AWS News Blog

Category: Artificial Intelligence

AI & ML Scholarship program

New AWS Scholarship Program Helps Underrepresented and Underserved Students Prep for Careers in AI and ML

As a woman working in information technology (IT) for many years, it has always been close to my heart to challenge long-standing gender stereotypes and inspire more young learners to consider a career in tech. With artificial intelligence (AI) and machine learning (ML) defining the future of technology, this future also depends on diverse representation. […]

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Amazon SageMaker Studio Lab

Now in Preview – Amazon SageMaker Studio Lab, a Free Service to Learn and Experiment with ML

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 […]

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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 […]

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New – Introducing SageMaker Training Compiler

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 […]

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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 […]

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Announcing Amazon SageMaker Ground Truth Plus – Create Training Datasets Without Code or In-house Resources

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 […]

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New – Amazon DevOps Guru for RDS to Detect, Diagnose, and Resolve Amazon Aurora-Related Issues using ML

Today we are announcing Amazon DevOps Guru for RDS, a new capability for Amazon DevOps Guru. It allows developers to easily detect, diagnose, and resolve performance and operational issues in Amazon Aurora. Hundreds of thousands of customers nowadays are using Amazon Aurora because it is highly available, scalable, and durable. But as applications grow in […]

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Announcing Amazon SageMaker Canvas – a Visual, No Code Machine Learning Capability for Business Analysts

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 […]

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