Indexing 10M vector embeddings in 1 minute on a single CPU | Leonardo Kuffo

Summary

This blog post introduces SuperKMeans, a super-fast clustering library that reduces indexing time for high-dimensional vector embeddings from hours to seconds. It demonstrates how SuperKMeans can index 10 million 1024-dimensional vector embeddings in just 1 minute on a single CPU, and explains the algorithm's extremely fast clustering performance compared to FAISS.

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