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Google's AlphaGo Beats Lee Se-dol In the First Match (theverge.com)
New submitter Fref writes with news from The Verge that "A huge milestone has just been reached in the field of artificial intelligence: AlphaGo, the program developed by Google's DeepMind unit, has defeated legendary Go player Lee Se-dol in the first of five historic matches being held in Seoul, South Korea. Lee resigned after about three and a half hours, with 28 minutes and 28 seconds remaining on his clock. "
Lee will face off against AlphaGo again tomorrow and on Saturday, Sunday, and Tuesday. Also at the New York Times. Science magazine says the loss may be less significant than it seems at first.
Lee will face off against AlphaGo again tomorrow and on Saturday, Sunday, and Tuesday. Also at the New York Times. Science magazine says the loss may be less significant than it seems at first.
This is a great accomplishment for A.I., but it's likely he will rebound from this opening round loss.
Happiness in intelligent people is the rarest thing I know.
Ernest Hemingway
It's not hard to play a game.
Well, that's up for debate. Go is arguably the hardest game to play (and master) there is.
Tag?
"Go is arguably the hardest game to play (and master) there is."
Hardly. Try Diplomacy some time. Complex negotiation and justifying back-stabbing,
If the computer disdains or is incompetent at unstructured negotiation with other players,
let's see how long it will last with the players ganged up against it.
Well, that's up for debate. Go is arguably the hardest game to play (and master) there is.
Hex (a.k.a. Con-tac-tix or Nash) is a very subtle and interesting game. Programs still can't beat the best human Hex players. DeepMind's CEO was quoted in the NYTimes today saying, "Really, the only game left after chess is Go". I wish reporters knew to ask him, "What about Hex?"
I respectfully disagree.
Diplomacy with it's self-references and multi-body perturbations is closer to a set of non-linear partial differential equations whose solution is extremely difficult and idiosyncratic and chaotic.
Ever had a disagreement with someone who is basing their behavior upon yours, who in turn is basing their behavior upon theirs? Now add as many as five more players, all intertwining their interactions with yours over time. We are not talking here about enumerating numerical solutions to nice set of equations, either. We are talking about inputs including revenge, boredom, capriciousness, contrariness.
Basically Chess and Go are nerfed versions of real world problems that humans have learned to deal with pretty well.
Even humans have significant problems with these cicular and self-referential domains, see R.D. Laing's book Knots, for example.
go uses sgf
https://gogameguru.com/i/2016/03/Lee-Sedol-vs-AlphaGo-20160309.sgf
"The Game".
See? They've already lost.
Since I doubt that most people unfamiliar with go have a way to view an sgf file here is link to the gogameguru article about the game. At the bottom there is a javascript applet you can use to play through the game.
https://gogameguru.com/alphago-defeats-lee-sedol-game-1/
Here's a talk by deepmind about this AI https://www.youtube.com/watch?...
I am still waiting for a computer who can recognize my bags at a conveyor belt at least as efficiently as me
I've worked with industrial vision devices in the past and trust me, you could set up a machine to recognize luggage as efficiently as a human being today if you wanted to. In fact, it will do better.
The only thing surprising about the Go event is that it did not happen like ten, or even twenty, years ago. You may be impressed, but I find this most underwhelming.
That's likely because you don't understand what it involves. Go is unlike chess in the sense that just throwing raw computing power at the problem won't help you at all; for a "small" 13x13 there are over 10^300 valid game trees to compute, and the number gets exponentially worse once the board increases in size. For reference, the estimated number of atoms in the universe is 10^130.
Google's AlphaGo engine is an actual machine-learning AI which had to be trained plays the game much like a regular person would - Myungwan Kim actually remarked that it feels like playing against a human being. Having a competitive Go engine today is a major milestone, make no mistake about it.
In game design theory, the kinds of politics you describe is normally treated as a form of luck - and as such it makes determining "who is better at this game" a meaningless question. If 3 random people are playing Risk against the best Risk player in the world (the person who understands the game the best), there's a rational argument that their best strategy is to co-operate and eliminate him first (no matter what he does or says or how he behaves). This sort of interaction effectively decouples skill from game success.
This is also why modern game design has generally abandoned games with lots of politics - they effectively all become the same game, and that game is really uninteresting after a while.
Let's not stir that bag of worms...
It requires more than skill. Pruning such a massive game tree is no minor feat - in fact, we don't know how to do it even today. All Go engines are based on some form of adaptive AI.
Again, chess is waaaaay easier in comparison. Pretty much all chess engines work the same way: they start with precomputed moves from an opening book and then move to what's an essentially brute force approach where the engine tries positions, assigns them scores and then picks the highest score available. How these positions are scored / discarded is what separates them, but the base procedure is unchanged. This is also what leads to what chess players call "computer moves" - most chess engines will favor unassuming, conservative moves yielding small positional advantages instead of, well, more "human", intelligent ones. Picking up pivotal moments from classic games (move 17 on Fischer-Byrne, for example) and feeding them to top-rated chess engines is an enlightening exercise.
This is all but impossible to perform in Go with even modest board sizes. The game complexity, given its simple rules, is just staggering.
Go is a far better demonstration of "intelligence" than chess in the sense that you require some form of actual AI to be competitive in it. The opening book+brute force combo used by modern chess engines is useless here.
AlphaGo relies heavily on machine learning neural network to play.