Also, if you’d ask it “Why did large SMP systems become mainstream?", it would (presumably) spit out a plausible-sounding explanation for that. The models seem to take the prompt as a premise, and then go from there. Maybe that’s also why when you point out a mistake, they oblige and provide a correction.

I haven’t tried: If you point out something they said as a mistake when in fact it was correct, do they notice and object? Maybe if the evidence from the training data is strong enough.