4 ms·
https://github.com/google-research/google-research/tree/master/scann https://github.com/google-research/google-research/tree/mast... We use ScaNN for a large s
by ramoz 4y ago
https://github.com/google-research/google-research/tree/master/scann https://github.com/google-research/google-research/tree/mast...
We use ScaNN for a large scale/performant neural search. Otherwise this all feels bloated.
- freediver 4y agoAnother upvote for ScaNN. Used on Teclis.com search engine in production (replaced previously used Faiss, which was excellent). ScaNN is almost double the performance and with same 5 lines of code to implement locally. At this point vector search is almost 'solved', the challenge remains the quality of vectors fed into the index. Producing accurate text/image/... vector representations (aka embeddings) is where lot more progress needs to be made.
- thirdtrigger 4y ago> At this point vector search is almost 'solved' Well, there is is still a lot to do. Going from memory to disk, etc. But I see your point. What might be a bit confusing is the mix of vector search libraries with vector search engines. It's a bit like comparing an inverted index library with SOLR :) But we (I.e., the wider vector search ecosystem) are working on this
- moab 4y agoThere are many "extra" features that one needs in practice which are patently not solved, starting with working in a dynamic setting.
- liminal 4y agoWhat sort of scale are you dealing with? ScaNN looks more like a vector index like FAISS, rather than a full database.