Formula 1 teams race for AI edge | information age

Oracle is the name sponsor and cloud provider for Red Bull Racing. Photo: Robert Cianflone/Getty Images

You can be forgiven for not thinking too much about data analysis and AI when you sit among Grand Prix bettors in the Turn 12 grandstand at Melbourne’s Albert Park during a practice session. sunny afternoon training.

The smell of grass, burnt rubber and petrol combined with the scream of F1 cars is intoxicating enough when you watch elite drivers race around the track testing ways to win crucial split seconds during races. qualifying the next day.

“There’s the Oracle car,” a journalist points out as defending champion Max Verstappen rounds Turn 11 and appears, the American tech company’s name prominently displayed on his red, yellow and blue Red Bull Racing Oracle car .

Oracle is paying $300 million over five years to be named sponsor of Red Bull Racing, says Reuters sources.

It’s an agreement that expands the relationship forged early last year when Oracle was tapped to provide Red Bull with cloud infrastructure for data analysis.

At the time, Red Bull boss Christian Horner said the relationship was “a big step forward” for the racing team to have “one of the most recognizable and trusted names in industry in database management and cloud computing” on board.

Just under nine months later, a controversial steward’s decision in the final race of the season helped Verstappen claim his first championship victory and end Englishman Lewis Hamilton’s four-game winning streak.

Oracle’s precise role in this championship would be easy to overestimate; no amount of cloud infrastructure and data analysis can explain the driver errors, mechanical failures and luck that combine with a nearly endless set of variables to affect any given race.

Whichever vendor teams choose, data management is a crucial part of modern racing.

Red Bull cars have around 150 sensors that constantly send data back to the race team over a Grand Prix weekend which, combined with video and audio data, can see hundreds of terabytes of data. back and fourth in just a few days.

“We are looking for every opportunity to make decisions that will improve our performance on the track,” Zoe Chilton, head of partnerships at Red Bull Racing, told reporters at the Commons Collective, a venue a short walk from the Melbourne F1 track. .

“Tools like artificial intelligence and machine learning are going to become very important in sports as we become more and more data driven.

“As the volumes of data grow, we need to think about how to get actionable insights from it.”

Using every possible data point collected from the track, car, historic races and practice and qualifying sessions, engineers run billions of simulations to help inform race strategy.

“It’s ultimately what decides when we make our pit stops and how we react to what’s going on around us on the track,” Chilton said.

But despite all the data modeling and Monte Carlo simulations testing the odds of the outcome, it was a mechanical failure that prevented Oracle Red Bull from finishing the Melbourne Grand Prix with two podium places, while a Verstappen frustrated came to an abrupt stop and turned off his car on lap 39, almost giving up the lead to Ferrari’s Charles Leclerc.

The Frenchman held up the race trophy on Sunday afternoon with a plain white Amazon Web Services (AWS) logo discreetly visible on his left shoulder.

Casey Tonkin traveled to Melbourne as a guest of Oracle.

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