AWS News Blog
Category: Amazon SageMaker AI
AWS AI League: Learn, innovate, and compete in our new ultimate AI showdown
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.
Announcing Amazon Nova customization in Amazon SageMaker AI
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.
DeepSeek-R1 models now available on AWS
DeepSeek-R1, a powerful large language model featuring reinforcement learning and chain-of-thought capabilities, is now available for deployment via Amazon Bedrock and Amazon SageMaker AI, enabling users to build and scale their generative AI applications with minimal infrastructure investment to meet diverse business needs.
Accelerate foundation model training and fine-tuning with new Amazon SageMaker HyperPod recipes
Amazon SageMaker HyperPod recipes help customers get started with training and fine-tuning popular publicly available foundation models, like Llama 3.1 405B, in just minutes with state-of-the-art performance.
Meet your training timelines and budgets with new Amazon SageMaker HyperPod flexible training plans
Unlock efficient large model training with SageMaker HyperPod flexible training plans – find optimal compute resources and complete training within timelines and budgets.
Maximize accelerator utilization for model development with new Amazon SageMaker HyperPod task governance
Enable priority-based resource allocation, fair-share utilization, and automated task preemption for optimal compute utilization across teams.
Amazon SageMaker HyperPod introduces Amazon EKS support
Amazon SageMaker HyperPod’s integration with Amazon EKS brings resilience, observability, and flexibility to large model training, reducing downtime by up to 40%.
Introducing Amazon Q Developer in SageMaker Studio to streamline ML workflows
Streamline your ML workflows with this generative AI assistant providing tailored guidance, code generation, and error troubleshooting, to build, train, and deploy models efficiently.