A naukri.com initiative
VentureBeat
3w
83
Image Credit: VentureBeat
AWS SageMaker is transforming into a combined data and AI hub
- Today at its annual huge conference re:Invent 2024, Amazon Web Services (AWS) announced the next generation of its cloud-based machine learning (ML) development platform SageMaker.
- AWS transformed it into a unified hub that allows enterprises to bring together data assets-spanning across different data lakes and sources in lakehouse architecture-interconnected with AWS ecosystem analytics and formerly disparate ML tools.
- The platform's integrated development environment, SageMaker Studio, gives teams a single, web-based visual interface to perform all machine learning development steps, right from data preparation, model building, training, tuning, and deployment.
- The company upgraded SageMaker with two key capabilities: Amazon SageMaker Lakehouse and Unified Studio.
- Lakehouse offering provides unified access to all the data stored in the data lakes built on top of Amazon Simple Storage Service (S3), Redshift data warehouses and other federated data sources, making it easily queryable regardless of where the information is originally stored.
- SageMaker Unified Studio acts as a unified environment that strings together all existing AI and analytics capabilities from Amazon's standalone studios, query editors, and visual tools.
- Users can even pull up Amazon Q Developer assistant and ask it to handle tasks like data integration, discovery, coding or SQL generation — in the same environment.
- SageMaker Lakehouse is compatible with Apache Iceberg, meaning it will also work with familiar AI and ML tools and query engines.
- The new SageMaker is available for AWS customers starting today.
- Companies like Roche and Natwast Group will be among the first users of the new capabilities.
Read Full Article
5 Likes
For uninterrupted reading, download the app