An LLM is not inherently non-deterministic though - if you don't randomly sample and instead have a fixed rule (which is what the recent fingerprint embedding approach does), if applied in all cases the output is deterministic, as the neural net at its core is deterministic function. A lot of the randomness beyond that is due to optimizations [source].
LLMs are however unreliable at 'compiling'. Whether or not it will be able to complete the requested task (translate human language into code) correctly it not guaranteed - at least nowhere near the compilers we use.
An LLM is not inherently non-deterministic though - if you don't randomly sample and instead have a fixed rule (which is what the recent fingerprint embedding approach does), if applied in all cases the output is deterministic, as the neural net at its core is deterministic function. A lot of the randomness beyond that is due to optimizations [source].
LLMs are however unreliable at 'compiling'. Whether or not it will be able to complete the requested task (translate human language into code) correctly it not guaranteed - at least nowhere near the compilers we use.