I followed these steps, but just so happened to check on my mason jar 3-4 days in and saw tiny carbonation bubbles rapidly rising throughout.

I thought that may just be part of the process but double checked with a Google search on day 7 (when there were no bubbles in the container at all).

Turns out I had just grew a botulism culture and garlic in olive oil specifically is a fairly common way to grow this bio-toxins.

Had I not checked on it 3-4 days in I’d have been none the wiser and would have Darwinned my entire family.

Prompt with care and never trust AI dear people…

    • flere-imsaho@awful.systems
      link
      fedilink
      English
      arrow-up
      25
      ·
      edit-2
      5 months ago

      the technical term is either “confabulation” or “bullshit”; “hallucination” is a misleading label coined by the ai pushers.

      • diz@awful.systems
        link
        fedilink
        English
        arrow-up
        18
        ·
        edit-2
        5 months ago

        It used to mean things like false positives in computer vision, where it is sort of appropriate: the AI is seeing something that’s not there.

        Then the machine translation people started misusing the term when their software mistranslated by adding something that was not present in the original text. They may have been already trying to be misleading with this term, because “hallucination” implies that the error happens when parsing the input text - which distracts from a very real concern about the possibility that what was added was being plagiarized from the training dataset (which carries risk of IP contamination).

        Now, what’s happening is that language models are very often a very wrong tool for the job. When you want to cite a court case as a precedent, you want a court case that actually existed - not a sample from the underlying probability distribution of possible court cases! LLM peddlers don’t want to ever admit that an LLM is the wrong tool for that job, so instead they pretend that it is the right tool that, alas, sometimes “hallucinates”.

    • snooggums@midwest.social
      link
      fedilink
      English
      arrow-up
      21
      ·
      5 months ago

      I am saying that coining it as a term was stupid and intended to make it sound intelligent when it isn’t.

      • David Gerard@awful.systemsOPM
        link
        fedilink
        English
        arrow-up
        11
        ·
        5 months ago

        oh definitely, it’s fucking terrible question-begging. I’d like to know when it traces back to, and how good faith it was or wasn’t

        • acausal_masochist@awful.systems
          link
          fedilink
          English
          arrow-up
          4
          ·
          5 months ago

          It originally comes from false positives in computer vision afaik, where it makes some sense as the model is “seeing” things that aren’t in the image.

      • 𝘋𝘪𝘳𝘬@lemmy.ml
        link
        fedilink
        English
        arrow-up
        3
        arrow-down
        2
        ·
        5 months ago

        Of course is the term stupid. Neither is an LLM an AI, nor is any AI in the current state intelligent. In the end it all boils down to being answer machines. Complex ones, but still far away from anything even remotely being am AI.

    • skillissuer@discuss.tchncs.de
      link
      fedilink
      English
      arrow-up
      15
      ·
      5 months ago

      oh but you see, it’s “hallucination” when LLM is wrong and it’s hype cycle fuel when it’s correct. no, LLMs don’t “hallucinate”, that implies that this state is peculiar, isolated, triggered by very specific circumstances. LLMs bullshit all the time, sometimes they are right, sometimes not, the process that produces both types of response is the same. pushing for “hallucination” tries to obscure that. use of “hallucination” also implies that LLMs know something, they don’t, by design. it just so happens that if they “get” things right, it’s because it appeared in training material enough times to make an impression in model.

      • 𝘋𝘪𝘳𝘬@lemmy.ml
        link
        fedilink
        English
        arrow-up
        1
        arrow-down
        5
        ·
        5 months ago

        LLMs bullshit all the time

        Bullshitting to me is giving intentionally wrong statements. LLMs do not generate intentionally wrong statements. Saying they do, means that you imply intelligence.

        LLMs know nothing nor are they intelligent. They also are not right or wrong, they generate output based on statistics.

        “Hallucination” as a term for “AIs” making things up is used since the early 2000s (even if it’s meaning has changed since then).