rag-ann-preferred-over-knn

Summary

When a system needs to find the most similar items in a large pool of high-dimensional vectors (like text embeddings), it uses a fast approximate method instead of checking every single candidate. This matters because exact searching becomes too slow and expensive as the collection grows, so the system accepts a tiny loss in match precision in exchange for responses that are practical in real time.