From Experimentation to Insights: Building an End-to-End Deep Learning System - Seguridad Mania.com - España y América Latina

Every organization wants to infuse the power of AI in its business. From development to production training, you need an end-to-end AI workflow that’s optimized for the rigors of deep learning, that offers predictable performance as your neural network models and datasets grow. Attend this session to get insights into use cases, best practices and architecture examples that can help you and your data science team get started now, accelerating your path from experimentation to business insights. About the Speakers: Tony Paikeday is the Director of Product Marketing for the NVIDIA Deep Learning Systems, responsible for the world's first portfolio of AI supercomputers for enterprise - NVIDIA DGX Systems. 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 held business development roles at Nortel working with 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. 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.