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[–] 9 points 1 year ago* (2 children)

I'll bait. Let's think:

-there are three humans who are 98% right about what they say, and where they know they might be wrong, they indicate it

  • now there is an llm (fuck capitalization, I hate the ways they are shoved everywhere that much) trained on their output

  • now llm is asked about the topic and computes the answer string

By definition that answer string can contain all the probably-wrong things without proper indicators ("might", "under such and such circumstances" etc)

If you want to say 40% wrong llm means 40% wrong sources, prove me wrong

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  • [–] 1 point 1 year ago (1 child)

    It's more up to you to prove that a hypothetical edge case you dreamed up is more likely than what happens in a normal bell curve. Given the size of typical LLM data this seems futile, but if that's how you want to spend your time, hey knock yourself out.

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