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Faiss: A library for efficient similarity search

engineering.fb.com · 2,683 words · saved by 3 readers

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By Hervé Jegou , Matthijs Douze , Jeff Johnson This month, we released Facebook AI Similarity Search (Faiss), a library that allows us to quickly search for multimedia documents that are similar to each other — a challenge where traditional query search engines fall short. We’ve built nearest-neighbor search implementations for billion-scale data sets that are some 8.5x faster than the previous reported state-of-the-art, along with the fastest k-selection algorithm on the GPU known in the literature. This lets us break some records, including the first k-nearest-neighbor graph constructe

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