Artificial intelligence tools are set to take on a much larger role in shaping Formula 1's future aerodynamic regulations, as The Race reports on a brand-new partnership between the FIA and Amazon Web Services. Under the deal, AWS becomes the official artificial intelligence, cloud computing, machine learning, and cloud infrastructure partner for the governing body. The scope of the agreement stretches from designing future car rules with advanced aero simulations to revamping global licensing systems and streamlining internal operations.
The core of the technical work involves running computational fluid dynamics testing on AWS hardware to unlock faster, higher-fidelity simulations. These setups feed into the FIA's virtual windtunnel, allowing engineers to test concept cars and check critical factors like downforce loss when following another machine. While traditional CFD runs can take hours of compute time, the introduction of AI surrogate models trained on past data could predict outcomes for new shapes in mere seconds or minutes without solving the underlying physics from scratch.
FIA deputy technical director for F1 Dominic Harlow explained that these surrogate approaches will extract greater productivity from the process while consuming less compute time, engineering hours, energy, and money. Work is already underway on aerodynamic concepts for future cars, looking toward a potential 2030 introduction for brand new chassis and power unit regulations. Harlow noted that generative AI won't be used to prompt raw design ideas just yet, keeping the focus entirely on accelerating and supporting human engineering work.
Beyond aerodynamics, the integration extends deep into the performance and power unit groups. Computer vision and incoming data dashboards will assist with trend monitoring, pattern spotting, safety metrics, energy management, and legality checks. Meanwhile, the power unit team plans to deploy neural networks for anomaly detection, comparing complex operational lines against track data to instantly spot issues like a sudden drop in oil pressure.
Hardware upgrades also sit at the heart of the deal, with the transition from traditional CPUs to modern graphics processing units capable of handling massive parallel calculations. Harlow pointed out that unsteady, time-sensitive simulations running on faster hardware could help the FIA understand complex physical phenomena like porpoising before cars hit the track. Additional plans include utilizing secure large language models to stress-test the sprawling rulebook and assist with operational tasks like filtering track-limit incidents for human review.
