> In general I've seen them split between 30% brilliance, and 70% pants of head outrageously stupid shit for electronics and automotive stuff

I assume the corpus of text they were trained on matches that 30/70 split?

I assume there's some selection or fine-tuning that happens to improve models fed similarly unreliable training data for other domains... curious how this works.