#chess

D.T. Max:

When Magnus Carlsen became the world chess champion a few days ago, I don’t think anyone in the chess world lost money. All bets were on the almost-twenty-three-year-old Norwegian’s beating the reigning grandmaster, Viswanathan Anand. With play in Chennai, India, Anand had the home-court advantage, but, at nearly forty-four, he is getting old for top-level chess, and Carlsen gained momentum as the match went on. He didn’t lose in ten games. Perhaps the biggest surprise was in the last one, when Carlsen, with the prize in his grasp, played to win rather than accepting what looked to be Anand’s offer of a draw, which would have clinched it for Carlsen anyway. He could have been the world champion a couple of hours sooner.

Despite his ad-hoc approach, Carlsen seems so good at so many things now, it’s not clear to chess commentators where it’s going to end. He’s like a great baseline tennis player who just keeps returning the ball deep and with power until he forces an error, but rarely makes any of his own. “He’s gotten a little older,” notes Mig Greengard, who works with Kasparov and tweets as @chessninja, “but as far as the actual games, I don’t think he’s really different now. He’s just more.” That Carlsen still hasn’t peaked he finds “frankly terrifying.”

Prodigy.

Speaking of simulations, here’s Christopher Chabris and David Goodman on the role that computers have settled into in chess:

Before the Deep Blue match, top players were using databases of games to prepare for tournaments. Computers could display games at high speed while the players searched for the patterns and weaknesses of their opponents. The programs could spot blunders, but they didn’t understand chess well enough to offer much more than that.

Once laptops could routinely dispatch grandmasters, however, it became possible to integrate their analysis fully into other aspects of the game. Commentators at major tournaments now consult computers to check their judgment. Online, fans get excited when their own “engines” discover moves the players miss. And elite grandmasters use computers to test their opening plans and generate new ideas.

This wouldn’t be very interesting if computers, with their ability to calculate millions of moves per second, were just correcting human blunders. But they are doing much more than that. When engines suggest surprising moves, or arrangements of pieces that look “ugly” to human sensibilities, they are often seeing more deeply into the game than their users. They are not perfect; sometimes long-term strategy still eludes them. But players have learned from computers that some kinds of chess positions are playable, or even advantageous, even though they might violate general principles. Having seen how machines go about attacking and especially defending, humans have become emboldened to try the same ideas.

Since the computers have already mastered chess, we’re now the ones learning from them. And becoming more like them…