专注AIGC领域的专业社区，关注微软&OpenAI、百度文心一言、讯飞星火等大语言模型（LLM）的发展和应用落地，聚焦LLM的市场研究和AIGC开发者生态，欢迎关注！ 我们都知道，大模型肚子里只有训练时学到的那些知识，有一个“截止日期”。为了解决这个问题，RAG ...

检索增强生成（RAG）早已不是简单的向量相似度匹配加 LLM 生成这一套路。LongRAG、Self-RAG 和 GraphRAG 代表了当下工程化的技术进展，它们各可以解决不同的实际问题。 传统 RAG 的核心限制 标准的 RAG 流程大概是这样的：把文档分割成小块、向量化、通过余弦相似度 ...

Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform discipline. Enterprises that succeed with RAG rely on a layered architecture.

Much of the interest surrounding artificial intelligence (AI) is caught up with the battle of competing AI models on benchmark tests or new so-called multi-modal capabilities. But users of Gen AI's ...

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).

Vectara, an early pioneer in Retrieval Augmented Generation (RAG) technology, is raising a $25 million Series A funding round today as demand for its technologies continues to grow among enterprise ...

随着 Anthropic 开源 skills 仓库，"Code Interpreter"（代码解释器）模式成为 Agent 开发的热门方向。许多开发者试图采取激进路线：赋予 LLM 联网和 Python 执行权限，让其现场编写代码来解决一切问题。但在构建企业级“智能文档分析 Agent”的实践中，我们发现这种“全 ...

This free eBook that covers enhancing generative AI systems by integrating internal data with large language models using RAG is free to download until 12/3. Claim your complimentary copy of ...