AI's fastest application yet: Formula One
Putting machine learning on the grid.
I've been an avid Formula One fan for something like (gulp) 35 years now, and in that time, there's, of course, been massive change. But the one constant has been every team’s obsession with the latest technology.
So, it should come as no surprise that AI has made its way to the pit lane in Formula One. There's more and more talk about machine learning used for things like pit strategy and even car setup, but my latest piece for TechCrunch covers a slightly different application.
It's a profile of Neural Concept, a startup that applies machine learning to computational fluid dynamics (CFD) and 3D modeling in general. The basic idea is similar to how ChatGPT's image generator can feed a half-dozen different visualizations to you based on a prompt.
Neural Concept's tech does something similar but with aerodynamic models, all tuned to fit within the FIA's draconian regulations, and all generated in a fraction of the time traditional CFD would require.
For a team like Williams Racing, a team desperately trying to climb back up towards the sharp end of the grid, it could be a huge advantage.
I spoke with Williams' Head of Aerodynamic Technology Hari Roberts and Neural Concept CEO Pierre Baqué to see how all this fits together, and you can read all about it here exclusively at TechCrunch.