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How do RAG systems understand what you're searching for? The answer is embeddings. In this video, I explain embeddings with a simple analogy and show you how to choose the right embedding model. š What You'll Learn: - What embeddings are (GPS analogy) - How semantic similarity works - Why keyword search fails and embeddings succeed - 4 factors for choosing embedding models: benchmark, dimensions, max tokens, cost š Models Mentioned: - text-embedding-3-large (high accuracy) - text-embedding-3-small (best value for production) - MTEB leaderboard for benchmarks š RAG Series: - Video 1: What is RAG - Video 2: RAG System with 89% Accuracy - Video 3: Chunking Strategy - Video 4: Embeddings Explained (this video) #Embeddings #RAG #MachineLearning #MLInterview #AIEngineer #VectorSearch #LLM #NLP