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  • It sounds alot like "make no mistakes" but honestly telling it to essentially stop bullshitting works pretty well
    by samrus
  • The "do not guess" sentence works but the last 20% will only close when a system stops being told to avoid guessing and actually knows what it does not know.

    A command can get you most of the way. It takes something else for the rest.

    by Shacharp
  • So my naive understanding is that the stochastic parrot part of this business is the "statistical likelyhood of the next token", so there must be abstractly a function of "whats the next token" right? I'm also assuming that this function could be able to also return how "right" that next token is, or somehow some "strength" based on how many close matches there are, like for instance some tokens are obviously the right next token by a long shot, some next token spaces might have more closely competing candidates, so I guess my question is whether there is any value in saving or accumulating information on whether overall the tokens were close matches or not? Like a "confidence" running total or "history log", or is that just somehow too expensive or nonsensical to do?
    by cowboylowrez
  • I've used "you're not trained on this data, return exclusively grounded results" to good effect.
    by literalAardvark
  • Cool, this will be added to harnesses and then it’ll stop being effective and we’ll move on to the next magical incantation.
    by datsci_est_2015
  • We're all turning into pigeons in a Skinner box.
    by l1ng0
  • I've tried all of these and nothing really works. I have only 1 line in my CLAUDE.md file and that is "Always ground your responses." and that's it.

    Claude didn't care about it. When I pointed that out, it was apologetic and that was it.

    by thallavajhula
  • 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.

    by BatchJob

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