AWS News Blog
Category: Artificial Intelligence
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 […]
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 – 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 […]
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 – 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 […]
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 […]
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 […]
New – Amazon EC2 G5g Instances Powered by AWS Graviton2 Processors and NVIDIA T4G Tensor Core GPUs
AWS Graviton2 processors are custom-designed by AWS to enable the best price performance in Amazon EC2. Thousands of customers are realizing significant price performance benefits for a wide variety of workloads with Graviton2-based instances. Today, we are announcing the general availability of Amazon EC2 G5g instances that extend Graviton2 price-performance benefits to GPU-based workloads including […]