Enterprises are looking to transform themselves with AI and machine learning by implementing new hybrid and multi-cloud MLOps capabilities to scale model-driven outcomes across their businesses — across regions, clouds, and on-premises infrastructure. Already today 45% of organizations train models in hybrid cloud environments, and that number is expected to rise rapidly as enterprises look to leverage hybrid- and multi-cloud to comply with data sovereignty laws, reduce cost and future-proof their infrastructure investments. Join us for "Unleashing Hybrid and Multi-Cloud Data Science at Scale" as we discuss the drivers and best practices for implementing hybrid cloud and multi-cloud platforms for AI/ML-driven business outcomes with industry-leading voices.
Nick Patience is a Research Director with responsibility for the Data, AI & Analytics Channel at 451 Research, a part of S&P Global Market Intelligence. Nick is also 451’s lead analyst for AI and machine learning and a co-founder of the company. He works across the entire research team to uncover and understand use cases for machine learning, an area he has been researching since 2001. Nick also oversees 451's Workforce Productivity & Collaboration research and is a member of 451 Research's Center of Excellence for Quantum Technologies. Nick has a long background in research into how applications can take advantage of data – in particular unstructured data – using AI and machine learning. He is a cofounder of 451 Research and rejoined the team in 2015 after almost three years running product marketing at machine learning-driven eDiscovery software company Recommind (now part of OpenText). He has held various senior management roles at 451 Research in both in New York and London since 1999.
Vikash is the Global Head of Cloud Program Office, leading hybrid and multi cloud strategy, engineering, adoption, and FinOps for Johnson & Johnson. He collaborates across Johnson & Johnson's technology organization to optimize cloud and infrastructure spend, improve developer productivity, drive innovation, and enable optimal utilization of public and private cloud computing environments for diverse technology groups building AI/ML, IoT, data analytics, and health tech applications. Vikash is leading a global team focused on engineering excellence, cloud security, and infrastructure reliability through an agile product development approach. The team drives reliable infrastructure automation at scale for enterprise data centers, edge locations (labs, warehouses, manufacturing sites, and distributions), and public clouds (AWS, Azure, and GCP). His team has developed best-in class infrastructure management to meet FDA (GxP) compliance.
Manuvir Das is Head of Enterprise Computing at NVIDIA, reporting to CEO Jensen Huang. He’s responsible for NVIDIA’s overall enterprise strategy, as well as product lines such as DGX and EGX. Manuvir was previously senior vice president and general manager of Unstructured Storage at Dell EMC, where he was responsible for the Isilon and ECS product lines. Manuvir has extensive experience leading R&D organizations, including key roles in developing Microsoft Azure and Dell EMC ViPR Controller, ECS, and Nautilus.