Introducing new Ray capabilities on SageMaker HyperPod | Amazon Web Services
Today, we are announcing new Ray capabilities on Amazon SageMaker HyperPod that integrate Ray with the HyperPod purpose-built infrastructure for…
Tag: SageMaker
Track SageMaker Unified Studio project costs with custom tags and AWS CUR | Amazon Web Services
Organizations running machine learning (ML), analytics, and generative AI workloads on Amazon SageMaker Unified Studio domains and projects face a…
NVIDIA Nemotron 3.5 Lightning now available in Amazon SageMaker JumpStart | Amazon Web Services
By Amazon Web Services Publication Date: 2026-08-17 18:06:00 NVIDIA Nemotron 3.5 Lightning is designed for the fast, specialized model execution…
Tiered KV cache for large LLMs on Amazon SageMaker HyperPod with Curvine | Amazon Web Services
Running large language model (LLM) inference at scale typically forces a KV cache trade-off: you either pay for oversized GPU…
End-to-end encrypted ML inference with Amazon SageMaker AI and FHE | Amazon Web Services
Machine learning (ML) inference often requires processing sensitive data—medical records, proprietary business information, or personal communications. What if you could…
NVIDIA Nemotron 3 Ultra now available on Amazon SageMaker JumpStart | Amazon Web Services
Today, we are excited to announce the day-zero availability of NVIDIA Nemotron 3 Ultra on Amazon SageMaker JumpStart. With this…
Fundamental’s Large Tabular Model NEXUS is now available on Amazon SageMaker JumpStart | Amazon Web Services
Today, we’re announcing support for Fundamental’s NEXUS model on Amazon SageMaker AI. With this launch, you can deploy a foundation…
Improve your agent’s tool-calling accuracy with SFT and DPO on Amazon SageMaker AI | Amazon Web Services
AI agents can autonomously handle complex, multi-step tasks, but their effectiveness depends on calling the right tools to retrieve information…
Comprehensive observability for Amazon SageMaker AI LLM inference: From GPU utilization to LLM quality | Amazon Web Services
Deploying large language models (LLMs) at scale on Amazon SageMaker AI Inference makes observability a critical pillar of any production…
Streamline external access to Amazon SageMaker MLflow using a REST API proxy | Amazon Web Services
Machine learning (ML) teams use MLflow to manage their ML lifecycle effectively. Amazon SageMaker MLflow provides comprehensive ML experiment tracking…