Faiss
Efficient similarity search library.
PublicW2017Artificial IntelligenceVector SearchC++ LibraryOpen Sourcegithub.com/facebookresearch/faiss
Launched by Meta's AI research labs, Faiss (Facebook AI Similarity Search) is the underlying engine that powers many commercial vector databases. It contains highly-optimized mathematical indexing algorithms that run directly on local GPU architectures, matching high-dimensional textual or visual embedding arrays in sub-millisecond timelines.
Active Founders
MD
Matthijs Douze
Lead Researcher
Matthijs coordinates Faiss's core open-source optimization matrices, crafting lightning-fast nearest-neighbor search logic layers used universally by AI engineers.
Faiss
Founded2017
BatchW2017
Team Size50
StatusPublic
LocationMenlo Park, CA, USA
CategoryArtificial Intelligence