AI engineering glossary · RAG vector search
What is vector quantisation?
Vector quantisation: Lossy compression of vectors by mapping each to an approximation from a limited set of representatives. In vector search it reduces memory and speeds up comparisons, at some cost in accuracy.
Vector quantisation: an example
Compressing 100 million vectors with quantisation lets the index fit in RAM on one server.
Related terms
More RAG vector search terms
- Abstention
- Access control in retrieval
- Agentic RAG
- Alpha weighting
- ANN recall
- Answer correctness
- Answer relevance
- Approximate nearest neighbour search
Where you learn it
Vector quantisation is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.