What is RAG in AI? Explained in Everyday Language for AI Beginners

Updates: AI for Absolute Beginners is an ongoing series that now covers:

• RAG
• Embedding
• Vector Database
• Fine-tuning
• Knowledge graph
• Chain-of-Thought Prompting
• Langchain
• Diffusion Model

If you’ve been following the recent AI hype, you must have heard “RAG” quite a bit. RAG stands for Retrieval-Augmented Generation, a critical step in enhancing the power of AI chatbots. However, this term isn’t as popular as phrases like ‘prompt engineering’, probably because abbreviations are generally less intuitive to understand and remember :) So in this article, let’s demystify the fascinating AI concept of Retrieval-Augmented Generation, or RAG.

What is RAG? At its core, RAG is a method used in AI to enhance the way machines understand and generate information (https://ai.meta.com/blog/retrieval-augmented-generation-streamlining-the-creation-of-intelligent-natural-language-processing-models/) While Large Language Models are good at summarizing and forming sentences like natural language, RAG gives its extended capabilities to provide additional information.