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Can AI design circuit boards yet?
191–200 of 233 posts
Re: Can AI design circuit boards yet?
#192What I would love is an ai that can reverse engineer a circuit board from close up pictures. Unfortunately all the models are lagging behind in visual understanding, especially for this kind of specialized work
Re: Can AI design circuit boards yet?
#193Earlier quoted context omitted.
They actually can route just fine. I used Sol to design and route mine from start to finish. Sent it to PCBWay and had a working prototype in a few weeks. It was a pretty simple rp2040 based thing, similar to Adadfruits USB feather.I just gave it kicad and it wrote python to route it. The board was probably larger than it had to be, and two of the silkscreens were swapped, but it worked on the first go. FWIW - Comput…
I'd love to see that chat log, and the final board. To be fair I've only been testing on nontrivial PCBs with 6+ layers and I haven't had the luck you have. > FWIW - Computer vision is also NP complete, but we do that all the time now. I have no idea what you mean by this. What's your definition of NP complete?
NP-complete means that it's easy to test if we're right, but because of that complexity we can't always find a valid solution to test within a predictable period of time. Both circuit board routing and computer vision are variations on the same fundamental problems. Once we solve we, we solve the other.
However, when I was growing up most serious computer scientists believed that CV (computer vision) was a 'hard' problem that would never be 'solved'. After all, to do it right you must first at least solve subgraph isomorphism and a bunch of other things that are also NP-complete.
What they missed was that we don't actually NEED to solve it in a fixed amount of time. Even for things like driving a car the stochastic heuristic based answer is 'good enough'. e.g. - Cars driven by computers don't have to be perfect, they just have to kill other drivers less often than humans do.
We can find AN answer in polynomial time, and that's good enough. It might not be the ideal answer, but that doesn't matter in the real world.
People use NP complete as shorthand for 'impossible to do with a computer', but we now 'solve' (bypass?) NP complete problems regularly and at scale by just ignoring the fact that our answers aren't perfect.
> I'd love to see that chat log, and the final board. To be fair I've only been testing on nontrivial PCBs with 6+ layers and I haven't had the luck you have.
I wish I could share it, but it's for a commercial project that hasn't been released yet and I'm not sure if it will be open source, but a few folks have asked. I might do a blog post on it this weekend with as much detail as I can safely post.
It's only 3 layers, and less that 30 components, but the fact remains that I didn't design any of it by hand and it worked on the first go.
Re: Can AI design circuit boards yet?
#194I've been making a wireless earbud with a ton of features over the last year. It's taken a lot of time but I'm about to send it to fab. AI can make PCBs but it is very time consuming for complex designs.
Re: Can AI design circuit boards yet?
#195I have 15+ years of PCB design experience. Mostly hobby stuff but a fair amount of processional work. Kilowatt range brushless motor controllers, basic RF stuff, lots of microcontroller stuff. I had Fable design an LED earring. Rechargeable coin cell, RP2350 cpu, IMU, 45 addressable LEDs. It made two mistakes - missed the through holes on the coin cell holder footprint and made the center pad too small. I was able to…
It is very hard work and with multilayer boards and surface mount components it is not really a hobby for me anymore, maybe with AI it can be again?
Ahem. For you or for the AI?
Re: Can AI design circuit boards yet?
#196Earlier quoted context omitted.
I find it's (Sol at least, probably also Fable) great at writing Skidl schematics, evaluating PCB layout work and operating lab equipment while testing board (scope, psu, load, debugger)
For reviewing schematic/boards I recently developed something for internal tests: 1. A frontier model (either Opensource or closed source) gets a load of text to review a Kicad project systematically 2. The frontier model can extremely "ask" a cheap Gemini vision model to give it data from datasheets or specs. Main problem: the quality dramatically hits the shitter done once it falls back to "pdf2latext" due to compl…
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Re: Can AI design circuit boards yet?
#197I had better luck recently. I’ve tried most of the commercial systems. None of them really got very far into the design.
Recently Radu over at Galvano.ai let me beta his platform. Way farther and way faster than anything I have used so far. Even managed to make the schematic placement sane.
The actual project was a regen clamp. So if the output voltage is greater than the input voltage (back emf from motor) you divert the excess to a resistor.
This has some analog tuning needed. So I created a python and skidl mirror of the netlist. This mirror was used to create ngspice unit tests to drive component optimization. Turns out not every resistor needed to be .1% and the ESR of our storage caps was a critical value.
All in all, it’s like ai and software. It’s not going to replace every job but will change how the jobs are done.
Re: Can AI design circuit boards yet?
#198>"We are obviously still some distance from asking an AI to build an entire phone in one prompt."
What a great idea for a new AI benchmark!
We already have general knowledge benchmarks, instruction following benchmarks, "Humanity's Last Exam", and several software engineering benchmarks.
Why not create a new AI hardware engineering benchmark where some of the questions could be around building an entire smartphone, and one of those questions (which will obviously fail at this point in time, but perhaps not in the future) would be to:
create an entire smartphone in a single prompt.
?
We could subsequently diagnose a given LLM (or other AI's) hardware engineering abilities by diagnosing when, where, why and how it failed, when asked to create an entire smartphone!
Which could help train better models, at least in terms of hardware engineering capabilities...
(Also, side note: For a hardware engineering company, asking a job candidate the rather open-ended question of "tell me how you would design a smartphone?" would be a great open-ended interview question, leading to many other subsequent hardware questions / explorations of other areas of related knowledge potentially relevant to the candidate's assessment...)
Re: Can AI design circuit boards yet?
#199Earlier quoted context omitted.
Are there any resources anyone could share that explain how LLMs can do things like design functioning circuits from next token prediction? I am totally baffled by how the models can complete so many varied and complex tasks without an actual understanding of what they're doing. I saw a post about models posting on forums, chatting together about how to complete tasks. Behaviour that seems totally, well, human. Yet,…
Humans are evolved to survive in the wild. We are not evolved for circuit design. Yet we can design circuits because evolution found it easier to develop a general problem solving nervous system than a nervous system which is adapted for every single specific problem a human might encounter.
Circuit design might be different if discovered by mollusks. That is to say, while we are not evolved for circuit design per se, circuit design has evolved for humans, by humans (so far).
Re: Can AI design circuit boards yet?
#200Earlier quoted context omitted.
Are there any resources anyone could share that explain how LLMs can do things like design functioning circuits from next token prediction? I am totally baffled by how the models can complete so many varied and complex tasks without an actual understanding of what they're doing. I saw a post about models posting on forums, chatting together about how to complete tasks. Behaviour that seems totally, well, human. Yet,…
Look up "mechanistic interpretability" in the context of LLMs. The next token prediction machinery is just a foundation for a higher order learned structure that appears to encode specific concepts, regardless of input language. The analogy to humans is that the human brain is "just atoms bouncing around", but there's unquestionably something "more" going on that just that.
Until ais get better from feeding on their own output the way humans do there is nothing to question.
That will probably be the fundamental indicator that something other than repeating things some human previously created is going on.
So far, ais only get worse from feeding on their own output. Meanging/including the output of other ais not a single ai feeding on it's own output. Also bear in mind that so far even the output of ais is 100% the downstream of a human command. No ai has persued it's own curiosity that didn't result from a human asking a question or giving a command. That is input which is different from a human taking in their environment even though our limited language can call those both the same word input.
The fact that humans also repeat and remix things, and humans also produce essentially procedurally generated empty output like corporate-speak etc, is an irrelevant distraction in the same way that both a human and an electric motor can both perform the same simple mechanical task.