I was starting to think this was impressive, if not impossible. 1B vectors in 48 MB of storage => < 1 bit per vector.
Maybe not impossible using shared/lossy storage if they were sparsely scattered over a large space ?
But anyways - minutes. Thanks.
Edit: Gemini suggested that this sort of (lossy) storage size could be achieved using "Product Quantization" (sub vectors, clustering, cluster indices), giving an example of 256 dimensional vectors being stored at an average of 6 bits per vector, with ANN being one application that might use this.
I was starting to think this was impressive, if not impossible. 1B vectors in 48 MB of storage => < 1 bit per vector.
Maybe not impossible using shared/lossy storage if they were sparsely scattered over a large space ?
But anyways - minutes. Thanks.
Edit: Gemini suggested that this sort of (lossy) storage size could be achieved using "Product Quantization" (sub vectors, clustering, cluster indices), giving an example of 256 dimensional vectors being stored at an average of 6 bits per vector, with ANN being one application that might use this.
Yeah, the SI symbol for minutes is min, if you're going to abbreviate it in a technical context. Super funky using M.
Agree the correct abbreviation is min.
Nitpick: could be wrong but I don’t think minutes is an SI derived unit.
Thank you, title needs edited.
Legend
Thankfully not months.
Oh the horrors of search indexing Ive seen... including weeks / months to rebuild an index.