Formula One (F1) has partnered with AWS to expand its "F1 insights" in a new initiative to use machine learning (ML) to improve the viewing experience of F1 races for fans. The announcement was made at the AWS re:Invent conference, hosted in Las Vegas.
Speaking to the audience, F1 managing director of motorsport Ross Brawn explained why the F1 body had decided to collaborate with AWS in the expansion of F1 Insights: "For next season we are expanding 'F1 Insights' for our viewers by further integrating the telemetry data such as car position, tyre condition, even the weather, so we can use SageMaker to predict car performance, pitstops and race strategy".
The Amazon SageMaker is an AWS service which gives developers the capability to "build, train, and deploy machine learning models quickly". SageMaker has been utilized by the F1 to track driver performance for viewers and let them see if drivers have "pushed themselves over the limit" in real time.
In a blog released by AWS, the cloud services company explores its plans to utilize ML to deliver new experience to fans. Through ML, AWS will be extracting a number of performance data to provide viewers with an "insight into the split-second decisions and strategies adopted by teams and drivers".
Outside of simply enhancing the viewer experience, the F1 is also planning to transfer its infrastructure to the AWS cloud in the hope that the various ML services it offers will aid in the "quality of the simulations their aerodynamics team can run as they work to develop the new car design rules for Formula 1 teams and drivers".
"We can bring that information to the fans and make them understand if the guy is in trouble or if he can manage the situation," said Brawn at the conference. "These are insights the teams always had but we are going to bring them to the fans and show them what is happening".