It's a long from pedal bicycles to Formula 1. But that is precisely the quantum leap that the artificial intelligence-based startup Neural Concept and its co-founder and CEO, Pierre Baqué, made in just six years.
In 2018, the company's fledgling software helped develop the world's most aerodynamic bicycle. Today, four out of 10 Formula 1 teams use an evolution of that same technology.
Along the way, Baqué's company secured contracts with aerospace suppliers such as Airbus and Safran, earning a $9.1 million Series A raise in 2022. Now with 50 employees, Switzerland-based Neural Concept is working towards a Serie B round as its software helps historic F1 teams like Williams Racing find their way back to the top of the world's biggest motorsport. .
However, while Formula 1 cars rely on 1,000-horsepower hybrid V6 engines, Baqué's first practical application of this technology was human-powered.
pedal power
In 2018, Baqué was studying at the Computer Vision Laboratory at the École Polytechnique Fédérale de Lausanne, working on the application of machine learning techniques to three-dimensional problems.
“They put me in touch with this guy who was leading this team, designing the sixth or seventh generation of bicycles, and his goal was to break a world record for bicycle speed,” Baqué said. That guy was Guillaume DeFrance and the team was IUT Annecy from the Université Savoie Mont Blanc. The cycling team had already gone through half a dozen iterations of bike designs.
“Two days later, I saw him again in a shape that almost looked like the current world record holder,” Baqué said. Impressed, the team asked for more iterations. The result was, according to Baqué, “the most aerodynamic bicycle in the world at this time.”
That's a strong statement, but it's backed up by multiple world records set in 2019. We're not talking about airfoil-shaped down tubes or dimpled tires to reduce drag. This bike is completely covered, with the rider sweating in a composite cocoon, completely protected from the wind.
The core technology is a product called Neural Concept Shape or NCS. It is a machine learning-based system that makes aerodynamic suggestions and recommendations. It fits into the broad field of computational fluid dynamics (CFD), where highly trained engineers use advanced software packages to run three-dimensional aerodynamic simulations.
CFD is much faster than carving physical models and throwing them into wind tunnels. Still, it also requires a lot of system usage and relies heavily on humans making good decisions.
In essence, NCS helps engineers avoid potential aerodynamic obstacles while pushing them in directions they may not have considered. In “co-pilot mode,” an engineer can load an existing 3D shape, providing a starting point, for example.
NCS will then delve into its neural network to suggest improvements or modifications, possible paths in a 3D choose-your-own-adventure game. The human engineer then chooses the most promising suggestions and subjects them to further testing and refinement, repeating their path to aerodynamic glory.
Not just “cheating the wind”
NCS is useful not only for racing but also in the automotive and aerospace industries. “The path to broad adoption in these types of companies is slow,” Baqué said of working within the somewhat conservative aerospace industry. “That's how we started to work more with the automotive industry, where the needs are a little more urgent and will change quickly.”
Neural Concept secured contracts with several global suppliers, including Bosch and Mahle. Aerodynamics are increasingly key in the automotive world, and manufacturers are looking for increasingly aerodynamic cars that offer the greatest range possible with a battery pack of a given size.
But it's not just about fooling the wind. NCS is also used in the development of things like battery cooling plates which, if made more efficient, can keep the battery at its optimal temperature without consuming too much energy in the process. “Enormous benefits can be achieved,” Baqué said, referring to greater reach.
While the ultimate testing ground for these technologies is always the road, the ultimate laboratory is Formula 1. A global motorsport phenomenon since 1950, F1 is currently experiencing an unprecedented wave of popularity.
The power of Netflix
The Netflix series “Formula 1: Drive to Survive” has brought the excitement of F1 to a whole new audience. While that series focuses on politics and team drama, success on the track has much more to do with aerodynamics. That's where Neural Concepts comes into play.
Baqué started watching Formula 1 before Netflix was even a twinkle in Reed Hastings' eye. “I always saw it, from the time of David Coulthard and Michael Schumacher.”
Today, parts developed with the help of his company's software are used in this pinnacle of world motorsport. “It's a great, great feeling of accomplishment,” Baqué said. “When I started the company, I saw it as a milestone. Not just Formula 1, but simply having parts designed with the software on the road. And yes, every time this happens, it is a fantastic feeling.”
Formula 1 is also an extremely secretive sport. Of the four teams Neural Concept works with, only one was willing to be identified as a client, and even this one was quite secretive about the entire process.
Williams Racing is one of the most historic teams in Formula 1. Founded in 1977 by racing legend Frank Williams, his team was so dominant in the 1990s that it won five constructors' world championships, including three in a row between 1992 and 1994.
But like most sports, success is cyclical for Formula 1 teams and Williams is currently in a rebuilding phase. The team finished last in the 2022 season, and only reached seventh place last year.
NCS is one of the tools helping Williams regain its competitive advantage. “We use this technology in a number of ways, some of which improve our simulation, and other methods we are working on will help deliver better results for the first time in CFD,” said Williams aerodynamics technology director Hari Roberts.
Once again, CFD simulations are time-consuming and expensive, a situation exacerbated by Formula 1 regulations that limit a team's ability to test. Physical time in the wind tunnel is highly restricted, while each team also has a limited budget for the calculation time they can use to develop their cars.
Any tool that can help a team get their aerodynamic designs into shape quickly is a potential advantage, and NCS is actually very fast. Baqué estimated that a full CFD simulation that normally takes an hour would take as little as 20 seconds through NCS.
And, since NCS doesn't run actual physics-based calculations, but rather makes ai-powered guesses based on its network of aerodynamic learnings, it is largely exempt from F1's draconian restrictions. “Anything we can do that allows us to extract more knowledge and therefore more performance from each CFD and wind tunnel gives us a competitive advantage,” Roberts said.
But teams still have to pay for it. Baqué said NCS costs vary depending on the size of the equipment and type of access, but typically range between 100,000 and 1 million euros per year. Considering F1 teams also operate with an annual cost cap of $135 million, that's a substantial commitment.
Williams' Roberts would not point to any specific parts or lap time improvements thanks to the NCS software, but said it has affected his car's performance: “This technology is used as part of our toolkit to aerodynamically develop the car. car. Therefore, we cannot attribute the lap time directly to it, but we know that it helps our correlation and the speed at which we can investigate new aerodynamic conditions.”
Beyond aerodynamics
The relentless march of ai will not stop there. There is talk of artificial agents on the pit wall that make decisions in race strategy and even in car configuration.
“It's an exciting time as the growth of the ai/ML industry is exponential,” Roberts said. “However, it is also a real challenge facing anyone involved in technology today. What new tools do we spend time exploring, developing and adopting?
That's not the kind of intrigue that will captivate the average “Drive to Survive” viewer, but for many F1 fans, the race behind the race is the main source of drama.
As for Neural Concept, the company continues to delve into the non-motorsports side of the automotive industry, working to develop more efficient electric motors, optimizing cabin heating and cooling, and even conducting crash tests.
Baqué said the company's software can help engineers optimize a car's crashworthiness while eliminating unnecessary weight. But for now, the company can only perform accident simulations on individual components, not entire cars. “This is one of the few applications where we have reached the limits of performance,” he said.
Maybe another app for the The EU's burgeoning ai supercomputing platforms?
