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Re:“Math 2.0” will need to value mathematical progress more ... by red75prime on Thursday October 08, 2026 @04:19AM (#50003175)
> The core technology of an LLM is sampling from a distribution so there is literally no way to make it deterministically robust (only probabilistically).

An LLM mostly deterministically (except parallel processing nondeterminism that can be mitigated) produces a probability distribution that can be sampled deterministically: just take the highest probability token or use beam search.

Re:“Math 2.0” will need to value mathematical progress more ... by gottheUIblues on Thursday October 08, 2026 @04:49AM (#50003396)
I think people on here tend to somewhat fixate on the determinism issue. Even with a deterministic LLM - stabilising the floating point arithmetic, and choosing from the distribution by a fixed method, or just save the random seeds - there is still a kind of a chaotic unpredictability that can exist between its inputs and outputs. However maybe that is a price that needs to be paid to get creativity.
Re:“Math 2.0” will need to value mathematical progress more ... by Vetch on Thursday October 08, 2026 @04:43AM (#50003359)
Deterministic yes, robust deterministic no. The most likely conjunction is not always the best nor representative of what the model is considering unless its certainty is high.
Re:“Math 2.0” will need to value mathematical progress more ... by red75prime on Thursday October 08, 2026 @06:29AM (#50004089)
I think determinism has nothing to do with it. If you mean sensitivity to word ordering and such, it's a generalization failure.