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points by jodrellblank 3 days ago | 0 comments

Far fewer than an LLM but then I “know” far less than an LLM. Sam Altman talked about a PhD level expert on any topic; if we expect a SOTA model to answer any question on any topic in a library, presumably that requires a library worth of books go into it?

Say I ask it who are the most beloved Indian cricketers and why, it might not be correct but it will have the right vocabulary - cricket terms and gameplay I’ve not heard of, player names and styles I don’t recognise, things critics and commentators like and dislike about game strategies. And it is like that for almost any topic.

If they hallucinate a Python function, it will look like a plausible function e.g. “hn.create_user_account()”. They don’t hallucinate like

    # create HN user account
    # requires eye of newt and frog leg
    “Oh great spirit of the internet I request and command you make a new account…”

It’s a terrific amount of facts to be able to write even plausibly about tons of topics.

[–] giardini 3 days ago

We don't need LLMs that can "answer any question on any topic in a library"!

We don't even need machines that can answer any question in a specific topic area. But we could use machines that can answer "I don't know." when they cannot compute the answer.

Consider the possibility of much-smaller LLMs that answer questions only in limited domains (physics, chemistry, math, medicine, etc.)?

Could not such LLMs exist? If not, why not? Would they not likely be more useful and far, far easier and cheaper to create and run (possibly even with far less hardware) than the current "know-all" LLMs? Also might they possibly avoid certain problems ( e.g., hallucinations, deceit, apparently undesirable behavior, etc.) associated with the "know-all" LLMs we now have?

[–] jodrellblank 1 day ago

I do wonder if a medical LLM needs to know anything about popstars or films or classic literature. But your particular examples make me wonder how you could train an LLM to talk medically about "blood pressure" without knowing any physics about what pressure is, or any of the other ways the STEM subjects overlap and blend into each other without clear boundaries - chemistry of drugs, math of dose calculations, language of drug and disease naming etymology, etc.

If a patient with high blood pressure asks "will my face look like Dizzy Gillespie?" isn't it better to answer "No, that was air pressure and cheek damage" than to answer "I don't know who that is, call your doctor"?

[–] whatshisface 2 days ago

I feel the intuition leads us astray here because the combined text of every science book ever written is much less than the size of a complete description of the human brain. To the hamburger of reason the library is a sesame seed.

[–] reactordev 3 days ago

We need to up the ante, we all know it's the Mumbai Indians. ;)

One can train a decent model at home, for a specific task but you are absolutely correct that in order to have a model that's an expert in any topic it requires training and data on all topics.

[–] splatter9859 3 days ago

I nearly spit out coffee reading this. Amazing use of vocabulary; especially "... oh great spirit of the internet".

I sometimes jokingly explain to certain people not immersed in tech that sometimes saying the "magic words" (commands) from the "codex" (script) in the right sequence with a lot of hand waving allow "magic" (applications/web apps/etc.) to happen.

It generally brightens a patients day and makes things relatable to those non-technical, children, the elderly, or the like.

TLDR: thanks for the chuckle.