Embeddings in LLM & RAG Explained in Hindi | What are Embeddings? | RAG Series #2

Embeddings are one of the most important concepts behind RAG (Retrieval-Augmented Generation) and semantic search. In this video, we’ll understand what embeddings are, why we need them, and how they are used in RAG — explained in simple Hindi with practical examples. 📌 What you’ll learn: What are Embeddings? How text is converted into vectors What does embedding dimension mean? How embeddings capture semantic meaning Keyword Search vs Semantic Search What is Vector Similarity? How embeddings are used in RAG How a Vector Database / PGVector helps retrieve relevant information