this post was submitted on 10 Apr 2026
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...Previously, a creative design engineer would develop a 3D model of a new car concept. This model would be sent to aerodynamics specialists, who would run physics simulations to determine the coefficient of drag of the proposed car—an important metric for energy efficiency of the vehicle. This simulation phase would take about two weeks, and the aerodynamics engineer would then report the drag coefficient back to the creative designer, possibly with suggested modifications.

Now, GM has trained an in-house large physics model on those simulation results. The AI takes in a 3D car model and outputs a coefficient of drag in a matter of minutes. “We have experts in the aerodynamics and the creative studio now who can sit together and iterate instantly to make decisions [about] our future products,” says Rene Strauss, director of virtual integration engineering at GM...

“What we’re seeing is that actually, these tools are empowering the engineers to be much more efficient,” Tschammer says. “Before, these engineers would spend a lot of time on low added value tasks, whereas now these manual tasks from the past can be automated using these AI models, and the engineers can focus on taking the design decisions at the end of the day. We still need engineers more than ever.”

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[–] stephen01king@piefed.zip 2 points 5 hours ago (1 children)

No, they said "it felt right" which is incomprehensible to anyone that doesn't have any experience with how a CFD results generally looks like.

[–] toynbee@piefed.social 2 points 22 minutes ago* (last edited 21 minutes ago) (1 children)

I don't have any experience with "CFD results" but the two sound similar to me. The ellipsis might have made it seem sarcastic, but that wasn't my intent.

[–] FauxLiving@lemmy.world 1 points 11 minutes ago

CFD = Computational Fluid Dynamics.

It is kind of what they said, you're right. I was more pointing how how it could be that they could 'sense the vibes' of a CFD result to determine if it is accurate or if the model decided to do something weird. Since it's a chaotic process and also an artificial one, the starting conditions can yield results that are impossible/not based on reality.

If you look at enough of them you start to notice the kinds of things that go wrong. They would also have a pretty good idea about how their design should perform and if the simulation shows different they'd first want to troubleshoot the simulation before attempting to re-design whatever system they're creating.