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Sometimes! Not for the GPU part, but to make the summary data for the ML data.

For example, genome sequencing data and intermediate results are easily in the TB area of space, but the resulting table of genomic variants (k-mers like n-grams in NLP) is only a few hundred GB.



I'm confused from your post where the petabytes of storage come in.


I'm guessing that there are just many data sets, and each one is in the TBs of size.




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