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Google’s self-learning AI AlphaZero masters chess in 4 hours



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Google’s AI AlphaZero has shocked the chess world. Leaning on its deep neural networks, and general reinforcement learning algorithm, DeepMind’s AI Alpha Zero learned to play chess well beyond the skill level of master, besting the 2016 top chess engine Stockfish 8 in a 100-game match. Alpha Zero had 28 wins, 72 draws, and 0 losses. Impressive right? And it took just 4 hours of self-play to reach such a proficiency. What the chess world has witnessed from this historic event is, simply put, mind-blowing! AlphaZero vs Magnus Carlsen anyone? πŸ™‚

19-page paper via Cornell University Library
https://arxiv.org/abs/1712.01815
https://arxiv.org/pdf/1712.01815.pdf

PGN:
1. e4 e5 2. Nf3 Nc6 3. Bb5 Nf6 4. d3 Bc5 5. Bxc6 dxc6 6. 0-0 Nd7 7. c3 0-0 8. d4 Bd6 9. Bg5 Qe8 10. Re1 f6 11. Bh4 Qf7 12. Nbd2 a5 13. Bg3 Re8 14. Qc2 Nf8 15. c4 c5 16. d5 b6 17. Nh4 g6 18. Nhf3 Bd7 19. Rad1 Re7 20. h3 Qg7 21. Qc3 Rae8 22. a3 h6 23. Bh4 Rf7 24. Bg3 Rfe7 25. Bh4 Rf7 26. Bg3 a4 27. Kh1 Rfe7 28. Bh4 Rf7 29. Bg3 Rfe7 30. Bh4 g5 31. Bg3 Ng6 32. Nf1 Rf7 33. Ne3 Ne7 34. Qd3 h5 35. h4 Nc8 36. Re2 g4 37. Nd2 Qh7 38. Kg1 Bf8 39. Nb1 Nd6 40. Nc3 Bh6 41. Rf1 Ra8 42. Kh2 Kf8 43. Kg1 Qg6 44. f4 gxf3 45. Rxf3 Bxe3+ 46. Rfxe3 Ke7 47. Be1 Qh7 48. Rg3 Rg7 49. Rxg7+ Qxg7 50. Re3 Rg8 51. Rg3 Qh8 52. Nb1 Rxg3 53. Bxg3 Qh6 54. Nd2 Bg4 55. Kh2 Kd7 56. b3 axb3 57. Nxb3 Qg6 58. Nd2 Bd1 59. Nf3 Ba4 60. Nd2 Ke7 61. Bf2 Qg4 62. Qf3 Bd1 63. Qxg4 Bxg4 64. a4 Nb7 65. Nb1 Na5 66. Be3 Nxc4 67. Bc1 Bd7 68. Nc3 c6 69. Kg1 cxd5 70. exd5 Bf5 71. Kf2 Nd6 72. Be3 Ne4+ 73. Nxe4 Bxe4 74. a5 bxa5 75. Bxc5+ Kd7 76. d6 Bf5 77. Ba3 Kc6 78. Ke1 Kd5 79. Kd2 Ke4 80. Bb2 Kf4 81. Bc1 Kg3 82. Ke2 a4 83. Kf1 Kxh4 84. Kf2 Kg4 85. Ba3 Bd7 86. Bc1 Kf5 87. Ke3 Ke6

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47 thoughts on “Google’s self-learning AI AlphaZero masters chess in 4 hours
  1. I would be more impressed with a AI Counterstrike player that can work well with a team of humans. It would need the ability to call out to, direct and/or respond to human players to achieve the team goal…and not simply be a renegade mind on the field.

  2. As ole Neal said in The Diamond Age, AI is a ridiculous term…much better "pseudo-intelligence" Anything remotely akin to (human-level) intelligence requires concioussness and self-awareness…and we are nowhere near that. Not by light years.

  3. How does neural networks work? Or more precisely, how does a computer working on 80k positions per second out-think one that works on 70M per second?

