"serving as an information gateway for students without constant reliance on the internet." But llms without knowledge augmentation are terrible at this! How can students know what they read is true?
What I have in mind is -
1. Topic specialized models which are frequently updated maybe every month or two.
2. Fact Checking & Moderation specialized, models which moderate or do fact checking on other model's output.
Kind of a chicken and egg problem. But I believe on the way we will be able to minimize the effects of hallucinations through output validation (both neural and rule based).
To avoid trolls and invisible downvotes, you can always use github issues. You are welcome there.
Thanks for the initial question. Ultimately it seems that there must always be a human in the loop somewhere.
While similar, I believe revisionist history is different than llm hallucination, but hard to say which is more dangerous. I guess it depends on the content. I suspect an llm won't jail you for questioning it, just happily hallucinate an apology and new answer :)