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Cost-optimizing AIML workloads on AWS

Many organizations are adopting AI/ML either as a core component or as a supporting workload to achieve high application performance, create delightful user experiences, build sustained competitive advantage, and manage costs effectively. In this session, learn about various ways to cost-optimize your AI/ML workloads. We will delve into ML cost management, highlighting innovative approaches, instance optimizations, lifecycle configurations, and the integration of Amazon SageMaker with Amazon EC2 Spot Instances and Managed Spot Training for Amazon SageMaker and other services. Additionally, we will explore how you can leverage the latest features of Amazon SageMaker to reduce expenses while maximizing the value of your ML workloads. Download slide »

Speaker: Yudho Ahmad Diponegoro, Senior Solutions Architect, AWS