Description
转自 https://www.youtube.com/watch?v=fZM3oX4xEyg
本视频是RAG（检索增强生成）系列教程的入门介绍，由AI工程师Krishna主讲。视频深入浅出地讲解了RAG的核心概念：通过在推理时从外部知识库检索相关信息，弥补大语言模型（LLM）训练数据过时、领域知识不足的缺陷。课程还涵盖了RAG的使用场景、关键开发pipeline要点，并预告了后续将通过Jupyter Notebook进行完整的实践实现。目前RAG已是AI工程领域最热门的技术方向之一，60-70%的企业AI项目都涉及RAG应用开发。
This is the introductory video of a comprehensive RAG (Retrieval-Augmented Generation) tutorial series by AI engineer Krishna. It explains what RAG is — the process of optimizing LLM outputs by referencing an authoritative external knowledge base at inference time, rather than relying solely on training data. The video covers the limitations of standalone LLMs, how RAG overcomes them, when to use RAG, and key pipeline considerations for building RAG applications. Hands-on implementations using Jupyter Notebook are planned for upcoming episodes. RAG is now one of the most in-demand skills in AI engineering, with 60-70% of enterprise AI projects involving RAG-based development.
原版视频：https://www.youtube.com/watch?v=fZM3oX4xEyg