Posted by Yahoo! Finance on August 1, 2018:

NetApp (NTAP), the data authority for the hybrid cloud, today introduced NetApp® ONTAP® AI proven architecture, powered by NVIDIA DGX™ supercomputers and NetApp AFF A800 cloud-connected all-flash storage to simplify, accelerate, and scale the data pipeline across edge, core and cloud for deep learning deployments and to help customers achieve real business impact with AI.

Although many organizations are adopting new AI platforms, tools, and practices, most don't have enough control over their distributed data stores to ensure that complete, current, and accessible data is available for their AI projects. Success with AI depends on a business's approach to data. To be effective in today's AI use cases and future-proof a business for new AI applications, organizations must achieve visibility into and control of their data, from edge to core to cloud.

"Companies of all sizes and across various industries are making significant inroads in using AI to solve real-life problems, especially in the enterprise. However, while very exciting, AI models and workloads are not easy to deploy, and many organizations are struggling," said Ritu Jyoti, program vice president, IDC. "The NetApp ONTAP AI proven architecture is a powerful solution that will help users accelerate AI-driven business outcomes and overcome deployment obstacles."

"Developing disruptive AI technology and turning this into breakthrough products and services for our customers is a vital requirement across many markets we work in," said Monty Barlow, head of artificial intelligence, Cambridge Consultants.

"Customers deploying AI and deep learning are looking for ways to reduce their time to outcomes. A highly available and powerful deep learning environment ensures that data scientists stay productive," said Bob Olwig, vice president of Corporate Business Development, WWT. "ONTAP AI is a proven architecture from NetApp and NVIDIA that complements WWT's broad portfolio of solutions and services for deep learning, giving customers an AI stack that can be implemented quickly with higher efficiency and lower risk."

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