We are excited to announce AWS AI Service Cards, a new resource to increase transparency and help customers better understand our AWS AI services, including how to use them in a responsible way. AI service cards are a form of responsible AI documentation that provides customers with a single place to find information on the […]

Today, we are excited to announce three new purpose-built tools for Amazon SageMaker to improve governance of your machine learning (ML) projects with simplified access control and enhanced transparency across your ML model’s lifecycle. With Amazon SageMaker Role Manager, you can define minimum permissions for users in minutes and onboard new users faster. SageMaker Role […]

Amazon GuardDuty now offers threat detection for Amazon Aurora to identify potential threats to data stored in Aurora databases. Amazon GuardDuty RDS Protection profiles and monitors access activity to existing and new databases in your account, and uses tailored machine learning models to accurately detect suspicious logins to Aurora databases. Once a potential threat is […]

Trusted Language Extensions for PostgreSQL is a new open source development kit to help you build high performance extensions that run safely on PostgreSQL. With Trusted Language Extensions, developers can install extensions written in a trusted language on Amazon Aurora PostgreSQL-Compatible Edition and Amazon Relational Database Service (RDS) for PostgreSQL. Read More for the details.

Amazon Redshift is introducing Multi-AZ deployments (Preview) that support running your data warehouse in multiple AWS Availability Zones (AZ) simultaneously and continue operating in unforeseen failure scenarios. A Multi-AZ deployment is intended for customers with business critical analytics applications that require the highest levels of availability and resiliency to AZ failures.  Read More for the […]

Amazon SageMaker now supports geospatial machine learning (ML), making it easier for data scientists and ML engineers to build, train, and deploy models using geospatial data. Today, the majority of all data generated contains geospatial information, but only a small fraction of it is used for ML because accessing, processing, and visualizing the data is complex, time […]

Amazon SageMaker Studio is an integrated development environment (IDE) that provides a single, web-based visual interface where users can access purpose-built tools to perform all machine learning (ML) development steps, from preparing data to building, training, and deploying ML models. Today, we are excited to announce a redesign that enhances the user experience by improving […]