{"id":5543,"date":"2017-05-21T16:58:10","date_gmt":"2017-05-21T16:58:10","guid":{"rendered":"https:\/\/www.rsoftsolution.com\/blog\/ready-set-go-rematch-of-man-vs-machine-in-ancient-game.html"},"modified":"2017-05-21T16:58:10","modified_gmt":"2017-05-21T16:58:10","slug":"ready-set-go-rematch-of-man-vs-machine-in-ancient-game","status":"publish","type":"post","link":"https:\/\/www.rbsitsoftwaresolution.in\/blog\/ready-set-go-rematch-of-man-vs-machine-in-ancient-game.html","title":{"rendered":"Ready, Set, Go! Rematch of man vs machine in ancient game"},"content":{"rendered":"
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\n \"Google's<\/a>
\n Google’s artificial intelligence programme AlphaGo will face the world’s top-ranked Go player, China’s 19-year-old Ke Jie, in a contest expected to end in another victory for rapid advances in AI
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It’s man vs machine this week as Google’s artificial intelligence programme AlphaGo faces the world’s top-ranked Go player in a contest expected to end in another victory for rapid advances in AI.\n <\/p>\n


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China’s 19-year-old Ke Jie is given little chance in the three-game series beginning Tuesday in the eastern Chinese city of Wuzhen after AlphaGo stunned observers last year by trouncing South Korean grandmaster Lee Se-Dol four games to one.<\/p>\n

Lee’s loss in Seoul marked the first time a computer programme had beaten a top player in a full match in the 3,000-year-old Chinese board game, and has been hailed as a landmark event in the development of AI.<\/p>\n

AI has previously beaten humans in cerebral contests, starting with IBM’s Deep Blue defeating chess grandmaster Garry Kasparov in 1997, but AlphaGo’s win last year is considered the most significant win for AI yet.<\/p>\n

Go is considered perhaps the most complex game ever devised, with an incomputable number of move options that puts a premium on “intuition.” <\/p>\n

Proponents had considered it a bastion in which human thought would remain superior, at least for the foreseeable future.<\/p>\n

AlphaGo’s triumph fuelled hopes of a brave new world in which AI is applied not only to driverless cars or “smart homes”, but to helping mankind figure out some of the most complex scientific, technical, and medical problems.<\/p>\n

“AlphaGo’s successes hint at the possibility for general AI to be applied to a wide range of tasks and areas, to perhaps find solutions to problems that we as human experts may not have considered,” Demis Hassabis, founder of London-based DeepMind, which developed AlphaGo, said ahead of this week’s matches.<\/p>\n

AI’s ultimate goal is to create “general” or multi-purpose, rather than “narrow,” task-specific intelligence\u2014something resembling human reasoning and the ability to learn.<\/p>\n

Sci-fi nightmare?<\/b><\/p>\n

But for some, it conjures sci-fi images of a future in which machines “wake up” and enslave humanity.<\/p>\n

Physicist Stephen Hawking is a leading voice for caution, warning in 2015 that computers may outsmart humans, “potentially subduing us with weapons we cannot even understand.”<\/p>\n

Ke faces AlphaGo on Tuesday, Thursday and Saturday.<\/p>\n

Ke is a brash prodigy who went pro at 11 years old, has been world number one for more than two years, and has described himself as a “pretentious prick”.<\/p>\n

After AlphaGo flattened Lee, Ke declared he would never lose to the machine.<\/p>\n

“Bring it on,” he said on China’s Twitter-like Weibo.<\/p>\n

But he has tempered his bravado since then.<\/p>\n

Ke was among many top Chinese players who were trounced in online contests in January by a mysterious adversary who reportedly won 60 straight victories. <\/p>\n

That opponent\u2014cheekily calling itself “The Master”\u2014was later revealed by DeepMind to have been an updated AlphaGo.<\/p>\n

“Even that was not AlphaGo’s best performance,” Gu Li, a past national champion, told Chinese state media last week. <\/p>\n

“It would be very hard for Ke to play against it, but then again, Ke has also been working extremely hard to change his methods in preparation. I hope he can play well.”<\/p>\n

Go involves two players alternately laying black and white stones on a grid. The winner is the player who seals off the most territory.<\/p>\n

AlphaGo uses two sets of “deep neural networks<\/a>” containing millions of connections similar to neurons in the brain. <\/p>\n

It is partly self-taught\u2014having played millions of games against itself after initial programming.\n <\/p>\n

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\n Explore further:<\/b>
\n Where does AlphaGo go?<\/a>\n <\/p>\n