3 ms·

> clearly don’t have if you’ve looked at lots of gpt4 examples for example, can you fine tune GPT to play chess at ELO 1600 ? If you don't know answer, you ar

• sebzim4500 3y ago
  Given the lc0 policy network plays at a 2000+ strength on its own, I would expect that with enough finetuning gpt4 would be able to play way above 1600 strength. It's possible that finetuning would basically be training a new network from scratch and the resulting network would forget everything apart from chess. It would be a really interesting experiment, GPT-2 is probably too small but I think llama-7B might be sufficient.
  • neatze 3y ago
    I am not sure how to go about it, one way would be is to prompt it as MDP (seems like not fair), another way just prompt only as movies history (eg. I guess GPT will have to learn some form of MDP representation). Most interesting aspect to me is if model can learn not make illegal moves ?
  • agalunar 3y ago
    It's worth mentioning the truly ludicrous number of positions that chess networks are trained on, usually in the billions. Which is a bit interesting, because it suggests they're not as good at generalizing from examples as human grandmasters, who might see only millions. Perhaps this isn't surprising, since LLMs are this way with language, but given the structure of chess it's be reasonable to expect they wouldn't be quite as data hungry. My personal take is that chess isn't all that structured, really. Yes, the ruleset, pieceset, and board are small, but the tactics of the game make it chaotic – seemingly trivial differences in board state can lead to dramatically different consequences.