Category: Amazon SageMaker AI

A couple of editions ago I wrote about what I find so energizing about working with startups. Last week I got a fresh dose of it: I spent a few days with the AWS Startups team, listening to stories of founders talking about the problems they’re actually solving. One story that stayed with me came […]

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.

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.

Amazon Prime Day 2025 achieved record-breaking sales with enhanced AI shopping features, while AWS infrastructure handled unprecedented volumes of data—including 1.7 trillion Lambda invocations per day, DynamoDB peaking at 151 million requests per second, and a 77% increase in Fargate container tasks—showcasing the massive scalability required to power the four-day shopping event.

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 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.