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 ...

本文会带你从零搭建一个完整的概念验证项目（POC），技术栈涵盖 Adaptive RAG、LangGraph、FastAPI 和 Streamlit 四个核心组件。Adaptive RAG 负责根据查询复杂度自动调整检索策略；LangGraph 把多步 LLM 推理组织成有状态的可靠工作流；FastAPI 作为高性能后端暴露整条 AI 管道 ...

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 ...

Retrieval-Augmented Generation (RAG) is rapidly emerging as a robust framework for organizations seeking to harness the full power of generative AI with their business data. As enterprises seek to ...

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.

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 ...