Category: Industries

Have you ever thought about how artificial intelligence could be used to detect events during live sports broadcasts? With machine learning (ML) techniques, we introduce a scalable multimodal solution for event detection on sports video data. Recent developments in deep learning show that event detection algorithms are performing well on sports data [1]; however, they’re […]

In this post, we walk you through the steps to build machine learning (ML) models in Amazon SageMaker with data stored in Amazon HealthLake using two example predictive disease models we trained on sample data using the MIMIC-III dataset. This dataset was developed by the MIT lab for Computational Physiology and consists of de-identified healthcare […]

Healthcare has recently been transformed by two remarkable innovations: Medical Interoperability and machine learning (ML). Medical Interoperability refers to the ability to share healthcare information across multiple systems. To take advantage of these transformations, we launched a new HIPAA-eligible healthcare service, Amazon HealthLake, now in preview at re:Invent 2020. In the re:Invent announcement, we talk […]

We’re excited to announce Amazon HealthLake, a new HIPAA-eligible service for healthcare providers, health insurance companies, and pharmaceutical companies to securely store, transform, query, analyze, and share health data in the cloud, at petabyte scale. HealthLake uses machine learning (ML) models trained to automatically understand and extract meaningful medical data from raw, disparate data, such […]

In a soccer game, fans get excited seeing a player sprint down the sideline during a counterattack or when a team is controlling the ball in the 18-yard box because those actions could lead to goals. However, it is difficult for human eyes to fully capture such fast movements, let alone predict goals. With machine […]

If you’re a Formula 1 (F1) fan, have you ever wondered why F1 teams have very different performances between qualifying and practice sessions? Why do they have multiple practice sessions in the first place? Can practice session results actually tell something about the upcoming qualifying race? In this post, we answer these questions and more. […]

This is a guest post by Ray Goh, a tech executive at DBS Bank.  AWS DeepRacer is an autonomous 1/18th scale race car powered by reinforcement learning, and the AWS DeepRacer League is the world’s first global autonomous racing league. It’s a fun and easy way to get started with machine learning (ML), regardless of […]

NFL’s Next Gen Stats (NGS) powered by AWS accurately captures player and ball data in real time for every play and every NFL game—over 300 million data points per season—through the extensive use of sensors in players’ pads and the ball. With this rich set of tracking data, NGS uses AWS machine learning (ML) technology […]

With the 2020 football season kicking off, Amazon Web Services (AWS) is continuing its work with the National Football League (NFL) on several ongoing game-changing initiatives. Specifically, the NFL and AWS are teaming up to develop state-of-the-art cloud technology using machine learning (ML) aimed at aiding the officiating process through real-time football detection. As a […]

University of Illinois, Urbana Champaign (UIUC) has partnered with the Amazon Machine Learning Solutions Lab to help UIUC football coaches prepare for games more efficiently and improve their odds of winning. Previously, coaches prepared for games by creating a game planning sheet that only featured types of plays for a certain down and distance, and […]