Ah, yes, "confident" and "wrong" is exactly the combination I need when designing with lethal voltages. /s
ChatGPT for Hardware Design
131–140 of 165 posts
Re: ChatGPT for Hardware Design
#132Earlier quoted context omitted.
The last time I tried to evaluate it was a long time ago and it seemed to be all svg uploads. I had to re-read the docs more closely after reading your comment. It says you need to enter svg only for non-rectangular symbols, but it's not clear if you can create or modify a pad shape other than circular or rectangular from within the tool. Obviously good progress, and more than I understood when I wrote my previous co…
Thanks for giving us another shot The circular and rectangular options have a bunch of transformations available…you can make turn circles into oblong shapes simple by providing async size value and you can set a corner radius for rectangular pads and even your layout. And as you probably saw you can load symbols as svg and you can also load custom pad, layout and silk shapes either as svg or dxf Less known but also…
In that case, the docs don't really do justice to it. They still read as if many features don't exist yet.
Re: ChatGPT for Hardware Design
#133Senior EE here! I'm not at all impressed with this page because you don't show the tool doing anything interesting. All your examples are undergrad-course or lower level of difficulty. I feel like reading several of the tool's responses actually wasted my time because it took longer for me to read the text than to come up with a better answer. (Though admittedly I've been at this a while. And the check-if-I-screwed-u…
So, kinda the same level for software development. But people keep repeating that I will be unemployed within 1 year.
Re: ChatGPT for Hardware Design
#134Earlier quoted context omitted.
I have no idea what you're talking about, but my experience 100% mirrors yours in most cases as a programmer. GPT-4 produces a lot of my code now. I'm leap-frogging my team a bit in productivity because they still don't like it, but it's so close to being undeniable.
I don't get this. I asked GPT-4 to help me build a machine learning program for historical stock prices. It spat back about 8 errors, functions that don't exist, nothing compiled, multiple logic flaws... Which one of us is lying?...
Maybe he just writes really really really simple code all day and faked his way into a developer position? And then his team mates have to fix/redo anything he does?
I've seen it happen several times.
Re: ChatGPT for Hardware Design
#135How do I exclude my account?
Re: ChatGPT for Hardware Design
#136Senior EE here! I'm not at all impressed with this page because you don't show the tool doing anything interesting. All your examples are undergrad-course or lower level of difficulty. I feel like reading several of the tool's responses actually wasted my time because it took longer for me to read the text than to come up with a better answer. (Though admittedly I've been at this a while. And the check-if-I-screwed-u…
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.
Re: ChatGPT for Hardware Design
#137Senior EE here! I'm not at all impressed with this page because you don't show the tool doing anything interesting. All your examples are undergrad-course or lower level of difficulty. I feel like reading several of the tool's responses actually wasted my time because it took longer for me to read the text than to come up with a better answer. (Though admittedly I've been at this a while. And the check-if-I-screwed-u…
> I'm not at all impressed with this page because you don't show the tool doing anything interesting.
a) has there been anything like this before?
b) give it a year and see what it does
Re: ChatGPT for Hardware Design
#138Earlier quoted context omitted.
When I go here: https://openai.com/product/gpt-4 it says "try on chatgpt plus" and sends me to the same page I log in with and that's where I've been testing it.
Be sure that you select GPT-4 from the drop down list of models. For each new chat, it reverts back to default GPT-3.5.
I don't see any dropdowns for such a thing.
Re: ChatGPT for Hardware Design
#139Senior EE here! I'm not at all impressed with this page because you don't show the tool doing anything interesting. All your examples are undergrad-course or lower level of difficulty. I feel like reading several of the tool's responses actually wasted my time because it took longer for me to read the text than to come up with a better answer. (Though admittedly I've been at this a while. And the check-if-I-screwed-u…
Not a senior EE, but equally unimpressed. The thing about LLM is that it answers based on data it has seen before. So if enough posts on stackoverflow in 2021 claimed mps340 is the best CPU for beginners, that's what the AI will recommend. There are 3 problems with this: it can and will be gamed, it is usually more conservative and not on the bleeding edge, and finally you can't ask questions you did't know you neede…
> The thing about LLM is that it answers based on data it has seen before.
Modern LLMs are able to perform web searches to make decisions on contemporary data. Once they have proper API support your concerns should be resolved, hopefully in a few weeks.
> reliablity and safety issues.
The solution to this is fine tuning / RHLF. OpenAI have done a pretty extensive job at getting political safety for ChatGPT with RHLF. It seems reasonable that RHLF could achieve a similar result in the hardware domain.
> you can't ask questions you did't know you needed ....
Solvable by prompt engineering. You can wrap user input in a prompt. As a toy example: "Here is user input $userInput if you have safety concerns about their project please respond with questions you think the user forgot to ask". Might also be possible to tweak with fine tuning/RHLF.
Re: ChatGPT for Hardware Design
#140Senior EE here! I'm not at all impressed with this page because you don't show the tool doing anything interesting. All your examples are undergrad-course or lower level of difficulty. I feel like reading several of the tool's responses actually wasted my time because it took longer for me to read the text than to come up with a better answer. (Though admittedly I've been at this a while. And the check-if-I-screwed-u…
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 specifi…
> 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.)