Announcing Amazon SageMaker Inference Recommender

Today, we’re pleased to announce Amazon SageMaker Inference Recommender — a brand-new Amazon SageMaker Studio capability that automates load testing and optimizes model performance across machine learning (ML) instances. Ultimately, it reduces the time it takes to get ML models from development to production and optimizes the costs associated with their operation. Until now, no […]

New – Create and Manage EMR Clusters and Spark Jobs with Amazon SageMaker Studio

Today, we’re very excited to offer three new enhancements to our Amazon SageMaker Studio service. As of now, users of SageMaker Studio can create, terminate, manage, discover, and connect to Amazon EMR clusters running within a single AWS account and in shared accounts across an organization—all directly from SageMaker Studio. Furthermore, SageMaker Studio Notebook users […]

Announcing Amazon SageMaker Ground Truth Plus

Today, we’re pleased to announce the latest service in the Amazon SageMaker suite that will make labeling datasets easier than ever before. Ground Truth Plus is a turn-key service that uses an expert workforce to deliver high-quality training datasets fast, and reduces costs by up to 40 percent. The Challenges of Machine Learning Model Creation […]

New – Securely manage your AWS IoT Greengrass edge devices using AWS Systems Manager

In 2020, we launched AWS IoT Greengrass 2.0, an open-source edge runtime and cloud service for building, deploying, and managing device software and applications. Today, we’re very excited to announce the ability to securely manage your AWS IoT Greengrass edge devices using AWS Systems Manager (SSM). Managing vast fleets of varying systems and applications remotely […]