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Comment by d_burfoot | Hacker News Reader

I don't know about this project specifically, but this kind of work is soon going to be tremendously valuable because of AI. Instead of engineers designing products directly, they will build a simulator, write an objective function, and submit this data to a general purpose ML/RL API hosted by one of the big labs. The AI will run a billion simulations and use RL to create a design that optimizes the objective function.

Simulate Literally Everything!

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I'm not so sure about this. We are not even the point where auto placement and routing for PCB is there. And the reason is simple, the amount of constraints required is just too much work to put in for a person. They may as well do it themselves at that point.

I would expect most design is like this. There are thousands of constraints a designer has in the back of their head, most they are not even consciously aware of. The optimization of the objective is the trivial part. Defining the proper objective function will be very hard.

This is actually one of the scenarios where AI (I just mean machine learning) would have a real value proposition, because of the need to infer the implicit constraints from many example circuits. Figuring out all the things that people think are obvious, but that take too long to input, is kind of the thing AI is useful for.

It's been tried. PCB design is a huge industry. And it has just not worked. I was of the same opinion you have but it's not like there has not been millions and millions invested into this without real impact. Every year there is a new sway of companies that tries. Perhaps AI is now good enough, I'm not holding my breath.

It's also been tried in the mechanical world ("Generative Design" in Autodesk's language) and it's still mostly in the "cool demo, bro" phase. The parts end up being expensive and difficult to manufacture due to the unusual geometry. You're penalized for exploring the design space because it runs on cloud credits (more exploration == more cost). Just not very compelling yet.

You could argue that millions and millions isnt enough, but leveraging the billions spent on AI might change things.

I'm not holding my breath either though.

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