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In this Easy English lesson, we explain embeddings: how AI turns text into vectors so apps can compare meaning, not just words. You will learn cosine similarity, vector databases, and RAG with simple examples and clear vocabulary. Chapters: 00:00 Why this matters 01:00 What is an embedding? 03:00 Cosine similarity 05:00 From words to sentences 06:00 Vector databases and ANN 08:00 RAG: Retrieval‑Augmented Generation 10:00 Quality tips and vocabulary Sources and further reading: • Mikolov et al., 2013 — Efficient Estimation of Word Representations in Vector Space (arXiv) • Sentence‑BERT: Sentence Embeddings using Siamese BERT‑Networks (arXiv) • Stanford CS224U — Vector Semantics • Hugging Face — Semantic Search and Embeddings Guide • FAISS — Facebook AI Similarity Search AI disclosure: This video uses AI-generated narration and graphics.