Today, tens of thousands of customers are building, training, and deploying machine learning (ML) models using Amazon SageMaker to power applications that have the potential to reinvent their businesses and customer experiences. These ML models have been increasing in size and complexity over the last few years, which has led to state-of-the-art accuracies across a range of tasks and also pushing the time to train from days to weeks. As a result, customers must scale their models across hundreds to thousands of accelerators, which makes them more expensive to train.
SageMaker is a fully managed ML service that helps developers and data scientists easily build, train, and deploy ML models. SageMaker already provides the broadest and deepest choice of compute offerings featuring hardware accelerators for ML training, including G5 (Nvidia A10G) instances and P4d (Nvidia A100) instances.
Growing compute requirements calls for faster and more cost-effective processing power. To further

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