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· 6 min read
Richard Blythman

The field of deep learning requires heavy amounts of storage. Machine learning datasets often reach into the 100s of GBs, and pre-trained model weights can be large too. Many datasets (like JFT-300M by Google) remain inaccessible to data scientists outside large organizations. Furthermore, open datasets can be scattered across many apps and websites, and require the user to follow a lengthy tutorial for download, setup and processing.