AI-Ready Infrastructure for Deep Learning Deployment at Scale

Era of AI is here. Enterprises face an extraordinary opportunity to innovate and lead. However, real-world AI initiatives are often stalled by scale-out infrastructure complexities. In this webinar we’ll explore new approaches that extend the power of NVIDIA DGX systems, enabling AI-at-scale in the enterprise, delivering time-to-insight in hours rather than weeks.
Wednesday, May 9, 2018
9:00am – 10:00am PT
1 Hour
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Presented By
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Tony Paikeday
Director of Product Marketing, AI, and Deep Learning, NVIDIA

Tony Paikeday is the Director of Product Marketing for the NVIDIA DGX Family. Tony was previously with VMware, managing product marketing for the Horizon 7 portfolio and focused on key enabling technologies, including GPU virtualization and software-defined data center. Prior to joining VMware, Tony was at Cisco, building its data center solutions marketing practice focused on desktop and application virtualization. Prior to Cisco, he spent 12 years at Nortel selling into enterprise and service provider accounts, after having started his career as a Manufacturing Engineer for Ford Motor Company. Tony holds an engineering degree from the University of Toronto.
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Roy Kim
AI & Analytics Lead, Director Product Marketing, Pure Storage

Roy Kim joined Pure in 2017 as Director of Product Marketing for FlashBlade. Previously, Roy led product marketing at NVIDIA for deep learning, HPC, and enterprise analytics industries. Roy has Masters of Computer Science and Electrical Engineering and Bachelors of Science in Electrical Engineering from Massachusetts Institute of Technology.
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Nick Ciarleglio
Distinguished Systems Engineer, Arista

Nick Ciarleglio is a Distinguished Systems Engineer at Arista Networks. Nick arrived at Arista Networks in 2008 as the company’s first Systems Engineer. In his current role Nick is responsible for network design and integration with Arista’s key partners and is focused on storage, AI, and real time media applications. Nick also provides field feedback and "real world" expertise to the Arista development teams, enabling tighter integrations and innovations for key applications and workloads.
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