分析
This article introduces RAG (Retrieval-Augmented Generation) as a solution to limitations of LLMs like ChatGPT, such as inability to answer questions based on internal documents, providing incorrect answers, and lacking up-to-date information. It aims to explain the inner workings of RAG in three steps without delving into implementation details or mathematical formulas, targeting readers who want to understand the concept and be able to explain it to others.
要点
引用
“"RAG (Retrieval-Augmented Generation) is a representative mechanism for solving these problems."”