Originally aired September, 2022 as part of NVIDIA's GTC Conference.
The cloud computing revolution has helped democratize ML by making it easy to access compute. But as datasets grow exponentially, and training time grows with computationally heavy ML models, cloud computing alone is no longer effective as a singular infrastructure.
Hybrid AI/ML infrastructure offers an equilibrium, breaking down silos between environments to run data science workloads where they make the most sense based on use case, cost, performance, and regulation.
Learn how Domino, NetApp, and NVIDIA are providing AI Centers of Excellence with holistic solutions needed for enterprise-wide governance, cross-team collaboration, and operational efficiency, across data and ML models - on-prem and in the cloud.
Senior Manager, Product Architecture | NVIDIA
Michael Balint is a senior manager, product architecture at NVIDIA, focused on cluster management, orchestration, and scheduling of NVIDIA DGX servers. Previously, Michael was a White House Presidential Innovation Fellow, where he brought his technical expertise to projects like Vice President Biden's Cancer Moonshot and Code.gov.
Principal Product Manager - AI Solutions | NetApp
Mark Cates is the principal product manager of AI and analytic solutions at NetApp. Mark has previous experience at NetApp as a product manager for FlexPod and HCI solutions, focusing on hybrid cloud, Kubernetes, AI, and analytic solutions. Before that, Mark led software development for Windows and Unix at SAS Institute. Mark has been a speaker at other industry events, including NetApp Insight and Cisco Live. He has a B.S./M.S. in computer science and an M.B.A. from Duke University Fuqua School of Business.
Senior Partner Solution Architect | Domino
Josh Mineroff loves solving technical problems with usability in mind. As a senior partner solution architect at Domino Data Lab, he currently architects enterprise-scale data science stacks with cutting-edge AI solutions from the data and analytics ecosystem. Previously, he founded Meet n’ Treat, a dog socialization platform. During his Ph.D. in applied optimization, Josh published papers on heart valve design and uncertainty quantification, generating over 250 cumulative citations.
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