alt Hacker NewsThere’s a kind of grief that I feel when I think about how, over the last 70 years, engineers have tended to increasingly rely on tech that makes the math knowledge unnecessary.
The beauty of math has played a huge role in the career choices that I’ve made so far. I changed fields at one point because I realized that the math that practitioners used was almost exclusively all baked into CAD tools. I figured that if that was where the applied math lived, then I wanted to write software for a living.
With a lot of the AI tools now (which I use and appreciate daily FWIW), I’m beginning to see that even in math-heavy sub disciplines of software engineering (e.g. robotics), we’re not exempt from this trend.
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I have never used more math since llms. My projects have just become more ambitious.
I completely agree that so much interesting math is hidden behind hyper-proprietary tools that engineers are expected to use.
As you note, all the Finite Element tricks are hidden, all the meshing tricks are hidden, and while you can find some in old research papers, in general the main companies hoard them.
The landscape has been 3 / 4 forces:
1) individual academics that do interesting work but more often than not abandon the codes they produce after a paper or three.
2) Proprietary companies that hire enough expertise to take academic research, generalize it, and sell a hyper-proprietary product with very little competition because the expertise is hard to come by
3) The national labs which do amazing work, that release a body of reliable open source work, though some of it is tailored to their systems - usually hard to use / very few people know about it outside academia.
4) Open projects like OpenFOAM / OpenCascade that struggle along at the edges to create a cohesive whole that can compete with the big companies.
I think that LLMs offer an opportunity free us from this status quo:
1) The open source work of the past is much easier to use / decipher with an LLM
2) The research is there, it just hasn't been productized (through an open source vector) / made accessible yet
3) I do believe that LLMs make learning the past codes / getting ideas for new codes / extending codes easier
I think engineering tools are up for a shakeup, as both LLMs + new paradigms are emerging. There is really interesting research into new meshing methods / CAD representation (Brep vs SDF) / topology optimization.
I believe this is an opportunity for an open source ecosystem to start making inroads into the bottom layers of the engineering stack (CAD kernels / representation), and from there make inroads into meshing + make open source FEA more accessible.
I am excited by what the future might bring, and remain cautiously optimistic that just like no one buys a programming language anymore, the lowest levels of the engineering stack might become open source so that research is accelerated, engineers are freed from total lockin, and in general the ecosystem is much healthier and innovative.