Figure 8.5 Three ways to give a model knowledge. RAG, in accent, pulls fresh or
private facts from an external store into the window at question time, leaving
the bulk behind; long context places a whole bounded corpus inside one large
window for close reading; fine-tuning adjusts the model itself, changing how it
behaves and formats rather than what it can look up. RAG is the lowest-risk
place to start, which is why it leads.
