It's a great achievement but I don't think framing it as thinking akin to humans is a valid framing.
>AlphaZero gives every appearance of having discovered some important principles about chess, but it can’t share that understanding with us.
No, it doesn't have any new principles, it just has a very good system of weights.
Imagine a perfect computer that plays the game by mapping out every single move. AlphaZero is a series of optimizations that allow for an efficient but lossy simulation of such a computer. Most of the research in this area is about making an oracle more practical/more accurate estimations of the theoretically correct response. I think it's fair to call it brute force with optimizations.
You could say the same about the way humans have learned to play chess. The main lines of the popular openings have been exhaustively searched. The way humans evaluate the middle game is also due to distilling features from brute force play and passing them on to other players who add on their own features and compute weights from additional brute force play.
The difference between AlphaZero and StockFish is that StockFish only does the latter (compute weights for features given to it by others), while AlphaZero also does the former (distill features from game state).
A good analogy is intuition. If someone says AlphaZero has developed a strong intuition for chess, I have no issue with that, and to the extent human chess is based on intuition comparison is fair. But to portray humans as having chess principles, then say AlphaZero has new ones but just can't describe them seems off.
To put it another way, humans have general intelligence and AlphaZero doesn't. At least some of the general intelligence is used for human chess play, so there is a dimension of that which AZ doesn't have.
In the context of playing chess, humans use general intelligence to featurize the game state in terms of piece value and position value and weight the relative importance of those. The rest is memorization and simulation, which is where the intuition of advanced players comes from — they aren't actively thinking of piece value and position rules like beginmers. I don't see a huge difference here between humans and AlphaZero in those terms.
If you look at the progress graph of AlphaZero / LeelaChess (open source clone), and look at how it plays in its weaker iterations, it actually pretty closely correlates to how a weaker human chess player would play at those levels of strength (positional blunders, simple tactical mistakes, etc).
I've played chess for many years and I've played a few games against Leela (not full strength, the early versions). I never got the feeling that I was playing a computer.
Additionally, one of the primary ways of improvement past the ~2000 level is review of master games. Most people who make it to GM level have reviewed upwards of 5,000 master games or more over a significant period of time. So they build up a similar system of "weights" in their mind for different positional features, very similarly to the way the NN would approach the problem.
Sure, AlphaZero/Leela has not obtained generalized intelligence, but within a constrained sphere (Chess, Go, etc), it has come just about as close as is possible to that.
Reviewing 5k games is nowhere near the level of computation required for AlphaZero. They would likely not even be able to beat a human if running on human level hardware. I think there's a long way to go, and a future, general algorithm would be at AlphaZero while running on a laptop
Probably. its almost like a "poor man's hash" where you can retrieve the "almost similar best response" for each move. It stores all the games it has self-played in it's network and then looks up best move based on that
>AlphaZero gives every appearance of having discovered some important principles about chess, but it can’t share that understanding with us.
No, it doesn't have any new principles, it just has a very good system of weights.
Imagine a perfect computer that plays the game by mapping out every single move. AlphaZero is a series of optimizations that allow for an efficient but lossy simulation of such a computer. Most of the research in this area is about making an oracle more practical/more accurate estimations of the theoretically correct response. I think it's fair to call it brute force with optimizations.