Deep Learning Places New Demands on Data Center Architectures

Machine and deep learning applications bring new workflows and challenges to enterprise data center architectures. One of the key challenges revolves around data and the storage solutions needed to store, manage, and deliver up to AI's demands. Today's intelligent applications require infrastructure that is very different from traditional analytics workloads, and an organization's data architecture decisions will have a big impact on the success of its AI projects. These are among the key takeaways from a new white paper by the research firm Moor Insights & Strategy. "While discussions of machine learning and deep learning naturally gravitate towards compute, it's clear that these solutions force new ways of thinking about data," the firm notes in its "Enterprise Machine & Deep Learning with Intelligent Storage" paper.