RAG systems have evolved from Naive RAG to Advanced RAG and ultimately Modular RAG, addressing challenges such as low precision and generation quality. Advanced RAG introduces techniques like Chunk Optimization, Query Rewriting, and Adaptive Retrieval. Modular RAG allows components to be configured, improving adaptability and efficiency.
Table of contents
Progression of Retrieval Augmented Generation (RAG) SystemsNaive RAGChallenges in Naive RAGAdvanced RAGAdvanced RAG Concepts– Pre-retrieval/Retrieval Stage– Post Retrieval StageModular RAGSome RAG ModulesIn ConclusionRetrieval Augmented Generation – A Simple IntroductionGenerative AI with Large Language Models (Coursera Course Notes)Don't miss a post!Getting the Most from LLMs: Building a Knowledge Brain for Retrieval Augmented GenerationRAG Value Chain: Retrieval Strategies in Information Augmentation for Large Language ModelsGradient Descent and the Melody of Optimization AlgorithmsContext is Key: The Significance of RAG in Language ModelsSort: