• TheTrueLinuxDev@beehaw.org
    link
    fedilink
    English
    arrow-up
    5
    ·
    1 year ago

    Walking right into Betteridge’s law of headlines, any article that asks a question could be answered with a word “no.”

    ChatGPT is just something I would describes as a “language interpolation.” It grasp basic flow and few nuances of the language, but it doesn’t have a “world understanding” of whatever it generates nor does it grasp logical reasoning. Until then, we’re quite a long way off.

  • 𝕸𝖔𝖘𝖘@infosec.pub
    link
    fedilink
    English
    arrow-up
    5
    ·
    edit-2
    1 year ago

    ChatGPT is that employee who always has a very confident answer to everything, so everyone tends to just trust him/her and assume s/he’s correct, but is often wrong (and seldom checked).

    Edit: correct an autocorrect

  • Richard A.@beehaw.org
    link
    fedilink
    English
    arrow-up
    3
    ·
    1 year ago

    One answer is "Not for anything that happened after September 2021. If you want it to fact check current affairs then you are out of luck. I wouldn’t use chatGPT to fact check. I would use chatGPT to direct my research. I would then look for primary and secondary sources to prove that what chatGPT generated, is either factual, or generative.

  • 0x815@feddit.de
    link
    fedilink
    English
    arrow-up
    0
    ·
    1 year ago

    That depends on the training data, but you better check yourself before you wreck yourself 😊

    • TheTrueLinuxDev@beehaw.org
      link
      fedilink
      English
      arrow-up
      0
      ·
      1 year ago

      Well, for language model, it basically regurgitate whatever it remembered from training data with some noises, so some information might be correct from the training data, but when it is generating something that it wasn’t trained on before, then it could present incorrect answer. I only really use ChatGPT for generating documentation, to make it sounds better and flow easier for the readers.

      • Kichae@kbin.social
        link
        fedilink
        arrow-up
        0
        ·
        1 year ago

        when it is generating something that it wasn’t trained on before, then it could present incorrect answer.

        Not could, will. It’s basically guaranteed to start spitting out garbage once it’s extrapolating beyond the training data. Any semblance of correctness is just luck at that point.

        This is true for basically all models, everywhere.