How Meta Searches Billions of Vectors Instantly

Standard nearest-neighbor searches quickly destroy your RAM and speed. Enter Faiss. It's Meta's library for blazing-fast similarity search. With native Python wrappers, Faiss uses compressed representations to search billions of vectors on a single server, even if they don't fit in memory. Plus, you get drop-in GPU acceleration. It gives you granular control over speed, accuracy, and memory when building massive AI apps.