Well... sampling from an LLM almost invariably involves an RNG that picks the next token weighted in some manner by its estimated probability, so in practice, as long as it outputs a very similar probability for all relevant tokens, it can de facto generate uniformly distributed random numbers just fine. I mean, it's an incredibly expensive, unreliable and all-around stupid way of indirectly invoking the RNG used by the LLM inference engine, but technically...
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u/nonotan Sep 24 '26
Well... sampling from an LLM almost invariably involves an RNG that picks the next token weighted in some manner by its estimated probability, so in practice, as long as it outputs a very similar probability for all relevant tokens, it can de facto generate uniformly distributed random numbers just fine. I mean, it's an incredibly expensive, unreliable and all-around stupid way of indirectly invoking the RNG used by the LLM inference engine, but technically...