When it comes to less popular knowledge, how should we train AI? Should we fine-tune it or let it retrieve information on the fly? In this episode, we break down a groundbreaking study that compares these two approaches—Fine-Tuning (FT) vs. Retrieval-Augmented Generation (RAG)—to see which one better equips AI models for niche factual knowledge. We also explore a novel approach called Stimulus RAG, which boosts retrieval accuracy without expensive fine-tuning. Tune in to find out which method wins and what it means for AI customization!