Vector databases and similarity search

After this lesson you can: Store embeddings and retrieve the nearest ones to a query.

First: Chunking documents

Watch

• What is a Vector Database? Powering Semantic Search & AI Applications - IBM Technology, 10 min. Concise industry overview likely useful for semantic search context, though language is unconfirmed.
• Vector Database Explained | What is Vector Database? - codebasics, 7 min. Short English concept explainer from a beginner-friendly coding channel, well matched to demystifying vector databases.

Notes

A vector database stores vectors, usually embeddings produced from text chunks, images, or other data. Each vector is just a list of numbers that represents meaning in a way a model can compare. When a user asks a question, you embed the question with the same embedding model, then search for stored vectors that are closest to the query vector.

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