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Kramnik and Deep Fritz Draw, Tied Before Final Game
iskander writes "Man and Machine were content to draw in game 7 of the Brains in Bahrain match. Now it's all down to the final game, in which Kramnik will enjoy the advantage of playing with white. It is worth noting that game 6, in which Kramnik may have resigned too early, was found to be a probable draw with best play, and that Kasparov lost to Deep Blue by tossing a drawable game. However, whereas Kasparov could only excuse himself (unconvincingly) by claiming that Deep Blue had been assisted by a human during play, Kramnik could simply request the adjudication of game 6 on the grounds of infractions committed by Deep Fritz, who is rumored to have heckled Kramnik with its Shakespearean chatter througout the game. :) So, will Dirty Fritz win it all or will Humanity's champion "rise above the chatter" and win back the crown for us? If you think you know, you may want to place a bet or register your opinion on the ChessLines survey soon, because the match ends tomorrow."
*HINT* It was a joke. The computer was not throwing quotes at him. The people that modded you "interesting" need to put down the crack pipes. And you need to get out more.
Although, iirc, Kramnik was able to study deep Fritz before hand, he is still at a disadvantage. Any hash tables that Deep Fritz uses will use library if GM games (properly ranked of course). Odds are, Deep Fritz has decades of Kramniks playing against other GM's and could easily do some kind of prediction of what Kramnik is going to play based off a probabisitic model. That's one thing the best GMs attempt to do against one another. Kramnik has very little experience against Deep Fritz, comparativly speaking, and walks into this tournament at a disadvantage. Give this, it's good to soo it's tied into the last game. I would be willing to be that if you put Deep Fritz into tournament play for 2 years and expose it's abilities complete against a cross section of the best GMs, Kramnik would beat it hands down.
Burn Hollywood Burn
A computer has no ability to learn from
mistakes? Is that so? How much do you know
about state-of-the-art in AI and the
design of Deep Fritz in particular?
Considered harmful.
Since everyone seems to have missed it, this was a joke on Chessbase. Fritz was not actually taunting anyone.
Irony. Hah!
Hmm.
On the one hand, I agree. Go is clearly a much more difficult game to program than Chess is, simply by the open nature of the game.
But computers are getting faster at an enormous rate. In ten years, it may be possible to have a Go program that plays at a 9Dan level, through brute force. Will that be more intelligent than these chess computers? Not in my mind.
We have to consider how the program works to judge how "intelligent" it is. If a Go program could play at a very high level with _today's_ technology, then it would have to have some sembalance of intelligence. If a Chess computer could have beat the grandmasters in 1970, then it would have been with intelligence rather than brute force.
With Chess computers heading towards a finite solution, Go will be the next target; and when the Go computers are able to beat the world's best, it'll be no more or less impressive than this, if they once again use brute force math to do it.
"People who do stupid things with hazardous materials often die." -- Jim Davidson on alt.folklore.urban
This is the classic moving the goal-posts that has plauged AI since its inception as a disipline. As soon as a computer can do something, it isn't AI anymore.
This has happened with Chess, visual recognition, speech recognition and a host of other tests of AI techniques.
I have complete and utter faith in human nature, and am quite sure that as soon as an algorythmic strategy for effectively attacking the problem of Go is developed, people will start saying: well, go is just a matter of implementing $foo on really good hardware, and that isn't a test of AI.
Give credit where credit is due. This is many years of AI development at work.
7. What we cannot speak about we must pass over in silence.
The taunting didn't occur, it was a joke by chessbase.com.
You can't blame Kasparov for whining, given the horrible conditions he had to face:
- the Deep Blue programmers changed the computer between games (rumours they even changed it during a game)
- it was loaded with all of GK's past games but GK had seen none of its past games
As a practicing AI researcher, I can only say that you have stumbled into some very deep waters here. Certainly, I can build a chess-playing program that will easily beat me every time, using moves I cannot understand or explain. To say that "I programmed it to play that way" is to raise the question: how did I do that, when I don't even understand what "that way" is? And how can someone who is even a worse chess player than I (OK, hardly possible) write a program that will play in a way that consistently beats my program?
The issue of assigning credit for machine chess play is far from settled, but I think there's a strong case for identifying the emergent behaviour of the chess machine as a kind of intelligence or "smarts" that is independent of the intelligence or smarts of the program's creator.
Blockquothe the poster: No one's yet found perfect play in go. There's no reason to think it's not possible, but it's a staggering challenge given that there are still many openings (called fuseki on a larger scale, and joseki for primarily corner plays) that haven't been fully explored. The most comprehensive book of joseki available lists over 60,000. Joseki are roughly equivalent in complexity and importance to opening libraries in chess. I see what you mean by "two-dimensional" (compared with chess, where different pieces have different weights due to their abilities), but I think you're wrong. In go, position is much more important than in chess, but so is relation to other stones. The associations between chess pieces are more linear (physically and metaphorically) than those between go stones. A stone is strong in relation to other stones near it, and those stones in turn, and to enemy stones. It's fantastically difficult to determine what a stone is "worth," but relatively easy for masters of the game to determine the strength or life of a shape or position.
Go is two-dimensional in the same way as a large, perfect expanse of grass - like a 500-year-old British lawn. From a distance it all looks the same, but once you get close enough you see that the variation is infinite. I hope that after you hit "post" on this you realized how ignorant that sounds. Are you saying that go masters and chess masters should be able to play competitively against each other? That there's one omni "board-playing" skill that transfers easily between games? That's like a poker player dissing a bridge player for not beating him, or a 100-yard sprinter ragging on a marathoner - pointless.
Some people are more blind about their game loyalties, and make silly comparisons. No reasonable person would say that chess is "easy." Chess is as easy as your opponent, just like go. From a game theory and programming perspective, however, chess is much easier than go. The world champion is in a serious match with a computer. Many people don't think that will happen for go this century. Number of moves has precious little to do with how interesting a game is. If you're whipping out your move numbers, though, check this: AI-Depot says: That's a great page to read, by the way. You're free to prefer any game you want, and I agree that there are snobs on both sides. But there's no question that, for computers, go makes chess look like tic-tac-toe.
This isn't as much "normalization" as it is "don't take so many drugs when you're designing tables."