AI workloads require handling large datasets that can rapidly scale to petabyte installations spanning on-premise and cloud environments. Performance requirements vary significantly from traditional enterprise workloads, posing challenges in data capacity and maintenance.
Customers are increasingly utilizing multiple cloud platforms alongside on-premise data centers for AI development. Storage solutions must integrate APIs, support data wrangling, and meet performance demands for AI workflows across hybrid cloud environments.
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