Category: Amazon SageMaker

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS! I’ve just come back from a long (extended) holiday weekend here in the US and I’m still catching up on all the AWS launches that happened this past week. I’m […]

In December 2021, we introduced Amazon SageMaker Serverless Inference (in preview) as a new option in Amazon SageMaker to deploy machine learning (ML) models for inference without having to configure or manage the underlying infrastructure. Today, I’m happy to announce that Amazon SageMaker Serverless Inference is now generally available (GA). Different ML inference use cases […]

Our mission at AWS is to make machine learning (ML) more accessible. Through many conversations over the past years, I learned about barriers that many ML beginners face. Existing ML environments are often too complex for beginners, or too limited to support modern ML experimentation. Beginners want to quickly start learning and not worry about […]

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 […]

Today, we’re pleased to announce Amazon SageMaker Training Compiler, a new Amazon SageMaker capability that can accelerate the training of deep learning (DL) models by up to 50%. As DL models grow in complexity, so too does the time it can take to optimize and train them. For example, it can take 25,000 GPU-hours to […]

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 […]

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 […]

As an organization facing business problems and dealing with data on a daily basis, the ability to build systems that can predict business outcomes becomes very important. This ability lets you solve problems and move faster by automating slow processes and embedding intelligence in your IT systems. But how do you make sure that all […]