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@sun @SuperDicq considering floating point is cooked math i'm not sure you even can deterministically train an ANN. even with the same seeds, FPUs are gooners that do math stupid at the best of times. you'd have to do fixed point arithmetic for that to work reliably.

tsetlin machines *could* be this. they use stochatic updates as a way to simulate heterogenous signal paths (which is important; it stops pattern recognizers from oscillating as a group and getting stuck on nothing), but you can make that deterministic with the right RNG, but also

is the argument that like, the source code for a human is every book they've ever read in the order they read it in?

@icedquinn@blob.cat @sun@shitposter.world I never said LLMs had to be fully reproducible and deterministic.

Even though that is technically possible but just hard to achieve through sheer complexity. A computer is still a computer and true randomness does not exist so everything a computer outputs is always reproducible with the same input.

What is missing with local LLMs still is the freedom to use it for any purpose and the freedom to change it to make it do what you wish.