The auto racing organization said it's migrating the vast majority of its on-premises infrastructure to AWS, and standardizing on on AWS' machine learning and data analytics services as part of its cloud and digital transformation strategy.
Formula 1 is also using SageMaker, Amazon's end-to-end machine learning service, to train deep learning models with more than 60 years of historical race data stored in Amazon DynamoDB and Glacier. The data will help the company glean race performance statistics that can be used to predict outcomes. AWS' serverless computing service Lambda is also on tap to help uncover race metrics, along with AWS Elemental Media Services, which will power Formula 1's video asset workflows.
"We are also excited that the Formula 1 Motorsports division will run High Performance Compute workloads in a scalable environment on AWS," said Pete Samara, director of innovation and digital technology at Formula 1. "This will significantly increase the number and quality of the simulations our aerodynamics team can run as we work to develop the new car design rules for Formula 1."
The goal for AWS is to put more machine learning services into the hands of developers.
The new mode is one of multiple updates AWS announced related to enabling AI and machine learning.
According to Capital One's Adam Wenchel, the firm will be using Amazon SageMaker to bolster the skills of its machine learning experts and the graph database Neptune to fight money laundering.