RAG vs Fine-Tuning: Which One Actually Makes AI Smarter?

Retrieval-Augmented Generation (RAG) and Fine-Tuning are two of the most important techniques used to inject knowledge into large language models. But they solve the problem in very different ways. In this video, we break down RAG vs Fine-Tuning and explain when each approach is more efficient. Instead of retraining a model, RAG retrieves relevant documents at inference time, allowing AI systems to use up-to-date information. Fine-tuning, on the other hand, modifies the model’s weights to permanently embed knowledge and change how the model behaves. If you're learning about LLM architecture, AI systems engineering, or building production AI applications, understanding the difference between RAG and fine-tuning is essential. #RAG #FineTuning #LargeLanguageModels #Transformers #AIEngineering #MachineLearning #DeepLearning #RetrievalAugmentedGeneration