Google Computers Defeat Human Players at 2,500-Year-Old Board Game of Go
Google Computers Defeat Human Players at 2,500-Year-Old Board Game
The seemingly uncrackable Chinese game Go has finally met its match: a machine.
By Jack Clark
January 27, 2016 — 10:00 AM PST
Computers have learned to master backgammon, chess, and Atari's Breakout, but one game has always eluded them. It's a Chinese board game called Go invented more than 2,500 years ago. The artificial-intelligence challenge has piqued the interest of researchers at Google and Facebook, and the search giant has recently made a breakthrough.
Google has developed the first AI software that learns to play Go and is able to beat some professional human players, according to an article to be published Wednesday in the science journal Nature. Google DeepMind, the London research group behind the project, is now getting the software ready for a competition in Seoul against the world's best Go player in March.
The event harks back to the highly publicized chess match in 1996 when IBM's Deep Blue computer defeated the world chess champion. However, Go is a much more complex game. It typically consists of a 19-by-19-square board, where players attempt to capture empty areas and surround an opponent's pieces. Whereas chess offers some 20 possible choices per move, Go has about 200, said Demis Hassabis, co-founder of Google DeepMind. "There's still a lot of uncertainty over this match, whether we win," he said. IBM demonstrated the phenomenal processing power available to modern computers. DeepMind should highlight how these phenomenally powerful machines are beginning to think in a more human way.
Computer scientists have been trying to crack Go for years. Facebook is working on a similar project using the same sorts of neural-network and search technology as Google.
The social networking company said on Tuesday that its software has also beaten humans. Google's version, called AlphaGo, achieved higher scores than Facebook's, according to data from the companies.
The research has implications beyond an old Chinese board game. The systems used by Facebook and Google were not preprogrammed with specific if-this-then-do-that code or explicitly told the rules. Instead, they learned to play at a very high level by themselves. These techniques can be adapted to any problem "where you have a large amount of data that you have to find insights in," Hassabis said. Facebook said its Go research will be used to improve its Facebook M virtual assistant and accessibility services, said Ari Entin, a company spokesman.
Jon Diamond, president of the British Go Association, said machines are five to 10 years ahead of where he expected them to be. "It's really quite a large, sudden leap in strength," he said. "This is a significantly better result than any other computer Go program has achieved up to now."
Google's AlphaGo learned to play at an expert level by watching people compete and then simulating millions of its own games against itself. It eventually became good enough to defeat even the best software that had been preprogrammed to play Go. In October, Google pitted AlphaGo against Fan Hui, the best player in Europe. They played five games. The computer won all of them.
Google DeepMind employs more than 200 AI researchers and engineers. Over the 18 months or so it's spent on AlphaGo, the team ballooned from two or three people to 15, Hassabis said. "Go is a pretty sizable project for us," he said. DeepMind recently hired Matthew Lai, a London researcher who developed a system capable of playing chess at the grandmaster level. His software was able to reason in a way similar to how humans do, a more efficient method than IBM's attempt to crunch every possible outcome before making a move in the 1990s.
Hassabis said Google may follow Facebook's lead in making a version of its Go software available online for people to play against. But first, the company must worry about the match in Seoul. AlphaGo is going up against Lee Sedol, the world's top player over the past decade. The winner will receive $1 million.
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