| This seems like a big assumption to me personally. To be clear, I happen to be of the opinion that AI/ML/LLMs/whatever cannot truly replace software engineers without the true advent of AGI. But to play devil's advocate. I'm an embedded SWE and work with circuit designers/have dabbled in some PCB design myself. Taking circuit design as an example: From an abstract logic standpoint, PCB design is not that different from software development. It essentially boils down to taking some input and feeding it through a cascade of various discrete transformations until you have some desired output. The fact that PCB designs are captured through schematics is irrelevant, as a schematic is just a visual representation of a netlist. There are even DSLs that allow for the design of circuits through code alone. The mechanisms that make LLMs work show some level of adaptability to domains outside of traditional language. It is totally conceivable today to finetune an LLM on netlists (or even on images of schematics with the right encoder model) and have it be able to generate circuit designs. The training data exists, though it's not as plentiful as say code or english texts.
I'm not an ML expert but I believe it's totally possible to have something where, for example, the text "555 timer-based LED-blinking circuit", could map in embedding space to a netlist that describes said circuit. There are in fact companies working on this exact thing today (Flux.ai) I don't see why this wouldn't work for other engineering disciplines aswell. There's lots of public scad code for various 3d models. It's totally conceivable to build a model trained on scad or even raw 3d object file geometry and text embeddings to generate mechanical designs. Lot's of research is going into generative meshes which could be seen as an early form of this. I think my point being that the hard part of engineering, discipline aside, is being able to take a fuzzy set of desires from a customer and a fuzzy set of constraints and being able to use the hard math and science to create and iteratively refine a product/system/whatever to make all stakeholders happy. LLMs can't really emulate this process today. |