| > Like if you have a friend who's very well-read and talkative but is also extremely confident and loves the sound of their own voice. You quickly learn to treat them as a source of probably-correct information, but only part of they way you learn any given topic. I can't speak to everyone's experience - but whenever I'm having a conversation around relatively complex topics with MY friends - the deeper they dive, the more they're constantly referring back to their dive computer. They'll also try to make arguments that are principally anchored to the pegs that they're convinced will hold. I'm aware I'm mixing metaphors here but the point stands. As far as "mixing information" - yes there are commonly known tricks to trying to get a more accurate answer: - Query several LLMs - Query the same LLM multiple times with different context histories - Socratically force it to re-assess itself - Provide RAG / documents / access to search engines - Force quantitative tests in the form of virtualized envs though this is more for Compsci/Tech/Math etc. LLMs don't currently have a good sense of their boundaries - they can't provide realistic confidence scores and weight their outputs accordingly - the human equivalent of saying, "I only have a passing familiarity with the original greek of the Septuagint, but I think...." It's a poor use of an LLM as a glorified fact checker - it's far better as a tool for free form exploration. > Being good at mixing together information from a variety of sources - of different levels of accuracy - is key to learning anything well. I have a pretty extensive background in teaching/education and I would heavily disagree with this assertion - at least when starting as a complete novice. The key to learning well is to establish a strong foundation by learning from the most accurate resources as possible. When you pick up a musical instrument, you don't want a teacher who's just one page ahead of you in the lesson book. |