AI learns the “dark art” of RFIC design

Now let's get them to come up with a valid design including a valid QR code. Maybe one containing Maxwell's equations.

Reminds me of good ol genetic algorithm search. Guess and check can be quite powerful, especially if you can toss in agent in the loop guidance.

https://en.wikipedia.org/wiki/Evolved_antenna

I wonder if our common expectation that true theories somehow had to be beautiful and elegant is going to survive the coming century. What if "real" nature phenomenon were actually best described by horrible mess of impossible equations, that only machines could actually manipulate and reason about ?

That would be really sad..

One great application of AI design is patent poisoning. Use AI to churn out masses of variant designs, make them publicly visible on a web site, and if future patents come out use any collisions to invalidate them or at least restrict their scope (generalization of a patent is limited by prior art.)

"Humans couldn't even imagine" seems like overselling it, but I'm sure that machine learning algorithms can brute force their way to chip designs no one has tried before and that some of those might be useful to us. That seems like a pretty reasonable thing for a computer to do.

I’m a bit frustrated. AI can do a looot of things; but I think as we continue to muddy the waters between LLMs and more traditional machine learning like Monte Carlo, Genetic Algoriths, Expert Systems and other Statistics magic tricks, we’re too aggressively conflating established and morally neutral activities in ML with the concerns that people have about LLMs and Stable Diffusion.

Though I also imagine that that is the point.

One takeaway from the article is that they had to get rid of the tried and tested fundamental building blocks of chip design to generate this advancement. I wonder if the same applies for mundane coding. Are the incredible innovations in AI coding actually hampered by rust and python? Should we let AI tools just code in the lowest level possible?

Reminds me of this old article - https://www.damninteresting.com/on-the-origin-of-circuits/

One of my favorite little morsels of internet goodness.

the biggest question for me is how robust are these designs.

in the journal articles they did show measurements of real devices which agreed fine with predictions, but i didn't find them addressing it explicitly in the text. also, some systems they presented contained subblocks that were conventionally designed that could be carrying some of the weight.

or maybe i'm just sour that they're coming for my job? or maybe that's what they want us to think?

i think what wins in practice is simple ideas that can work in spite of all manufacturing and environment variations, and model limitations -- think stuff like feedback and symmetry. and what they show here is the opposite of that. i've done blind optimization of circuit parameters some times only to end up realizing some pretty simple such ideas that i'd missed (like "you need symmetry here" or "you just need more bandwidth here") and made complete sense when you thought about them. so i wonder if we can't tweak a few pixels in their structures and reveal something simpler.

also, obligatory mention: "genetic antennas"

It's not really that magical. As TFA points out, RFIC design, way beyond normal RF engineering, is close to black magic that relies a lot on the knowledge and experience of the designer, assisted by what would have been supercomputer-level-a-few-decades-ago modelling and design tools. What AI can do is a breadth-first exploration of all possible outcomes and then pick the best-performing one rather than the human-level "this seems like a good path to go down, let's explore it further".

The methods outlined in this article aren't new. Scientists were using "genetic algorithms" to design antennas that weren't understood by anyone, but worked well, decades ago.

> That’s not even to speak of all the movie plots that would have been ruined.

I clicked on all the links. Pretty much all of those movies could still work with wired technology. Even the one called cellular, in which a woman is trapped in an attic with a broken landline phone and manages to connect wires and dial a random number.

Yes I'm nitpicking. I guess I'm glad we have Wi-Fi and all, but don't try to sell me on it as a crucial plot device

I work in a related field and “inverse” design is what this is called. Such designs usually are not manufacturable. I’m not too worried about my iob.

That said we’ve had some success internally having Claude do parameter sweeps

Ai can’t even place and route a two layer board with a microcontroller and a few peripherals.

Chips? I've tried to task Opus, Gemini and Codex with a simple PCB. All of them placed holes correctly but can't understand that the traces should not cross physically.

Hopefully one day AI will design away the need for popups and other-things-that-prevent-you-from-reading-the-damn-article.

The comments here are trending towards "There's nothing new here, I could design 5g radio chips with a cheap linux box running FTP".

I did my PhD on inverse design of electromagnetic structures. I really hate that we're calling this AI when there isn't any training, really.

In case anyone feels déjà vu, Popular Mechanics wrote about this professor's lab in Jan 2025, with almost the same title: "AI Designed Computer Chips That the Human Mind Can't Understand".

I feel a bit of unease when I read this title, not because of the threat of AI, but because the prevailing aphorism that "RF is black magic" is a slap in the face to the millions of physicists and RF engineers who DO understand every bit of this. It's a fun harmless anti-intellectual saw that I don't believe is harmless at all. We need more RF engineers and telling people it's all "black magic" and "wizardry" (and worst of all, saying "even RF engineers don't understand RF") makes it seem like it's not worth studying.

I don’t know. I can imagine quite a bit.

If you don't know how it works, then you don't know that it works.

We have always known the old trick of genetic algorithms to produce better radio chips.

The problem isn’t the design: its manufacturing restraints.

This is nothing new or impressive.

But is this AGI?

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I am confused, every day I read on HN that AI's can just interpolate the data they have seen in training, and that they are structurally incapable of coming up with something new, creative and not in the training distribution.