No worries, your workstation is more than enough to run accurate quantum simulations!
:)
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.
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."
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.
Why are people being so belligerent about this? I thought it's fairly obvious at this point that LLM reasoning is far beyond anyones understanding. Or does anyone have a refutation?
Edit: I stand corrected. According to Gemini:
Me: Does using more salt mean taking more of that claim?
Gemini: No, it actually means the exact opposite. If you say you need to take a claim with a huge pile of salt (or a shovel of salt), it means you believe the claim is highly unbelievable and you need an immense amount of skepticism to accept it. How the Metaphor Scales
• A single grain of salt: "I am slightly skeptical, but it could be true."
• A pinch of salt: "I have a healthy amount of doubt about this."
• A grain of sand / A truckload of salt: "This sounds completely made up, and I barely believe a single word of it."
The salt represents your skepticism, not your belief. Therefore, the more unbelievable the claim, the more "salt" you need to swallow it.
Is this a "actual impossible because it's inherently contradictory", or "we just don't know how to do it yet but give us a year"?
It maybe could be possible but beyond the reach of current material science.
The fact that the major "uses" of LLMs have been contributing to the acceleration of the dead internet theory, and building millions of versions of the same apps that no one is going to maintain, is extremely sad.
If ai becomes so prolific that we humans all stop doing those things then will they still work?
Thus, you can build ai/ml models+agents to explore those spaces, at a speed and scope much larger than what any human can do
I can imagine findings like these are going to keep increasing in frequency to a point in which the bar for novelty goes a lot higher
It took me (using Claude code and some codex), about 3 hours to put it together
And even though it was a cool demo, it seemed so easy, that it also felt like it wasn’t worth sharing
0: ChessFly (not mine), uses the FlyWire connectome (the fly’s brain’s weights) to play chess https://huggingface.co/spaces/mlabonne/chessfly
Are they a promoter / influencer for Anthropic?
This is a very bizarre introduction. People encounter diamagnets (e.g., copper) and paramagnets (e.g., aluminum) way more than they encounter antiferromagnets. I don't know why you'd ever cast magnetism as a false binary between ferromagnets and antiferromagnets, without even acknowledging any other types of magnetic order.
(I did a PhD in magnetic materials)
Not sure why we're calling it a discovery, when they've literally been made before, by a human.
I don't see any claims that this is better than the current silicon and gallium arsenide semiconductors that we use. And the use of "room temperature" seems a deliberate attempt to misconstrue this with superconductors
I can think of worse uses of VC AI funding.
Are you trying to say that human brains are incapable of inference?
Of course I don’t know how it got its ideas for what to try. But heck, I don’t even understand how I get my ideas half the time. But the process, like what code it wrote, simulations it ran etc can be understood by (some) humans just fine!
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.
In the case of quantum mechanics, it's the Schrödinger equation, which is no different than any other PDE. Agents are getting very good at searching through the space of possible simulation parameters and initial conditions to find solutions with certain properties. Coarser simulations are less accurate but faster to run, so the search likely uses simulations at different scales to find promising directions, and then refines those to verify that the simulation converges on the expected result.
One of the potential applications of quantum computing is that it might speed these simulations up exponentially. But scientists can and do regularly simulate quantum systems on classical computers.
No offense to the person writing this (assuming they did at all), but I'm not sure they really understand what they're doing..
"Debacle"? That was the most fun I've had on the Internet in years. When's the last time so many people engaged in so many arguments about materials science and electromagnetism? Sometime in the 1800s?
That's the pitch of LLMs lol
Ygg2•44m ago
ChickeNES•41m ago
xmodem•36m ago
Lerc•28m ago
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.