6/12/2026, 12:00:00 AM ~ 6/15/2026, 12:00:00 AM (UTC)

Recent Announcements

SageMaker AI now supports serverless fine-tuning for Nvidia Nemotron models

Amazon SageMaker AI now supports serverless model customization for Nvidia Nemotron 3 Nano model using supervised fine-tuning (SFT) and reinforcement fine-tuning (RFT). This is a popular open-weight model from Nvidia with 30B total parameters. In addition to deploying this model on SageMaker AI, you can now adapt it to your specific domains and workflows.\n Model customization enables you to tailor these foundation models with your proprietary data, whether that’s improving accuracy on domain-specific tasks, aligning outputs with your organization’s tone, or enhancing performance on new tasks using your labeled data. With serverless customization, SageMaker AI handles all infrastructure provisioning and training orchestration, so you can focus on your data and evaluation rather than cluster management, and only pay for what you use. Serverless model customization for Nvidia Nemotron 3 Nano on SageMaker AI is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland). To get started, navigate to the Models page in Amazon SageMaker Studio to launch a customization job, or use the SageMaker Python SDK for programmatic access. To learn more, see the Amazon SageMaker AI model customization documentation.

Amazon EC2 I7i instances now available in AWS Europe (Paris) Region

AWS is announcing the availability of high performance Storage optimized Amazon EC2 I7i instances in AWS Europe (Paris) region. Powered by 5th Gen Intel Xeon Processors with an all-core turbo frequency of 3.2 GHz, these new instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i instances.\n I7i instances offer compute and storage performance for x86-based storage optimized instances in Amazon EC2 ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access the small to medium size datasets. Additionally, torn write prevention feature support up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks. I7i instances are available in eleven sizes - nine virtual sizes up to 48xlarge and two bare metal sizes - delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth. To learn more, visit the I7i instances page.

Amazon EC2 Capacity Blocks for ML is now available in AWS GovCloud (US) Regions

Amazon EC2 Capacity Blocks for ML is now available in AWS GovCloud (US-West) and AWS GovCloud (US-East), enabling government and regulated-industry customers to reserve GPU capacity for machine learning workloads.\n EC2 Capacity Blocks for ML allows you to reserve GPU instances in advance for a defined duration, giving you assured access to accelerated compute for short-duration pre-training, fine-tuning, rapid prototyping, and inference demand surges. Capacity Blocks deliver low-latency, high-throughput connectivity through colocation in Amazon EC2 UltraClusters.

You can reserve capacity up to eight weeks in advance for durations up to 6 months, in cluster sizes of one to 64 instances. Capacity Blocks can also be shared across multiple accounts using AWS Resource Access Manager (RAM), helping organizations coordinate ML infrastructure investments and keep reserved capacity in continuous use across workloads.

In AWS GovCloud (US), EC2 Capacity Blocks for ML is available on P6-B200 instances in AWS GovCloud (US-West), and P6-B200 and P6-B300 instances in AWS GovCloud (US-East). To get started, visit the EC2 Capacity Blocks documentation.

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