We are seeing a convergence of analytics and AI, with customers using data in increasingly interconnected ways. The next generation of SageMaker brings together capabilities to give customers all the tools they need for data processing, machine learning model development and training, and generative AI, directly within SageMaker.
Using SageMaker Unified Studio, customers can publish and share data, models, apps, and other artifacts with members of their team or broader org. The service exposes data security controls and adjustable permissions, as well as integrations with AWS' Bedrock model development platform.
Q Developer can support development tasks such as data discovery, coding, SQL generation, and data integration in SageMaker Unified Studio, allowing users to efficiently utilize AI tools.
AWS also introduced two additional tools to the SageMaker family: SageMaker Catalog and SageMaker Lakehouse, further enhancing the data management and processing capabilities for users.
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