RAG Explained: Why AI Needs Retrieval-Augmented Generation to Avoid Hallucinations

In a new Telugu-language explainer, the channel CodePulse breaks down why modern AI systems rely on Retrieval-Augmented Generation (RAG) to stay accurate. The video tackles a core problem: AI hallucinations — when models generate plausible but incorrect information. RAG solves this by fetching real-time, relevant data from external sources before generating a response, ensuring answers are both current and grounded. This technique is vital for developers and AI enthusiasts building reliable applications.