Vector Database எப்படி Work ஆகுது? | RAG & Vector DB Explained

Ever wondered how Vector Databases actually work behind the scenes? In this video, I break down the core concepts of Vector Databases in a simple and practical way — from converting data into vectors to storing, indexing, and retrieving the most relevant information. You’ll understand how Vector Databases power modern RAG applications, semantic search, AI chatbots, and LLM-based applications. 🔥 In this video: What is a Vector Database? Why do we need Vector Databases? How text becomes vectors Embeddings & similarity search How vector storage works How similarity search retrieves relevant data Vector Databases in RAG Real-world AI use cases 🔥 Don't just watch - try the workflow yourself! If you're a creator, marketer, entrepreneur, or AI enthusiast, this AI video creation workflow can save you a lot of time and effort. To learn Gen AI, AI Agents, Agentic AI, AI Automation and Microsaas Building, Join GEN AI Architect Community Now: https://becomeaneagle.edgeone.app/?fo... Machine Learning Book: https://topmate.io/thirumurugan_r/191... Instagram: https://www.instagram.com/ai_with_thi... LinkedIn:   / thirumurugan-r-85a41b24a   If you want to learn ML, DL, NLP, Gen AI, AI Agents, and Agentic AI in Tamil, subscribe now. vector database, how vector database works, vector database explained, vector db, vector databases explained, embeddings, vector embeddings, similarity search, semantic search, RAG, retrieval augmented generation, RAG explained, LLM, GenAI, generative AI, AI database, AI search, vector search, AI chatbot, Pinecone, ChromaDB, FAISS, Weaviate, Milvus, LangChain, AI agents, agentic AI #VectorDatabase #VectorDB #RAG #GenerativeAI #GenAI #LLM #Embeddings #SemanticSearch #AI #AIAgents #AgenticAI #MachineLearning #AIwithThiru