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
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]
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.[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]
First 99 moves
Moves 100–183 (182 at 169)
Game 3
Fan Hui (black) v. AlphaGo (white), 7 October 2015, AlphaGo won by resignation.[5]
First 99 moves
Moves 100–166
Game 4
AlphaGo (black) v. Fan Hui (white), 8 October 2015, AlphaGo won by resignation.[5]
First 99 moves (96 at 10)
Moves 100-165
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)
Moves 200–214
Responses
AlphaGo's victory shocked the Go community.
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]
^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.
; 250 at 
)
