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AI learns the “dark art” of RFIC design

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

#121

Post by vlovich123 »

programjames wrote: post #115
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..

That is very unlikely due to Solomonoff induction...

Solomonoff induction doesn’t concern itself with what is truth and reality. It just says which theory to prefer and how to determine so objectively when multiple are equally precise in making predictions of observations. It’s a formal description of Occam’s razor.

OPs argument is that reality is expressed by very complex equations and interactions; by definition this is outside of Solomonoff induction because it’s easy to imagine this accurate model by definition is the shortest algorithmic explanation, it’s just orders of magnitude more complex than our current approximations.

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

#122

Post by dyauspitr »

goatlover wrote: post #117
dyauspitr wrote: post #109

Earlier quoted context omitted.

It would be really cool. We already know everything at the lowest levels is a probability cloud. There’s beauty and contentment in not really being able to nail anything down for eternity…

That's a result of the Copenhagen Interpretation. There are other interpretations of the math which don't rely on reality fundamentally being a probability cloud/wave/field.

I’m not well versed in this but if fundamental particles are probability clouds, the future is not deterministic.

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

#123

Post by aeve890 »

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 wonder if our common expectation that true theories somehow had to be beautiful and elegant is going to survive the coming century.

That's the layman's idea of physics theories. They are beautiful and elegant only on the surface, that's why they're technically models and approximations of the real world. The standard model renormalization techniques are a mess of patches and ad-hoc heuristics, pretty far from the "this lagrangian literally contains all physics". Generally you just _ignore_ higher order terms and just call it a day. The famous E=mc^2 it's just the first term of a Taylor expansion. The beautiful form of physics it's what you would call "good enough" and often just a pedagogical tool.

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

#124

Post by idiotsecant »

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.

Biology is incredibly robust!! I'd say barely held together bag of mess describes something like an internal combustion engine. A primate, on the other hand, is a self-replicating machine capable of self-repair and just about universal fuel sourcing. It has a robust defense network capable of identifying and eradicating a staggering number of foreign replicators. It has holographic design storage, with each cell containing the plan for the whole organisim. It has general cognition based on a world model, and does all this on almost no energy.

Biology is incredibly well oiled!

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

#125

Post by sestep »

aeve890 wrote: post #123
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 wonder if our common expectation that true theories somehow had to be beautiful and elegant is going to survive the coming century. That's the layman's idea of physics theories. They are beautiful and elegant only on the surface, that's why they're technically models and approximations of the real world. The standard model renormalization techniques are a mess of patches and ad-hoc heuristics, pretty far from the…

> The famous E=mc^2 it's just the first term of a Taylor expansion.

Is this actually true? My understanding was that E=mc^2 is exact for a particle at rest.

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

#126

Post by rebolek »

anonu wrote: post #102

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?

No. I'm really not fan of Python but you're not going to parse JSON at assembler level. You need to choose right level of indirection for each task. And LLMs are good at more than Python and Rust. I'm using LLMs to write programs in my own language that is compiled by a very fringe language and it happily does everything from scripting on ESP32 to audio plugins and 3D gfx on desktop.

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

#127

Post by lomlobon »

slopinthebag wrote: post #100
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.

Look up diagrams for cell signaling cascades sometime. It's emblematic.

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

#128

Post by taffydavid »

pfdietz wrote: post #105
taffydavid wrote: post #53

> 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…

And what about all the movie plots ruined by the existence of cell phones?

People seem to (in)conveniently have no service in movies a lot, exactly when they need it

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

#129

Post by paytonjjones »

idiotsecant wrote: post #124
iamflimflam1 wrote: post #85

Earlier quoted context omitted.

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.

Biology is incredibly robust!! I'd say barely held together bag of mess describes something like an internal combustion engine. A primate, on the other hand, is a self-replicating machine capable of self-repair and just about universal fuel sourcing. It has a robust defense network capable of identifying and eradicating a staggering number of foreign replicators. It has holographic design storage, with each cell cont…

I think your reply and the parent can both be true, you're just using slightly the same words to describe different things.

The parent is talking more about elegant simplicity vs. sprawling, seemingly haphazard complexity, and you're talking more about durability to failure points and 'completeness'.

Likewise, in code, a lot of the most durable, battle tested software looks extremely inelegant and duct taped, as 90% of the code is dedicated to handling one-off patches and weird edge cases.

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

#130

Post by p1esk »

goatlover wrote: post #119
p1esk wrote: post #90

Earlier quoted context omitted.

You realize llms as a field is barely 5 years old? Give it at least another 5.

I doubt LLMs will give us full embodied intelligence that science fiction androids have. Maybe some other approach. But I suspect for the forseable future LLMs, robots and other AI methods will remain tools, not independent agents like Star Trek Data or Skynet.

VLAs are new LLMs. Give them 5 years to develop. But even good old LLMs are still improving every six months.
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