143,000 fans. Hundreds of millions of dollars are at stake. The very fastest drivers in the world. The Saudi Arabian Grand Prix is quite the spectacle - and to make it happen, powerful technology is at work behind the scenes. AI, machine learning, and deep learning are powering more elements of the sport each year, giving both the teams and the fans deeper insights and improving performance.

For teams

When race weekend comes in Saudi Arabia, on every car, more than 300 sensors are relaying information from 1.1 million data points in real-time, transmitting more than 2 gigabytes of data back to the teams on the pit wall each lap.

That data gives teams a minutely detailed picture of what’s happening on every individual lap or track sector - from brake pressure to steering wheel angle, G force to throttle position. Race strategists can then build a detailed picture of the current performance of each car and driver to adapt their tire and pit strategies accordingly.

On race day, advanced analytics help teams make more informed decisions - on the optimal moment to pit a driver, for example - by creating an AI model based on data from practice sessions and previous races to predict how a car will perform based on its earlier pace.

The weather, too, can turn race standings on their heads, presenting another challenge for teams - and another application for AI. Inaccurate temperature predictions in the Saudi climate means excess tire degradation and could be the end of the day for a driver who spins - but machine learning algorithms use up-to-the-minute forecasts to determine where on the track drivers need to take more care and ease off the throttle in the heat.

And off-track, machine learning is transforming teams’ racing simulations, giving drivers an ultra-realistic experience of their car in real-world conditions. AI-powered simulation is crucial in the development of next-generation cars, helping teams reduce downforce loss from 50% to 15% - which translates into a significant increase in pace.

For fans

F1 has been using machine learning models to understand how cars and drivers perform in every race since 2018. Fans can compare drivers on an individual basis across different seasons to understand team performances over time.

To deliver a rich data experience at scale, F1 needs a fast and reliable infrastructure solution capable of handling terabytes of data every second and instantaneously transmitting it to TV screens around the world.

The experience is built on cloud infrastructure, which turns millions of data points from cars and trackside into an engaging fan experience, F1 Insights. It draws on 70 years of historical race data, stored on Amazon S3 and analyzed by complex models that reveal the nuances of split-second decision-making.

Machine learning helps predict when an overtake may occur on any corner or straight, based on thousands of previous laps. Corner exit speeds are another key metric; at each turn, drivers brake, steer, and accelerate—in that order— in milliseconds, maintaining control of the car and touching the apexes at speeds at cornering speeds in excess of 250kph on the sweeping Jeddah circuit - home to the season’s fastest corners.

Cloud infrastructure can show viewers at home just how quickly any driver is reacting to any corner in real-time, enhancing the viewing experience and bringing fans closer to the action. AI is also used to analyze data from previous races, which can be used to predict qualifying times and car performance.

Powering the future of racing

Formula One is already one of the world’s most complex sports - and technology will ensure the future is still more so. F1 teams won’t be replaced by algorithms any time soon - but are certainly informing human decision-making at every level of the sport, from split-second move on race day to major strategic choices on how they’ll approach the season as a whole.

So what comes next for professional racing in Saudi Arabia? There’s already talk of entirely autonomous race cars, able to maneuver with the same speed and agility of the most advanced autonomous drones - and the most talented human drivers. That future might be closer than it seems.