AlphaGo versus Fan Hui was a five-game Go match between European champion

Fan Hui Fan Hui (; born 27 December 1981) is a Chinese-born French Go player. Becoming a professional Go player in 1996, Fan moved to France in 2000 and became the coach of the French national Go team in 2005. He was the winner of the European Go Champio ...

, a 2-dan (out of 9 dan possible) professional, and

AlphaGo AlphaGo is a computer program that plays the board game Go. It was developed by DeepMind Technologies a subsidiary of Google (now Alphabet Inc.). Subsequent versions of AlphaGo became increasingly powerful, including a version that competed u ...

, a

computer Go Computer Go is the field of artificial intelligence (AI) dedicated to creating a computer program that plays the traditional board game Go. The field is sharply divided into two eras. Before 2015, the programs of the era were weak. The best ...

program developed by DeepMind, held at DeepMind's headquarters in

London London is the capital and List of urban areas in the United Kingdom, largest city of England and the United Kingdom, with a population of just under 9 million. It stands on the River Thames in south-east England at the head of a estuary dow ...

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 Nature, in the broadest sense, is the physical world or universe. "Nature" can refer to the phenomena of the physical world, and also to life in general. The study of nature is a large, if not the only, part of science. Although humans are ...

'' 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 Central processing unit, CPUs and 176 Graphics processing unit, 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. 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.

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.

Game 3

Fan Hui (black) v. AlphaGo (white), 7 October 2015, AlphaGo won by resignation.

Game 4

AlphaGo (black) v. Fan Hui (white), 8 October 2015, AlphaGo won by resignation.

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.

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 Handicap (go), 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 (Go player), 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 versus Garry Kasparov, Deep Blue moment", and said that the real achievement would be "when the program plays a player in the true top echelon".

References

{{Go (game) Computer Go games 2015 in go October 2015 sports events in the United Kingdom Sports competitions in London AlphaGo Human versus computer matches 2015 in London