Right. Reinforcement learning trains them that question and answer sessions contain answers which statistically correlate with factual statements in their broa

Right. Reinforcement learning trains them that question and answer sessions contain answers which statistically correlate with factual statements in their broader learning corpus. When formulating answers, this leads them to formulate answers that reflect the factual information on which they were trained. My point is that the source data contains a far muddier range of information than just unarguable facts. We largely want LLM based Q&A bots to answer questions about fictional or mythical characters in their own terms. As I said, those questions above all have reasonably ‘correct’ answers. The fact that from all that LLMs do as well as they do is remarkable. But it also seems like it requires us to assume that LLMs are capable of a remarkable degree of cultural nuance, media literacy and contextual awareness for them to figure out the different authorship, salience, trustworthiness, agenda, biases, and assumptions of all the gigareams of text they’ve ingested.