Category: Amazon SageMaker

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.

Next week, don’t miss AWS re:Invent, Dec. 1-5, 2025, for the latest AWS news, expert insights, and global cloud community connections! Our News Blog team is finalizing posts to introduce the most exciting launches from our service teams. If you’re joining us in person in Las Vegas, review the agenda, session catalog, and attendee guides […]

Let me start this week’s update with something I’m especially excited about – the upcoming BeSA (Become a Solutions Architect) cohort. BeSA is a free mentoring program that I host along with a few other AWS employees on a volunteer basis to help people excel in their cloud careers. Last week, the instructors’ lineup was […]

AWS continues to expand access to the most advanced foundation models with OpenAI open weight models now available in Amazon Bedrock and Amazon SageMaker JumpStart. Accessing these new models from OpenAI on AWS, gpt-oss-120b and gpt-oss-20b, gives you more freedom to innovate and choose the right model for your specific use cases while maintaining complete control over your infrastructure and data.

AWS AI league is a program that helps organizations upskill their workforce by combining fun competition with hands-on learning using AWS AI services. It offers a unique opportunity for both enterprises and developers to gain valuable and practical skills in fine-tuning, model customization, and prompt engineering – essential skills for building generative AI solutions.

AWS now enables extensive customization of Amazon Nova foundation models through SageMaker AI with techniques including continued pre-training, supervised fine-tuning, direct preference optimization, reinforcement learning from human feedback and model distillation to better address domain-specific requirements across industries.