基于向量的 RAG 优化的是语义相似度（semantic similarity）：比如"不允许退货的政策"和"允许退货的政策"这两个查询会产生几乎相同的 embedding。模型理解的不是逻辑而是向量空间中的邻近关系。

OpenAI 联合创始人、特斯拉 AI 总监、百万粉丝的 AI 教育博主，发了一条推文，结果炸了！ 1500 万浏览。 9 万收藏。 不是代码。 是一套用 AI 管理知识的方法论。 而且他说了一句让很多人愣住的话—— "我现在 90% 的 token 都花在构建个人知识库上，而不是写代码。

AI search has outgrown simple RAG. Learn how today’s hidden AI retrieval systems decide whether your content gets surfaced or ...

A new study from Google researchers introduces "sufficient context," a novel perspective for understanding and improving retrieval augmented generation (RAG) systems in large language models (LLMs).

RAG can make your AI analytics way smarter — but only if your data’s clean, your prompts sharp and your setup solid. The arrival of generative AI-enhanced business intelligence (GenBI) for enterprise ...

The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via ...

Local LLMs degrade fast when context fills up. An embedding model and RAG pipeline fixes that — and runs entirely on your ...