Sure, this will end well lol
Testing Generative AI for Circuit Board Design
131–140 of 180 posts
Re: Testing Generative AI for Circuit Board Design
#132I 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
Depends on the website, right. Because a single index.html can easily be a website which it cam generate.
Re: Testing Generative AI for Circuit Board Design
#133Earlier quoted context omitted.
Why do people think inserting an LLM into the mix will make it better than just an evolutionary or reinforcement model applied? Who cares if you can talk to it like a human?
Yeah, when the author was writing about that initial query about delay-per-unit-length, I'm thinking: "This doesn't tell us whether an LLM can apply the concepts, only whether relevant text was included in its training data." It's a distinction I fear many people will have trouble keeping in-mind, faced with the misleading eloquence of LLM output.
I think you are looking at the term generalizing and memorisation.
It have been shown that LLM generalize, what is important to know is if they generalized it or memorized it.
Re: Testing Generative AI for Circuit Board Design
#134Earlier quoted context omitted.
What goals were achieved that I missed? Even for creative writing and image creation it still requires significant human guidance and correction.
This is a great example of goalposts shifting. Even having a model that can engage in coherent conversation and synthesize new information on the fly is revolutionary compared to just a few years ago. Now the bar has moved up to creativity without human intervention.
But isn't this goalpost shifting actually reasonable?
We discovered this nearly-magical technology. But now the novelty is wearing off, and the question is no longer "how awesome is this?". It's "what can I do with it for today?".
And frustratingly, the apparent list of uses is shrinking, mostly because many serious applications come with a footnote of "yeah, it can do that, but unreliably and with failure modes that are hard for most users to spot and correct".
So yes, adding "...but without making up dangerous nonsense" is moving the goalposts, but is it wrong?
Re: Testing Generative AI for Circuit Board Design
#135I 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 problem is going to be getting those functional blocks in the first place.
The industry does not like sharing, and the openly available datasets are full of mistakes. As a junior EE you learn quite quickly to never trust third-party symbols and footprints - if you can find them at all. Even when they come directly from the manufacturer there's a decent chance they don't 100% agree with the datasheet PDF. And good luck if that datasheet is locked behind a NDA!
If we can't even get basic stuff like that done properly, I don't think we can reasonably expect manufacturers to provide ready-to-use "building blocks" any time soon. It would require the manufacturers to invest a lot of engineer-hours into manually writing those, for essentially zero gain to them. After all, the information is already available to customers via the datasheet...
Re: Testing Generative AI for Circuit Board Design
#136Just 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.
As long as you are OK with destructive methods, grinding/sanding the board down gives you all layers. "PCB delayering" is the search term.
Re: Testing Generative AI for Circuit Board Design
#137Earlier quoted context omitted.
> 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.
These are tools. Humans driving the tools have heart and soul and create things of value through their lens. Your argument rhymes with: - "Let's keep using horses. They're good enough." - "Photography lacks the artistic merit of portrait art." - "Electronic music isn't music." - "Vinyl is the only way to listen to music." - "Digital photography ruins photography." - "Digital illustration isn't real illustration and t…
Surely there's some point where it ceases being a tool though. We can't both be making AIs out to be comparable to humans while simultaneously calling them tools. Otherwise people who commission art would be considered artists using a tool.
Re: Testing Generative AI for Circuit Board Design
#138TBH the LLM seems worse than useless for a lot of these tasks - entering a netlist from a datasheet is tedious, but CHECKING a netlist that's mostly correct (except for some hallucinated resistors) seems even more tedious.
Re: Testing Generative AI for Circuit Board Design
#139Earlier quoted context omitted.
There are recent papers based on diffusion that perform quite well. Here's an example of a recent paper https://arxiv.org/pdf/2406.01661 . I am also working on ML-based CO. My approach has a close 1% gap on hard instances with 800-1200 nodes and less than 0.1% for 200-300 nodes on Maximum Cut, Minimum Independent Set, and Maximum Clique problems. I think these are very promising times for neural network-based discret…
Thanks, will try to give it a read this weekend. Would you say that diffusion is the architectural change that opened up CO for neural nets? Haven't followed this particular niche in a while
I believe it helps but not the sole reason. Because there are also autoregressive models that perform slightly worse. Unsupervised learning + Diffusion + Neural Search is the way to go in my opinion. However, currently, the literature lacks efficient Neural search space exploration. The diffusion process is a good starting point for neural search space exploration, especially when it is used not just to create a solution from scratch but also as a local search method. Still, there is no clear exploration and exploration control in current papers. We need to incorporate more ideas from heuristic search paradigms to neural network CO pipelines to take it to the next step.
Re: Testing Generative AI for Circuit Board Design
#140Earlier quoted context omitted.
And both flavors have a base flavor of excrement... Still, since I started using Claude 3 Opus (and now 3.5 Sonnet) a couple of months back, I don't see myself switching from them nor stopping use of LLM-based AI tech; it's just made me feel like the computer is actually working for and with me and even that alone can be enough to get me motivated and accomplish what I set out to do.
"it's just made me feel like the computer is actually working for and with me and even that alone can be enough to get me motivated and accomplish what I set out to do." This is a great way to describe what I've been feeling / experiencing as well.
Just an update on my initial impressions of Claude 3.5 Sonnet. It's a better programmer than I am in Python; that's not saying much, but this is now two nights in a row I've been impressed with what I've created with it.