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Accelerate ML workflows with Amazon SageMaker Studio Local Mode and Docker support

We are excited to announce two new capabilities in Amazon SageMaker Studio that will accelerate iterative development for machine learning (ML) practitioners: Local Mode and Docker support. ML model development often involves slow iteration cycles as developers switch between coding, training, and deployment. Each step requires waiting for remote compute resources to start up, which …

Deployable architecture on IBM Cloud: Simplifying system deployment

Deployable architecture (DA) refers to a specific design pattern or approach that allows an application or system to be easily deployed and managed across various environments. A deployable architecture involves components, modules and dependencies in a way that allows for seamless deployment and makes it easy for developers and operations teams to quickly deploy new …

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Integrate HyperPod clusters with Active Directory for seamless multi-user login

Amazon SageMaker HyperPod is purpose-built to accelerate foundation model (FM) training, removing the undifferentiated heavy lifting involved in managing and optimizing a large training compute cluster. With SageMaker HyperPod, you can train FMs for weeks and months without disruption. Typically, HyperPod clusters are used by multiple users: machine learning (ML) researchers, software engineers, data scientists, …

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Climate Tech Startups Integrate NVIDIA AI for Sustainability Applications

Whether they’re monitoring miniscule insects or delivering insights from satellites in space, NVIDIA-accelerated startups are making every day Earth Day. Sustainable Futures, an initiative within the NVIDIA Inception program for cutting-edge startups, is supporting 750+ companies globally focused on agriculture, carbon capture, clean energy, climate and weather, environmental analysis, green computing, sustainable infrastructure and waste …