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deathanatosyesterday at 10:41 PM1 replyview on HN

The entire second on chess engines is, from the view of the entire thesis of TFA, is incoherent. Let's assume, for sake of argument, that I agree with the section: that an idealized chess move predictor isn't a predictor — which is not a thing that exists, as the space of chess is enormous, but let's pretend! — that's not what LLMs are? Even if we just restrict ourselves to the space of written English prose, the space is quite literally infinite. So, hopefully obviously, no LLM is comparable to an idealized chess engine. Similarly, incoherently, we wave away the "make_more_likely", when, at least to me, the entire meat of that argument would be in the reward function, and we just gloss over that entirely.

(I would also agree with the parent commenter on that the writing smells like an LLM.)


Replies

astrobe_yesterday at 10:57 PM

The reward function seems indeed to be the protagonist there, still it stays in the shadows. One can only imagine that it is some kind of evaluator that scores the sequence based on grammar correctness, semantic consistency, etc.? To use the proposed chess analogy, maybe it could be a Stockfish engine that evaluates the submitted position that results from the move submitted by the LLM?