In October, though it soundly beat Fan Hui, AlphaGo was not good enough to beat someone like Lee Sedol. Fan Hui is ranked 633rd in the world, while Lee Sedol is ranked number five and widely regarded as the top player of the last decade. But over the last five months, using a technology called reinforcement learning, AlphaGo essentially played game after game again against itself as a way of improving its skills.
Clearly, the system has improved its play a great deal. At the lunch prior to the match, Hassabis also said that since October, he and his team had also used machine learning techniques to improve AlphaGo's ability to manage time. In the early to middle part of the game, it matched Lee Sedol with a rapid rate of play. "Both of them are playing fairly quickly," Redmond said.
'A Scary Variation'
Lee Sedol took an (allowed) break about an hour-and-a-half into the game as his clock continued to run. And then the match returned to what commentator Chris Garlock called "a little bit more of a ballet." Redmond said that AlphaGo was planning very much like a human professional, trying to reinforce its weaknesses---that is, its vulnerable groups of stones. "That is a pattern it has always had---the same as a really good Go player," he said, referring to AlphaGo's match with Fan Hui. "That is: making strong moves to reinforce weak groups---and potentially create weak groups [for its opponent]."
Then, at the two hour mark, AlphaGo made another particularly aggressive move, and Garlock said he was nervous---for Lee Sedol. "It just looks scary," he said. And to a certain extent, Redmond agreed. "It's a scary variation. Black has to be careful," he said, referring to Lee Sedol. He was also impressed that AlphaGo was avoiding mistakes of its own. During the match with Fan Hui, Redmond said, AlphaGo made a number of fundamental errors, but this did not really happen in the early to middle part of today's game.
Twenty minutes later, Redmond said that Lee Sedol could not survive by playing "peacefully." He needed to attack on the right side of the board. But many other parts of board were very much up for grabs. Garlock and Redmond agreed that the match was very much in the balance.
The End Game
As the two players entered the end game, at the two-hour-and-forty-minute mark, the contest remained on a knife edge. Garlock and Redmond loosely tallied the number of points available to each player in various parts of the board, deciding that the match was still too close to call. But Garlock said that this could favor AlphaGo, because its strength is in "calculation." There is some truth to this. AlphaGo uses its machine learning techniques to narrow down the scope of potentially advantageous moves, but then it uses what's called a tree search to examine the possible outcomes of those moves.
Regardless, the machine continued to play at an enormously high level. "It's more than I hoped for," Redmond said. And, yes, the two commentators continually referred to AlphaGo as "he."
As the game approached its conclusion, AlphaGo began using more and more of its available time (each player has 2 hours of unrestricted play, and then, basically, they must make all subsequent moves in less than 60 seconds). But as his clock dropped to around 34 minutes, Lee Sedol seemed to show the first signs of frustration, turning in his chair, wincing, and putting his hand to the back of his head. Then, about six minutes later, Redmond said: "I don't think it's gonna be that close."
Indeed, at the three-hour-and-thirty-minute mark, Lee Sedol resigned.
Remond called the result "a big surprise," saying he had not expected a win for Google and AlphaGo. Of course, this was only the first of five games. The next is tomorrow at 1pm Seoul time, followed by a rest day. Game three is scheduled for Saturday. Whatever the ultimate outcome of the match, AlphaGo has proven its worth. And perhaps more importantly, it has proven that it can improve by leaps and bounds---mostly on its own. As Redmond said of AlphaGo, well before today's match was over: "It's already a success."
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