[potatofrenzy]

I've been playing with this for a while. In my experience, current LLMs work really well for looking up general electronics knowledge and reinterpreting it in the context of your problem. "What are the reasons my resistor-based voltage divider isn't working", that kind of stuff. Not useful for seasoned EEs, great for hobbyists.

But the moment you're asking LLMs to reason about the specs or the applications of specific chips, they will give made-up answers around 80% of the time. This is probably a matter of the data being a bit too sparse. Pick a chip and ask about its supply voltage range, and it will probably get it wrong, even for the most popular stuff.

[exmadscientist]

> the moment you're asking LLMs to reason about the specs or the applications of specific chips, they will give made-up answers around 80% of the time. This is probably a matter of the data being a bit too sparse. Pick a chip and ask about its supply voltage range, and it will probably get it wrong

But isn't your supply voltage example exactly the sort of stuff they should get right? It's just regurgitating data sheets.

I kind of expect a tool like this to be able to operate in one of two, theoretically distinct (but maybe not practically distinct) modes. One is basically "blueprints", very much in line with the example I suggested earlier: draw me up one of these that fits in here. I wouldn't expect creativity, just more or less rote execution of a common plan. The other mode let's call "tuning": continuing with the class-AB stage example, this would be things like setting the biasing resistors correctly. That's a tedious task, possibly requiring simulation to do well, possibly just copyable, but with a large margin for usable results. I may not care exactly what I get as long as it's somewhat workable, which would be a good place for machine help. Or I might just want a decent starting point for my own simulation. I think "AI" techniques could handle either of those general modes and produce useful (if imperfect) results that save overall time.

What I don't expect AI to do is design architectures for me, or pick approaches. A tremendous amount of my value-add as an engineer is just me saying "no, don't choose approach A, I know it looks nearly equivalent to B on paper, but B is going to work out better". AI is not there now and I don't see LLM-style AI getting there any time soon, just by its nature. (At least not when it's a genuine judgement question and not an education/"A is never right" situation.)

What I don't think AI can do but I really, really wish it could is help me pick parts. All it needs to do for this is read and halfassedly-understand a bunch of datasheets, more datasheets than I can read myself. I think LLMs can do that! Though they might need to also be able to read graphs or simple diagrams ("Find me an EEPROM in the 208-mil SOIC package" is a great prompt and seems thoroughly actionable! But sometimes that dimension is only provided as part of the package drawing, which might be an issue.)

Recently I needed a PMOS FET with particular specs and was getting frustrated not finding quite what I wanted. So I asked ChatGPT. It was great at making me laugh and giving me a little break from datasheets! It did not actually help find a part. (It kept suggesting NMOS parts when I needed and asked for PMOS.)