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Go match in 2015
AlphaGo versus Fan Hui was a five-game Go match between European championFan Hui, a 2-dan (out of 9 dan possible) professional, and AlphaGo, a computer Go program developed by DeepMind, held at DeepMind's headquarters in London in October 2015. AlphaGo won all five games. This was the first time a computer Go program had beaten a professional human player on a full-sized board without handicap. This match was not disclosed to the public until 27 January 2016 to coincide with the publication of a paper in the journal Nature describing the algorithms AlphaGo used.
Fan described the program as "very strong and stable, it seems like a wall. ... I know AlphaGo is a computer, but if no one told me, maybe I would think the player was a little strange, but a very strong player, a real person."
Games
Summary
In this match, DeepMind used AlphaGo's distributed version with 1,202 CPUs and 176 GPUs with Elo rating 3,144. For each game there was a one-hour set time limit for each player followed by three 30-second byo-yomi overtime periods.
Game
Date
Black
White
Result
Moves
1
5 October 2015
Fan Hui
AlphaGo
White won 2.5 points
272
2
6 October 2015
AlphaGo
Fan Hui
Black won by resignation
183
3
7 October 2015
Fan Hui
AlphaGo
White won by resignation
166
4
8 October 2015
AlphaGo
Fan Hui
Black won by resignation
165
5
9 October 2015
Fan Hui
AlphaGo
White won by resignation
214
Result: AlphaGo 5 – 0 Fan Hui
During this match, AlphaGo and Fan Hui also played another five informal games with shorter time control (each player having just three 30-second byo-yomi) and AlphaGo defeated Fan by three to two.
Game 1
Fan Hui (black) v. AlphaGo (white), 5 October 2015, AlphaGo won by 2.5 points.
First 99 moves
Moves 100–199
Moves 200–272 (234 at ; 250 at )
Game 2
AlphaGo (black) v. Fan Hui (white), 6 October 2015, AlphaGo won by resignation. Although the white stones at the lower-left corner could have been captured if black 135 had been placed at "a", AlphaGo's choice might be safer to win.
First 99 moves
Moves 100–183 (182 at 169)
Game 3
Fan Hui (black) v. AlphaGo (white), 7 October 2015, AlphaGo won by resignation.
First 99 moves
Moves 100–166
Game 4
AlphaGo (black) v. Fan Hui (white), 8 October 2015, AlphaGo won by resignation.
First 99 moves (96 at 10)
Moves 100-165
Game 5
Fan Hui (black) v. AlphaGo (white), 9 October 2015, AlphaGo won by resignation. Black 75 should be placed at 83, and Fan Hui missed the opportunity.
First 99 moves (90 at 15)
Moves 100–199 (151/157/163 at 141, 154/160 at 148)
Moves 200–214
Responses
AlphaGo's victory shocked the Go community. Lee Sedol commented that AlphaGo reached the top of the amateur level in this match, but had not yet reached the professional level, and he could give AlphaGo one or two stones. Ke Jie and Mi Yuting thought that the strength of AlphaGo in this match was equal to that of a candidate for Go professional, and extremely close to the professional level, while Shi Yue thought that it already reached the professional level. "It was terrifying," said Ke Jie, "that AlphaGo could learn and evolve although its power was still limited then."
Canadian AI specialist Jonathan Schaeffer, comparing AlphaGo with a "child prodigy" that lacked experience, considered this match "not yet a Deep Blue moment", and said that the real achievement would be "when the program plays a player in the true top echelon".
Liu Xing and Zhao Shouxun (28 January 2016). 重磅！tv独家解密——解密人工智能（一） (in Chinese). WeiqiTV. See the 39th-46th minutes. Archived from the original on 24 October 2017. Retrieved 24 October 2017.
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