In this informative session, Raghu Ramesha, a senior machine learning architect at Amazon, delves into the powerful capabilities of Amazon SageMaker for high-performance, cost-effective machine learning inference. He explains why customers choose SageMaker over DIY solutions, highlighting its managed infrastructure, automatic scaling, and deployment strategies. Raghu explores various deployment options including real-time, serverless, asynchronous, and batch inference, each tailored for different use cases. The presentation also covers cost optimization techniques such as multi-model endpoints, instance right-sizing, and SageMaker Savings Plans. Viewers will gain insights into best practices for maximizing performance while minimizing costs in machine learning deployments using Amazon SageMaker.