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Apr 2018 - IDC Survey Spotlight - Doc # US43731818

What Is the Preferred Deployment Location for AI/ML/DL Workloads?

By: Ritu JyotiProgram Vice President, Systems Infrastructure Research Portfolio

Abstract

This IDC Survey Spotlight provides analysis of the deployment location/computing model used for AI/ML/DL workloads. Specifically, this Survey Spotlight highlights the broad use of public cloud and expected increase of private cloud and edge location for specific phases and use cases.

"Today, public cloud leads the deployment location for run of AI/ML/DL workloads due to the scale of compute and storage resources available, as well as easy access to AI services, but with the need for organizations to hold on to their IP and insights adoption, private cloud adoption is expected to increase for the training phase of most of the AI deployments," said Ritu Jyoti, research director, for IDC's Enterprise Storage, Server, and Infrastructure software team at IDC. "This will lead a broad reconfiguration of the on-premises infrastructure supporting AI workloads."


Coverage

Content
  • 2 slides


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