Yep. But the idea that a RAG backed LLM is merely an efficient summarizer is missing the real power, which is it can summarize then be interrogated iteratively

Yep. But the idea that a RAG backed LLM is merely an efficient summarizer is missing the real power, which is it can summarize then be interrogated iteratively to refine in a semantic sense the actual questions you have, or explore adjacent spaces. It’s not just a search engine that can summarize, it’s a search engine that you can interrogate in natural language and it responds directly to your questions, as opposed to throwing a bunch of documents at you that have a probability of being related to your query.