7 ms·

LLMs are bad at creating abstraction boundaries since inception. People have been calling it out since inception. (Heck, even I got a twitter post somewhere >12

• w0m 9mo ago
  I believe his argument is that now that you've defined the limitation, it's a ceiling that will likely be cracked in the relatively near future.
  • emp17344 9mo ago
    Well, hallucinations have been identified as an issue since the inception of LLMs, so this doesn’t appear true.
    • johnfn 9mo ago
      Hallucinations are more or less a solved problem for me ever since I made a simple harness to have Codex/Claude check its work by using static typechecking.
      • emp17344 9mo ago
        But there aren’t very many domains where this type of verification is even possible.
        • nextaccountic 9mo ago
          Then you apply LLMs in domains where things can be checked Indeed I expect to see a huge push into formally verified software just because sound mathematical proofs provide an excellent verifier to put into a LLM hardness. Just see how Aristotle has been successful at math, and it could be applied to coding too Maybe Lean will become the new Python https://harmonic.fun/news#blog-post-verina-bench-sota https://harmonic.fun/news#blog-post-verina-bench-sota
          • filoeleven 9mo ago
            "LLMs reliably fail at abstraction." "This limitation will go away soon." "Hallucinations haven't." "I found a workaround for that." "That doesn't work for most things." "Then don't use LLMs for most things."
            • baq 9mo ago
              Um, yes? Except ‘most things’ are not much at all by volume.
            • johnfn 9mo ago
              "Autocomplete is great!" "It doesn't work in bash" "Then don't use it in bash." I don't see what's wrong with this argument, and I certainly don't see it as a proof that the particular technology is actually useless, as you seem to be suggesting.
    • w0m 9mo ago
      I mean, Hallucinations are 95% better now than the first time I heard the term and experienced them in this context. To claim otherwise is simply shifting goalposts. No one is saying it's perfect or will be perfect, just that there has been steady progression and likely will continue to be for the foreseeable future.
• TeMPOraL 9mo ago
  > The technology cannot create new concepts/abstractions, and so fails at abstraction. Reliably. That statement is way too strong, as it implies either that humans cannot create new concepts/abstractions, or that magic exists.
  • atty 9mo ago
    I think both your statement and their statement are too strong. There is no reason to think LLMs can do everything a human can do, which seems to be your implication. On the other hand, the technology is still improving, so maybe it’ll get there.
    • TeMPOraL 9mo ago
      My take is that: 1) LLMs cannot do everything humans can, but 2) There's no fundamental reason preventing some future technology to do everything humans can, and 3) LLMs are explicitly designed and trained to mimic human capabilities in fully general sense. Point 2) is the "or else magic exists" bit; point 3) says you need a more specific reason to justify assertion that LLMs can't create new concepts/abstractions, given that they're trained in order to achieve just that. Note: I read OP as saying they fundamentally can't and thus never will. If they meant just that the current breed can't, I'm not going to dispute it.
      • Jensson 9mo ago
        > 3) LLMs are explicitly designed and trained to mimic human capabilities in fully general sense. This is wrong, LLM are trained to mimic human writing not to mimic human capabilities. Writing is just the end result not the inner workings of a human, most of what we do happens before we write it down. You could argue you think that writing captures everything about humans, but that is another belief you have to add to your takes. So first that LLM are explicitly designed to mimic human writing, and then that human writing captures human capabilities in a fully general sense.
        • TeMPOraL 9mo ago
• 131hn 9mo ago
  There’s only one way to implement a mission, an algorithm, a task. But there’s an infinity of path, inconsistants, fuzzy and always subjective way to live. Thàt’s our lives, that’s the code LLM are trained on. I do not think, and hope, it will ever change much