点击上方“Deephub Imba”,关注公众号,好文章不错过 !检索找到了某个语义上接近的片段，LLM 围绕它写出一段文字，但是没人发现答案是错的。这是 vector RAG 调参解决不了的失败问题。而现在有2种方法可以解决他：GraphRAG 增加了一层 knowledge graph，用来描绘实体之间的关系。Vectorless RAG 完全抛弃向量数据库，让 ...

If you’re building generative AI applications, you need to control the data used to generate answers to user queries. Simply dropping ChatGPT into your platform isn’t going to work, especially if ...

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 ...

VCs are hungry to back vector database startups and other behind-the-scenes tech that improves AI. Vector databases store and structure data that LLMs can then pull from. Business Insider has ...

Intelligence is proliferating. As the hurly-burly surrounding development of generative AI (gen-AI) with its use of open Large Language Model (LLM) technologies designed to create ever more human-like ...

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...

Writing code that interacts with LLM services requires bridging two different worlds. Use these tips and techniques to bind ...

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