All systems Go as Google’s program beats a champion
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GOOGLE’S computer program AlphaGo defeated its human opponent, South Korean Go champion Lee Sedol, yesterday in the first face-off of a historic five-game match.
AlphaGo’s victory in the ancient Chinese board game is a breakthrough for artificial intelligence, showing the program developed by Google DeepMind has mastered one of the most creative and complex games ever devised.
Commentators said the match was close, with both AlphaGo and Lee making mistakes.
Lee’s loss was a shock to South Koreans and Go fans. The 33-year-old had been confident of victory two weeks ago, but sounded less optimistic a day before the match.
“I was very surprised because I did not think that I would lose the game. A mistake I made at the very beginning lasted until the very last,” said Lee, who has won 18 world championships since becoming a professional Go player at the age of 12.
Lee said AlphaGo’s early strategy was “excellent” and that he was stunned by one unconventional move a human would never have played.
Despite his initial loss, he did not regret accepting the challenge. “I had a lot of fun playing Go and I’m looking forward to the future games,” he said.
The loss shook the South Korean Go community. Yoo Chang-hyuk, also a South Korean Go master, said it was a big shock.
“It did not play like a human at all,” Kim Sung-ryong, another Go expert, said of the computer’s lack of emotion despite some potentially fatal mistakes.
Hundreds of thousands of people watched the game live on TV and YouTube. The remaining four matches will end on Tuesday.
Computers conquered chess in 1997 in a match between IBM’s Deep Blue and chess champion Garry Kasparov, leaving Go as “the only game left above chess,” Demis Hassabis, Google DeepMind’s CEO, said before yesterday’s game.
Top human players rely heavily on intuition and feelings to choose among a near-infinite number of board positions in Go, making the game extremely challenging for the artificial intelligence community.
AI experts had forecast it would take another decade for computers to beat professional players. That changed when AlphaGo defeated a European Go champion last year in a closed-door match. Since then, AlphaGo’s performance has steadily improved.
The DeepMind team built “reinforcement learning” into AlphaGo, meaning the machine plays against itself and adjusts its own neural networks based on trial and error. AlphaGo can also narrow down the search space for the next best move from the near-infinite to something more manageable. It can also anticipate the long-term results of each move and predict the winner.
AlphaGo’s win over a human champion shows computers can mimic intuition and tackle more complex tasks, its creators say. They believe that ability could be used to help scientists solve tough real-world problems in health care and other areas.
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