![]() Stockfish had a hash size of 32GB and used syzygy endgame tablebases.ĪlphaZero's results vs. According to DeepMind, it took the new AlphaZero just four hours of training to surpass Stockfish by nine hours it was far ahead of the world-champion engine.įor the games themselves, Stockfish used 44 CPU (central processing unit) cores and AlphaZero used a single machine with four TPUs and 44 CPU cores. The total training time in chess was nine hours from scratch. According to DeepMind, 5,000 TPUs (Google's tensor processing unit, an application-specific integrated circuit for article intelligence) were used to generate the first set of self-play games, and then 16 TPUs were used to train the neural networks. The new version of AlphaZero trained itself to play chess starting just from the rules of the game, using machine-learning techniques to continually update its neural networks. Update: After this article was published, DeepMind released 210 sample games that you can download here. You can download the 20 sample games at the bottom of this article, analyzed by Stockfish 10, and four sample games analyzed by Lc0. has selected three of these games with deep analysis by Stockfish 10 and video analysis by GM Robert Hess. Perhaps the establishment of these pawns is a critical winning strategy, as it seems AlphaZero and Lc0 have independently learned it.ĭeepMind released 20 sample games chosen by GM Matthew Sadler from the 1,000 game match. Lc0 now competes along with the champion Stockfish and the rest of the world's top engines in the ongoing Computer Chess Championship.ĬCC fans will be pleased to see that some of the new AlphaZero games include "fawn pawns," the CCC-chat nickname for lone advanced pawns that cramp an opponent's position. Since then, an open-source project called Lc0 has attempted to replicate the success of AlphaZero, and the project has fascinated chess fans. The updated AlphaZero results come exactly one year to the day since DeepMind unveiled the first, historic AlphaZero results in a surprise match vs Stockfish that changed chess forever. ![]() This version of AlphaZero was able to beat the top computer players of all three games after just a few hours of self-training, starting from just the basic rules of the games. But the results are even more intriguing if you're following the ability of artificial intelligence to master general gameplay.Īccording to the journal article, the updated AlphaZero algorithm is identical in three challenging games: chess, shogi, and go. What can computer chess fans conclude after reading these results? AlphaZero has solidified its status as one of the elite chess players in the world. Īn illustration of how AlphaZero searches for chess moves. ![]() Stockfish only began to outscore AlphaZero when the odds reached 30-to-1.ĪlphaZero's results (wins green, losses red) vs Stockfish 8 in time odds matches. In the time odds games, AlphaZero was dominant up to 10-to-1 odds. With three hours plus the 15-second increment, no such argument can be made, as that is an enormous amount of playing time for any computer engine. This time control would seem to make obsolete one of the biggest arguments against the impact of last year's match, namely that the 2017 time control of one minute per move played to Stockfish's disadvantage. In the match, both AlphaZero and Stockfish were given three hours each game plus a 15-second increment per move. The 1,000-game match was played in early 2018. The results will be published in an upcoming article by DeepMind researchers in the journal Scienceand were provided to selected chess media by DeepMind, which is based in London and owned by Alphabet, the parent company of Google. Adding the opening book did seem to help Stockfish, which finally won a substantial number of games when AlphaZero was Black-but not enough to win the match.ĪlphaZero's results (wins green, losses red) vs the latest Stockfish and vs Stockfish with a strong opening book. The machine-learning engine also won all matches against "a variant of Stockfish that uses a strong opening book," according to DeepMind.
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