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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

#481

Post by hosh »

rictic wrote: post #473
gcr wrote: post #409

Earlier quoted context omitted.

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.…

My understanding is that it is much more expensive for AlphaGo to evaluate a position than it was for Deep Blue. I'm not certain, but I would be surprised if AlphaGo did not need significantly more computation than Deep Blue. edit: some actual estimates. Deep Blue had 11.38 GFLOPS[1]. According to the paper in Nature, distributed AlphaGo used 1202 CPUs and 176 GPUs. A single modern GPU can do between 100 and 2000 dou…

A brute force approach for Go doesn't work. It doesn't work for humans (deep reading skills) and doesn't work for computers. The Monte Carlo approach was the first one that allowed Go AIs to scale with the hardware. This was at least two years ago.

AlphaGo went way beyond that. It actually learned more like how a Go player does. It was able to examine and play a lot of games. That's why it was able to beat a 2p pro, and within less than half a year, challenge a 9p world-class player at least on even terms.

The big thing isn't that AlphaGo is able to play Go at all at that level, but that learned a specific subject much faster than a human.

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

#482

Post by seanp2k2 »

hosh wrote: post #370
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…

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…

What I always think about with AI, and speaking to the "man's programming vs man" higher up, is what we'll get when we can teach computers how to solve these problems so that e.g. They could come up with the solution for + implement something like this on their own.

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

#483

Post by [deleted] »

hosh wrote: post #417
gcr wrote: post #409

Earlier quoted context omitted.

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.

[deleted]

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

#484

Post by cm2012 »

LockeWatts wrote: post #475
zouhair wrote: post #436

Earlier quoted context omitted.

Good luck with that.

Starcraft in many ways is a much easier game for an AI to beat top pros at than Go.

They say Starcraft is still 5-10 years out for AI to beat pros: http://www.newyorker.com/tech/elements/deepmind-artificial-i... (ctrl+f for Starcraft at the bottom of this article)

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

#485

Post by cm2012 »

LockeWatts wrote: post #478
sago wrote: post #469

Earlier quoted context omitted.

The obvious problem is that speed of tactical execution can make up for a lot of strategic thought. The famous example: you can rush a line of siege tanks with zerglings if you can micro them fast enough[0]. [0]: https://www.youtube.com/watch?v=IKVFZ28ybQs

I hope that in the interest of fair play they'll limit their AI to 300 APM or so. Make it win not on mechanical execution, but on decision making.

Even with that though, They say Starcraft is still 5-10 years out for AI to beat pros: http://www.newyorker.com/tech/elements/deepmind-artificial-i... (ctrl+f for Starcraft at the bottom of this article) -----

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

#486

Post by chimtim »

AlphaGo can be beaten. It uses reinforcement learning so it will perform the set of moves that in the past led to its win. So predictable. Sedol just needs to take control and make it play in a predictable fashion. Also, perhaps play obscure moves that AlphaGo wouldn't have trained on. Perhaps next year's Go winner will have a PhD in computer science.

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

#487

Post by rictic »

hosh wrote: post #481
rictic wrote: post #473

Earlier quoted context omitted.

My understanding is that it is much more expensive for AlphaGo to evaluate a position than it was for Deep Blue. I'm not certain, but I would be surprised if AlphaGo did not need significantly more computation than Deep Blue. edit: some actual estimates. Deep Blue had 11.38 GFLOPS[1]. According to the paper in Nature, distributed AlphaGo used 1202 CPUs and 176 GPUs. A single modern GPU can do between 100 and 2000 dou…

A brute force approach for Go doesn't work. It doesn't work for humans (deep reading skills) and doesn't work for computers. The Monte Carlo approach was the first one that allowed Go AIs to scale with the hardware. This was at least two years ago. AlphaGo went way beyond that. It actually learned more like how a Go player does. It was able to examine and play a lot of games. That's why it was able to beat a 2p pro,…

Strong agreement that it wasn't purely about computational power, and that there were significant software advances. I just want to make the point that hardware has advanced considerably as well.

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

#488

Post by ghaff »

darkmighty wrote: post #479
soup10 wrote: post #428

Earlier quoted context omitted.

People that try to predict the future in ai are breathing hot air more often then not.

Serious predictions actually inferred from the progress of existing (MCTS and others before) bots, which was something like 1 stone every two years (I don't recall the details, but it's easy to find out there). Top professionals were estimated to be something like 10 stones stronger than the best bot at 2008, so 2025 wouldn't sound too conservative. "At the US Congress 2008, he [Myungwan Kim] also played a historic d…

Go seemed to progress in a lot more fits and starts than did chess (which, admittedly, probably had a lot more effort put into it). Prior to 2005 or so, Go programs were relatively weak and there were people working on them who were saying that they didn't really see a path forward.

Then people hit on using Monte Carlo which was the big step forward you show in your graphs. But then, that progress seemed to stall to the degree that various people were quoted in a Wired article a couple years ago about how they weren't sure what was going to happen.

Yet, here we are today.

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

#489

Post by jcoffland »

hosh wrote: post #392
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…

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…

This is misleading. AlphaGo beat a 2p player five months ago. Now it has beaten a 9p player. That tells is nothing about it's improvement in the intervening time. Given only this information, however unlikely, AlphaGo could have actually been stronger before.

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

#490

Post by kybernetikos »

FeepingCreature wrote: post #123
ubernostrum wrote: post #109

Earlier quoted context omitted.

Sort-of repeating a comment I made last time AlphaGo came up: As far as I know there is nothing particularly novel about AlphaGo, in the sense that if we stuck an AI researcher from ten years ago in a time machine to today, the researcher would not be astonished by the brilliant new techniques and ideas behind AlphaGo; rather, the time-traveling researcher would probably categorize AlphaGo as the result of ten years'…

I think the thing that would surprise a researcher from ten years ago is mainly the use of graphics cards for general compute. The shader units of 2005 would only be starting to get to a degree of flexibility and power where you could think to use them for gpgpu tasks.

I got my first consumer gpu in 1997 and was thinking about how to do nongraphical tasks on it almost immediately. I didn't come up with anything practically useful back then and they were much more limited but I don't think someone from 2006 would find it surprising to hear that this was a thing.
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