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Calling the AI bluff: Adding "Do not guess" cut made-up claims from 71% to 20%

96 points · 42 comments · FKJ

BatchJob · 1790562354 · focus · HN ↗
The LLM will take a statistical path to reply and will not refuse to do so under any circumstances except where its been coded to do so.
Your examples are contrived and will not be borne out in any significant way. Inaccuracies are usually not simply made up claims they are false information based on statistical paths to misleading results or which elude the current context. LLMS dont understand the word dont. LLMS dont understand the meaning of any words.
Neither you, nor aristotle nor god will ever make an LLM return the truth or correct results via prompting.
1. astrange · 1790616388 · focus · HN ↗
  > LLMS dont understand the meaning of any words.
  In what way do you understand the meaning of the word "unicorn" that an LLM does not? It has experienced exactly as many real unicorns as you have.
  1. shiandow · 1790617605 · focus · HN ↗
    Experience is not understanding, but an LLM does not reason so it cannot understand.
    It can produce text that looks like reasoning. It can even produce text with mostly sound logic, but there is no internal experience or reasoning that occured there just the generation of language.
    LLMs therefore tend to be very bad at tasks that involve meta cognition. I've yet to successfully convince one to tell me when it knows something.
    astrange · 1790623660 · focus · HN ↗
    There is internal experience.
    <a href="https://www.anthropic.com/research/global-workspace" rel="nofollow">https://www.anthropic.com/research/global-workspace
    However, we don't /want/ them to have too much internal experience, because we want to know what they're thinking* for safety reasons.
    * or, we want to be able to assume that the answer text is causally related to the thinking text

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