CIO Roundtable: Enterprise Strategies for Maximizing Platform Flexibility for SAP Modernization in Hybrid Infrastructure Environments (Oct. 20th)
DDN News

Deep learning and AI applications that rely on large amounts of unstructured data, like autonomous vehicle development and natural language processing, face unique challenges. NVIDIA DGX SuperPOD with DDN A3I storage can boost productivity by 20% while lowering costs compared to existing IT infrastructure or cloud-based deployments.

The interest in deep learning and AI as a way to tap into massive amounts of unstructured data continues unabated. While some companies were built with deep learning and AI at the center of their value, like autonomous vehicle companies and some financial organizations, many institutions are still working out how to capture and extract all the value that exists in their collection of unstructured data - and strategizing on how to collect and analyze new source data. This means that for each company poised to revolutionize markets because they were founded around machine learning and AI, there are hundreds of companies that are still assessing the potential value in their data and haven't begun to understand the AI infrastructure choices that need to be made.

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