What is Embedding?
An embedding is a list of numbers that represents the meaning of a piece of text, image, or other data, so that similar things end up close together in that numeric space. Embeddings are what let a vector database find content by meaning rather than by exact words.
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Why it matters
Embeddings turn fuzzy human meaning into something a computer can compare quickly. They power semantic search, recommendations, and the retrieval step in RAG.
In practice
A model converts each chunk of your data into an embedding once, and stores it. Queries are embedded the same way, and similarity is measured by how close two embeddings sit. The choice of embedding model sets the ceiling on search quality.