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Discover how to transform your AI model development lifecycle using Amazon SageMaker AI's unified environment in this AWS re:Invent 2025 conference session. Explore the comprehensive capabilities of SageMaker Studio as an integrated development environment for developing, submitting, and monitoring machine learning jobs while harnessing the scalability and resiliency of the HyperPod environment for computationally intensive tasks. Learn to leverage SageMaker's unified platform for all AI workloads, from interactive model development in familiar IDEs to maximizing task and compute resource utilization across training and inference operations. Understand how to effectively train and deploy large foundation models using HyperPod's robust infrastructure, and master the task governance capabilities that automatically allocate compute resources based on task prioritization throughout the entire model development lifecycle, ensuring optimal resource management and workflow efficiency.
