After reading that article it seems like it would be better to replace the “grandmaster norm” part of the process with standardized tournaments against a calibrated computer engine.
Is that not a viable strategy on the new engines?
On the other hand traditional algorithms might not be very good at positional chess when on a budget, wheras even weak human players can understand basic concepts like putting your rook on an open file. Then it gets even more complicated with the NNUE position evaluation models - maybe even with a one-move budget the neural net is still implicitly strong at understanding several moves ahead, and could still beat a strong human player.
Without knowing much about chess, I'd be inclined to say this can't possibly be true. Predicting human chess moves given an ELO rating sounds like a much easier task than training it to be good at the game. It is a different task alltogether, but until you reach relatively high elo scores, I'd expect a fake human ai would have a much easier time simply because it only needs to plan a few moves ahead to mimic the mindset of a lower level player.
There are many chess AIs on chess.com specifically designed to play "like" a specific grandmaster or well known chess streamer. I don't think any titled player would not be able to guess they're playing a computer if they played a few games against the AI without being told. It's very well known that computer moves are very different from human moves, even the ones specifically designed to represent a human.
As a modest 1400 blitz player, I definitely evaluate future states. That's not all I do, but it's certainly one thing I do. AlphaZero can also run just intuiting the next move without evaluating any additional states also fwiw. Though it is much better when it is allowed to do so.
> Consider the task of picking apples from a tree. You could easily make a machine to do that. But what if you had to make a machine that to an onlooker (who couldn't see the robot's "face", let's say) would appear to be a human picking apples from a tree? That would be much harder.
This is a very deep and nuanced task, made doubly difficult by obscure robotic hardware requirements. Not a great parallel.
> There are many chess AIs on chess.com, specifically designed to play "like" a specific grandmaster or well known chess streamer. I don't think any titled player would not be able to guess they're playing a computer if they played a few games against the AI without being told. It's very well known that computer moves are very different from human moves.
Maybe? A quick google suggested Maia is a close match to what I was suggesting. People are suggesting it does feel like a human in the thread. https://www.reddit.com/r/chess/comments/k4o6z1/introducing_m...
Humans see fewer candidate moves. They regularly miss quiet moves that are the strongest. They often calculate to a certain depth (even a very shallow one) and stop based on gut instinct. But it’s still just trees of moves with some eval function.
I don’t think it’s fundamentally that hard to mimic, and it would actually be genuinely interesting for didactic purposes. But for fairly obvious reasons it’s not a priority outside of a couple of projects.
I submit that you're wrong there: https://maiachess.com/
However, even as a weak player, Maia is exploitable in a way that even novice humans are not. For example, it loves to give up obvious back-rank mates and almost never protects against it (e.g. with h3). It is easy for humans to spot if they are in danger of back-rank mate (especially if you’ve been burned before) and defend against it, so it does not happen much even at low levels. But Maia, game after game, gifts you an obvious mate in 1.
> Internally, MultiPV is enabled, and with a certain probability depending on the Skill Level a weaker move will be played.
Within the constraints of the depth and calculation times it determines the best move, but depending on MultiPV it will deliberately not play that move and play an inferior one instead.
Here is a game I just played that illustrates this phenomenon:
https://lichess.org/PiIFqI2c/black
The engine plays well before making a series of random blunders no human would make. You can try this yourself by playing the different Stockfish levels on lichess.org. You will be unable to find a level that makes for an enjoyable game. There are some new engines that use neural networks to try and play similarly to how humans do [1]. I can't comment on their success, but their lack of wide adoption by the chess community signals to me that it is still incomparable to humans.