> I hoped that when an AI beat a pro at go, it would be with a more adaptive algorithm, one not specifically designed to play go.
The particular algorithm used by AlphaGo is of course specific to Go (the neural network inputs have a number of hand-crafted features), but the overall structure of the algorithm - MCTS, deep neural nets, reinforcement learning - is very general. So there's two ways to look at it. One is that what you wanted has actually transpired.
The other is that what you asked for is completely unreasonable. I think it highly unlikely that an algorithm not specialised to Go will ever be able to beat all specialist Go playing programs.
AlphaGo can't explain the outputs of its two NNs, but it can still explain its moves by showing which variations it thinks are likely.
> ...the overall structure of the algorithm - MCTS, deep neural nets, reinforcement learning - is very general.
It is general in the sense that humans can apply those algorithms to different problems (and have been doing so for decades). It isn't general in the sense that we can't apply AlphaGo to other problems unmodified. AlphaGo can't even play chess badly. It is not really even a step toward strong AI. (Note that "strong AI" is a term with a specific meaning. [1])
> The other is that what you asked for is completely unreasonable.
That's tantamount to saying strong AI is unreasonable.
> That's tantamount to saying strong AI is unreasonable.
No, what I said is that it's unreasonable to expect that strong AI would play better Go than whatever the contemporary state-of-the-art Go AI is. But stated like that, I'm not sure I can agree with my statement. Strong AI could design and implement its own specialised Go AI. How would you count that?!
Yeah, that's an interesting case. My initial reaction is that I'd think of it as a tool that the AI was using. If a human used such a tool I'd consider it cheating at the game. But a self-modifying strong AI could integrate the specialized go AI into itself. If that is not considered cheating, should it be considered cheating for a human player to integrate tools into their physiology? Today it's pacemakers, why not a specialized go chip with a neural interface tomorrow? And this is assuming the strong AI even has a concept of a self separate from the software it controls; that separation might not even make sense.
I think we might not be able to answer these questions until a strong AI emerges.
The particular algorithm used by AlphaGo is of course specific to Go (the neural network inputs have a number of hand-crafted features), but the overall structure of the algorithm - MCTS, deep neural nets, reinforcement learning - is very general. So there's two ways to look at it. One is that what you wanted has actually transpired.
The other is that what you asked for is completely unreasonable. I think it highly unlikely that an algorithm not specialised to Go will ever be able to beat all specialist Go playing programs.
AlphaGo can't explain the outputs of its two NNs, but it can still explain its moves by showing which variations it thinks are likely.