Leverage the best of Ray and Google Kubernetes Engine (GKE) to build your next-generation machine learning (ML) platform. Google and Anyscale are making Ray and Kubernetes the distributing operating system for AI/ML. Discover how on GKE, Ray enables you to deliver a unified platform to scale your workloads from development to large-scale production. Learn about GKE’s latest advancements for fast data access, intelligent scheduling, and optimized utilization of hardware accelerators, and how Ray and Anyscale RayTurbo are enhancing that with best-in-class performance, efficiency, and developer productivity. Leave this session equipped to build a scalable AI/ML platform to empower your researchers and engineers.

Modernizing high-performance and AI workloads that need to stay on-premises can be challenging. Learn from the experts how to optimize your hybrid cloud by deploying Google Kubernetes Engine (GKE) on Google Distributed Cloud. Deliver a consistent developer experience on-premise and in the cloud, and preserve your return on investments by leveraging your existing HW investments. Discover how to optimize upgrade cycles, streamline operations, and empower your developers with the same cloud-born tools they use with GKE.

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