检索增强生成（Retrieval-Augmented Generation，简称 RAG）是一种旨在提升大型语言模型（Large Language Models，LLMs）性能的技术方法。其核心思想是通过整合外部可靠知识库的信息来增强模型的输出质量。 RAG 的工作原理可以概括如下：当 LLM 接收到查询时，它不仅依赖于 ...

Through natural language queries and graph-based RAG, TigerGraph CoPilot addresses the complex challenges of data analysis and the serious shortcomings of LLMs for business applications. Data has the ...

Progress’ semantic and graph RAG approach—featuring MarkLogic Server 12—delivers 33% higher LLM accuracy and faster discovery for customers Unlike other solutions, MarkLogic Server 12 enables scalable ...

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...

Daniel D. Gutierrez, Editor-in-Chief & Resident Data Scientist, insideAI News, is a practicing data scientist who’s been working with data long before the field came in vogue. He is especially excited ...