Keep us posted!

Great News! I still believed computers weren't able to play high profile Go.
Good to hear that programmers are catching up

I don't know much about Go, but what's the deal with "handicap"? That doesn't seem fair when it comes to deciding the winner between man and machine.

Handicap makes sense. This isn't really the ultimate man vs. machine match, its purpose is more to explore just how good a modern program can be on a powerful cluster. I would be very surprised if Mogo won an even game, but I hope we will see a good improvement from the 1k it is at on conventional hardware.

But what the final match will show is whether man underestimates machine. I think we do

8 dan is a pretty serious rank, is it not? How many players in the world are above that level?

Many many players.

That is 8 dan professional. There are many people above that... but not that many. According to http://senseis.xmp.net/?Top20EuropeanPlayers, no one in Europe. It is in any case solidly beyond where the vast majority of go players can hope to reach.

Thanks for the info!

This is super cool. I'm loving these new monte carlo algos, and this is the best human player that I've seen one pitted against.

I'd not say this is a fight of man vs algorithm... We are talking about a 3000 core cluster! With that much processing power, a chess engine would crush a professional like a grape. Nobody is doing it because we know what the result would be, and nobody really likes to see it.

If anything, seeing that an AI based on running MC simulations is the best we can do for go is nothing but disheartening. It's using sheer speed with relatively little reasoning. It doesn't teach us much, other than to invest in faster processors. We'd get more out of a program that learned how to solve Life and Death problems efficiently.

Mogo is hardly just Monte-Carlo. Technically, it's not even UCT, because it doesn't use confidence bounds. Playouts are guided by hand-made patterns, and it apparently has new techniques to handle capturing races, which MC programs are known to be bad at.

Any AI is going to be disappointing once you know what's "under the hood". But isn't playouts closer to how humans operate? We figure out which moves are good by learning basic ideas and theory (vaguely similar to Mogo's patterns) and playing lots of lots of games, which is also what Mogo does. Only we are far better at generalization, therefore we learn far more from far fewer games, and can keep our knowledge across sessions.

So it's easier for a computer to beat a human playing chess than playing Go? Why?