Retrieval Augmented Generation (RAG) › RAG vs Fine-Tuning

What is RAG vs Fine-Tuning

Beginner

Answer

RAG and fine tuning are two different approaches to giving an AI model access to specific knowledge, where RAG retrieves external information at answer time and fine tuning bakes new knowledge directly into the model's weights.

Real-world example A company chooses RAG over fine tuning so it can update its chatbot's knowledge simply by updating documents, without retraining the entire model.

Common follow-ups: What is Retrieval Augmented Generation (RAG), How is RAG vs Fine-Tuning evaluated in practice, What tools are commonly used for RAG vs Fine-Tuning

Retrieval Augmented Generation (RAG) topics: Introduction to Retrieval Augmented Generation Vector Databases for RAG Embedding Models for Retrieval