To my surprise almost if not all LLM are set not to be deterministic and have one unique input result in always the same output.
They all are set to have a “temperature” setting so that they sound more natural.
Personally I think quality of the output tokens of LLM is surprisingly not as much their priority as the quality and truthfulness of the result.
I would 100% prefer a LLM that is purely deterministic and repeats the same answer exactly to the same question. Instead LLM are constantly choosing the next likely token more TL appear human rather than being accurate.
These LLM are designed as sycophants and set up and trained as such.
So a fingerprinting in the output seems quite realistic. An LLM is not giving you it’s best most likely answer. It’s taking one of the most likely answer and adds a sprinkle of uncertainty and randomness on top of it so it looks natural…
Wouldn’t that potentially affect output quality particularly in code/tool calls?
To my surprise almost if not all LLM are set not to be deterministic and have one unique input result in always the same output.
They all are set to have a “temperature” setting so that they sound more natural.
Personally I think quality of the output tokens of LLM is surprisingly not as much their priority as the quality and truthfulness of the result.
I would 100% prefer a LLM that is purely deterministic and repeats the same answer exactly to the same question. Instead LLM are constantly choosing the next likely token more TL appear human rather than being accurate.
These LLM are designed as sycophants and set up and trained as such.
So a fingerprinting in the output seems quite realistic. An LLM is not giving you it’s best most likely answer. It’s taking one of the most likely answer and adds a sprinkle of uncertainty and randomness on top of it so it looks natural…