| ▲ | nazgul17 9 hours ago | |||||||
That's not an interesting difference, from my point of view. The box m black box we all use is non deterministic, period. Doesn't matter where on the inside the system stops being deterministic: if I hit the black box twice, I get two different replies. And that doesn't even matter, which you also said. The more important property is that, unlike compilers, type checkers, linters, verifiers and tests, the output is unreliable. It comes with no guarantees. One could be pedantic and argue that bugs affect all of the above. Or that cosmic rays make everything unreliable. Or that people are non deterministic. All true, but the rate of failure, measured in orders of magnitude, is vastly different. | ||||||||
| ▲ | nowittyusername 9 hours ago | parent [-] | |||||||
My man did you even check my video, did you even try the app. This is not "bug related" nowhere did i say it was a bug. Batch processing is a FEATURE that is intentionally turned on in the inference engine for large scale providers. That does not mean it has to be on. If they turn off batch processing al llm api calls will be 100% deterministic but it will cost them more money to provide the services as now you are stuck with providing 1 api call per GPU. "if I hit the black box twice, I get two different replies" what you are saying here is 100% verifiably wrong. Just because someone chose to turn on a feature in the inference engine to save money does not mean llms are anon deterministic. LLM's are stateless. their weights are froze, you never "run" an LLM, you can only sample it. just like a hologram. and depending on the inference sampling settings you use is what determines the outcome..... | ||||||||
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