• sem@piefed.blahaj.zone
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    4 days ago

    What the example shows is that you cannot “teach” the llm how to count the letter R, because LLMs don’t work that way.

    The AI company would have to solve the problem another way, let’s say by recognizing that the user is asking for letter-counting, and pass that off to a different kind of algorithm that can count letters.

    • SorryQuick@lemmy.ca
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      4 days ago

      Yes, and that’s called a harness, which everyone uses these days. The harness increases perceived intelligence (or accuracy) by absurd amounts. You can “teach” (or the equivalent of) LLMs anything with a custom harness.

        • SorryQuick@lemmy.ca
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          4 days ago

          Well the idea is you don’t need to code it yourself, you can have it do it for you. Sure it’ll have bugs the first few times, but humans also make mistakes the until they get the hang of it.

          • sem@piefed.blahaj.zone
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            3 days ago

            The difference i guess is that humans are capable of learning and producing better code as they become more expert at it.

            The big tech companies are surely trying to improve AI with these “harnesses” as you call them, and you can try vibe coding them yourself.

            But it seems to me like spending a lot of time adding features to a technology to try to catch edge cases, but the edge cases will never end, and you’ll never be able to use it for anything except rough approximations or bullshit

      • sqw@lemmy.sdf.org
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        4 days ago

        yes lets have the llm be a blurry frontend for a bunch of invisible proprietary harness programs. that surely is a valuable human endeavor

        • SorryQuick@lemmy.ca
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          4 days ago

          Because right now LLMs (and potentially other forms of AI) are the only technology capable of doing it. Humans can too, but are much slower and more expensive.