Amazon Web Services (AWS) announced five new capabilities within Amazon SageMaker to accelerate the building, training, and deployment of large language models and other foundation models. The new capabilities aim to manage model development, usage, and performance more efficiently. They include a feature that speeds up model training time and another that reduces deployment costs and latency of models. AWS also introduced a new SageMaker Clarify capability that simplifies model selection based on quality parameters that support responsible use of AI. Additionally, a new no-code capability in SageMaker Canvas was introduced to facilitate data preparation using natural-language instructions. SageMaker Canvas also makes it easier for customers to use models to extract insights, make predictions, and generate content using an organization’s proprietary data. These advancements aim to help customers innovate with machine learning at scale.