AI and Data Centers
The discussion highlights the distinction between model training and inference in the context of cloud data centers. While model training can be curtailed during certain periods due to its batch process nature, inference demands high availability akin to traditional cloud applications. The economic implications of running these data centers are significant, suggesting that while some flexibility exists, the overall infrastructure must maintain high utilization to remain viable.In this clip
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Catalyst with Shayle Kann
Under the hood of data center power demand
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