The Sequence Knowledge #473: Not All RAGs are Created Equal
Understanding the different types of RAG.
Today we will Discuss:
A taxonomy about the different types of RAG.
Google Research’s REALM method that uses RAG at pretraining time.
💡 ML Concept of the Day: The Different Types of RAG
Retrieval Augmented Generation (RAG) is a machine learning technique that enhances Large Language Models (LLMs) by allowing them to access and process external information sources. This integration enables the LLMs to generate more accurate and contextually relevant outputs than relying solely on pre-trained knowledge. The evolution of RAG has led to various types, each addressing specific challenges and leveraging unique advantages. Some of these variations include Standard RAG, Corrective RAG, Speculative RAG, Fusion RAG, Agnostic RAG, Self RAG, Graph RAG, Modular RAG, and RadioRAG. Understanding the nuances of these different RAG types is crucial for AI practitioners and researchers.