We chess players have had to put up with taunts from our Go playing counterparts for quite some time. First there was the jibe that Go is so much easier to learn than chess. Then the dubious charge that Go is actually more complex than chess. Some have argued that the superiority of Go over chess represents he difference between Eastern and Western values. (In Go you start with an empty board and gradually build up structures that control territory. Chess is just a bloodbath where rival armies try to slaughter the other guy’s leader.) And then there was the undeniable fact that chess-playing computers have been humiliating top-level human competition for some time, while the best Go playing software had it’s work cut out for it beating the average dog.
Just a few years ago, the best Go programs were routinely beaten by skilled children, even when given a head start. Artificial intelligence researchers routinely said that computers capable of beating our best were literally unthinkable. And so it was. Until now.
“It’s a silly human conceit that such a domain would exist, that there’s something only we can figure out with our wetware brains,” said David Doshay, a University of California at Santa Cruz computer scientist. “Because at the same time, another set of humans is just as busily saying, ‘Yes, but we can knock this problem into another domain, and solve it using these machines.’”
In February, at the Taiwan Open — Go’s popularity in East Asia roughly compares to America’s enthusiasm for golf – a program called MoGo beat two professionals. At an exhibition in Chicago, the Many Faces program beat another pro. The programs still had a head start, but the trend is clear.
Kidding aside, like most mathematicians I went through a Go phase in graduate school, an interest that was recently revived when some friends of mine got interested in the game. It’s a terrific game, no question about it. It undoubtedly comes out on top when measured by the ratio of richness of play divided by ease of learning to play. It’s just that, having already spent so much time learning to play chess, it’s hard to find time to start learning yet another game.