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How does AI find accurate answers in real-time? Traditional AI models struggle with outdated information and hallucinations, but Retrieval-Augmented Generation (RAG) solves this problem! In this video, we break down how RAG works, why vector embeddings are crucial, and how AI retrieves, structures, and generates fact-based responses. 📌 What You’ll Learn: ✅ Why AI models fail without RAG (outdated knowledge, hallucinations) ✅ How RAG retrieves, refines & generates more accurate responses ✅ The role of vector embeddings & vector databases (Weaviate, FAISS, Pinecone) ✅ How structured prompts prevent AI from making things up ✅ Real-world applications—Union Budget 2025, financial AI, and more! 🔔 Subscribe for AI Deep Dives! Next up: How Embeddings Work in AI – The Core of RAG & Search! #RAG #ArtificialIntelligence #AIExplained #MachineLearning #VectorDatabase #Embeddings #OpenAI #ChatGPT #Weaviate #Pinecone #LLMs #AIModels #AIResearch #TechExplained