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Vector similarity search can require huge amounts of memory. Indexes containing 1M dense vectors (a small dataset in today’s world) will often require several GBs of memory to store. When building recommendation systems or semantic search engines, this is not acceptable. The problem of excessive memory usage is exasperated by high-dimensional ...
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