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Testing Generative AI for Circuit Board Design

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Re: Testing Generative AI for Circuit Board Design

#81

Post by shermantanktop »

refulgentis wrote: post #75
surfingdino wrote: post #45

Earlier quoted context omitted.

> This feels like an excellent demonstration of the limitation of zero-shot LLMs. It feels like the wrong way to approach this. There is one posted on HN every week. How many more do we need to accept the fact this tech is not what it is sold at and we are bored waiting for it get good? I am not say "get better", because it keeps getting better, but somehow doesn't get good.

There's this odd strain of thought that there's some general thing that will pop for hucksters and the unwashed masses, who are sheep led along by huckster wolves who won't admit LLMs aint ???, because they're profiting off it It's frustrating because it's infantalizing, it derails the potential of an interesting technical discussion (ex. Here, diffusion), and it misses the mark substantially. At the end of the day,…

So what should we make of the presence of actual hucksters and actual senior execs who are acting like credulous sheep? I see this every day in my world.

At the same time I do appreciate the actual performance and potential future promise of this tech. I have to remind myself that the wolf and sheep show is a side attraction, but for some people it’s clearly the main attraction.

Re: Testing Generative AI for Circuit Board Design

#82

Post by rzzzt »

cjk2 wrote: post #7

Ex EE here > The AI generated circuit was three times the cost and size of the design created by that expert engineer at TI. It is also missing many of the necessary connections. Exactly what I expected. Edit: to clarify this is even below the expectations of a junior EE who had a heavy weekend on the vodka.

I read an article on evolutionary algorithm-based designs a long time ago -- they are effectively indecipherable by humans and rely on the imperfections of the very FPGA that they are synthesized on, but work great otherwise.

- https://www.damninteresting.com/on-the-origin-of-circuits/

- https://www.sciencedirect.com/science/article/abs/pii/S03784...

Re: Testing Generative AI for Circuit Board Design

#83

Post by robxorb »

DHaldane wrote: post #54
neltnerb wrote: post #40

Earlier quoted context omitted.

I think the only bit that looked handy in there would be if it could parse PDF datasheets and help you sort them by some hidden parameter. If I give it 100 datasheets for microphones it really should be able to sort them by mechanical height. Maybe I'm too optimistic. The number of times I've had to entirely redo a circuit because of one misplaced connection, yeah, none of those circuits worked for any price before I…

Agree that PDF digesting was the most useful. I think Gemini could definitely do that microphone study. Good test case! I remember spending 8 hours on DigiKey in the bad old times, looking for an audio jack that was 0.5mm shorter.

Anyone looking for an idea for something potentially valuable to make: ingest PDF datasheets and let us search/compare etc, across them. The PDF datasheet is possibly one of the biggest and most unecessary hurdles to electronics design efficiency.

Re: Testing Generative AI for Circuit Board Design

#84

Post by ben_w »

exe34 wrote: post #65
surfingdino wrote: post #45

Earlier quoted context omitted.

> This feels like an excellent demonstration of the limitation of zero-shot LLMs. It feels like the wrong way to approach this. There is one posted on HN every week. How many more do we need to accept the fact this tech is not what it is sold at and we are bored waiting for it get good? I am not say "get better", because it keeps getting better, but somehow doesn't get good.

how long does it take for a child to start doing surgery? publishing novel theorems? how long has the humble transformer been around?

Wall-clock or subjective time?

I think it would take a human about 2.6 million (waking) years to actually read Common Crawl[0]; though obviously faster if they simply absorb token streams as direct sensory input.

The strength of computers is that transistors are (literally) faster than synapses to the degree to which marathon runners are faster than continental drift; the weakness is they need to, too — current generation AI is only able to be this good due to this advantage allowing it to read far more than any human.

How much this difference matters depends on the use-case: if AI were as good at learning as we are, Tesla's FSD would be level 5 autonomy years ago already, even with just optical input.

[0] April 2024: 386 TiB; assuming 9.83 bits per word and 250 w.p.m: https://www.wolframalpha.com/input?i=386+TiB+%2F+9.83+bits+p...

Re: Testing Generative AI for Circuit Board Design

#85

Post by kristopolous »

Just the other day I came up with an idea of doing a flatbed scan of a circuit board and then using machine learning and a bit of text promoting to get to a schematic

I don't know how feasible it is. This would probably take low $millions or so of training, data collection and research to get not trash results.

I'd certainly love it for trying to diagnose circuits.

It's probably not really that possible even at higher end consumer grade 1200dpi.

Re: Testing Generative AI for Circuit Board Design

#86

Post by slg »

makk wrote: post #60
surfingdino wrote: post #45

Earlier quoted context omitted.

