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▲Opus 5.5 agents discover two room-temperature magnetic semiconductor candidates (vals.ai)
scrlk 19 minutes ago [-]
After the LK-99 debacle, I'm taking this with a truck load of salt.
zaep 11 minutes ago [-]
I think, of course, skepticism around this "LLM discovers X" thing is warranted, and there have been plenty of more recent examples around questionable LLM "discoveries". Just stating this because the LK99 thing I believe was notable as a (supposed) room-temp _super_conductor while this is about a _semi_conductor.
dev_l1x_be 20 minutes ago [-]
I am not sure how this process looks like. When they "discover" these, what are they actually doing?

    The agents ran quantum-mechanical simulations of each crystal with the standard method for this, density functional theory, at two levels of approximation: a faster one (PBE+U) and a slower, usually more accurate one (HSE06). The band gaps and spin windows below come from the more accurate one.
So the agent runs a classic simulation or I am missing something.
fasterik 34 seconds ago [-]
From the little I understand about this topic, it's similar to the recent Navier-Stokes breakthrough. These physical systems are governed by partial differential equations which can be solved numerically using standard algorithms. In the case of quantum mechanics, it's the Schrödinger equation, which is no different than any other PDE except it uses complex numbers. Agents are getting very good at searching through the space of possible simulation parameters and initial conditions to find solutions with certain properties.
__MatrixMan__ 7 minutes ago [-]
I'm under the impression that this kind of modeling is one of the applications that quantum computers are likely to be good at.

I'd imagine there's a lot of documented research which has attempted to find such things using classical computers.

Seems like there would be a lot of well structured context for somebody to use while directing agents to repeat that research, now with updated models once quantum computing is ready for that kind of task.

rfgplk 11 minutes ago [-]
Frankly, there is no point in trying to "understand" what an LLM does. Their thought process is effectively undecipherable by humans (it's essentially information arising from information) so even such a "simple explanation" is almost certainly wrong. The agents might appear to have "used this method", but the actual method of computation is far beyond our grasp.
reasonableklout 7 minutes ago [-]
This is a strange attitude. When an agent is optimizing a piece of code, comes up with 2 variations, and runs benchmarks on them to figure out which one is faster, then selects one of them based on tradeoffs between performance and other things it reasons about, do you ignore its explanation and all experiment runs?
amoorthy 8 minutes ago [-]
Yes I saw 3Blue1Brown say the same thing in his tutorial on how neural nets worked where he built a simple model to recognize a particular letter. Good reminder.
rfgplk 5 minutes ago [-]
I've been dabbling with some of my own (tiny) models recently and it's actually shocking at what they can "learn" despite having _zero_ mention of it in it's training data.
Legend2440 17 minutes ago [-]
Interesting; but until actually made and tested, not worth getting excited over.
devmor 13 minutes ago [-]
One of the materials is most likely impossible to synthesize. The other already exists, so that may actually be capable of being tested. It's only been synthesized once, 27 years ago though.
colijobles 6 minutes ago [-]
While we should be skeptical until made in a lab or verified by others, this is a much better use of LLMs than solving math theorems/conjectures
matthova 7 minutes ago [-]
Sounds interesting. Excited to see physical versions of this cooked up. Also, very excited for a world a few years from now where we can talk about accomplishments like this from the frame of the driver of the AI, rather than hype that AI helped.
postepowanieadm 17 minutes ago [-]
Discovered in whose data?
14 minutes ago [-]
vatsachak 21 minutes ago [-]
I could have gotten this in one prompt lmao
rfgplk 18 minutes ago [-]
This gave me the idea to actually create a full (QED accurate) atomic simulation software. Essentially would allow you to play around with things like this. At a glance my workstation _probably_ has enough compute to handle it. At least to fully simulate at least a few dozen atoms and compounds.
xgulfie 18 minutes ago [-]
Anyone remember LK99 lol
frereubu 9 minutes ago [-]
This is semiconductors, not superconductors.
zamadatix 10 minutes ago [-]
That was a room temperature superconductor, a bit different of a task.
SpicyLemonZest 15 minutes ago [-]
[flagged]
Ygg2 23 minutes ago [-]
Ugh. Unless this has been actually experimentally verified to be a room-temperature and room-pressure superconductor, it's about as ground breaking as "Yet another promising nuclear fusion candidate theoretically described."
ChickeNES 19 minutes ago [-]
Well, given that this is a semiconductor, and not a superconductor, I don't see how that is relevant?
xmodem 15 minutes ago [-]
Reading the title I saw the words "room-temperature" and my mind auto-completed it to superconductor, and based on other comments I don't think i'm alone in that.
Lerc 6 minutes ago [-]
I agree that it is about as ground breaking as "Yet another promising nuclear fusion candidate theoretically described."

I'm not sure why you would consider new and promising avenues for research to not be ground breaking. If it's an idea worth trying, it's an idea worth trying. If it doesn't survive testing, then it was still worth trying.

rfgplk 21 minutes ago [-]
Current frontier LLMs empower effectively anyone with limitless knowledge. Historically, if I wanted to hire an engineer to, say, create something like this I would have needed a multi-million dollar budget. Now, anyone with $200 (or less) can achieve it.
devmor 19 minutes ago [-]
You are vastly overestimating what has been achieved here.

This is something a couple of materials science grad students can do in limited time for poor compensation as well. The expensive budget is for the part that comes next.

rfgplk 16 minutes ago [-]
Of course, "LLM solves quantum gravity and proves existence of God", "nah brah, that's easy brah any kid could have done this brah".

This is what you sound like. I also like how the goalposts keep moving on a daily basis, a year ago it was that LLMs can't even write a Hello World program without making an error, but now things like this are "so easy a minimum wage intern could do it."

suddenlybananas 14 minutes ago [-]
It hasn't done that though.
SpicyLemonZest 11 minutes ago [-]
Isn't there quite a bit of space between "so easy a minimum wage intern could do it" and your original claim that it would have cost millions of dollars to produce these results?
devmor 12 minutes ago [-]
Why hyperbolize when I am commenting on something it has actually done and the vastly exaggerated claims related to this?
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