AWS Machine Learning Blog

You can now control the Amazon Virtual Private Cloud (Amazon VPC) and encryption settings for your Amazon Comprehend APIs using AWS Identity and Access Management (IAM) condition keys, and encrypt your Amazon Comprehend custom models using customer managed keys (CMK) via AWS Key Management Service (AWS KMS). IAM condition keys enable you to further refine […]

Today, we’re pleased to launch Machine Learning Essentials for Business and Technical Decision Makers—a series of three free, on-demand, digital-training courses from AWS Training and Certification. These courses are intended to empower business leaders and technical decision makers with the foundational knowledge needed to begin shaping a machine learning (ML) strategy for their organization, even […]

In preparation for the upcoming Olympic Games, Intel®, an American multinational corporation and one of the world’s largest technology companies, developed a concept around 3D Athlete Tracking (3DAT). 3DAT is a machine learning (ML) solution to create real-time digital models of athletes in competition in order to increase fan engagement during broadcasts. Intel was looking […]

Customers often ask us how can they lower their costs when conducting deep learning training on AWS. Training deep learning models with libraries such as TensorFlow, PyTorch, and Apache MXNet usually requires access to GPU instances, which are AWS instances types that provide access to NVIDIA GPUs with thousands of compute cores. GPU instance types […]

This post is cowritten by Ian Avilez and Tim Pavlick from HawkEye 360. HawkEye 360 is a commercial radio frequency (RF) satellite constellation data analytics provider. Our signals of interest include very high frequency (VHF) push-to-talk radios, maritime radar systems, AIS beacons, satellite mobile comms, and more. Our Mission Space offering, released in February 2021, […]

April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. As companies welcome more autonomous robots and other heavy […]

Amazon SageMaker Data Wrangler is the fastest and easiest way for data scientists to prepare data for machine learning (ML) applications. With Data Wrangler, you can simplify the process of feature engineering and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization through a single visual interface. Data Wrangler […]

AWS continues to innovate on behalf of our customers. We’re working with NVIDIA to bring an Arm processor-based, NVIDIA GPU accelerated Amazon Elastic Compute Cloud (Amazon EC2) instance to the cloud in the second half of 2021. This instance will feature the Arm-based AWS Graviton2 processor, which was built from the ground up by AWS […]

Companies that operate and maintain a broad range of industrial machinery such as generators, compressors, and turbines are constantly working to improve operational efficiency and avoid unplanned downtime due to component failure. They invest heavily in physical sensors (tags), data connectivity, data storage, and data visualization to monitor the condition of their equipment and get […]

As the modern factory becomes more connected, manufacturers are increasingly using a range of inputs (such as process data, audio, and visual) to increase their operational efficiency. Companies use this information to monitor equipment performance and anticipate failures using predictive maintenance techniques powered by machine learning (ML) and artificial intelligence (AI). Although traditional sensors built […]