Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

AI learns the “dark art” of RFIC design

spectrum.ieee.org

Post reply on HN
Print view View original

91–100 of 194 posts

Re: AI learns the “dark art” of RFIC design

#91

Post by ambicapter »

bsaul wrote: post #83

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..

The "common expectation" I think, misses the point. The idea isn't that fundamental theories are simple or elegant (quantum physics equations are pretty darn ugly), it's that, given the choice between a more complicated and a more simple theory, generally the simplest one is the most accurate choice.

Re: AI learns the “dark art” of RFIC design

#92

Post by HPsquared »

iamflimflam1 wrote: post #85
bsaul wrote: post #83

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..

I often think this about medicine and the human body. We want to believe that our bodies are some miraculous well oiled machine. But it often seems that it’s a barely held together bag of mess.

I think politics and economics work along similar lines.

Re: AI learns the “dark art” of RFIC design

#93

Post by alwa »

pfdietz wrote: post #70

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.)

I’m reminded of lawyer Damien Riehl’s (performative) reaction to the Sam Smith infringement decision, back in 2019/2020. He and programmer Noah Rubin algorithmically generated every possible melody (within a certain combinatorial space, in MIDI format as I recall), and purported to release them under CC-0 license [0]. He went on to attract some attention and explain his argument at a regional TEDx event [1].

I seem to recall legal commentators reacting with an eyeroll—apparently judges split much finer hairs than these for a living—but it was a cute stunt.

[0] https://allthemusic.info/

[1] https://m.youtube.com/watch?v=sJtm0MoOgiU and https://www.the-independent.com/tech/music-copyright-algorit...

Re: AI learns the “dark art” of RFIC design

#94

Post by dist-epoch »

fnordpiglet wrote: post #82
dist-epoch wrote: post #4

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.

This is wrong - the training data is necessary but insufficient. There are a lot of other parts of the architectures used that add a lot of value - otherwise Markov chains would be all you need. There are layers upon layers with non linear activation functions, learned residuals, etc. They still absolutely must interpolate but the space they interpolate through is much more complex than the training data, and they ca…

the existence of free will is far from settled

Re: AI learns the “dark art” of RFIC design

#95

Post by p_j_w »

phendrenad2 wrote: post #22

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 eve…

> 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 think the opposite is true. It being advertised as difficult to understand is one of the reasons I personally decided to study RF Engineering. The prospect of learning something so challenging pulled me in. The Smith Chart helped.

Re: AI learns the “dark art” of RFIC design

#97

Post by formerly_proven »

ben_w wrote: post #11
robviren wrote: post #5

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

Was going to say much the same. I recall one story about a genetic algorithm to make an oscillator with the fewest possible components, and it successfully did so by surprising the humans with a single wire, i.e. an antenna picking up nearby stray RF.

That sounds apocryphal but there was a noted paper describing a frequency discriminator implemented using a genetic algorithm and it ended up tied to the exact piece of silicon used to evolve it, with logic cells not connected to anything still changing the output.

https://osmarks.net/assets/misc/evolved-circuit.pdf

Re: AI learns the “dark art” of RFIC design

#98

Post by orbital-decay »

fnordpiglet wrote: post #82
dist-epoch wrote: post #4

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.

This is wrong - the training data is necessary but insufficient. There are a lot of other parts of the architectures used that add a lot of value - otherwise Markov chains would be all you need. There are layers upon layers with non linear activation functions, learned residuals, etc. They still absolutely must interpolate but the space they interpolate through is much more complex than the training data, and they ca…

>Generally though I challenge you to define “creative” in a way that is precise enough to measure and isn’t self referential or refer to concepts ill defined.

While I have no hope for a rigorous definition (I don't think it's possible), there are two very distinct kinds of creativity:

1. Result is sufficiently novel for the system itself, i.e. it never seen it previously. This kind is too trivial to even talk about.

2. Result is novel for the side observer. This kind of creativity is meaningless because it depends on at least one unknown (side observer).

Re: AI learns the “dark art” of RFIC design

#99

Post by jordanb »

bsaul wrote: post #83

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..

> our common expectation

I think you're going too far with this. Most people understand scientific theories to be an approximation. F=ma is approximately true, in the sense that it's only accurate within the newtonian regime and each of those terms includes so many asterisks that you will only ever measure it approximately.

The latter is the jokes about the physicists "assuming a perfectly spherical cow."

In fact that's kinda the whole point of the "unreasonable effectiveness of mathematics" essay. It is unreasonable that mathematical approximations are so good at describing our world.

Re: AI learns the “dark art” of RFIC design

#100

Post by slopinthebag »

bsaul wrote: post #83

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..

How would nature be best described as a horrible mess of impossible equations? They would be best described as elegant and beautiful no?

I think your point is more that we might be able to initially describe complex phenomena as messy, horrible complex equations, that doesn’t mean we shouldn’t work to simplify them and make them more understandable to us.

Post reply on HN