Category: Artificial Intelligence

In December 2021, we introduced HAQM SageMaker Serverless Inference (in preview) as a new option in HAQM 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 HAQM SageMaker Serverless Inference is now generally available (GA). Different ML inference use cases […]

Today we are announcing HAQM DevOps Guru for Serverless, a new capability for HAQM DevOps Guru. It allows developers to improve the operational performance and availability of serverless applications. AWS pioneered the serverless computing space with the launch of AWS Lambda in 2014. Today, hundreds of thousands of customers are using AWS Lambda. Lambda allows […]

HAQM CodeGuru Reviewer is a developer tool that detects security vulnerabilities in your code and provides intelligent recommendations to improve code quality. For example, CodeGuru Reviewer introduced Security Detectors for Java and Python code to identify security risks from the top ten Open Web Application Security Project (OWASP) categories and follow security best practices for AWS […]

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. […]

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 HAQM SageMaker Inference Recommender — a brand-new HAQM 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 HAQM SageMaker Training Compiler, a new HAQM 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 HAQM SageMaker Studio service. As of now, users of SageMaker Studio can create, terminate, manage, discover, and connect to HAQM 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 […]