I wonder how long before humans start learning from AlphaGo!

I want to see AlphaGo vs AlphaGo :-)

AlphaGo has already played millions of games against AlphaGo during the reinforcement learning stage.

Is it possible to view games somewhere?

No, but they might release more info after these games.

Seeing the way chess computers have evolved, this won't be far into the future. There are several tournaments just for chess computers, and it is very hard even for grandmasters to follow every more. Somehow, after a 20-move sequence that appears to accomplish nothing, one side is slightly up, and the rest of the game is decided.

There's been a big annual Go computer cup for a while now, it's been fun to read about: http://jsb.cs.uec.ac.jp/~igo/eng/index.html Of interest this year is Facebook's new bot is competing, which employs the same strategy as AlphaGo (Deep nets with MCTS), but from what I remember they've said (they've been a lot more open about its performance, you could even play a version on KGS, though I did really like AlphaGo's paper) it's quite a bit weaker. However I suspect it's also running on a lot less computer power, and that it will still be a while before you can get AlphaGo or better performance from a mere modest gaming rig let alone a standard laptop.

One benefit of programs like AlphaGo eventually becoming available to individuals is that we'll see a rise in some incredibly strong young players that leave their ancestors in the dust, as I think has happened with Chess via Magnus. For the amount of training that can only be done by playing more and more games, being able to do that against a computer will be a lot more efficient.

> Seeing the way chess computers have evolved, this won't be far into the future.

With chess, there were two breakthroughs. First, there was Deep Blue, which threw massive hardware resources at the problem and achieved world champion level play.

That was interesting, of course, but didn't really do anything for human chess, because most humans did not have access to the necessary hardware.

The second breakthrough was when the developers of chess programs that ran on commodity desktop computers improved their algorithms to the point that they could play at (and far beyond) Deep Blue's level even though they were only able to search about 1/100th as many positions per second.

That was when humans started being able to really use computers to help the humans understand chess.

The breakthroughs in chess algorithms on commodity computers had little, if anything, to do with the Deep Blue breakthrough. The two are just too different.

Can AlphaGo be made available on hardware that top human Go players have access to, or is AlphaGo to Go as Deep Blue was to chess?

The fact that Lee Sedols hardware is a couple of pounds of wetware running on a peanut butter sandwich suggests the answer to your question is yes.

Whether those insights will come soon or not is the big question.

Hey, that wetware is ten time as powerful as what AlphaGo has to work with. Give or take a few orders of magnitude. And given that Lee's brain only uses a portion of that on Go.

> Hey, that wetware is ten time as powerful as what AlphaGo has to work with.

I don't think that's actually true. The hardware that AlphaGo is on is probably a lot more powerful than the one that is available in a single human brain, the big difference is in the software.

See the difference between the very best chess programs of a decade ago versus the ones now.

Related, the highest ELO chess program is open source: https://en.wikipedia.org/wiki/Stockfish_(chess)

Seems like somewhere in-between. They created a novel approach that is scalable and improves as you throw more hardware at it. And Google is throwing a lot of hardware at it based on their past matches with hundreds of CPUs and GPUs. I think the fact that they have been so mum about what hardware they're using suggests it's quite extreme, but hopefully they release more details soon.

Its somewhat interesting to think about the differences in marketing between IBM and Google; IBM was marketing hardware and HPC with deep blue, but Google is marketing AI when so much of their advances in AlphaGo are enabled by distributed systems and HPC running billions of games training deep neural networks. It feels a little smoke and mirrors which is probably why they won't release much until after they get enough marketing value from this tournament :)

AlphaGo uses much simpler hardware for play than for training. I think the Go associations can afford to run the hardware.

It's only a couple hundred GPUs for training. You can afford to rent that in the cloud for probably a hundred bucks or less per game.

Fan Hui has already learned from AlphaGo. He's been playing matches against her regularly, and (perhaps as a result of that) won _all_ his games in the last European championship.

I find it interesting that people are using gendered pronouns for AlphaGo. Getting some definite Turing-test vibes here.

Myungwan Kim said he feels like it plays like a she. Personally I think its informal gender was determined by the nigiri of the first match, as it's common to refer to black as he and white as she absent of player names. And I'm expecting to see at least one really cute AlphaGo-tan drawing any day now.

Here you go:

https://twitter.com/zpdldlfrkwl/status/707858454317178880

A little NSFW. Was expecting cartoon cute instead got cartoon sexy

Interesting. Mind if I ask for a source? Where did you read this?

Heard it. Internal tech talk at Google. (Though I don't think it's a secret. If yes, I just leaked inadvertently.)

You're off the hook.. it was already public ;o)

https://youtu.be/4fjmnOQuqao?t=2881

It was mentioned in a recent talk. Here's a link to a few seconds before that comment was made...

https://youtu.be/4fjmnOQuqao?t=2881

Thanks for the link!

You can see tournament results here: http://senseis.xmp.net/?EuropeanProfessionalGoChampionship