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 LLM ...

Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More More companies are looking to include retrieval augmented generation (RAG ...

As many developers have come to realize, “Just use Postgres” is generally a good strategy. If and when your needs grow, you might want to swap in a larger and more performant vector database. Until ...

Building retrieval-augmented generation (RAG) systems for AI agents often involves using multiple layers and technologies for structured data, vectors and graph information. In recent months it has ...

RAG is a pragmatic and effective approach to using large language models in the enterprise. Learn how it works, why we need it, and how to implement it with OpenAI and LangChain. Typically, the use of ...

TOKYO--(BUSINESS WIRE)--In an ongoing effort to improve the usability of AI vector database searches within retrieval-augmented generation (RAG) systems by optimizing the use of solid-state drives ...

BERLIN & NEW YORK--(BUSINESS WIRE)--Qdrant, the leading high-performance open-source vector database, today announced the launch of BM42, a pure vector-based hybrid search approach that delivers more ...

AI solves everything. Well, it might do one day, but for now, claims being lambasted around in this direction may be a little overblown in places, with some of the discussion perhaps only (sometimes ...