Well thats not always why they give an incorrect prediction. It’s also because statistics are inherently never going to reflect reality perfectly (“all models are wrong, some are useful”), but also we intentionally inject randomness into LLMs and other ML programs to ensure the output isn’t over fitting and spitting out raw training data. Usually adjustable via seed values, temperature, etc