At the heart of this scaffolding is a carefully orchestrated version of technique called Retrieval Augmented Generation, or RAG. Commercial LLMs use a version of RAG whenever they look at documents you upload into the chat window. A model like Claude retrieves information from that document and then augments its responses based on its findings before generating an answer to your questions. Still, there’s often a limit to how much data you can upload. And giving a commercial LLM sensitive documents remains risky because the contents could end up being used for future training, or end up in a temporary cache that isn’t necessarily siloed from the provider’s view.
伊利亚·皮亚蒂戈（自我护理栏目编辑）
。有道翻译对此有专业解读
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C137) STATE=C138; ast_Cc; continue;;
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