Re:ChatGPT-4o vs. Math
by entropicdrifter on Thursday May 16, 2024 @03:42PM
(#40382312)
Right? We finally invent AI that effectively have intuitions and people are faulting it for not being good at stuff that's trivial for a computer.
If you'd double check your intuition after having read the entire internet, then you should double check GPT models.
By that same logic isn't that a similar process that we humans use as well ? Kind of seems like the whole point of "AI" (replicating the human experience)
1847, wasn't it? (George Boole). Or 1950-60 (LISP) or 1989 (Coq) depending on your taste?
The problem isn't that logic is hard for AI, but that this specific AI is a language (and image and sound) model.
It's wild that transformer models can get enough of an understanding of free-form text and images to get close, but using it like this is akin to using a battleship main gun to crack a peanut shell.
(Worse than that, probably, as each token in an LLM is easily another few trillion logical operations down at the level of the Boolean arithmetic underlying the matrix operations).
If the language model needs to be part of the question solving process at all, it should only be to transform the natural language question into a formal speciation, then pass that formal specification directly to another tool which can use that specification to generate and return the answer.