• howrar@lemmy.ca
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    2 months ago

    Why does everyone keep calling them Markov chains? They’re missing all the required properties, including the eponymous Markovian property. Wouldn’t it be more correct to call them stochastic processes?

    Edit: Correction, turns out the only difference between a stochastic process and a Markov process is the Markovian property. It’s literally defined as “stochastic process but Markovian”.

    • TheOubliette@lemmy.ml
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      2 months ago

      Because it’s close enough. Turn off beam and redefine your state space and the property holds.

      • howrar@lemmy.ca
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        2 months ago

        Why settle for good enough when you have a term that is both actually correct and more widely understood?

              • howrar@lemmy.ca
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                2 months ago

                That’s basically like saying that typical smartphones are square because it’s close enough to rectangle and rectangle is too vague of a term. The point of more specific terms is to narrow down the set of possibilities. If you use “square” to mean the set of rectangles, then you lose the ability to do that and now both words are equally vague.

                • TheOubliette@lemmy.ml
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                  2 months ago

                  Is this referring to what I said about Markov chains or stochastic processes? If it’s the former the only discriminating factor is beam and not all LLMs use that. If it’s the latter then I don’t know what you mean. Molecular dffusion is a classic stochastic process, I am 100% correct in my example.

                  • howrar@lemmy.ca
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                    2 months ago

                    It’s in reference to your complaint about the imprecision of “stochastic process”. I’m not disagreeing that molecular diffusion is a stochastic process. I’m saying that if you want to use “Markov process” to describe a non-Markovian stochastic process, then you no longer have the precision you’re looking for and now molecular diffusion also falls under your new definition of Markov process.