Learn to optimize and accelerate AI model training workloads using AWS's purpose-built infrastructure and tools in this comprehensive conference talk from AWS re:Invent 2025. Discover how to leverage Amazon SageMaker HyperPod for distributed training at scale and SageMaker fully managed training jobs for cost-effective machine learning acceleration. Explore advanced scaling techniques including data and model parallelism, automated model tuning, and efficient checkpoint management to maximize training performance across clusters. Examine real customer case studies demonstrating how to reduce training time by up to 40%, optimize costs, and build high-performance training pipelines for large AI models. Gain practical insights into overcoming the compute resource challenges and time-intensive nature of training large-scale AI models through AWS's specialized services and optimization strategies.