Alphabet machine beats world's top Go Player in a victory for AI

2017-05-25 11:22 - Bloomberg News
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Beijing - A machine built by Alphabet has officially defeated the world’s top-ranked player of the ancient board-game Go, a decisive demonstration of artificial intelligence’s ability to master some of the most complex human endeavours.

AlphaGo bested Ke Jie, a 19-year-old Chinese prodigy who boasted a year ago that the AI could never beat him at a game he’s played professionally since the age of 10. But on Thursday, the world No. 1 lost his second match in a three-game series in the tourist town of Wuzhen, China.

The victory, which came during a week-long conference dedicated to AI, is a show of strength for the parent of Google as it attempts to find a way to offer its services in the country.

The search giant’s most popular services from Gmail to YouTube have been blocked by Chinese authorities since 2014.

Go, invented in China more than 2 000 years ago, is a battle for territory involving the placement of white or black stones on a grid. AlphaGo’s success has stunned experts, who thought it would take as much as a decade before AI could beat top-ranked professional players of the game.

Ke employed an ambitious strategy, opening up multiple fronts across the board in a move that online commentators said was an attempt to take advantage of AlphaGo’s preference for certainty over game points. But the AI-player gradually closed up opportunities and gained a large block of territory that would’ve been hard to break up.

The Chinese player declared AlphaGo a "god"of the game after his first defeat on Tuesday. While the final scores were relatively even, experts said this was largely because AlphaGo played defensively to shore up a near-assured victory.

Executive chairperson Eric Schmidt and a cadre of mid-level Chinese government officials kicked off the summit in Wuzhen this week.

Google experts and prominent local academics exchanged notes while executives promoted Alphabet’s expertise in AI and suite of technologies, including Tensor Processing Unit chips designed to supercharge the training of computer systems.

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