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Show HN: AlphaZero Science paper

by Inufu on 12/6/18, 7:01 PM with 89 comments

  • by gamegoblin on 12/6/18, 9:41 PM

    It's a shame they still played against 2016 Stockfish (Stockfish 8), when Stockfish 9 or Stockfish Dev were available (Stockfish 10 is out now, but only very recently, so I can understand why they didn't use it).

    Their results show that they are only just barely stronger than Stockfish 8, but Stockfish 9 and 10 are stronger than 8 as well.

    EDIT: Also meant to include a shout-out to http://www.lczero.org/ which is an open source implementation of AlphaZero chess. Here is their forum post for this paper: https://groups.google.com/forum/#!topic/lczero/TfmaNHI99gk

    SECOND EDIT: I was wrong! They did play against a newer SF than 8, specifically, SF at this commit: https://github.com/official-stockfish/Stockfish/commit/b508f... , which was about 2 weeks before SF 9 was released, so maybe it is close in strength to SF 9.

  • by mindgam3 on 12/7/18, 12:11 AM

    To OP or anyone else at DeepMind: can you comment on why you decided not to release all of the games?

    IMHO as a competitive scholastic chess player (former national U16 champion and top 3 world U10) and software engineer, it would significantly increase credibility of results. Not to mention would be fascinating to see the “ugly” games in addition to the ones handpicked by your team.

  • by mcphage on 12/6/18, 10:24 PM

    > AlphaZero and AlphaGo Zero used a single machine with 4 first-generation TPUs and 44 CPU cores. A first generation TPU is roughly similar in inference speed to commodity hardware such as an NVIDIA Titan V GPU, although the architectures are not directly comparable.

    > The amount of training the network needs depends on the style and complexity of the game, taking approximately 9 hours for chess, 12 hours for shogi, and 13 days for Go.

    How much would that much computing power would cost on something like AWS? That's a lot of hardware, but if you're only renting it for 9 hours... the beefiest EC2+GPU instance Amazon has currently is p3.16xlarge, which has 8 Tesla V100 GPUs, and 64 (virtual) CPUs, for $25/hour on-demand. My understanding is that a V100 is slightly more powerful than a Titan V, so does that mean you could run the Chess training (at least the AlphaZero side) for $225? That seems impossible?

    EDIT: pacala below pointed out that the hardware listed was just for running AlphaZero against Stockfish, not for training it. Digging through the preprint itself, they say that for training they used:

    > During training only, 5,000 first-generation tensor processing units (TPUs) (19) were used to generate self-play games, and 16 second-generation TPUs were used to train the neural networks.

    So that would be... a lot more.

  • by madisfun on 12/7/18, 8:57 AM

    It would be nice if A0 participated in at least one public computer chess championship, Chess.com's CCC or TCEC. That's a level playing field and all games published.

    AlphaZero was a great concept and execution, but if we have to judge its relative strength, it should compete fairly. 4 TPUs (~ 4 Titan V) + 44 cores for AlphaZero vs only 44 cores for Stockfish pre-9 may or may not have put Stockfish at a disadvantage.

    BTW, current, presumably balanced, TCEC 14 configurations are:

    Non-GPU Server: CPUs: 2 x Intel Xeon E5 2699 v4 @ 2.8 GHz, Cores: 44 physical, RAM: 64 GB DDR4 ECC

    GPU Server: GPUs: 1 x 2080 ti + 1 x 2080, CPU: Quad Core i5 2600k, RAM: 16GB DDR3-2133

    TCEC GPU server looks more modest than what A0 authors used to "beat" SF.

  • by RivieraKid on 12/6/18, 7:50 PM

    Finally! I've been waiting for this for a year. I love that it learned from scratch without human bias and how it plays in a much more captivating style than alpha-beta engines.

    Will you be answering questions?

  • by antirez on 12/7/18, 9:58 AM

    How it is possible that a so high profile article says a so doubtful statement?

    "Traditional chess engines – including the world computer chess champion Stockfish and IBM’s ground-breaking Deep Blue – rely on thousands of rules and heuristics handcrafted by strong human players that try to account for every eventuality in a game."

  • by stabbles on 12/6/18, 8:17 PM

    So they finally released more games?! Really looking forward to Kingscrusher or Chessnetwork covering more of these 210 games on YouTube: https://deepmind.com/research/alphago/alphazero-resources/

  • by schaefer on 12/6/18, 11:03 PM

    Inufu,

    As a Go player, is there any way I could download and review the game records described in this paper?

  • by Rampoina on 12/7/18, 1:51 PM

    What is Deepmind's interest in not releasing the source code and weights for the neural networks?

    I'm excited about their work but it seems that it would be much better for everyone if they just released their work openly.

  • by kevinwang on 12/7/18, 6:42 PM

    Dunno if I just missed it in the paper, but is there an explanation for why alphazero is better at go than alphago zero?

  • by detaro on 12/6/18, 7:04 PM

    I don't see anything I can try out? https://news.ycombinator.com/showhn.html

  • by YetAnotherNick on 12/6/18, 10:05 PM

    Why Show HN? It generally implies a single person or just a few people behind it.

  • by thom on 12/6/18, 9:43 PM

    Another set of games against an outdated Stockfish which appears to make moves that a recent Stockfish at any reasonably depth disagrees with. I've no doubt at all that AlphaZero has a much stronger evaluation algorithm than Stockfish, but I do wish they'd be a bit more transparent about its actual strength (although presumably they're selling access to it right now if you connect all the dots).

  • by nuguy on 12/7/18, 4:51 AM

    It is my moral obligation to express to you the fact that AI, even this kind of AI, is a death sentence for humanity. The progress of automation will eventually meet and surpass the human mind. But even before it does, perhaps long before it does, it will cause massive economic disruption and unemployment. The more complete automation becomes, the less power humans will have, the less influence humans will have over the powerful entities that hold the keys to critical resources such as jobs. The economics of automation leave little doubt that the outcome will be bad for humans. I’m sorry I can’t explain it more effectively here. But I think it’s clear to anyone who thinks it through carefully.

    Please stop applying your intillenge to AI.

    Edit: substantive counter-arguments would be highly appreciated