Ke Jie, the world's top-ranked Go player, started a three-round showdown on Tuesday against Google's artificial intelligence program, AlphaGo, which beat a South Korean Go master in a five-round showdown past year.
Google's AlphaGo is slowly but surely becoming the best Go player in the world, with one key difference: Unlike other top players, it's not human.
Go, an ancient Chinese board game, is favored by AI researchers because of the large number of outcomes compared to other games such as western chess.
Now all that's left for AlphaGo is to finish crushing the 19-year-old grandmaster Ke Jie, or for the teen to miraculously pull out a win.
Ke, who went professional at the age of 11, has attained the ninth dan, the game's highest level. Now, the AI has defeated Ke Jie, who's widely-regarded as the world's best (human) Go player.
This week's games between AlphaGo and Ke are being live streamed by Google online, but Chinese censors already block access to Google and its services, such as Gmail and YouTube, in the country. "Last year, it was still quite humanlike when it played", Jie said after Tuesday's game. His peers agreed, with former world champ Gu Li giving him just a 10 percent chance to win even a single game against AlphaGo - odds some still considered generous. While in the team Go match, a five-player Chinese team will collectively go up against AlphaGo on the same day. Founder Demis Hassabis hailed the AI's Chinese opponent after the match: "Ke Jie fought bravely and some wonderful moves were played".
For China, the birth place of weiqi, the match is particularly symbolic.
The only problem is, is that this is not the first time that Ke has been defeated by AlphaGo. AlphaGo beat Ke Jie with only half a point difference-the smallest possible-but that may be due to the AI's "safer" winning strategy. While the grander drama plays out, a $1.5 million prize is also at stake.
The ceremonial game - the second time AlphaGo has gone head-to-head with a master Go player in a public showdown - represents a major bridge-building exercise for Google in China, following a charm offensive in recent years.
AlphaGo's machine-learning algorithm integrated advantages of both a "policy network" and a "value network", storing not only innumerable past games played by humans but also those played against the continuously improved versions of itself.