world has finally come to my vision? It was sort of a relief that people finally came to their senses. (laughs) (gentle music) For Hinton, this was
clearly a redemptive moment after decades of toil. And for Canada, it meant
something even bigger. Hinton and his students
put the country on the map as an AI superpower, something no one, and no computer, could ever have predicted.

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About the Author: Oren Garnes

100 Comments

  1. lol Sorry but this is a nationalist place holder claim…. "Canada invented AI" kinda bs. Like how UK tries to claim they invented the computer because of Turing.

  2. Society should recognize these scientist better,while people praise football players,mumble rappers,entrepreuners people who shape our society were mocked as nerdy and underpaid

  3. Buffalo's at the eastern end of Lake Erie, not Lake Ontario. Pittsburgh is farther east than you show it. This may sound like nitpicking, but it destroyed your credibility for me.

    I was wrong in my earlier post myself — Buffalo is indeed on the Niagara River, but where it flows out of Lake Erie. My apologies. I still think an American publication should know where Buffalo is, though.

  4. I'd like to see more specific videos of how the code was actually written. You know if you want to influence people to code, probably want to show them how it was written. Everything you see about "machine learning" is a narrator struggling to explain the networks with the same exact graphic with the dots and lines without talking about why they chose to code it the way they did.

    Basically – what solved Geoffs computing power problem was time()

  5. Now we just need to create a time machine and send a cyborg to kill him before he made this breakthrough.

  6. So Frank Rosenblatt is creating an AI, and he called it Mark I (Perceptron) as you can see at 2:48.. that reminds me of Tony Stark

  7. We need his face in one of our bills. WAIT! I forgot that the current government only chooses people who didn't want to move from theater's sits back in the days. What a shame.

  8. Johannes Marinus Paulus van Waveren was the real father of AI the bots on quake 3 were created in 95 and they were next level for the time and a pretty advanced computer learning system. This guy wouldn't figure this out for ten years?

  9. Very cool, but I’d love to hear the guy’s views on how we’re going to cope with having advanced AI among us. He clearly must have given it a lot of thought!

  10. Do you mean he 'invented' (stole) the term AI? Because AI doesn't exist yet except in science fiction fantasy. If you think it is a real thing then show me a HAL 9000 that can answer questions put to it by a human without having another human hiding somewhere answering in place of the so-called (fake, hoax) AI. Oh, what? You can't because it doesn't exist yet? Exactly. Not a real thing so let's stop pretending that a term use by advertiser to sell washing machines is actually a real thing now. Stop lying.

  11. Bibleman thinks this is revolutionary in a bad way. Robots are sinners just like the the men who made the Toxic Tonic of Disrespect. You shall join me in the fight to slay these infidels!

  12. According to Jared who works at Porter Hospital in Littleton, CO they can hardwire into any ones brain to upload and download data 24/7. Jared works at Porter as a sleep specialist. These sleep studies are conducted on hotel rooms to make the experience comfortable and conducive to extracting data from patients who have sleep apnea and other sleeping disorders. If you want to take classes and graduate from a University with a PHD or doctorate you can. While you sleep your brain can be uploaded with all kinds of data and you can broaden your knowledge while you sleep. I have already designed alnd have several inventions and ideas that have been copyrighted. Look for news about these new technologies in the not to distant future.

  13. It's tricky to say that AI is sorted of imitation from human brain, which is a early mistake which blocked the evolution of AI. The interview also presents that it's the enhancement of compute power today changes situation of AI (and information). Another AI farther Sutton who is much more frank to admit the fact that more efficient way to utilize increased compute power is the true evolution of AI.

  14. What a badass. Life treated him horribly by crippling him, and everyone doubted his work that would go on to be crucial in some of our life aspects today. Thank you, Geoff Hinton.

  15. We just have more computation power today. And Deep Learning is nothing but brute forcing. We’re still too too far away from a concept called General AI.

  16. What is missing from this is calling out the people responsible for undermining any work on Neural Networks in the 70s.

    Marvin Minsky, currently frozen courtesey of Arcor, and hoping to one day be revived by a future society who he can continue regale with his erroneous diatribes about the future you should take a bow

  17. Just a thing that most think but are afraid to ask.
    What heapens when you combine power of computer and human emotions. Disaster in the making, AI is the ultimate weapon of self destruction.

  18. ARTIFICIAL INTELLIGENCE will eventually get rid of mankind as it evolves. That's the simple truth. The elites will be in their underground cities.

  19. He's no genius – he is the cause for millions of people becoming unemployed and the 2nd Great Depression that we are witnessing. Some genius huh, more like the greatest selfish dumbass that ever existed

  20. FED UP! with all the loud, disruptive noise pollution on this documentary!!! AI is not the danger.. It's human stupidity, and gross insensitivity that's destroying humanity!

  21. There seems to be a pattern. If you want to be remembered as a genius do something differently while everyone is trying to do it like everyone else. Of course you also shouldn't fail…

  22. even we as a engineering students have made projects based on machine learning, thats how the machine learning is trending now a days, also google made tensorflow as an open source wow…

  23. Since this man is alive we know that sending someone from the future to stop him didn’t work out. The machines have won the war.

  24. Must have been hard for this bloke to hear about kids out of college launching $B unicorns 🦄. Meanwhile he had to pitch for decades real intelligent products, not just Ponzi schemes that flooded our markets in recent times.

  25. 🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦🇨🇦

  26. Sir… Ur a genius and great respect for your dedication and self belief. Sad to hear about ur spine condition hope going further in future AI on QUANTUM COMPS would find a solution for this and you get well

  27. Oh man… It must be horrible to not be able to sit down 🙁 maybe he could use some kind of strap, which is hung at the ceiling. Atleast to get this weight off of his legs and feet.

  28. Ashlee: Hi! This is Ashlee from Bloomberg. I was wondering if we could sit and talk for a few minutes for an interview.
    Geoff: No.
    long pause
    We cannot sit.

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