datsci_est_2015 an hour ago

So why then do we stop training LLMs and keep them stored at a specific state? Is it perhaps because the results become terrible and LLMs have a delicate optimal state for general use? This sounds like an even worse case for a model of intelligence.

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stavros an hour ago | parent [-]

Nope, it's not that, but it's nice of you to offer a straw man. Makes the argument flow better.

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datsci_est_2015 an hour ago | parent [-]

Not entirely a straw man. What is the purpose of storing and retrieving LLMs at a fixed state if not to guarantee a specific performance? Wouldn’t a strong model of intelligence be capable of, to extend your analogy, running without having its hippocampus lobotomized?

Given the precariousness of managing LLM context windows, I don’t think it’s particularly unfair to assume that LLMs that learn without limit become very unstable.

To steelman, if it’s possible, it may be prohibitively expensive. But somehow I doubt it’s possible.

	▲	stavros 43 minutes ago \| parent [-]
		It is, indeed, prohibitively expensive. But it's not impossible. The proof is in the fact that you can fine-tune LLMs.