AlphaGo beats the world champion Lee Sedol in first of five matches • Hacker News Board

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

#411

Post by cjbprime » Wed, Mar 09, 2016, 6:24 PM UTC

geebee wrote: post #401

cjbprime wrote: post #399

Earlier quoted context omitted.

No, I think the statement's approximately correct. Chess has an average branching factor of 35, Go has an average branching factor of 250, intuition is required to prune candidate moves in Go in a way that it is only extremely minimally required in Chess.

But is this true as humans play it? I'm not good enough at either to really know for sure, but my impression is that while the branching factor makes a big difference for computers, it is essentially impossible for a human to manage the branching in either game (massive numbers of branches vs exceptionally massive numbers of branches). As a result, humans play both games at a high level by relying on intuition. For i…

I think humans usually have ten or less plausibly-good moves to consider per turn in Chess, and simply consider all of them, compared to tens to hundreds in Go.

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

#412

Post by nazka » Wed, Mar 09, 2016, 6:25 PM UTC

javierluraschi wrote: post #360

nazka wrote: post #241

Earlier quoted context omitted.

> 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.

I am wondering how much the amount of hardware they used had an effect on the bottom line, compared to the wisdom of their algorithm. Everybody knows it's a great step in AI. But how much? How much their algorithm is smart? Or simply put did they overfit by throwing a lot of layers and GPUs to the task? Or the algorithm is truly smart? What is the ratio of that.

It is the same question for the data they used. Facebook, Google and others seem to agree that, at the end, the quantity and quality of data are more important than the algorithm itself. So how much is it at play here? Knowing that will be able to show us why it is performing well and how much we can appreciate their work.

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

#413

Post by d0m » Wed, Mar 09, 2016, 6:26 PM UTC

visarga wrote: post #36

kul wrote: post #32

Here's one: how long until a computer can beat a human assisted by a computer?

Will humans be able to keep up with the depth of analysis these AIs will have, or will it become a problem for the AI to dumb down its thinking in order for us to grasp it? More generally, scientists using AI for research will probably have to do research on the research, to understand what the AI discoveries mean. Maybe they mean something we can't grasp at all, in which case they go completely over our heads, like…

I wouldn't say "dumb down" but it definitely needs to explain why it took some lines of reasoning. With deep learning, you need to rebuild the whole system with different test-cases to change a minor behavior.. but imagine if we could just say "Why did you do that? XYZ. And adjust it: "Oh, gotcha. You can't because of ABC", and then the AI has that problem solved. I guess that would be the next step in AI. I think it's called symbolic reasoning.

Here's a very good article: http://dustycloud.org/blog/sussman-on-ai/ (A conversation with Sussman on AI and asynchronous programming)

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

#414

Post by terryf » Wed, Mar 09, 2016, 6:27 PM UTC

GolDDranks wrote: post #351

terryf wrote: 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 t…

right, yes, but my question was meant to be a bit more general - this and various other results have shown that it is possible to train a deep net to do a specific task very successfully - my question was if it's possible to train it to do two or more tasks as successfully or will the network then have to be exponentially larger. I suppose there is no known way to "combine" trained networks together.

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

#415

Post by d0m » Wed, Mar 09, 2016, 6:28 PM UTC

hosh wrote: post #403

d0m wrote: post #398

Earlier quoted context omitted.

I think it's fair to say that in the future, people will look back and wonder how it was possible to live without having a good AI.. similar to how we look past at caveman and wonder how they could live without electricity. AI is really just a tool that we leverage, the same was as we leveraged the wheel or electricity.

Yep. I was just talking with the founder of a startup I work with. His son was born in the past 5 months or so. The son is never going to live in a world that doesn't have deep learning. Like the kids who never knew what the world was like before the smartphone. Like the kids who never knew what the world was like before the web browser. And AI is just one strand. There are several strands that are as deeply changing…

Here's a video where teens discover Windows 95: https://www.youtube.com/watch?v=8ucCxtgN6sc It gives a visual analogy of what you're saying about the new generation and AI!

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

#416

Post by YeGoblynQueenne » Wed, Mar 09, 2016, 6:29 PM UTC

21 wrote: 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.

Go is literally infinitely more easy to solve than general intelligence. "Literally" in the sense that Go has a finite number of board states, while a general intelligence must be able to deal with an infinite amount of novel situations, presumably by generalising from previously experienced ones.

Infinity is a real problem. When you try to learn from examples, you first need to see "enough" examples of whatever you're trying to learn. If there are infinitely many such examples, no matter how clever you are in tackling your search space there will always be infinitely many examples of infinitely many situations you've never come across, and that you won't be able to learn.

The typical example of this is language. You could give a learner all phrases of a given language every produced and it would still be missing an infinite amount of necessary examples. Somehow (and it's freaky when you stop to think about it) humans get around this and we can produce and understand parts of infinity, without sweating it.

Machine learning is simply incapable of generalising like that and anyone who thinks AGI is just around the corner has just failed to consider what "general" really, really means.

Though to be fair, now that I had my little rant I have to admit that you don't need to go "general intelligence" before you can be really, really dangerous. Even if AI doesn't "take over" it can do a lot of damage, frex if we start using autonomous weapon systems or hand over critical infrastructure maintenance to limited and inflexible mechanical intelligence.

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

#417

Post by hosh » Wed, Mar 09, 2016, 6:30 PM UTC

gcr wrote: post #409

hosh wrote: post #370

Earlier quoted context omitted.

The 2003 match was a brute force approach. AlphaGo's architecture resembles much closer to how humans think and learn. I initially learned Go to be able to have some chance of an AI. I then had some transformative experiences that coincided with my early kyu learning of basic Go lessons. On of the big lessons in Go is to learn how to let go of something. Taking solace in anything on the Go board is one of the blocks…

This isn't about Moore's Law though. From the AlphaGo paper: > During the match against Fan Hui, AlphaGo evaluated thousands of times > fewer positions than Deep Blue did in its chess match against > Kasparov; compensating by selecting those positions more intelli- > gently, using the policy network, and evaluating them more precisely, > using the value network—an approach that is perhaps closer to how > humans play.…

I know that. You didn't read my comment very thoroughly.

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

#418

Post by Florin_Andrei » Wed, Mar 09, 2016, 6:31 PM UTC

areyousure wrote: post #393

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. Can anyone provide some written references to this effect? Last time I searched (extensively), I couldn't really find anyone saying this.

FWIW, before AlphaGo defeated Fan Hui 2-dan last year, everyone was saying that would not be possible before 2025 or so. That was the consensus.

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

#419

Post by [deleted] » Wed, Mar 09, 2016, 6:31 PM UTC

cjbprime wrote: post #411

geebee wrote: post #401

Earlier quoted context omitted.

But is this true as humans play it? I'm not good enough at either to really know for sure, but my impression is that while the branching factor makes a big difference for computers, it is essentially impossible for a human to manage the branching in either game (massive numbers of branches vs exceptionally massive numbers of branches). As a result, humans play both games at a high level by relying on intuition. For i…

I think humans usually have ten or less plausibly-good moves to consider per turn in Chess, and simply consider all of them, compared to tens to hundreds in Go.

[deleted]

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

#420

Post by [deleted] » Wed, Mar 09, 2016, 6:31 PM UTC

areyousure wrote: post #393

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. Can anyone provide some written references to this effect? Last time I searched (extensively), I couldn't really find anyone saying this.

[deleted]