Facebook 'very close' to building artificial intelligence to finally beat humans at Chinese game Go
Facebook Founder Mark Zuckerberg On Wednesday Revealed That His Company Is Creating An Artificial Intelligence To Beat Players In The Game Of Chinese Game GO.
Facebook founder Mark Zuckerberg on Wednesday revealed that his company is creating an Artificial Intelligence to beat players in the game of Chinese game GO.
This issue has evaded computer scientists for decades i.e. how to build software that can beat humans at Go, the 2,500-year-old strategy board game.
Notably, due to Go's structure — you place black or white stones at the intersection of lines on a 19-by-19 grid — the game has more possible permutations than chess, despite its simple ruleset.
However, nobody has been able to decode it as the number of possible arrangements makes it difficult to design systems that can look far enough into the future to adequately assess a good play in the way humans can.
But Facebook is ver close to develop a strategy to beat humans at the game.
On Wednesday Zuckerberg wrote on the social network:
(function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = "//connect.facebook.net/en_US/sdk.js#xfbml=1&version=v2.3"; fjs.parentNode.insertBefore(js, fjs);}(document, 'script', 'facebook-jssdk'));The ancient Chinese game of Go is one of the last games where the best human players can still beat the best artificial...
Posted by Mark Zuckerberg on Tuesday, January 26, 2016"The ancient Chinese game of Go is one of the last games where the best human players can still beat the best artificial intelligence players. Last year, the Facebook AI Research team started creating an AI that can learn to play Go.
Scientists have been trying to teach computers to win at Go for 20 years. We're getting close, and in the past six months we've built an AI that can make moves in as fast as 0.1 seconds and still be as good as previous systems that took years to build.
Our AI combines a search-based approach that models every possible move as the game progresses along with a pattern matching system built by our computer vision team.
The researcher who works on this, Yuandong Tian, sits about 20 feet from my desk. I love having our AI team right near me so I can learn from what they're working on.
You can learn more about this research here:http://arxiv.org/abs/1511.06410"
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