• Warl0k3@lemmy.world
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    5 hours ago

    (Minor side point because you’re using it colloquially and that’s fine: LLMs absolutely are deterministic systems. We aren’t even sure if a non-deterministic system is possible to construct.)

    • Car@lemmy.dbzer0.com
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      4 hours ago

      Functionally non-deterministic if we compare the same input with outputs over a short enough period.

      Deterministic if you have infinite time to run the gamut of model weights against temperature/creativity/programmed randomness, but even then maybe not if floating point math is taken into account. I don’t know where the current thought is on extreme precision being deterministic or not given cloud environments, local operating and environmental factors, variance in manufacturing, and the like.

      • vala@lemmy.dbzer0.com
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        1 hour ago

        Nah. LLMs use a random seed to noise the parameters.

        Same input + same seed = same output every time. (Kinda like Minecraft)

        LLM providers just always use a random seed for stuff like this.

        • floquant@lemmy.dbzer0.com
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          1 hour ago

          Repeatability is still not easy to guarantee. A version upgrade in a library might yield a slightly different result from the same seed

      • Warl0k3@lemmy.world
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        4 hours ago

        Functionally non-deterministic

        (Well literally no, but I’m only pointing that out for the cheap math pun (and to share a good summary article on this subject))

        But I do understand what you’re saying - and for anyone not concerned with the mathematics just about any complex system a user does not control is, in that limited context, indistinguishable a black box and is effectively non-deterministic. But outside of that context no - just because a seed value is (I suppose theoretically) random does not make the system itself non-deterministic. It’s a semantic argument though, and most people really don’t need to care about the distinction.