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AlphaGo beats the world champion Lee Sedol in first of five matches

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Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#571

Post by tamana »

Florin_Andrei wrote: post #425
hosh wrote: post #392

Earlier quoted context omitted.

And just to emphasize the big point here: The AlphaGo that beat the 2p European champion five months ago was not as strong as the AlphaGo that beat Lee Sedol (9p). I don't think this was just the AlphaGo team throwing more hardware. I think they had been constantly running the self-training during the intervening months so that AlphaGo was improving itself. If that is so, then the big thing here isn't that AlphaGo is…

Correct. It played like a top level human player, pretty evenly matched with Lee Sedol. AlphaGo from yesterday would have wiped the floor with AlphaGo from 6 months ago. Various commentators mentioned how both players, human and synthetic, made a few mistakes. Even I caught a slow move made by the AI. So whether Lee Sedol was at the top of his peformance, or not, is a bit of a debate. But the AI was clearly on the sa…

Is there any evidence that Sedol was anywhere close to winning?

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#572

Post by bjourne »

sethbannon wrote: post #7

I was at the 2003 match of Garry Kasparov vs Deep Junior -- the strongest chess player of all time vs what was at that point the strongest chess playing computer in history. Kasparov drew that match, but it was clear it was the last stand of homo sapiens in the man vs machine chess battle. Back then, people took solace in the game of Go. Many boldly and confidently predicted we wouldn't see a computer beat the Go wor…

> Many boldly and confidently predicted we wouldn't see a computer beat the Go world champion in our lifetimes.

To add to that, in Godel Escher Bach, Hofstadter in 1979 predicted that no chess engine would ever beat a human grandmaster player. It just goes to show how hard it is to predict what is, and also will remain, impossible for machines!

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#573

Post by conceit »

conceit wrote: post #567
eternalban wrote: post #558

Earlier quoted context omitted.

The story of Chess, according to Iranian mythological sources (recounted in Shahnameh) is that it was presented to the Iranian Court by the emissaries of the Indian Court, as a 'semantic puzzle' invented by Indian sages. (These games, it should be noted, were pedagogical in nature and used as symbolic means of training monarchs by the intellectual elites.) The response of the Iranian sages was the invention of Backga…

The origin is unclear. The fact that the thematic of a game of war is prevailing now, to me means that it might have as well been in the beginning. Actually it shows at least that those semantics are relevant to war, and to live, so what I was saying stands.

* to life

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#574

Post by Houshalter »

YeGoblynQueenne wrote: post #569
Houshalter wrote: post #561

Earlier quoted context omitted.

Machine learning doesn't "need to be told what to do all the time". No one told alphaGo what strategies were the best. It figured that out on it's own, by playing against itself. There is also unsupervised and semi-supervised learning, which can take advantage of unlabelled data. Even supervised learning can work really well on weakly labelled data. E.g. taking pictures from the internet and using the words that occu…

>> Machine learning doesn't "need to be told what to do all the time". No one told alphaGo what strategies were the best. Of course they did. They trained it with examples of Go games and they also programmed it with a reward function that led it to select the winning games. Otherwise, it wouldn't have learned anything useful. >> There is also unsupervised and semi-supervised learning, which can take advantage of unl…

>Of course they did. They trained it with examples of Go games and they also programmed it with a reward function that led it to select the winning games. Otherwise, it wouldn't have learned anything useful.

Yes, but it doesn't need to be trained with examples of Go games. It helps a lot, but it isn't 100% necessary. It can learn to play entirely through self play. The atari games were entirely self play.

As for having a reward function for winning games, of course that is necessary. Without a reward function, any AI would cease to function. That's true even of humans. All agents need reward functions. See my original comment.

>That was an instance of humour

Yes I know what humour is lel. I asked you for a specific example where you think this would matter. Where your kind of AI would do better than a reinforcement learning AI.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#575

Post by YeGoblynQueenne »

Houshalter wrote: post #574
YeGoblynQueenne wrote: post #569

Earlier quoted context omitted.

