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Embeddings and vector databases are the foundation of modern AI systems. They power: - semantic search - RAG systems - recommendations - clustering - AI retrieval pipelines The core idea is simple: Text → Embedding Vector → Similarity Search Instead of matching exact keywords, embeddings allow systems to search by meaning. In this video, we break down how embeddings and vector databases actually work.