Self play results are much better than play against another opponent (since the faster version sees everything the slower one does, plus more). At stronger levels, the win rate for a stone difference is higher. Pure computer power increase will take much longer than your estimate. On the other hand, monte carlo is still new, and there will be big improvements in the algorithm without more processing power. I think the algorithm is more important, so perhaps a top pro will lose an even 19x19 in 20 years or less.
David > -----Original Message----- > From: computer-go-boun...@computer-go.org [mailto:computer-go- > boun...@computer-go.org] On Behalf Of Bob Hearn > Sent: Thursday, February 12, 2009 9:42 PM > To: computer-go > Subject: [computer-go] Poll: how long until computers are as strong as pros? > > How long until a computer beats a pro -- any pro -- in an even game? > How long until a computer can routinely beat the best pros? > > Not a very scientific poll, I realize, but I'd like some numbers to > use in my AAAS talk on Saturday. > > FWIW, this is a back-of-the-envelope calculation I did in August, when > MoGo beat Myungwan Kim 8p at H9: > > > After the match, one of the MoGo programmers mentioned that doubling > > the computation led to a 63% win rate against the baseline version, > > and that so far this scaling seemed to continue as computation power > > increased. > > > > So -- quick back-of-the-envelope calculation, tell me where I am > > wrong. 63% win rate = about half a stone advantage in go. So we need > > 4x processing power to increase by a stone. At the current rate of > > Moore's law, that's about 4 years. Kim estimated that the game with > > MoGo would be hard at 8 stones. That suggests that in 32 years a > > supercomputer comparable to the one that played in this match would > > be as strong as Kim. > > > > This calculation is optimistic in assuming that you can meaningfully > > scale the 63% win rate indefinitely, especially when measuring > > strength against other opponents, and not a weaker version of > > itself. It's also pessimistic in assuming there will be no > > improvement in the Monte Carlo technique. > > > > But still, 32 years seems like a surprisingly long time, much longer > > than the 10 years that seems intuitively reasonable. Naively, it > > would seem that improvements in the Monte Carlo algorithms could > > gain some small number of stones in strength for fixed computation, > > but that would just shrink the 32 years by maybe a decade. > > > Thanks, > Bob Hearn > > --------------------------------------------- > Robert A. Hearn > Neukom Institute for Computational Science, Dartmouth College > robert.a.he...@dartmouth.edu > http://www.dartmouth.edu/~rah/ > > > _______________________________________________ > computer-go mailing list > computer-go@computer-go.org > http://www.computer-go.org/mailman/listinfo/computer-go/ _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
