RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each
Helps builders make informed architectural decisions about when to use RAG vs fine-tuning for domain-specific LLM applications.
AI Summary
This article explains the fundamental differences between RAG (Retrieval-Augmented Generation) and for LLM applications, clarifying that they solve different problems rather than competing against each other. It provides practical guidance on when to use each technique based on specific use cases and application requirements. The author draws from extensive experience with RAG implementations and offers clear technical explanations.
Excerpt
Two techniques, two different problems, and why the question is not really "which one wins" The post RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each appeared first on Towards Data Science.