The community has created Leela Chess Zero, a chess engine that started by using the same basic concepts as AlphaZero, but has since seen many additional improvements. It's probably stronger than AlphaZero ever was. Their site has a page on how to play against it, either download it or play against one of the lichess bots.
According to this website, AlphaZero was one of the strongest chess engine and defeated Stockfish (28 victories, 72 draws, and no losses). It runs on Google's supercomputer and is developed by DeepMind. There is no website which currently supports this type of chess engine. As discussed on the answer above, you'll have to get special permission from DeepMind to play against it. So, the answer is no. Read the article that I've linked on the top of this post for more information about its history, development, and impact in the chess world.
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Unfortunately, AlphaZero is not available to the public in any form. The match results versus Stockfish and AlphaZero's incredible games have led to multiple open-source neural network chess projects being created. Leela Chess Zero, Leelenstein, Alliestein, and others try to emulate AlphaZero's learning and playing style. Even Stockfish, the conventional brute-force king, has added neural networks.
From the moment it stepped onto the scene, AlphaZero has changed chess by spawning a new generation of neural network chess engines, by contributing to chess variants, and through its transcendent games.
As mentioned, AlphaZero defeated the world's strongest chess engine, Stockfish, in a one-sided 100-game match in December 2017 (scoring 28 wins, 72 draws, and zero losses). The public was given 10 example games from this match, and the chess world's reaction was borderline disbelief. GM Peter Heine Nielsen likened watching AlphaZero's games to seeing a superior species landing on earth and showing us how to play chess:
Other grandmasters shared Nielsen's sentiment, including the legendary GM Garry Kasparov, who told Chess.com, "It's a remarkable achievement.... It approaches the 'Type B,' human-like approach to machine chess dreamt of by Claude Shannon and Alan Turing instead of brute force."
In 2019 and 2020 GM Vladimir Kramnik was able to spend some time with AlphaZero and the DeepMind team to explore chess variants and co-wrote a paper with DeepMind about the exploration of new chess variants, including sideways pawns, no castling, torpedo chess (where pawns can always move forward one or more squares).
Many of these chess variants (and more) have been added to Chess.com. This article outlines the new chess variants and how to play them. If you want to check out any of these variants for yourself, simply head over to Chess.com/variants or hover your mouse over the "Play" button in the menu bar and select "Variants":
AlphaZero is a computer program developed by artificial intelligence research company DeepMind to master the games of chess, shogi and go. This algorithm uses an approach similar to AlphaGo Zero.
On December 5, 2017, the DeepMind team released a preprint paper introducing AlphaZero, which within 24 hours of training achieved a superhuman level of play in these three games by defeating world-champion programs Stockfish, Elmo, and the three-day version of AlphaGo Zero. In each case it made use of custom tensor processing units (TPUs) that the Google programs were optimized to use.[1] AlphaZero was trained solely via self-play using 5,000 first-generation TPUs to generate the games and 64 second-generation TPUs to train the neural networks, all in parallel, with no access to opening books or endgame tables. After four hours of training, DeepMind estimated AlphaZero was playing chess at a higher Elo rating than Stockfish 8; after nine hours of training, the algorithm defeated Stockfish 8 in a time-controlled 100-game tournament (28 wins, 0 losses, and 72 draws).[1][2][3] The trained algorithm played on a single machine with four TPUs.
