Tim Stevens

3D designs when it comes to improving aerodynamics of components, for example.

And also we're seeing some AI design when it comes to battery chemistry engineering as well.

There's a lot that goes into the battery chemistry of an EV in terms of cathode and anode design.

Different compositions of those materials can have very interesting different effects on the charging speed, on the lifetime of a battery, temperature sensitivity, things like that.

And it's the kind of things where you have a lot of different permutations and can take a long time to test those different things.

If you can feed all that into some kind of a machine learning algorithm, it can spit you back some options pretty quickly without you having to build 20 different batteries and run them all through your testing procedures.

Yeah.

There have definitely been improvements on that front.

Competitional fluid dynamics, for example, which is another big thing in Formula 1 and 2, which is the ability to simulate wind tunnel runs effectively.

And that has definitely sped up that process.

You don't necessarily have to create a 3D model for everything.

They do like to do actual models in wind tunnel testing just to make sure that everything is right.

But typically, they'll do a few rounds of computational fluid dynamics.

But that typically takes a big supercomputer.

It takes specialized training.

It takes weeks to even run those simulations sometimes.

And so what this AI stuff can do, there's a company called Neuroconcept, for example, that's working on basically

bringing that kind of computational fluid dynamics into AI to be able to simulate those runs in minutes that would typically take hours and hours and hours on a supercomputer.

So that is another step that they're being able to bring that in, make that process more quickly.

And it's still, you know,