Can we have an AI that reads datasheets and produces Spice circuits? With the goal of building a library of simulation components.
That's the kind of thing where verification is really hard, and things will look plausible even if incorrect.
Testing Generative AI for Circuit Board Design
101–110 of 180 posts
Re: Testing Generative AI for Circuit Board Design
#102Earlier 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.
They already are, when using the meaning of "AI" that I grew up with.
The Facebook feed is AI; Google PageRank is AI; anti-spam filters are AI; A/B testing is AI; recommendation systems are AI.
It's been a long time since computers took over from humans with designing transistor layouts in CPUs — I was hearing about the software needing to account for quantum mechanics nearly a decade ago already.
Re: Testing Generative AI for Circuit Board Design
#103Just 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.
Maybe not. I scanned a bluetooth aux transceiver yesterday as a test of how well a flatbed can pick up details. There's a bunch of these on the market and the cheap ones, they are more or less equivalent. It's a CSR 8365 based device, which you can read from the scan. The industry is generally convergent on the major design decisions for some hardware purpose for some given time period.
And the devices, in this case, bluetooth aux transceivers, they all do the same things. They've even more or less converged on all being 3 buttons. When optimizing for cost reduction with the commodity chips that everyone is using to do the same things, the manufacturer variation isn't that vast.
In the same way you can get 3d models from 2d photos because you can identify the object based on a database of samples and then guess the 3d contours, the hypothesis to test is whether with enough scans and schematics, a sufficiently large statistical model will be good enough to make decent guesses.
If you've got say 40 devices with 80% of the same chips doing the same things for the same purpose, a 41st device might have lots of guessable things that you can't necessarily capture on a cheap flatbed
This will probably work but it's a couple million away from becoming a reality. There's shortcuts that might make this a couple $100,000s project (essentially data contracts with bespoke chip printers) but I'd have to make those connections. And even then, it's just a hobbyist product. The chances of recouping that investment is probably zero although the tech would certainly be cool and useful. Just not "I'll pay you money" level useful.
Re: Testing Generative AI for Circuit Board Design
#104Earlier 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.
[deleted]
Re: Testing Generative AI for Circuit Board Design
#105Earlier quoted context omitted.
The other side of this coin is everyone overhyping what AI can do, and when the inevitable criticism comes, they respond by claiming the goal posts are being moved. Perhaps, but you also told me it could do XYZ, when it can only do X and some Y, but not much Z, and it’s still not general intelligence in the he broad sense.
I appreciate this comment because I think it really demonstrates the core problem with what I'll call the "get off my lawn >:|" argument, because it's avowedly about personal emotions. It's not "general intelligence", so it's over hyped, and They get so whiny about the inevitable criticism, and They are ignoring that it's so mindnumbingly boring to have people making the excuse that "designed a circuit board from scr…
> Who told you LLMs are [artificial] general intelligence?
*waves*
Everyone means a different thing by each letter of AGI, and sometimes also by the combination.
I know my opinion is an unpopular one, but given how much more general-purpose they are than most other AI, I count LLMs as "general" AI; and I'm old enough to remember when AI didn't automatically mean "expert level or better", when it was a surprise that Kasparov was beaten (let alone Lee Sedol).
LLMs are (currently) the ultimate form of "Jack of all trades, master of none".
I'm not surprised that it failed with these tests, even though it clearly knows more about electronics than me. (I once tried to buy a 220 kΩ resistor, didn't have the skill to notice the shop had given me a 220 Ω resistor, the resistor caught fire).
I'd still like to call these things "AGI"… except for the fact that people don't agree on what the word means and keep objecting to my usage of the initials as is, so it would't really communicate anything for me to do so.
Re: Testing Generative AI for Circuit Board Design
#106I work on generative AI for circuit board design with tscircuit, IMO it's definitely going to be the dominant form of bootstrapping or combining circuit designs in the near future ( Most people are wrong that AI won't be able to do this soon. The same way you can't expect an AI to generate a website in assembly, but you CAN expect it to generate a website with React/tailwind, you can't expect an AI to generate circui…
> The same way you can't expect an AI to generate a website in assembly, but you CAN expect it to generate a website with React/tailwind
Can you? Because last time I tried (probably about February) it still wasn’t a thing
Re: Testing Generative AI for Circuit Board Design
#107Earlier quoted context omitted.
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 gener…
Subjective time doesn't really matter unless something is experiencing it. It could be 2.6 million years, but if the wall-clock time is half a year, then great - we've managed to brute-force some degree of intelligence in half a year! And we're at the beginning of this journey; there surely are many things to optimize that will decrease both wall-clock and subjective training time.
As the saying goes - "make it work, make it right, make it fast".
Re: Testing Generative AI for Circuit Board Design
#108Earlier quoted context omitted.
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.
The wolves/sheep thing was to indicate how moralizing and infantalizing serves as a substitute for actually explaining what the problem is, because surely, it's not that the prose machine isn't doing circuit design. I'm sure you see it, I'd just love for someone to pause their internal passion play long enough to explain what they're seeing. Because I refuse to infantalize, I refuse to believe it's just grumbling bec…
I am literally right now explaining to a senior exec why some PR hype numbers about developer productivity from genAI are not comparable to internal numbers, because he is hoping to say to his bosses that we’re doing better than others. This is a smart, accomplished person, but he can read the tea leaves.
The problem with hype is that it can become a pathological form of social proof.
Re: Testing Generative AI for Circuit Board Design
#109I had it generate some opencad but never looked into it further.
Re: Testing Generative AI for Circuit Board Design
#110Earlier quoted context omitted.
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.
The wolves/sheep thing was to indicate how moralizing and infantalizing serves as a substitute for actually explaining what the problem is, because surely, it's not that the prose machine isn't doing circuit design. I'm sure you see it, I'd just love for someone to pause their internal passion play long enough to explain what they're seeing. Because I refuse to infantalize, I refuse to believe it's just grumbling bec…
I’ll play along. The thing that’s annoying me lately is that session details leaking between chats has been enabled as a “feature”, which is quickly making ChatGPT more like the search engine and social media echo chambers that I think lots of us want to escape. It’s also harmful for the already slim chances of having reproducible / deterministic results, which is bad since we’re using these things for code generation as well as rewriting emails and essays or whatever.
Why? Is this naive engineering refusing to acknowledge the same old design flaws? Nefarious management fast tracking enshittification? Or do users actually want their write-a-naughty-limerick goofs to get mixed up with their serious effort to fast track circuit design? I wouldn’t want to appear cynical but one of these explanations just makes more sense than the others!
The core tech such as it is is fine, great even. But it’s not hard to see many different ways that it’s already spiraling out of control.