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 lean on computers more and more to try to make sense of the teraflops of data they now amass each and every weekend.

But the need to become much more efficient in dealing with data has ramped up massively as the cost cap bites – especially for the big outfits that are right on the limits of the $145 million spend.

It was fascinating therefore to hear recently that one of the core components 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 the team and its partner was in how they both 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 though.

For F1 is a war between teams, and any detailed information Red Bull and Oracle give out about how they intend to unleash AI and ML would only help inform rivals to go and do the same thing themselves.

As Horner points out: “We don't want to tell all our competitors exactly what we're doing!”

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. “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. So 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 when it comes to attacking races.

Computers could also offer guidance on the setup choice for a race weekend, and also even help lead the car designers on the directions that would be best placed to take when it comes to upgrade developments.

Plus, do not forget the impact of the cost cap this year which means teams are needing to put efficiency above almost everything else when it comes to deciding where they deploy resources.

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.”

Then, in terms of driver choice, there could be a fascinating dynamic at play where the final choice of who would be Max Verstappen’s teammate in the future comes down not to the gut feeling of Horner and Helmut Marko, but instead what an AI machine tells them!

One area though where the team can be more open about where AI will be used is in marketing, and helping get the team closer to fans.

For 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 his 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.

“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, driver selection, 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.”

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