Go match in 2015
AlphaGo versus Fan Hui was a five-game Go match between European champion Fan 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.[1] AlphaGo won all five games.[2][3] This was the first time a computer Go program had beaten a professional human player on a full-sized board without handicap.[4] This match was not disclosed to the public until 27 January 2016 to coincide with the publication of a paper in the journal Nature[5] describing the algorithms AlphaGo used.[2]
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."[6]
Games
Summary
In this match, DeepMind used AlphaGo's distributed version with 1,202 CPUs and 176 GPUs[5] with Elo rating 3,144.[7] 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.[5]
Game 1
Fan Hui (black) v. AlphaGo (white), 5 October 2015, AlphaGo won by 2.5 points.[5]
|
Moves 200–272 (234 at ; 250 at )
|
Game 2
AlphaGo (black) v. Fan Hui (white), 6 October 2015, AlphaGo won by resignation.[5] 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.[8]
|
Moves 100–183 (182 at 169)
|
Game 3
Fan Hui (black) v. AlphaGo (white), 7 October 2015, AlphaGo won by resignation.[5]
Game 4
AlphaGo (black) v. Fan Hui (white), 8 October 2015, AlphaGo won by resignation.[5]
|
First 99 moves (96 at 10)
|
Game 5
Fan Hui (black) v. AlphaGo (white), 9 October 2015, AlphaGo won by resignation.[5] Black 75 should be placed at 83, and Fan Hui missed the opportunity.[9]
|
First 99 moves (90 at 15)
|
|
Moves 100–199 (151/157/163 at 141, 154/160 at 148)
|
Responses
AlphaGo's victory shocked the Go community.[10][11][12] Lee Sedol commented that AlphaGo reached the top of the amateur level in this match, but had not yet reached the professional level,[13][14] and he could give AlphaGo one or two stones.[15] Ke Jie and Mi Yuting thought that the strength of AlphaGo in this match was equal to that of a candidate for Go professional,[16][17] and extremely close to the professional level,[18] while Shi Yue thought that it already reached the professional level.[19][11] "It was terrifying," said Ke Jie, "that AlphaGo could learn and evolve although its power was still limited then."[20][17][21]
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".[22]