[thinkmachyx]

Thanks a lot for the thoughtful and respectful reply! I really appreciate that you raising the engine issue without dismissing the whole idea.

Although building such engine requires tons of work, but the engine we’re having is indeed a bit of old. Except for the problems I mentioned, you also mentioned they’re still single threaded. That’s why I think it’s still worth building a new one, especially when there’s no good open sourced one currently.

I’m a big supporter of open source. If we have something like that in the future, we should of course make it open source like Linux kernel and allow everyone to enjoy the benefit of it.

[ddingus]

Me too, and you are quite welcome!

CAD is close to my heart. I jumped in during the 80's as a high schooler running on an Apple 2! Even back then, limited 8 bit CAD could do a lot. And it was one application that helped me see the future! Product design was gonna change as manufacturing already was and the people who knew CAD were gonna be there.

Now here we are, and the CAD companies own design and manufacturing.

I had a flash of an idea this morning reading your comment:

Perhaps we could license Parasolid for a year, or maybe we try what tomfoolery I am about to put here with Open Cascade.

Maybe an AI model of some kind can get us a leg up?

Going back to the fillet example I put here earlier, I want to share a bit of backstory...

I was at SDRC, who had built out a fantastic concurrent engineering and analysis system called I-DEAS. I loved that CAD software and was an applications engineer and trainer on it. Taught many groups of engineers how CAD works, and I got to do that on a system that had collaboration built in from the beginning! Fully revision controlled concurrent engineering and analysis. Fun stuff.

But it died.

My years of skills gone. Kernel could not keep up. So I moved all that onto what is NX today and many of the best parts of the software I loved ended up being implemented because some mergers resulted in the same smart people being product managers! I am particularly redeemed!

And therein lies the lesson of the geometry kernel. You build your true skill on Parasolid systems or risk seeing them lying dormant, cast aside.

The kernel upon which I-DEAS was built was written in Fortran 90. Beautiful software too. It offered capabilities well ahead of Parasolid in some ways, but consistently failed on some common geometry cases that come up rather frequently. Things tangent to things, touching a a point was a big one.

One thing I taught was overbuild or underbuild. Rather than draw a rectangle tangent to a circle to prepare for an extrude, place that end of the rectangle inside the circle and let a boolean operator sort out the two resulting solids.

So yeah, build it kind of wrong so the kernel can build solids. Messy. :)

I was in a room talking to the people who do fillers. Edge blend to some of us.

We talked about my fillet gauntlet. It was a collection of geometry cases that fillet operations failed to complete.

Parasolid could always resolve more of them, and it did that with fairly sloppy tolerances. The SDRC kernel was catching up each rev, but the trend line looked like a decade of analysis of the successful resolutions, and coding for those, wash, rinse repeat a lot.

I wonder if it might be possible to generate geometry cases using parameters such that whole problem spaces could or can be created. Have good kernels solve and train an AI on all that to see what it may then solve differently?

Maybe man years boils down to compute/watt hours?

[thinkmachyx]

I really appreciate your reply — it's an honor to hear from someone with such deep experience in the field. Your insights from decades of working with CAD and kernels are incredibly valuable, and it means a lot that you'd take the time to share them here.

The idea of parameterizing geometric problem spaces and learning from how different kernels handle them is strikingly similar to what compiler researchers have done in CS: generating corner cases, analyzing compile errors, and training AI to self-correct. AI coding is used widely in the industry currently, with tools like cursor gaining huge popularity.

And the move to a text-based representation is what makes this all tractable — binary formats never gave us that level of observability or editability. With source-level CAD, it becomes much more realistic to analyze failures, share test cases, and eventually integrate AI tools that can reason about geometry the same way they reason about code.

[layerdynamicsai]

“Parasolid could always resolve more of them, and it did that with fairly sloppy tolerances”

Doesn’t that come down to the precision, 1.e-7?