Semantic search
Finding documents by comparing embeddings of the query and the documents, so matches can share meaning without sharing words.
Interview questions about Semantic search
- Your assistant's semantic search over user content is slow and expensive. How do you optimise it: embedding choice, ANN indexing and sharding?
Embeddings: shortlist models on public retrieval benchmarks, then pick on your own queries; smaller dimensions or int8 vectors cut memory and latency.