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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

#241

Post by nazka »

brian_cloutier wrote: post #71
panic wrote: post #48

Earlier quoted context omitted.

Regardless of how good the deep learning network is on its own, the algorithm described in the DeepMind paper is an improved tree search.

Forest for the trees. Monte Carlo Tree Search was necessary and itself a massive improvement over minimax but not sufficient for creating a Go program to challenge professional players. The true innovation here is the neural networks. Without those networks to guide it AlphaGo plays far worse than existing programs. The fact that those networks are sufficient is pretty incredible. We already knew that by inventing th…

> but it's surprising that the pattern recognition coupled with some tree search seems to be all you need to play Go as well as humans.

Is it really all we need? Or it is more that they threw a lot of hardware to it? What if if a part of its efficiency is because they threw a lot of GPUs with a huge network, rather than having a NN efficient by itself?

We see that: "AlphaGos Elo when it beat Fan Hui was 3140 using 1202 CPUs and 176 GPUs. Lee Sedol has an equivalent Elo to 3515 on the same scale (Elos on different scales aren't directly comparable). For each doubling of computer resources AlphaGo gains about 60 points of Elo."

It's a lot of hardware.

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

#242

Post by mafribe »

mjn wrote: post #63
taneq wrote: post #35

Earlier quoted context omitted.

It's a proof-of-concept. What they've proved is that the same kind of intelligence required to play Go can be implemented with computer hardware. Before now, software couldn't beat a ranked human player at Go no matter how much computing power we threw at it . Now we can. Give it ten years and, between algorithmic optimizations and advances in processing, you'll have an unbeatable Go app on your phone.

> What they've proved is that the same kind of intelligence required to play Go can be implemented with computer hardware. Before now, software couldn't beat a ranked human player at Go no matter how much computing power we threw at it . I don't think that's quite true as a description of what we knew about computer Go previously, though it depends on what precisely you mean. Recent systems (meaning the past 10 years…

   Play strength scales roughly with the log 
   of computing power
The rumor I have heard is that the new Deep Mind learning algorithm really improves on this and scales linearly with computing power.

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

#243

Post by hendekagon »

Radim wrote: post #151

Beating humans in Go is, in itself, not all that exciting. Go bots have been beating strong humans for quite some time now (just not the very top humans). There are other implications that make this AlphaGo progress super exciting though. Go captures strategic elements that go well beyond the microcosm of one nerdy board game. That's the real reason Go has been around for >2,000 years, and why this AI progress is rel…

Yes. This is the point. To what extent can AlphaGo transfer what it has learned in Go to other domains. It was a very smart move to train their first AI on Go!

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

#244

Post by argonaut »

kqr wrote: post #201
argonaut wrote: post #122

Earlier quoted context omitted.

Some experts in Go less than 10 years ago believed it would be accomplished within 10 years. Also, you didn't actually refute his argument. Can you point to an algorithm that is not an incremental improvement over algorithms that existed 10 years ago? MCTS and reinforcement learning with function approximators definitely existed 20 years ago.

No, that's what they're saying. Take any invention and you can break it down into just a slight improvement of the sub-inventions it consists of. A light bulb is just a metal wire encased in a non-flammable gas and you run electricity through it. It was long known that things get hot when you run electricity through them, and that hot things burst into fire, and that you can prevent fire by removing oxygen, and that…

No, not all inventions are incremental improvements of existing techniques. Backpropagation and convolutional nets, for example. Now, you might counter with the fact that it's just the chain rule (and convolution existed before that), but the point is it that algorithm had never been used in machine learning before.

People have used neural nets as function approximators for reinforcement learning with MCTS for game playing well before AlphaGo (!!).

Your lightbulb example actually supports my point. The lightbulb was the product of more than a half-century of work by hundreds of engineers/scientists. I have no problem with pointing to 70 years of work as a breakthrough invention.

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

#246

Post by peteretep »

exDM69 wrote: post #219
Cyph0n wrote: post #190

Earlier quoted context omitted.

Your making the same assumption people made about computing in the 50s, then 70s, then 90s, etc.

Please do elaborate. I try to base my assumptions (which I accept may turn out to be completely wrong) on physics and experience in working in semiconductors. I just don't see a 1000x+ decrease in the power required happening in a decade or two without some revolutionary technology I can't even imagine. Is this what you meant? I'm sure most people couldn't imagine modern silicon chips in the 1950s vacuum tube era. Bu…

    > physics and experience in working in semiconductors

    > without some revolutionary technology I can't even
    > imagine
I suspect (in the nicest possible way) that in a lineup of your imagination (on current assumptions) vs the combined ingenuiety of the human race driven by the hidden hand, the latter wins.

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

#247

Post by argonaut »

eru wrote: post #227
Fede_V wrote: post #204

Earlier quoted context omitted.

That's actually true - going from the pixel level to the board state is trivial and not particularly interesting.

It's trivial today. It would have been interesting perhaps twenty years ago?

No, because even handcrafted computer vision systems from 20 years ago would be able to parse a Go board (edge detection + check the color contrast).

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

#248

Post by versteegen »

jules wrote: post #207
ragebol wrote: post #188

Earlier quoted context omitted.

But the computer certainly does not win on the amount of training samples required. The human is at the same level as the computer now for Go, but the computer has had much more training samples as Lee Sedol could process in his lifetime. The next step is to reduce the training time/samples for the computer to get the same performance.

That's silly. Why would you want to put human limitations on the computer? We don't artificially put computer limitations on the human.

Learning is the ability to generalise from examples. Learning is far easier to define than intelligence. Whether algorithms can learn better than humans (generalise better from the same training data) is actually probably a more interesting question than whether they can get better results given unlimited data.

EDIT: But come to think of it this is a bad example, because you don't need any training data at all to learn to play a game well. Computer programs can play against themselves and rediscover strategies that work well. It's just an advantage.

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

#249

Post by talles »

esturk wrote: post #24
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…

I've never felt playing against what is suppose to be an entire room of machines (wether Deep Blue or Watson) to be fair. What would be fair is to limit the total mass of the computer to say 200kg and leave it at that. What is effectively happening is AlphaGo is running on a distributed system of many, many machines. Even Watson took an entire room. Google is paying a premium to push AlphaGo to win.

Are you suggesting to measure computing power by kilograms? That's even stupider than measuring software complexity by LOC.

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

#250

Post by girvo »

exDM69 wrote: post #219
Cyph0n wrote: post #190

Earlier quoted context omitted.

Your making the same assumption people made about computing in the 50s, then 70s, then 90s, etc.

Please do elaborate. I try to base my assumptions (which I accept may turn out to be completely wrong) on physics and experience in working in semiconductors. I just don't see a 1000x+ decrease in the power required happening in a decade or two without some revolutionary technology I can't even imagine. Is this what you meant? I'm sure most people couldn't imagine modern silicon chips in the 1950s vacuum tube era. Bu…

Sure. But so far, we've found that revolutionary step every time we've hit these sorts of walls, and if I was a betting man I'd wager we'll do the same again.
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