NetApp had a strong presence at SAP SAPPHIRE NOW with an impressive booth, multiple speaking sessions and customer events, and innovative demos. One of the coolest demos was an NVIDIA inference demo where artificial intelligence (AI) learned how to imitate art.

An NVIDIA® DGX StationTM and their Real-Time Artistic Style Transfer demo were live in the NetApp booth at SAP SAPPHIRE, instantly applying a particular style of art to the live video feed in the booth.

Deep learning (DL) is an aspect of AI that is concerned with emulating the learning approach that humans use to gain certain types of knowledge. Because deep learning models process information in ways similar to the human brain, models can be applied to many tasks that people do.

AI can optimize existing solutions, and machine learning is already integrated into many SAP products. As AI becomes a core business capability, virtually all organizations will rely on insights generated from the large datasets they're generating. AI requires massive compute power and an infrastructure architecture that can keep pace. Disciplines like DL demand extreme performance to feed the graphic processing units (GPUs) that power data-hungry algorithms.

NetApp has partnered with NVIDIA to introduce a rack-scale architecture that enables organizations to start small and grow the infrastructure seamlessly as the number of projects and dataset sizes increase. Adopting these AI solutions empowers businesses to meet even the most demanding performance requirements, ushering in a new era of intelligent applications.

For more information about NetApp® solutions for AI and DL, read the Scalable Infrastructure for AI white paper based on the NVIDIA DGX-1 and the new NetApp AFF A800, the industry's first end-to-end NVMe unified all-flash system. Also, view theCube interview with NVIDIA in the NetApp booth. To learn more about NetApp and SAP, visit www.netapp.com/sap.

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NetApp Inc. published this content on 19 June 2018 and is solely responsible for the information contained herein. Distributed by Public, unedited and unaltered, on 19 June 2018 18:02:14 UTC