> AI problems are always mysterious until they're solved.
There's truth there but this line is over-used. Playing chess better than a human was never deemed impossible and the ultimate solution doesn't seem to have any crazy insights that would stun a researcher from the 1960s. (You can read the source for Stockfish which is state of the art and open source). The improvements came in the form of more and more horsepower through hardware, more and more efficient innovations in the tree search very specific to the game of chess (bit board representation, move ordering), and simplifying evaluation and tweaking parameters according to unsupervised learning. Correct me if I'm wrong?
At the end of the day, chess (and go) are discrete games with perfect information played one turn at a time according to a tree of simple and trivially determined possible moves with clear criteria for winning. I don't see why we'd put this on a pedestal as the example of something generally considered uniquely human, so we'd better expand our imaginations of what we can achieve with AI. As the parent said, the mistake may have been in supposing there wasn't a solvable evaluation function for Go positions when in fact, through some more human ingenuity, there is.
So what happens if (when?) we come up with a system that does everything a human can do, better than a human, but doesn't contain any 'crazy insights', just a bunch of incremental improvements on what we have now?
Does that mean we aren't intelligent? Or does it mean that the system isn't intelligent but that we are "because we do it differently"? Or do we accept at that point that intelligence is composed of simple building blocks interacting in complex ways (which we already know, if we eschew Cartesian duelism)?
We would declare it intelligent? Certainly the people of today would call it intelligent. What I suspect you are claiming is that the people of that future would not call it intelligent, and this is the basis for arguing why that objection is not valid today. But that extrapolation to the future is just your speculation.
Or, in my view the most likely, that isn't in fact possible and the system we eventually arrive at that does that, _will be_ extremely different from what we have now.
Although I actually think that we'll never make a system that does _everything_ a human can do at all, simply because that would be silly.
And of course, there also has never been a human who can do everything that humans can do, so this bar is way too high anyway.
Perfect information isn't true, you don't exactly know the opponents next move. This broadens the search tree exponentially. Generally, with many hard problems, the size of the problem is a problem, when memory is limited.
Playing chess better than humans was certainly deemed impossible by some people (not the ones who wrote chess programs, of course). See for example Hubert Dreyfus:
While progress came not as quickly as AI researchers (or their universities' publicity departments) had hoped, computers can now do a lot of the things that he wrote about for example in "What computers can't do".
Dreyfus does not appear to have claimed that computers would never be able to play chess well. At least, not in that book.
He reacted with skepticism when Newell and Simon said in 1957 that a computer would be world chess champion by 1967 and, well, he was right to.
He said that the computational techniques in use for computer chess in the 1970s wouldn't be capable of producing a world-class player, and he was probably wrong about that -- largely, I guess, because he didn't foresee how big an impact a performance improvement of ~10000x could have.
If he actually claimed that playing chess better than humans was impossible, can you say where?
There's truth there but this line is over-used. Playing chess better than a human was never deemed impossible and the ultimate solution doesn't seem to have any crazy insights that would stun a researcher from the 1960s. (You can read the source for Stockfish which is state of the art and open source). The improvements came in the form of more and more horsepower through hardware, more and more efficient innovations in the tree search very specific to the game of chess (bit board representation, move ordering), and simplifying evaluation and tweaking parameters according to unsupervised learning. Correct me if I'm wrong?
At the end of the day, chess (and go) are discrete games with perfect information played one turn at a time according to a tree of simple and trivially determined possible moves with clear criteria for winning. I don't see why we'd put this on a pedestal as the example of something generally considered uniquely human, so we'd better expand our imaginations of what we can achieve with AI. As the parent said, the mistake may have been in supposing there wasn't a solvable evaluation function for Go positions when in fact, through some more human ingenuity, there is.