Category: Amazon SageMaker

Last week, what excited me most was the launch of the 2026 AWS AI & ML Scholars program by Swami Sivasubramanian, VP of AWS Agentic AI, to provide free AI education to up to 100,000 learners worldwide. The program has two phases: a Challenge phase where you’ll learn foundational generative AI skills, followed by a […]

Last week, my team met many developers at Developer Week in San Jose. My colleague, Vinicius Senger delivered a great keynote about renascent software—a new way of building and evolving applications where humans and AI collaborate as co-developers using Kiro. Other colleagues, Du’An Lightfoot, Elizabeth Fuentes, Laura Salinas, and Sandhya Subramani spoke about building and […]

AWS launches Amazon SageMaker Inference for custom Amazon Nova models. You can now configure the instance types, auto-scaling policies, and concurrency settings for custom Nova model deployments to best meet their needs.

Accelerate AI model development with new training features that enable rapid recovery from failures and automatic scaling based on resource availability.

Accelerate AI model development with new training features that enable instant recovery from failures and automatic scaling based on resource availability.

Simplify AI experimentation with zero-infrastructure MLflow that launches in minutes, scales automatically, and seamlessly integrates with SageMaker’s model customization and pipeline capabilities.

Access FSx for NetApp ONTAP file data through S3 to enable AI/ML workloads and analytics—letting you use enterprise file data with Bedrock, SageMaker, and analytics services while it remains in your file system.

New program gives organizations unprecedented access to Nova model training, enabling them to build custom frontier models that deeply embed domain expertise without the traditional barriers of cost, compute, and time.