FlyVector

An embedding compressor and search index built on the locality-sensitive hashing scheme described for the fly's olfactory circuit, where a small dense input is expanded into a large sparse binary code. The published benchmark compresses 10,000 vectors of 1,536 dimensions from 58.59 MB to 2.44 MB, 256 bytes each, and reports a median search latency of 815 microseconds against 3.20 milliseconds for a dense baseline on one core. It runs in memory with numpy alone and no database. The core is open source, with a separately sold professional edition.

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#locality-sensitive-hashing#embeddings#compression#vector-search#benchmark