>> Machine learning doesn't "need to be told what to do all the time". No one told alphaGo what strategies were the best. Of course they did. They trained it with examples of Go games and they also programmed it with a reward function that led it to select the winning games. Otherwise, it wouldn't have learned anything useful. >> There is also unsupervised and semi-supervised learning, which can take advantage of unl…

>Of course they did. They trained it with examples of Go games and they also programmed it with a reward function that led it to select the winning games. Otherwise, it wouldn't have learned anything useful. Yes, but it doesn't need to be trained with examples of Go games. It helps a lot, but it isn't 100% necessary. It can learn to play entirely through self play. The atari games were entirely self play. As for havi…

>> The atari games were entirely self play.

That's reinforcement learning and it's even more "telling the computer what to do" than teaching it with examples.

Because you're actually telling it what to do to get a reward.

>> Without a reward function, any AI would cease to function.

I can't understand this comment, which you made before. Not all AI has a reward function. Specific algorithms do. "All" AI? Do you mean all game-playing AI? Even that's stretching it, I don't remember minimax being described in terms of rewards say, and I certainly haven't heard any of about a dozen classifiers I've studied and a bunch of other systems of all sorts (not just machine learning) being described in terms of rewards either.

Unless you mean "reward function" as the flip side of a cost function? I suppose you could argue that- but could you please clarify?

>> your kind of AI

Here, there's clearly some misunderstanding because even if I have a "my kind" of AI, I didn't say anything like that.

I'm sorry if I didn't make that clear. I'm not trying to push some specific kind of AI, though of course I have my preferences. I'm saying that machine learning can't lead to AGI, because of reasons I detailed above.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#576

Post by argonaut »

Houshalter wrote: post #562
argonaut wrote: post #501

Earlier quoted context omitted.

No, not if you have a strong prior belief that coins in general are fair. By your logic, you can predict the failure of AGI predictions by past failures of (every) AGI prediction.

>No, not if you have a strong prior belief Why would you have a strong prior belief about the invention of AGI? Now you are claiming to have far more certainty than I am. >By your logic, you can predict the failure of AGI predictions by past failures of (every) AGI prediction. This logic is extremely flawed. First not every prediction was wrong. Many people predicted it would happen in 2045, a few in 2030. Second the…

I was refuting your coin argument, which was pretty ridiculous, if I do say so.

The vast majority of predictions were wrong.

Yes, the logic is flawed, that's why I said it was your logic.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#577

Post by argonaut »

Houshalter wrote: post #560
argonaut wrote: post #497

Earlier quoted context omitted.

Even without the neural net system, AI is able to beat most amateurs, and predict moves experts would make.

I'm not sure that's correct. MCTS has well known weaknesses, and isn't even a predictive algorithm. MCTS on it's own couldn't get anywhere near beating the top Go champion, that requires deepminds neural networks.

http://www.milesbrundage.com/blog-posts/alphago-and-ai-progr...

The best Go program before AlphaGo was CrazyStone, ranked at 5-dan ("high amateur" range).

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#578

Post by argonaut »

ogrisel wrote: post #550
argonaut wrote: post #547

Earlier quoted context omitted.

A really really large number of distinct decisions that need to be made. A car only needs to control a small set of actions (wheels, engine, a couple others I'm missing). A game player only needs to choose from a small set of actions (e.g. place piece at position X, move left/right/up/down/jump).

A human brain also has a limited number of muscles to control to interact with the world.

And a much larger set of decisions.

Re: AlphaGo beats the world champion Lee Sedol in first of five matches

#579

Post by argonaut »

Houshalter wrote: post #563
argonaut wrote: post #505

Earlier quoted context omitted.

I said exactly what I said. Calling out "moving the goalposts" does not refute the assertion that this does not get us nontrivially closer to AGI. Whenever AI beats a milestone, there are a bunch of over-optimists that come out and make predictions about AGI. They have been wrong over and over again over the course of half a century. It's classic hindsight bias.

Yes it does! If you keep changing what you consider "AI", every time it makes progress, then it looks like we are never getting closer to AI. When in fact it is just classic moving goalposts. And the optimists are being proven right. AGI is almost here.

This doesn't address my argument at all.
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