Artificial intelligence and machine learning are giving the McLaren Formula One and esports teams a big leg up by improving the efficiency and effectiveness of their digital systems utilised for information dissemination and security.
From telemetry to cybersecurity, Formula 1 collects massive amounts of data, and it is vital to have a firm grasp on this sometimes highly complicated data in order to maximise performance in a sport where speed is of the highest importance.
The opportunity to talk to Ed Green, McLaren’s Head of Commercial Technology, and James Hodge, Splunk’s GVP and Chief Strategy Advisor, on artificial intelligence’s role in the equation, how it may assist to secure the company’s digital world and improve decision making, and its limits.
Predictability and choice-making in terms of safety
You can bet that McLaren takes safety seriously throughout the board. Green provided an example of a typical setup for the McLaren Shadow esports squad.
To put it another way, “if you’ve got eight gamers on stage, that implies eight PCs behind them, and possibly another four directing and editing the performance,” leading to a grand total of 24 PCs.
Green said, “we have standard endpoint protection we implement throughout the estate” to safeguard all of these computers. We have firewall providers who can see precisely where the traffic is going, and we also employ internal capabilities provided by our different cybersecurity partners to track its movement.
It is known that Darktrace is employed in McLaren’s security posture to some degree, despite the fact that McLaren has been tight-lipped about the specific software it employs.
Security measures in cyberspace must also be somewhat lightweight so as not to significantly drain simulation hardware batteries.
“Many things are often pretty light, so consumers don’t want many agents on their PCs performing bits and pieces,” explains Green.
During the race, “I can get a glimpse of it to monitor since we utilise natural endpoint clients throughout McLaren and they report up into a serious of dashboards that might be beneficial.”
Green said that the company uses AI and machine intelligence for more than only race data security:
As one of our senior executives put it, “it’s a pretty dull and monotonous job to sit there reading through lines and lines of cybersecurity information, so we’ve deployed a lot of machine learning and AI throughout [the cybersecurity] industry.”
To paraphrase, “embracing machine learning and AI is incredibly essential for us since it has allowed us to reduce the size of our cybersecurity staff while providing them with more relevant context, allowing them to understand where the information is heading.”
‘When you look at AI in cybersecurity, or in general, it’s either there to help you be more efficient, to help you combine and solve incredibly huge difficult issues, or to offer you with more support,’ he said.
AI’s role in cybersecurity, on the racing team, and in strategy is primarily advisory; it does not take over operational duties. It’s possible that you’ll be working under extremely tight time constraints; for example, a pit stop might only give you three seconds to make a decision. In such a situation, it’s helpful to have access to the next best decision or to be able to simulate potential outcomes so that we can make the best choice possible under pressure.
Green did hint that AI might play a role for the esports F1 team in the future, despite the fact that it is employed primarily for the real-world Formula 1 team.
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