> but LLMs don’t even "see" the board
This is a very vague claim, but they can reconstruct the board from the list of moves, which I would say proves this wrong.
> LLMs have limited memory
For the recent models this is not a problem for the chess example. You can feed whole books into them if you want to.
> so they struggle to remember previous moves
Chess is stateless with perfect information. Unless you're going for mind games, you don't need to remember previous moves.
> They’re great at explaining chess concepts or moves but not actually competing in a match.
What's the difference between a great explanation of a move and explaining every possible move then selecting the best one?
This is a very vague claim, but they can reconstruct the board from the list of moves, which I would say proves this wrong.
> LLMs have limited memory
For the recent models this is not a problem for the chess example. You can feed whole books into them if you want to.
> so they struggle to remember previous moves
Chess is stateless with perfect information. Unless you're going for mind games, you don't need to remember previous moves.
> They’re great at explaining chess concepts or moves but not actually competing in a match.
What's the difference between a great explanation of a move and explaining every possible move then selecting the best one?