RAG or Fine-Tune? You're Asking the Wrong Question

Most people treat RAG vs Fine-Tuning as a binary choice. It isn't — the real question is where new knowledge lives.

In this video:
→ How RAG works: query → embed → vector DB → retrieve → inject → answer
→ How Fine-Tuning works: training pairs → gradient descent → baked-in weights
→ Full comparison: freshness, scale, latency, style control, hallucination risk, setup cost
→ The often-missed insight: fine-tuning teaches behavior, not facts

RAG for factual grounding. Fine-tuning for behavioral alignment. Best systems use both.

Видео RAG or Fine-Tune? You're Asking the Wrong Question канала Neural AI Flair