Determinism isn’t important, but there are usually threshold of acceptable performance in all off those cases. Machine Learning was all about improving accuracy even when you know that there’s probably an error somewhere. But the current LLM hypers refuses to acknowledge that the answer to a prompt may be wrong (even though the providers have a warning line about it).

Instead of assessing the risk and provide corrective methods, all they do is pushing to use it more and more everywhere.