Vector similarity search makes massive datasets searchable in fractions of a second. Yet despite the brilliance and utility of this technology, often what seem to be the most straightforward problems are the most difficult to solve. Such as filtering.
Filtering takes the top place in being seemingly simple — but actually incredibly complex. Applying fast-but-accurate filters when performing a vector search (ie, nearest-neighbor search) on massive datasets is a surprisingly stubborn problem.
This is a companion discussion topic for the original entry at https://www.pinecone.io/learn/vector-search-filtering/