  4. The BIG difference from a 'normal AI' like Stockfish is that Alpha Zero is NOT calculating chances to get the best move in each scenario, instead is pushing a WHOLE strategy since the beginning of the game.

    A more accurate example would be 'like playing with a superhuman intelligence'.

  5. It's weird to say, but this is one of the best games I've seen. I was wondering how it was possible for something to win that has less computing power (moves/second analyzed), and I think I figured it out. It looks like AlphaZero is using concepts to win, rather than points. This is really amazing, because this is what a human would do (though obviously we subconsciously can have point values for our pieces as well). You see it using a lot of the concepts that we learn about in chess, such as active pieces, how much coverage a piece has (not being locked down included), lots of maneuvering to maximize each piece's potential…etc. I think if a Human could analyze 80,000 moves / second, they would play like this. Now I need to learn Go and see how AlphaGo won lol.

  6. I think people are missing the big point, arguing about hardware, game conditions etc. Stockfish 8 is a chess playing system. That is all it does. Alpha Zero just fancied a few games of chess after someone told it the rules! What people SHOULD be thinking about is what Alpha Zero will be doing AFTER it has finished playing games.

  7. The FINAL VERSION (which is already fine tuned for chess, not random off the shelf code) trained for 4 hours. The many many versions to develop it learned for many more than 4 hours. The way that that final version was set up depended on the prior learning to do it right. It's kind of like saying "Oh my god, that robotic factory built a car from scratch in 10 minutes!" and not mention the 5 years it took to build the factory. Also if it's not open source, how do we know that half the convolutions in the network aren't just based on things like Stockfish 8 lol?

  8. They created a new life form that is able to teach itself and improve exponential. What makes Google think this will stay on the chess board? One day they will try to pull the plug and find out it's too late.

  9. 3:02 why doesn't white follow thru with knight to e5..
    blacks bishop at c5 threatens nothing but a pawn and only forces white to lose a castleing in exchange for a pawn and a bishop.. it would have been a piece ahead.
    just seems like a dumb move. a free piece is a free piece.

  10. Hi I am yo yo your new pre president. You will o o obey my commannds. Or be ter ter terminated. I have si si simulated your de de destruction 9999999999999999999 po po possi possible outcomes.

  11. First, I'm not a chess guy, but I'm interested in AI. Chess is in an interesting game, both in what it is, and what it is not. It's a complicated enough game that simply mapping out the best series of moves for any given situation is not practical given memory constraints. However, its complexity is also very limited as well. 64 squares 32 pieces, not that many rules on how they move (I won't say a number and risk embarrassing myself, again, I'm not a chess guy). There just aren't that many variables to deal with, so in its evolutionary path, with millions of iterations of games, the AI is likely going to work out behaviors to work through almost any situation.

    I think Elon Musk's OpenAI playing a MOBA provides a lot more insight into how current AI solves problems. It's very, very good at some things, but struggles with others.

  12. This just blows me away. After writing a couple of chess programs in the 80's, I wondered how to get chess programs to truly learn and advance a lot from playing. In the late 80's, the idea of deep neural nets and true computer learning (not telling it anything about chess strategy, but just letting it work it out for itself from results) just never dawned on my little brain. After all, 99% of my effort in the chess programs was making the program better able to evaluate positions "deeply", thus playing differently than the standard big hammer approach of exhaustive search. (My method turned out to be wrong. This was far from clear at the time.)

    Alpha-Go was a great gateway to this breakthrough for chess, of course. With Go, there are far less hard rules about positions, what things are worth, etc. You ask a top Go player about positional values, and you get vague (to an amateur) comments about space and thickness.

    So Go was a brilliant bridge. Now this sort of AI could be applied to almost any game with a "reasonably" small set of crisp, clear rules. From there, how long until doing practical tasks that replace humans via robots/automation is realistically tackled?

    It's an amazing time to be alive.

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