AND someone with a PhD in the field notices.

Everyone else is fooled.

> The common one, the fridge magnet, is ferromagnetic — its atomic magnets all point the same way (up or down), adding their magnetic effects.

Ferromagnets typically have domains with magnetic moments that point in different directions. Ferromagnets rarely have every 'atomic magnet' pointing the same way.

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

Refrigerator magnets in particular are usually magnetized as Halbach arrays, where the whole point is that the 'atomic magnets' are not pointing in the same direction. This is more energetically stable, which allows you to use cheaper materials.

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

Lastly, I believe most refrigerator magnets are actually ferrimagnetic, not ferromagnetic. (The distinction doesn't matter much for users of magnets, but is important for the materials scientists studying and designing them.)

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

"Magnetism is second nature to us electromagnetic chemists, so it's easy to forget that the average person probably only knows the formulas for one or two paramagnetic substances."

"And diamagnetic, of course."

"Of course."

And if not for that word, the article would be completely unexciting. You found that you can make magnets out of multiple materials? We already knew that. If the materials aren’t abundant/cheap and easier to manufacture then this isn’t a story. And neither of those claims are tested or verified in this. So this isn’t a big deal.

There was one particular (like 10 tweet long) Twitter thread [1] that was repeatedly being linked from HN purporting to describe the sort of technologies that a room temp superconductor like LK-99 could enable. All sorts of awesome sci-fi stuff like quantum computers! Fusion reactors! Batteries that last forever!

One might think it was from some kind of materials scientist or at least some kind of engineer working in a related industry. But nope, it was actually from a guy whose title at the time was "Head of Coffee Product", formerly "Coffee Specialist" at a "technology-driven company, looking to revolutionize the $400+ billion global coffee market". (I checked his Linkedin to make sure I was remembering the details correctly and see his current position is "Growth" at Cognition, the makers of the Devin AI LLM coding tool, hype continuing apace...).

People on HN with relevant expertise would try to gently push back with specific criticisms like how superconductor batteries would likely underperform li-ion, fusion is far more complicated than just requiring more powerful magnets, quantum computing doesn't have any clear application for superconductors, etc. But they were overwhelmed by the exuberant futurist fantasies that people wanted to read about instead. A stock accusation was that critics were being stereotypical HN cynics who can only poke holes in other people's work. Or questioning why they felt the need to rain on the parade and that we should all be optimistic for humanity and root for LK-99 being real.

It peaked when the Nature editorial came out from a scientist in the field listing specific substantive criticisms which led him to believe the evidence for LK-99 superconductivity was weak to non-existent. There were many angry HN comments with stock complaints about self-interested Nature "gatekeepers" unhappy about science happening in the open, bitter scientists lashing out for being scooped, etc. But the vibes had shifted and it only took a few more days before the remaining hype finally evaporated and everyone quietly moved on like it never happened.

Overall, it seemed like a net negative for actual scientific understanding and produced a lot of vacuous hype.

[1] https://xxcancel.com/alexkaplan0/status/1684044616528453633

I think as far as the 'debacle', there was definitely a lot of hype (at least as far as HN goes) around it, the level of buzz felt similar to what one would see today around a new AI model release.

(+) Or a "grain" if you're from the US since American English sayings seem to all date from the middle ages, while the rest of the English speaking world tends to update ours over time. No shade meant, I've just always found that interesting.

As far as I understand, you downloaded the structure of a neural network, ran it with essentially arbitrary weights, trained a classifier on the essentially arbitrary behavior, then simulated an approximation of that arbitrary behavior.

You could argue that there might be biases towards certain behaviors encoded in the connectivity, and I'm sure you'd be right, but your experiment is incapable of differentiating between those interesting behaviors and random noise. Especially because flies sorta act random anyway.

I have no idea about those actual models, but there are layers of models that you can create, and for each, you can explore with data and compute

It's not a free lunch though. Depending on the task, you might need to collect a lot of the data, or review it manually, or pay a lot for compute, or wait a lot for compute. And still have to iterate a lot on the results, and do your own explorations as a human operator/driver of the whole thing. And then create the materials, test them, get funding to do the whole thing... so theoretically, I think we are in a place where we can successfully apply models to a lot of things, but realistically, we won't be applying all the resources to everything

https://orlp.net/blog/bad-ai/#objective-p-mathrm-relevant-1-...

I think it still holds up.

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!

https://www.technologyreview.com/2020/11/03/1011616/ai-godfa...

Next gen of scientists might look quite different.

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"?

No worries, your workstation is more than enough to run accurate quantum simulations!

:)

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."