YouSaid · the spoken record

David Silver

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114
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2020-04-03
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2020-04-03
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1
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Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

  1. “To evaluate in a position how to come up with these intuitive judgments was the key reason why Go was so hard in addition to its enormous search space and the reason why methods which had succeeded so well elsewhere failed in Go. And so people really felt deep down that in order to crack Go, we would need to get something akin to human intuition. And if we got something akin to human intuition, we'd be able to solve”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  2. “It wasn't through lack of effort people had tried many, many things. And so there was a strong sense that something different would be required for Go than had been needed for all of these other domains where AI had been successful. And maybe the single clearest example is that Go unlike those other domains had this kind of intuitive property that a Go player would look at a position and say, hey, here's this mess of black and white stones. But from this mess, oh, I can predict that this part of the border has become my territory, this part of the board has become your territory, and I've got this overall sense that I'm going to win and that this is about the right move to play. And that intuitive sense of judgment of being able to evaluate what's going on in a position was pivotal to humans being able to play this game and something that people had no idea how to put into computers. So this question of how to”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  3. “Systems had been able to defeat the human world champion in each of those domains. And yet, in that same time period, there was a million dollar prize available for the game of Go, for the first system to be a human professional player. And at the end of that time period, in year 2000, when the prize expired, the strongest Go program in the world was defeated by a nine-year-old child when that nine-year-old child was giving nine free moves to the computer at the start of the game to try and even things up. beat that strongest same”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  4. “Be able to. And so even in those days, I had this idea that what if, what if it was possible to build a program that could crack this? And as I started to explore the domain, I discovered that this was really the domain where people felt deeply that if progress could be made and go, it would really mean a giant leap forward for AI. It was the challenge where all other approaches had failed. This is coming out of the era you mentioned, which was in some sense the golden era for the classical methods of AI, like heuristic search. In the 90s, they all fell one after another, not just chess with deep blue, but checkers, backgammon, Othello. There were numerous cases where systems built on top of heuristic search methods with these high performance”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  5. “So, these are amazing moments when they happen. But where did it all start? Well, for me it started when I became fascinated in the game of Go. So Go for me, I've grown up playing games. I've always had a fascination in board games. I played chess as a kid. I played Scrabble as a kid. When I was at university, I discovered the game of Go. And to me, it just blew all of those other games out of the water. It was just so deep and profound in its complexity with endless levels to it. What I discovered was that I could devote endless hours to this game. And I knew in my heart of hearts that no matter how many hours I would devote to it, I would never become a grandmaster. Or there was another path and the other path was to try and understand how you could get some other intelligence to play this game better than I was.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  6. “First of all, thank you. That's a very kind word. And funnily enough, I just came from a panel where I was actually in a conversation with Gary Kasparov and Murray Campbell, who was the author of Deep Blue. And it was their first meeting together since the match. That just appeared yesterday. So I'm literally fresh from that experience.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  7. “Were no neural networks in those days. This was pre deep learning revolution. But it was a principled self-learning system based on a lot of the principles which people still use in deep reinforcement learning. How did I feel? I think I found it immensely satisfying that a system which was able to learn from first principles for itself was able to reach the point that it was understanding this domain better than I could and able to outwit me. I don't think it was a sense of awe. It was a sense that satisfaction that something I felt should work had worked.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  8. “Things faster or because they had some pattern which was able to exploit repeatedly. I think if we're talking about real AI, the first experience for me came after that when I realized that this path I was on wasn't taking me towards dealing with that bug which I still had inside me to really understand intelligence and try and try and solve it. Everything people were doing in games was short-term fixes rather than long-term vision. And so I went back to study for my PhD, which was funnily enough trying to apply reinforcement learning to the game of Go. And I built my first Go program using reinforcement learning, a system which would by trial and error play against itself and was able to learn which patterns were actually helpful to predict whether it was going to win or lose the game and then choose the move.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  9. “So, I used to work in the games industry, so for five years I programmed games for my first job. So it was an amazing opportunity to get involved in a startup company. And so I was involved in building AI at that time. And so for sure, there was a sense of building handcrafted what people used to call AI in the games industry, which I think is not really what we might think of as AI in its fullest sense, but something which is able to take actions in a way which makes things interesting and challenging for the human player. And at that time, I was able to build these handcrafted agents, which in certain limited cases could do things which were able to do better than me, but mostly in these kind of Twitch-like scenarios where they were able to do.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  10. “Well, I mean, unless you believe in something metaphysical, then what are our brains doing? Well, at some level, their information processing systems, which Able to take whatever information is in there, transform it through some form of program, and produce some kind of output which enables that human being to do all the amazing things that they can do in this incredible world.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  11. “I think it was really when I went to study at university, so I was an undergrad at Cambridge and studying computer science. Really starts to question what really are the goals? What's the goal? Where do we want to go with computer science? And it seemed to me that the Only step of major significance to take was to try and recreate something akin to human intelligence. If we could do that, that would be a major leap forward. And that idea certainly wasn't the first to have it, but it nestled within me somewhere and became like a bug. I really wanted to crack that problem.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  12. “Programming Prolog and do things like querying your family tree. And those are some of my earliest memories of trying to figure things out on a computer.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  13. “It was always more than solving puzzles. It was something where there was this. Limitless possibilities once you have a computer in front of you, you can do anything with it. I used to play with Lego with the same feeling. You can make anything you want out of Lego, but even more so with a computer, you're not constrained by the amount of kit you've got. And so I was fascinated by it and started pulling out the user guide and the advanced user guide and then learning. So I started in basic and then later 6502. My father was also became interested in this machine and gave up his career to go back to school and study for a master's degree in artificial intelligence funnily enough at Essex University when I was seven. I was exposed to those things at an early age. He showed me how to”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source

  14. “I remember very clearly my parents brought home this BBC Modelled B microcomputer. It was just this fascinating thing to me. I was about seven years old and couldn't resist just playing around with it. So I think first program ever was writing my name out in different colors and getting it to loop. Repeat that, and there was something magical about that, which just led to more and more.”

    2020-04-03 · Lex Fridman Podcast · #86 – David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning · IDENTIFIED FROM THE TRANSCRIPT · source