You're right to notice the changes in Amazon SageMaker, as AWS has indeed been evolving its offerings in the data and AI space. Let me clarify the relationship between SageMaker AI and SageMaker Unified Studio to help you understand the direction. Amazon SageMaker Unified Studio is actually the next generation of Amazon SageMaker, representing a more comprehensive and integrated approach to data, analytics, and AI development. It's designed to bring together various AWS tools and services into a single, collaborative environment. SageMaker Unified Studio is built on top of the existing SageMaker capabilities and integrates functionality from multiple AWS services, including Amazon EMR, AWS Glue, Amazon Athena, Amazon Redshift, Amazon Bedrock, and Amazon SageMaker AI. This means that SageMaker AI is now a part of the broader SageMaker Unified Studio ecosystem. The key difference is in the scope and integration: 1. SageMaker AI focuses specifically on machine learning and AI capabilities. 2. SageMaker Unified Studio is a more comprehensive platform that includes SageMaker AI, but also incorporates data processing, SQL analytics, and generative AI application development tools. Regarding domains, in the context of SageMaker Unified Studio, a domain is the organizing entity that connects assets, users, and their projects. It's managed through the SageMaker AI management console, where domain administrators can configure user management, account associations, project profiles, blueprints, Amazon Bedrock models, Git connections, and Amazon Q usage. The concept of domains in SageMaker Unified Studio is more expansive and central to the organization of resources and collaboration across teams. It's designed to provide a unified experience for data scientists, analysts, and developers working on various aspects of data and AI projects. In essence, SageMaker Unified Studio represents AWS's vision for a more integrated, collaborative, and comprehensive data and AI development environment, with SageMaker AI being a crucial component within this larger ecosystem. This new approach aims to streamline workflows, improve collaboration, and provide a single environment for a wide range of data and AI tasks. **Sources** The next generation of Amazon SageMaker: The center for all your data, analytics, and AI | AWS Big Data Blog A single data and AI development environment - Amazon SageMaker Unified Studio - AWS Announcing the preview of Amazon SageMaker Unified Studio - AWS Amazon SageMaker Unified Studio terminology and concepts - Amazon SageMaker Unified Studio