Category: Amazon SageMaker

Today, I am happy to announce that you can now use Amazon SageMaker Ground Truth to generate labeled synthetic image data. Building machine learning (ML) models is an iterative process that, at a high level, starts with data collection and preparation, followed by model training and model deployment. And especially the first step, collecting large, […]

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! Last Week’s Launches It’s been a quiet week on the AWS News Blog, however a glance at What’s New page shows the various service teams have been busy as usual. […]

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! Last Week’s Launches I made a short trip to Austin, Texas last week in order to visit and learn from some customers. As is always the case, the days when […]

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 […]