I don’t know how they did it, but I played a chess game against GPT4 by saying the following:
”I’m going to play a chess game. I’ll play white, and you play black. On each chat, I’ll post a move for white, and you follow with the best move for black. Does that make sense?”
And then going through the moves 1-by-1 in algebraic notation.
My experience largely follows that of GoteNoSente’s. I played one full game that lasted 41 moves and all of GPT4′s moves were reasonable. It did make one invalid move when I forgot to include the number before my move (e.g. Ne4 instead of 12. Ne4), but it fixed it when I put in the number in advance. Also, I think it was better in the opening than in the endgame. I suspect this is probably because of the large amount of similar openings in its training data.
Interesting, I tried the same experiment on ChatGPT and it didn’t seem able to keep an accurate representation of the current game state and would consistently make moves that were blocked by other pieces.
I don’t know how they did it, but I played a chess game against GPT4 by saying the following:
”I’m going to play a chess game. I’ll play white, and you play black. On each chat, I’ll post a move for white, and you follow with the best move for black. Does that make sense?”
And then going through the moves 1-by-1 in algebraic notation.
My experience largely follows that of GoteNoSente’s. I played one full game that lasted 41 moves and all of GPT4′s moves were reasonable. It did make one invalid move when I forgot to include the number before my move (e.g. Ne4 instead of 12. Ne4), but it fixed it when I put in the number in advance. Also, I think it was better in the opening than in the endgame. I suspect this is probably because of the large amount of similar openings in its training data.
Interesting, I tried the same experiment on ChatGPT and it didn’t seem able to keep an accurate representation of the current game state and would consistently make moves that were blocked by other pieces.