Your question is Fine-Tuning vs RAG. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are building a language model application that must answer questions using information that changes over time. Some teams want to adapt the model with training data, while others want to connect it to an external knowledge base at query time.
What is the difference between fine-tuning and retrieval-augmented generation (RAG)?