Googles AI beats European Go Champion 5-0

Absolutely.
Same concept applies when somebody asks you to formally describe how you can tell there is a dog in the picture.
You can't.

https://twitter.com/demishassabis/status/695379217870008321

Spoiler: Spoiler

3-0 for AlphaGo, which apparently has improved quite a lot since last year. They'll still play the 4th and the 5th match I think, but just for show. I guess now it really can be said for sure: Go no longer is a domain in which humans outrank AIs. Albeit I wonder how long it will be until an AI like this can do it's magic without a huge cluster of CPUs and GPUs.

Quite a while, I imagine. Without knowing anything about the AI, I'm assuming that it computes all possible next moves and determines the best next move. And that is a lot of combinations to do in a short period of time. It also wouldn't surprise me if it does go in with an optimal strategy to get started.

There are more possible legal Go positions than atoms in the universe. The whole point of this is that Go is simply impossible to brute force. You have games with 100+ turns and 100+ (or 200?) possible moves each turn for each player. On top of that it is really hard to judge how well a position is for a player.
To be precise there are 208168199381979984699478633344862770286522453884530548425639456820927419612738015378525648451698519643907259916015628128546089888314427129715319317557736620397247064840935 legal positions you'd have to consider to completely solve Go by brute force.

AlphaGo certainly considers tens of thousands of ways it can be play out from any given location, but that is a tiny, tiny fraction of the possibilities that Go offers. The amazing thing about AlphaGo is that using two neural nets, one for selecting a move and the other for evaluating how good a board is, it actually has managed to basically get an "intuition" about how to play. It's not a victory of raw computation power, it is mainly a victory of machine learning.
It plays sort of like a human plays ("consider which moves seem to be good, think about what happens if you do those moves only, ignore moves that look bad from the start") and it has learned sort of like a human as well by studying games of the best players and than experimenting against itself.

I need to watch the second and third games. The first was pretty brutal.

After seeing GO here first I've given it a go on mobile. Since I liked it's idea.

Fun, but I'm getting rekt by the computers, even on easy. XD

Its good fun to waste time and improve on my downtime. XP

Wasn't the score 4-1, not 5-0?

The 5-0 was against the European top player, Fan Hui, in January, which started this thread. The 4-1 is against the world top player, Lee Sedol, that was played just last week.

Though the AlphaGo that Fan Hui faced in October of last year (it was only made public in late January this year) apparently was vastly inferior to the one that defeated Lee Sedol.
Fan Hui actually played 10 games overall. He won a single game if I remember correctly, but it was an unrated practice game.

Reading timestamps is hard.

I believe I read that AlphaGo was running on a single desktop for this.

Training the computer is a much, much more time consuming process than using what has been learned.

And I'm sure it didn't take any GPUs, right? Since there's no graphic processing going on?

No, it was using a distributed network of around 1200 CPUs and 180 GPUs.

GPUs are much better than CPUs for operations you want to run in parallel so are used all the time for non-graphics processing.

Think of a single high end GPU as a 3000 core CPU. It might only run at 1GHz, but that's far better for many things than 4 cores at 4GHz.

More like a very stupid 1ghz cpu. They can't do all that much, but they're really really fast if you have simple number crunching to do that can be parallized very well. Like the 1 million+ pixels you'd work on for an imagine. Or the many small calculations you do when you evaluate an artifical neural network.

Deepmind is apparently aiming at SC2 next

awesome. though really FA would be a healthier environement to grow an ai in. there really is only one best strategy in starcraft that you modulate according to the situation.

a case-by-case bot build from the counsel of the starcraft top 50 will systematically beat an neural net AI figuring it out by itself.

I don't think there is much of a difference, you're not giving sc2 enough credit

Well yeah, the current state of sc AIs clearly is more in the region of hard coded stuff. But that is because figuring out how to learn to play without hardcoding it is incredibly hard and nobody really knows how to do it.
Ergo a perfect next step towards better AI.