Formula 1 looks to AI to fuel efficiencies and improve sustainability scorecard

Formula One (F1) has turned to data and artificial intelligence (AI) to achieve higher operational efficiencies and, in turn, become a more sustainable sport despite being known for burning fuel. 

As it is, the motor-racing organization has reduced its carbon footprint by 13% from 2018 and is on track to meet its net zero target by 2030, according to its ESG report. Its sustainability efforts include an energy pilot rolled out at the Australian Grand Prix, which cut emissions by at least 90% in the pit lane, paddock, and broadcast sites. The British Grand Pix was also powered by green energy alternatives and included the use of 2,746 solar panels and hydrotreated vegetable oil fuel in all temporary generators. 

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The organization is constantly looking at ways to optimize its operations and reduce freight, so it can reduce its carbon footprint, said F1’s director of IT Chris Roberts. 

This includes enabling the majority of its IT infrastructure to run remotely in the UK, for instance. Its use of more efficient systems has meant that 40 truckloads of servers no longer need to be shipped from one circuit to another, helping to cut the organization’s environmental impact said Roberts, who spoke with ZDNET on the sidelines of the Singapore Grand Prix, whose title was claimed by McLaren’s Lando Norris. 

It also means procuring the right technology and systems that can bring greater sustainability, said Roberts at a media briefing with Lenovo executives. Early this month, the tech vendor inked a multi-year agreement with F1, further extending its global partnership to provide products and services, including mobile devices, high-performance computing systems, and backend servers. 

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Roberts said the collaboration has already helped F1 recycle and repurpose more than 800 devices. He added that more than 95% of its old hardware has been recycled. 

“In the future, we hope to use AI-driven predictive analysis to allow asset recovery to be even more efficient, predicting when machines could be recycled or reused,” he said. 

F1 has started deploying AI-powered devices out on the field and hopes to use the technology, alongside the data it collects, to extract insights that can improve user experience for its fans, Roberts said. 

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The organization processes more than 500TB of data during a race weekend and will run 24 races this year over 40 weeks. 

AI increasingly will be leveraged throughout its tech stack, including AI-enabled personal computers, to gain the best value for the organization and its audience, he added. The sport is followed by more than 700 million fans worldwide. 

The future of AI is “hybrid AI” said Matt Codrington, Lenovo’s Greater Asia-Pacific vice president and general manager, where the technology is delivered to wherever it is needed — whether it is on-premises, cloud, and on edge devices, including mobile and desktop devices.

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It means an organization’s use cases and data management will drive where and how AI capabilities are deployed, said Codrington. This will take into account key factors such as security, cost, and availability. 

Security, in particular, is as critical as data — the lifeblood of any organization, including an F1 team, said James Southerland, racing head of partnerships for Williams Racing. 

The UK-based F1 team has increasingly relied on data to improve the performance of its cars, said Southerland, during a media luncheon with Williams’ cybersecurity partner Keeper Security, ahead of the Singapore F1 race.

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There are more than 300 data sensors on an F1 car, collecting 1TB worth of data each race weekend, including video files, that Williams analyzes for insights to constantly improve its vehicles, he said. 

Hence, any data breach can potentially bring down an organization and hinder its ability to enhance the car’s performance, he noted. 

As organizations look to further tap AI, including generative AI (gen AI) to optimize efficiencies, they also need to ensure customer data remains protected, Roberts told ZDNET.

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He noted that F1 has an internal AI working group that gathers technologists across different principles, including media, software development, and research, to greenfield ideas, as well as a separate AI steering committee that includes representatives from legal, risk, and compliance. The latter reviews AI and machine learning initiatives to ensure they adhere to the necessary rules and safeguards, including AI ethics, he said. 

Projects that are red-flagged will be dropped or tweaked and reassessed again, he added. These steps help ensure AI is used responsibly within the organization, he said. 

Each F1 car generates 1.1 million telemetry data points per second, which is transmitted from the cars to the pits, according to Amazon Web Services, F1’s cloud partner. The data is used alongside decades worth of historical datasets to train and power AI models, which generate insights used to drive teams’ race strategies and provide fans with information on decisions made on tracks. 

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For example, the Alternative Strategy feature gives viewers alternative perspectives on how races might have turned out if drivers had made a different on-track decision.