Comparing Monte Carlo tree search searches, AlphaZero searches just 80,000 positions per second in chess and 40,000 in shogi, compared to 70 million for Stockfish and 35 million for Elmo. AlphaZero compensates for the lower number of evaluations by using its deep neural network to focus much more selectively on the most promising variation.[1]
In AlphaZero's chess match against Stockfish 8 (2016 TCEC world champion), each program was given one minute per move. AlphaZero was flying the English flag, while Stockfish the Norwegian.[7] Stockfish was allocated 64 threads and a hash size of 1 GB,[1] a setting that Stockfish's Tord Romstad later criticized as suboptimal.[8][note 1] AlphaZero was trained on chess for a total of nine hours before the match. During the match, AlphaZero ran on a single machine with four application-specific TPUs. In 100 games from the normal starting position, AlphaZero won 25 games as White, won 3 as Black, and drew the remaining 72.[9] In a series of twelve, 100-game matches (of unspecified time or resource constraints) against Stockfish starting from the 12 most popular human openings, AlphaZero won 290, drew 886 and lost 24.[1]
AlphaZero was trained on shogi for a total of two hours before the tournament. In 100 shogi games against Elmo (World Computer Shogi Championship 27 summer 2017 tournament version with YaneuraOu 4.73 search), AlphaZero won 90 times, lost 8 times and drew twice.[9] As in the chess games, each program got one minute per move, and Elmo was given 64 threads and a hash size of 1 GB.[1]
Papers headlined that the chess training took only four hours: "It was managed in little more than the time between breakfast and lunch."[2][15] Wired described AlphaZero as "the first multi-skilled AI board-game champ".[16] AI expert Joanna Bryson noted that Google's "knack for good publicity" was putting it in a strong position against challengers. "It's not only about hiring the best programmers. It's also very political, as it helps make Google as strong as possible when negotiating with governments and regulators looking at the AI sector."[9]
Human chess grandmasters generally expressed excitement about AlphaZero. Danish grandmaster Peter Heine Nielsen likened AlphaZero's play to that of a superior alien species.[9] Norwegian grandmaster Jon Ludvig Hammer characterized AlphaZero's play as "insane attacking chess" with profound positional understanding.[2] Former champion Garry Kasparov said, "It's a remarkable achievement, even if we should have expected it after AlphaGo."[11][17]
Top US correspondence chess player Wolff Morrow was also unimpressed, claiming that AlphaZero would probably not make the semifinals of a fair competition such as TCEC where all engines play on equal hardware. Morrow further stated that although he might not be able to beat AlphaZero if AlphaZero played drawish openings such as the Petroff Defence, AlphaZero would not be able to beat him in a correspondence chess game either.[18]
In the final results, Stockfish version 8 ran under the same conditions as in the TCEC superfinal: 44 CPU cores, Syzygy endgame tablebases, and a 32GB hash size. Instead of a fixed time control of one move per minute, both engines were given 3 hours plus 15 seconds per move to finish the game. In a 1000-game match, AlphaZero won with a score of 155 wins, 6 losses, and 839 draws. DeepMind also played a series of games using the TCEC opening positions; AlphaZero also won convincingly. Stockfish needed 10-to-1 time odds to match AlphaZero.[21]
AlphaZero inspired the computer chess community to develop Leela Chess Zero, using the same techniques as AlphaZero. Leela contested several championships against Stockfish, where it showed roughly similar strength to Stockfish, although Stockfish has since pulled away.[25]
In 2019 DeepMind published MuZero, a unified system that played excellent chess, shogi, and go, as well as games in the Atari Learning Environment, without being pre-programmed with their rules.[26][27]
All the more remarkable was that the Deep Mind group published peer-reviewed papers that detailed exactly how it was achieved. In a sense, this was the equivalent of IBM creating the world-beating Deep Blue, and then publishing blueprints the very same day so that anyone could build their own. As a sidenote, Feng Hsu and the Deep Blue team did eventually publish papers describing the entire thing inside and out. Nevertheless, it was believed that while a game such as Go, might fit this form of software engineering, it would never really work for a chess program. At least not at the highest level. After all, Go is less about calculating exact lines, and more about extensive pattern recognition, while chess is highly tactical and seeing just a single extra move ahead can make or break a program.
Then along came Deep Mind, who poured in their resources and built a world-beating engine that learned the game itself within 24 hours. Naturally, there were plenty of special conditions in play, such as having access to thousands of incredibly powerful processors to help develop its ability in such a short time, but they did it. Consider that if Murray Campbell and Co. had thought that just piling in special hardware would somehow solve chess for them in 24 hours, they would have done it. Deep Blue had a system performance of 12 GFLOPS, while the horsepower DeepMind used easily exceeded 40 million GLOPS.
The new Alpha Zero chess program lead to an astounding media frenzy, and just as much controversy in the chess world. Much was made about the conditions of the match against a 64-thread version of Stockfish used to test its strength, but this was to completely overlook the important aspect of it all: a new world-class engine, using a completely new method and technique, had been developed in 24 hours. What was more, anyone was invited to make their own.
But some programmers took up the challenge, and after developing a Go program, Leela Zero, the strongest one publicly available now, based on community effort and contributions, it has been transferred to chess. 2351a5e196