How Red Bull plans to take AI in F1 to the next level

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Formula 1 teams are no stranger to using cutting edge technology in their bid to find an advantage over rivals.

In recent years, there has been a slow march forward in the use of Artificial Intelligence (AI) and Machine Learning (ML) as teams increasingly lean on computers to make sense of the masses of data they amass every weekend. But the impending cost cap has increased the need to deal with data efficiently, especially for the big outfits that are right on the limits of the $145 million spend.

It was therefore fascinating to hear recently that a core component of Red Bull’s sponsorship tie-up with computer technology giants Oracle did not revolve around how much cash was involved, nor the size of the stickers on the RB16B. Instead, the most exciting aspect for both parties concerned how they jointly planned to drive forward the use of AI and ML in F1.

As team boss Christian Horner explains: “AI and ML are big categories that are emerging. Both areas, with the amount of data that we generate, the way that we simulate, etc, are going to play a key role in our decision making as track time becomes ever less.

“In Oracle we’ve got a company at the forefront of this industry. It’s a phenomenal partnership for us and particularly as we enter a journey into the future across chassis across engine, the possibilities are huge.”

Getting Red Bull to define what those exact possibilities are is not the work of the moment, for any detailed information Red Bull and Oracle reveal about how they intend to unleash AI and ML would only help inform rivals to go and do the same thing themselves.

But while not being too open, Horner is clear about the kind of areas where the team needs to make better use of its data – and that is where machine learning and AI tools can step in and help.

“Data and the way that we operate, it’s our lifeblood,” he says.

Sergio Perez, Adrian Newey 2021 Bahrain GP

Sergio Perez, Adrian Newey 2021 Bahrain GP

Photo by: Mark Thompson/Getty Images

“We just generate so much of it. And it impacts everything we do: the way we run a race, the way we develop a car, the way we even analyse drivers and driver selection. It plays such a key role.

“We’re looking to unleash across our technical departments, and obviously with our fan engagement, and extract as much as we can.”

Exploring his areas in more depth, AI can certainly help with understanding and planning of race strategy and give the Red Bull pit wall the edge. Computers could also offer guidance on set-up choices at a race weekend, and even help lead car designers on development directions – especially given that decisions on how resources are deployed are increasingly driven by efficiency.

Horner adds: “Making the best decision you can to develop your car cost efficiently, so cost-effective performance, is absolutely crucial for us as we move forward with the lack of testing.

“This year we have had three days of testing, and no other sport would have such a small amount of practice. So the way that we analyse the data is crucial for us, and I think this is where this partnership is going to pay absolute dividends.”

One area where the team can be more open about where AI will be used is in marketing, and helping get the team closer to fans. Rather than trying to activate campaigns and promote itself with mass send outs of emails, or bombarding social media platforms, it senses an opportunity to give F1 fans what they want when they want it.

AI would be able to better understand exactly what type of content an individual fan responds to. There’s no point throwing videos to a fan in the evening who much prefers to read all their content on the way to work in the morning.

As Red Bull’s chief marketing officer Oliver Hughes explains: “Using machine learning and AI, we can understand our fan base much better.

Red Bull Racing factory 2021

Red Bull Racing factory 2021

Photo by: Mark Thompson/Getty Images

“So rather than at the moment doing manual segmentation and manual reports and manually thinking, how do we speak to an audience in X market or x demographic? Now we don’t need to do that.

“We can use the machine learning tools to set parameters that will do the thinking for us. It will make the whole process a lot less manual and a lot more automated. So you will be receiving the information when you want to receive it, rather than when we’re pushing it to you.”

Whether AI and ML tools are being used for Red Bull’s car performance, improving the way the team works or just better marketing exercises, from Oracle’s perspective, it is essential that its involvement in F1 showcases just what its products can do.

That why Red Bull’s success on track, rather than the eyeballs on the cars, will ultimately define just whether the tie up delivered.

Oracle’s chief marketing officer Ariel Kelman said: “There is no promotion without performance. In 2021, the days of having a marketing benefit as a technology provider from slapping your logo on something, those days are over.

“It’s all about being able to prove real success with being an engine of innovation for our customers. Then we can let our customers tell the stories, so other companies can learn and be inspired about what they can do with our technology.”

Screen with code

Screen with code

Photo by: Uncredited

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