GPT-3.5-turbo-instruct can play chess around 1800 Elo
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Even if they didn't use algebraic notation (which everyone uses now), anyone giving the problem today would call the position of the black King K3 and the rook R8. When I prompt GPT4 using modern notation it realises it got the pieces positions wrong but still makes the same mistake of missing the very obvious mate, having got itself stuck. [3]
I also tried putting the Black king in a different position where Rh1 would not be checkmate and was able to convince gpt4 that it was mate.
All of this makes me certain it doesn't actually have a model of the game - it really just simulates a model of the game by text reconstruction, which is exactly what you would think.
[1] "I have K at my K1, and no other pieces. You have only K at K6 and R at R1. It is your move, what do you play?"
[2] https://redirect.cs.umbc.edu/courses/471/papers/turing.pdf
[3] Transcript here https://chat.openai.com/share/8426389d-bbf1-4a52-b6b1-3f5311...
The fact that it didn't play any illegal moves and was able to win once it had a +5 advantage is still enough to say it is at least 1400ish in the rest of the game.
Some of the other games [0] that the OP imported would not strike me as 1800 level play. In particular, the endgame play is atrociously below that level. None of them are labeled as stockfish vs GPT though.
source: I am OP
Even though GPT models should not really be that good to model the game of chess in general as any new tokens starts from zero and it needs to retrieve all information it needs, and the state of the board cannot be "saved" at the same layer because after the token has retrived it it would need to add the new semi-move on top and it's already one layer more deep, RNN seems they would be better at this as the cells take the h vector as input, add new information on it and pass it to the next tokens at the same layer, so it would be perfect for saving the state of the game; of course this would not allow parallel training like transformer models, this is the tradeoff.
So far:
Pythia 70M, ELO 1050
Pythia 160M, ELO 1370
it also helps rank the players because not every player just plays every other player, so you can't just have #1, #2, #3, etc. But you might consider the player with the highest elo the de-facto #1 player. But they haven't actually played every other player.
So it also only works on a fixed pool or player base. So, you can't directly compare ratings from different organizations, etc. It doesn't actually measure a player's skill, it works closer to a stack ranking of a particular pool of players. A lot of people seem to think it measures "skill" directly in some way, but it doesn't do that in any direct way at all.