Yah, I have some vague experience in the space and, without getting into things covered by NDAs, I guess I can say…
First, The popular media talks about the classic style of physics solvers as these magical black boxes but my experience is that they are sufficiently unreliable that I would never trust my life solely to the answers of a solver. They do provide very valuable feedback for refining a design without an endless hardware-rich cycle of destructive testing. Thus, I think that a large physics model is probably going to be the same sort of useful tool.
Second, while the CAE engineers can be very very protective over the time they spend on the two week cycle the article talks about, it’s fucking drudge work and a waste of a good mind. At the same time, the article does not really talk about some of the nitty gritty details. Aerodynamics is a great place to start because there’s less setup but the coefficient of drag is only one problem that needs to be considered.
Third, the good engineers can “see” things intuitively because things do operate with a pattern. Vorticies from protruding features… stress fractures from square holes in a beam… etc. This does feel like an area where spicy autocorrect can spicy autocorrect you to a useful answer.
Finally, cycle time for real world engineers is just like the cycle time for software engineers. Nobody wants to go back to the world where programmers submitted a deck of cards and got the printout back a week later.
The only real risk here is that somebody gets high on their own supply and decides that a large physics model is actually predictive and we don’t need the same set of actual physical tests that validate the models.
To riff off of Margret Atwood, men go to AI chatbots because they won’t laugh at them. Women go to AI chatbots because they won’t kill them.