After Go, what games should be next for DeepMind?

This interview, dated yesterday, doesn't go quite that far - he mentions Starcraft as a possibility, but explicitly says that they won't necessarily pursue it.

If the series continues this way with AlphaGo winning, what’s next — is there potential for another AI-vs-game showdown in the future?

I think for perfect information games, Go is the pinnacle. Certainly there are still other top Go players to play. There are other games — no-limit poker is very difficult, multiplayer has its challenges because it’s an imperfect information game. And then there are obviously all sorts of video games that humans play way better than computers, like StarCraft is another big game in Korea as well. Strategy games require a high level of strategic capability in an imperfect information world — "partially observed," it’s called. The thing about Go is obviously you can see everything on the board, so that makes it slightly easier for computers.

Is beating StarCraft something that you would personally be interested in?

Maybe. We’re only interested in things to the extent that they are on the main track of our research program. So the aim of DeepMind is not just to beat games, fun and exciting though that is. And personally you know, I love games, I used to write computer games. But it’s to the extent that they’re useful as a testbed, a platform for trying to write our algorithmic ideas and testing out how far they scale and how well they do and it’s just a very efficient way of doing that. Ultimately we want to apply this to big real-world problems.

Oh no! The AI would make us hate each other before betraying us.

It could become better than people at playing Pictionary, by drawing images that are most likely to be correctly recognized rather than the human way of translating the model in its head into a picture, and by analyzing what models are most likely to produce a picture rather than the human way of translating the picture into a model in its head. Except if you mean that it playing against itself would make it diverge into its own language of pictures.

Although it might optimize in a direction that doesn't follow the spirit of the game, anologous to writing out the name of its task.

Actually that could be interesting - could it invent a language that is maximally efficient at communicating concepts?

To your last one, you might enjoy a MOBA where individual players have only information about stuff in their line of sight, but there's an extra player whose job it is to see everything and give "orders". I think there was one like that...

Demis Hassabis mentioned StarCraft as something they might want to do next. Video.

I don't expect to see highly sophisticated AI in games (at least adversarial, battle-it-out games) because there is no point. Games have to be fun which means that the goal of the AI is to gracefully lose to the human player after making him exert some effort.

I'm not sure about that. A common complaint about these kinds of games is that the AI's blatantly cheat, especially on higher difficulty levels. I could very well see a market for an AI that could give the human a challenge without cheating.

And yet, humans currently have the edge in Brood War. Humans are probably doomed once StarCraft AIs get AlphaGo-level decision-making, but flawless micro—even on top of flawless* macro—won't help you if you only have zealots when your opponent does a muta switch. (Zealots can only attack ground and mutalisks fly, so zealots can't attack mutalisks; mutalisks are also faster than zealots.)

*By flawless, I mean macro doesn't falter because of micro elsewhere; often, even at the highest levels, players won't build new units because they're too busy controlling a big engagement or heavily multitasking (dropping at one point, defending a poke elsewhere, etc). If you look at it broadly, making the correct units is part of macro, but that's not what I'm talking about when I say flawless macro.

Games have to be fun which means that the goal of the AI is to gracefully lose to the human player after making him exert some effort.

The problem is that most RTS games stand no chance against me or any other half-descent player, unless they are cheating. And when they cheat, the game is very much brute force vs strategy.

I've been playing "Ultimate general: Gettysburg", which was touted as having put a lot off effort into AI, and which paid off - when I play it on the highest difficulty settings, I can still win convincingly, but it does feel like I am playing an incompitant human, rather than an artificial stupidity. Its far more enjoyable to play.

RTS is a bit of a special case because a lot of the skill involved is micromanagement and software is MUCH better at micromanagement than humans.

The micro capabilities of the AI could be limited so they're more or less equivalent to a human pro gamer's, forcing the AI to win via build choice and tactics.

RTS is special because it's realtime. An AI that's only 'good enough' in terms of strategy or tactics could still win by being far better at parallelizing and reaction speed. The bigger the game world, the more this is true.

Human Starcraft players need to have a basic skill of taking hundreds of actions per minute before they can bring their superior strategy or tactics into play.

If there was any movement in Alphabet, it should've been in January when the news came out. Markets don't move on anticipated events but unexpected events, and judging from the various betting markets an Alphago victory was not that surprising; the victory also didn't mean much because the widely held opinion was that Alphago can be expected to improve steadily over time and so even if Lee Sedol won, he would lose in the coming months (I believe Sedol said something like that before the games started, and Ke Jie has also revised his earlier comments and is now saying that he would lose to Alphago in a few months too), in which case the meaning of the match is reduced to a slight shift in the improvement rate - along the lines of 'Alphago didn't improve quite as fast as Deepmind expected'. Which is not something which is meaningful to Google's bottom line.

(The real point of the match was to prove a point to the muggles and AI-deniers and get good publicity, of course.)

It is not a good proxy. Deepmind is a small team and there are many more teams within Alphabet doing machine learning. Remember that the market cap of Goog is $500 billion. (Although if one wants to invest in AI in general I think it is a cheap stock)

Just outsource it to Pentagon.

That's pretty darn far from perfect information.

As if there aren't tons of other people using neural nets on the stock market.

Run the algorithm on the Bitcoin market, and then on the stock market.

Yeah, that.

The video games are far more interesting than just violating perfect information: the AI has to figure out the rules of the game.

(Actually, they probably don't violate perfect information, which refers to the two players having access to different information and only makes sense when you think of both players as optimizing agents.)

Why not check out the AGI capabilities of Alphago... It might be possible to train chess without architectural modifications. Each chessboard square could be modelled by a 2x2 three-state Go field storing information about chess figure type. How good can Alphago get? How much of its Go playing abilities will it loose?

http://arxiv.org/abs/1509.01549 is relevant.

That isn't a formally specified game. For example, it is illegal to make up complicated ("synthetic") bidding systems.

Oooh. If we're going to look at boardgames, the best one ever designed (IMO, of course) is : 1817

This I would love to see.

But being able to draft a winning fantasy team is a lot harder than it seems.

I would be very of that prediction. Do you know how the best AI's perform at Fantasy Football?