SageMaker AI: Accelerating Precision Medicine MLOps
Discover how Sonrai leverages Amazon SageMaker AI for MLOps, accelerating precision medicine trials with robust experiment tracking, secure data, and traceable model deployment.
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Boosting Generative AI: SageMaker’s 2025 Inference Upgrades
Explore Amazon SageMaker AI’s 2025 advancements: Flexible Training Plans for guaranteed GPU capacity, enhanced inference performance with EAGLE-3, and dynamic LoRA adapter management.
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Amazon SageMaker AI: 2025 Innovations for Enterprise Generative AI
SageMaker AI’s 2025 enhancements boost generative AI with granular observability, secure rolling updates, serverless customization, real-time bidirectional streaming, and PrivateLink/IPv6 connectivity.
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Nemotron 3 Nano 30B MoE: Open Generative AI on SageMaker JumpStart
NVIDIA Nemotron 3 Nano 30B MoE is now on SageMaker JumpStart. This open, efficient model excels in coding and reasoning with a hybrid architecture and 1M token context, simplifying generative AI deployment on AWS.
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Streamline SageMaker HyperPod Management with CLI & SDK
Simplify Amazon SageMaker HyperPod cluster management with the new CLI and SDK. Streamline distributed training, inference, and cluster lifecycle for AI/ML workloads.
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Enhance AI Model Evaluation with Amazon Nova on SageMaker
Discover Amazon Nova’s new features in SageMaker AI, including custom metrics, LLM-as-a-Judge, log probabilities, metadata passthrough, and multi-node scaling for robust model evaluation.
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Boost ML Productivity: SageMaker HyperPod with Interactive IDEs
Discover how Amazon SageMaker HyperPod now supports interactive IDEs like JupyterLab and VS Code via SageMaker Spaces. Optimize GPU usage, streamline ML workflows, and enhance developer productivity with managed, collaborative environments.
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Optimize SageMaker ML Training with AWS Batch for 2x Throughput
Learn how Amazon Search doubled ML training throughput and boosted GPU utilization to 80%+ by integrating AWS Batch with SageMaker for advanced job prioritization and resource management.
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Deploy No-Code ML Models with SageMaker Serverless Inference
Learn how to deploy Amazon SageMaker Canvas no-code ML models using SageMaker Serverless Inference. Automate scalable, cost-effective predictions without managing infrastructure.
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Enhanced AI Training: SageMaker HyperPod Operator on Kubernetes
Accelerate large-scale AI training on Kubernetes with Amazon SageMaker HyperPod training operator. Discover its fault resiliency, pinpoint recovery, and advanced monitoring for efficient, cost-effective model development across thousands of GPUs.