> This feels like an excellent demonstration of the limitation of zero-shot LLMs. It feels like the wrong way to approach this. There is one posted on HN every week. How many more do we need to accept the fact this tech is not what it is sold at and we are bored waiting for it get good? I am not say "get better", because it keeps getting better, but somehow doesn't get good.

That’s a perception and the problem isn’t the AI it’s human nature: 1. every time AI is able to do a thing we move the goalposts and say, yeah, but it can’t do that other thing over there; 2. We are impatient, so our ability to get bored tends to outpace the rate of change.

I don’t think the problem is moving the goalposts, but rather there are no actual goalposts. Advocates for this technology imply it can do anything either because they believe it will be true in the near future or they just want others to believe it for a wide range of reasons including to get rich of it. Therefore the general public has no real idea what the ideal use cases are for this technology in its current state so they keep asking it to do stuff it can’t do well. It is really no different than the blockchain in that regard.

Re: Testing Generative AI for Circuit Board Design

#87

Post by cmbuck »

kristopolous wrote: post #85

Just the other day I came up with an idea of doing a flatbed scan of a circuit board and then using machine learning and a bit of text promoting to get to a schematic I don't know how feasible it is. This would probably take low $millions or so of training, data collection and research to get not trash results. I'd certainly love it for trying to diagnose circuits. It's probably not really that possible even at highe…

This would be an interesting idea if you were able to solve the problem of inner layers. Currently to reverse engineer a board with more than 2 layers an x-ray machine is required to glean information about internal routing. Otherwise you're making inferences based on surface copper only.

Re: Testing Generative AI for Circuit Board Design

#88

Post by wruza »

shermantanktop wrote: post #81
refulgentis wrote: post #75

Earlier quoted context omitted.

There's this odd strain of thought that there's some general thing that will pop for hucksters and the unwashed masses, who are sheep led along by huckster wolves who won't admit LLMs aint ???, because they're profiting off it It's frustrating because it's infantalizing, it derails the potential of an interesting technical discussion (ex. Here, diffusion), and it misses the mark substantially. At the end of the day,…

So what should we make of the presence of actual hucksters and actual senior execs who are acting like credulous sheep? I see this every day in my world. At the same time I do appreciate the actual performance and potential future promise of this tech. I have to remind myself that the wolf and sheep show is a side attraction, but for some people it’s clearly the main attraction.

Why should we even?

The problem with everything today is not only that it’s hype-centric, but that that carries away those who were otherwise reasonable. AI isn’t any special in this regard, it’s just “crypto” of this decade.

I see this trend everywhere, in tech, socio, markets. Everything is way too fake, screamy and blown out of proportion.

Re: Testing Generative AI for Circuit Board Design

#89

Post by slg »

echelon wrote: post #72
surfingdino wrote: post #45

Earlier quoted context omitted.

> This feels like an excellent demonstration of the limitation of zero-shot LLMs. It feels like the wrong way to approach this. There is one posted on HN every week. How many more do we need to accept the fact this tech is not what it is sold at and we are bored waiting for it get good? I am not say "get better", because it keeps getting better, but somehow doesn't get good.

I'm in awe of the progress in AI images, music, and video. This is probably where AI shines the most. Soon everything you see and hear will be built up through a myriad of AI models and pipelines.

> Soon everything you see and hear will be built up through a myriad of AI models and pipelines.

It is so bizarre that some people view this as a positive outcome.

Re: Testing Generative AI for Circuit Board Design

#90

Post by nurple »

AdamH12113 wrote: post #69
bmicraft wrote: post #43

Earlier quoted context omitted.

It would seem to me that the majority of boards would be a lot more forgiving. Are you saying you wouldn't be impressed if it could do only say 70% of board designs completely?

Not the GP, but as an EE I can tell you that the majority of boards are not forgiving. One bad connection or one wrong component often means the circuit just doesn't work. One bad footprint often means the board is worthless. On top of that, making an AI that can regurgitate simple textbook circuits and connect them together in reasonable ways is only the first step towards a much more difficult goal. More subtle pro…

I hate that this is true. I think ML itself could be applied to the problem to help you catch mistakes in realtime, like language servers in software eng.

I have experience building boards in Altium and found it rather enjoyable; my own knowledge was often a constraint as I started out, but once I got proficient it just seemed to flow out onto the canvas.

There are some design considerations that would be awesome to farm out to genai, but I think we are far from that. Like stable-diffusion is to images, the source data for text-to-PCB would need to be well-labeled in addition to being correllated with the physical PCB features themselves.

The part where I think we lose a lot of data in pursuit of something like this, is all of the research and integration work that went on behind everything that eventually got put into the schematic and then laid out on a board. I think it would be really difficult to "diffuse" a finished PCB from an RFQ-level description.

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