Beyond Fine-Tuning: The Power of RAG
This article explores Retrieval-Augmented Generation as a flexible and cost-effective alternative to LLM fine-tuning, demonstrating how it leverages dynamic knowledge retrieval to enhance accuracy, explainability, and adaptability across various applications.