DeepMind/YouTube

"Godlike" Artificial Intelligence Just Officially Beat The World's #1 Go Player

Game over.

PETER DOCKRILL
24 MAY 2017
 

By the end of this week, it's a good bet that the world's best player of the ancient Chinese board game Go will no longer be a human being.

The Chinese Go champion, 19-year-old Ke Jie - ranked number one in the world - was just narrowly beaten by Google DeepMind's AlphaGo in the first of a three-match series, and if the algorithm's winning form keeps up, it'll be a watershed moment in the evolution of artificial intelligence (AI).

 

The latest win, played in the Chinese city of Wuzhen on Tuesday, cements AlphaGo's steady rise to the peak of the professional Go-playing circuit, after celebrated victories over European Go champion Fan Hui in 2015 and South Korean grandmaster Lee Sedol last year.

After those decisive tournaments, won by AlphaGo 5-0 and 4-1 respectively, it's possible Ke had even less a chance of beating the system than his human predecessors. DeepMind's developers say the tweaked and revamped AI is now more efficient than ever, using 10 times less computational power than the algorithm that trounced Sedol in 2016.

For his part, Ke was unintimidated by AlphaGo's rising dominance in his chosen game, boasting last year that he would never lose to an AI.

By the end of Tuesday's contest - which achieved the closest possible result, with AlphaGo winning by just half a point - it's fair to say Ke had adopted a new attitude.

The human champion, who appeared visibly baffled at times through the match, described the AI as peerless, even divine.

"I feel like [its] game is more and more like the 'Go god'. Really, it is brilliant," he said at a press conference afterwards, wishing to never have to go again through such a "horrible experience".

 

"In the past it had some weaknesses," he added, "but now I feel that its understanding of the Go game and its judgments are beyond our ability."

What makes AlphaGo's mastery of Go so impressive is the inconceivable amount of potentially playable positions on the board, with estimates ranging in between 10170 and 10751.

That makes it greater than the estimated number of atoms in the observable Universe (1080), and the number of playable positions in Chess (10120).

What makes these dizzying possibilities learnable at all for AlphaGo's programming is the way that it absorbs the game: trained on millions of Go moves, and then bettering its knowledge by continually playing thousands of games against human players and itself, amassing a vast amount of game experience that no single person could ever accumulate.

In fact, Ke's initial loss in this most recent tournament really shouldn't come as a surprise to most following these contests, since AlphaGo has also been covertly moonlighting as a mysterious unknown Go player online, beating Ke and a number of other professionals earlier in the year before the algorithm's identity was revealed.

In that series, AlphaGo did not lose a single contest in some 60 games, so the chances of Ke turning this current tournament around look pretty slim.

 

That said, rather than reading AlphaGo's winning streak as a story in which human players are bested by a "cold machine" (Ke's words), we should celebrate the rise of AI as something will ultimately benefit the world.

Away from the publicity magnet of AlphaGo's games victories, DeepMind says the main aim of the software is to one day address real human problems, like reducing energy use and analysing medical data.

"This isn't about man competing with machines, but rather using them as tools to explore and discover new knowledge together," DeepMind founder Demis Hassabis told media before Tuesday's match.

"Ultimately, it doesn't matter whether AlphaGo wins or loses... either way, humanity wins."

If you've got a spare 6 hours or so to indulge in AlphaGo's seemingly inevitable Go ascendancy, here's the match and debrief in full.

Stay tuned to DeepMind's YouTube channel for the remaining games in the series, due to be played on Thursday (10:30 to 17:30, UTC+8) and Saturday (10:30 to 17:30, UTC+8):

 

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