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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

#351
post #329

Extremely interesting news and kind of sad as a human being :) I don't really know that much about AI, but hopefully some experts can tell me - how different are the networks that play go vs chess for example? Or recognise images vs play go? What I mean is - if you train a network to play go and recognise images at the same time, will the current techniques of reinforcement learning/deep learning work or are the tech…

This is basically a combination. A "traditional" chess program would use a tree search, but trees get quickly ot of hand since they grow exponentially. The trick is to prune them, and they trained a network to do that. It selects just the moves that look good to it. (It has some level of randomness to it, too) After reaching deep enough in the search tree, they use another network to evaluate who's winning. Usually this is hard to do in Go, and that's why the second network is quite novel and helpful.

So, they use a combination of techniques. And they're doing well at it.

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

#352
post #174
post #12

The thing that was supposed to take at least 10 years happened. Only last month people were still saying that no way AlphaGo will beat the champion and that it will be crushed. Today everybody will have seen it coming and say that it was normal. Yet people will still tell that worrying about AI taking over is like worrying about overpopulation on Mars, and that this is a problem at least 50 years out.

It's only been the first round and I'm not throwing in the towel yet. Unlike AlphaGo, Lee Sedol has an opportunity to learn from their opponents since AlphaGo takes about 30 days of wall clock time to train the networks. There will be 5 games during the next week. Despite my optimism, the writing is on the wall. AlphaGo and algorithms like it will only improve as you throw more CPU time at them. I actually want Lee S…

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

#353

Earlier quoted context omitted.

> An AI is not going to take over the world by impressing us with its game-playing skills. What if you train an AI to play an RTS where matter, energy, and time are the resources and the goal is to take over the world?

I'm not going to fear an AI whose idea of "the world" is a computer game, an AI that isn't even aware of the existence of the real world, and isn't even aware of the existence of the set of real world actions.

I should have put "RTS" in quotes. I'm referring to the real world -- the original RTS.

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

#354
post #35
post #24

Earlier quoted context omitted.

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.

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"

Not necessarily the same kind, and, if I had to make the call, I would say they aren't of the same kind.

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

#356
post #54

Earlier quoted context omitted.

Yep, terrific commentary by Myungwan Kim 9p on the AGA channel. For the folks who aren't as familiar with the game, how did you find the commentary (for any channel)? What would you be interested in hearing for events like these?

As a person who knew only the basic rules beforehand, I wouldn't imagine it any better. Any more complicated and I'd get lost. I'd love to see one day a live commentary, with an extra window showing what computer is thinking at the moment.

Having worked on some code very similar to this, showing the computer's best moves would be quite artificial. Here's some thoughts as to why that is:

1. The computer can discard all its current best ideas and flip through new ones so fast, it would be a flickering blur to humans.

2. Even if we put a speed limit on it, the move being considered is itself the result of considering a lot of slight variations.

3. The ability to _articulate_ in a human language what makes the move nice is itself a "hard problem" closely related to natural language processing.

4. Even just having some color codes or symbols and grouping related ideas has some serious problems: now the visualization is pretty technical to begin with, the computer is still able to memorize and compare moves at an unbelievable rate, and it's still fundamentally not the same as the method Go masters use to find a solution.

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

#357
post #91

Earlier quoted context omitted.

The only remaining are language-related. Natural languages are the next focal point of AI research.

Skill related. I'd be interesting to see how quickly driving AIs take to beat the best human drivers, in a weight-equal vehicle. An algorithmic competitor in formula one, would be interesting.

Would be a stomp for the computer; they don't have to respect G-forces.

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

#358

Earlier quoted context omitted.

There is a lot of progress being made in AI right now. Hard problems that were expected to take decades, are being beaten regularly. Who is to say how much AI could advance in the next 20-30 years? "We've beaten some hard problems more quickly than expected therefore we'll likely beat other hard problems more quickly than expected" is logical induction. It's equivalent to "I just flipped a coin and got heads. I'll pr…

Do you think it's better to propose we won't, and not start preparing for a smarter-than-human intelligence. Or to propose we might, and that we should prepare for it to happen?

On the face of it we should definitely have a strategy for dealing with strong AI, but with no knowledge of what strong AI will look like how would we prepare for it? There's ostensibly nothing we can do. Until we make more progress in the field we can't make any preparations other than wild speculation. And that is what I see no value in.

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

#359
post #119

Earlier quoted context omitted.

Yeah according to Redmond, it seemed that AlphaGo made a few "mistakes" whereas Sedol made none. And yet AlphaGo came out substantially ahead. So I'm not sure what that means. Perhaps we need to see more in-depth analysis of the moves, but it seems that AlphaGo just out-calculated Sedol.

I wonder if their move selection algorithm takes into account the "surprise" factor: given two moves that are almost equal in strength when analyzed to a depth of N, chose the one that looks worst at N-1. That is, if all else is equal, assume that you can search deeper than your human opponent, and lay traps accordingly.

That's interesting. And a sign of truly understanding what a human would think.

Btw. There's a concept in Go called "overplaying". That means selecting a move that isn't objectively the best you could come up with, but that is most confusing, considering the level of the opponent. It's generally thought of as a bad practice, and if you misestimated the level of your opponent, she can punish you by exploiting the fact you didn't play your best move.

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

#360
post #241

Earlier quoted context omitted.

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 12…

What does a lot of hardware means? The human brain has about 100B neurons with about 100+ dendrites per neuron, while AlphaGo has about 1K CPUs with about 2B transistors per CPU.
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