dgfl

This is a pipe dream and I’m almost tempted to say a fever dream. The chemistry part seems somewhat sound, even though that’s outside of my field of expertise. But the entire readout process is questionable, and has clear signs of heavy AI writing.

The AFM mechanism described as “tier 1” (very strong LLMism, btw) is somewhat optimistic but realistic. The fields needed are large compared to usual values in solid state devices, but I’d guess achievable with an AFM. But “tier 2” is vague and completely speculative. Some random things I noted: - handwaving that (not exact quote) “the read controller is cached. No need to read the same bit twice”. Cached with what?? If this miraculous technology can achieve 25 PB/s, what can possibly hope to cache it? More generally, it’s a strange thing to point out. - some magic and completely handwaved MEMS array that converts an 8um spot size laser beam into atomic-resolution 2D addressing? In my opinion this is the biggest sin of the manuscript. What I understood to be depicted is just fundamentally physically impossible. - a general misunderstanding of integrated electronics, and dishonest benchmarking, comparing real memory technologies being sold at scale right now, vs theoretical physical bounds on an untested idea. Also no mention of existing magnetic tape as far as I can tell. - constantly pulling out specific numbers or estimates with no citation and insufficient justification. Too many examples to even count.

I’m sorry for the harsh language, I wouldn’t use it for a usual review. But in my opinion this needs a very heavy toning down and complete rewrite, and is unfit for a proper review. Final remark: electronics is, and will always fundamentally be, intrinsically denser than optics. Some techniques “described” here, if they were possible, would have been applied to existing optical tech (i.e. phase change materials in blue-ray).

Yes, this is a fair point. I agree that orbital mechanics is trivially easy compared to everything else. The chances of a math mistake in particular are null, these trajectories have all been calculated years in advance.

Yes, challenger. The O-ring failed, creating a gas exhaust that almost instantly destroyed the main propellant tank.

This is underselling the risks. On top of the many trajectories which push them into unrecoverable situations, leaving them stranded in orbit, there can be trajectories where the moon gives a gravity assist strong enough to fling the spacecraft into escape velocity, fulfilling the OP.

In fact, the trajectory they chose for this mission exploited the opposite effect to yield a free return without propellant expense.

In the modern day, the chance of a math error being the root cause behind this failure mode are vanishingly small, but minor burn execution mistakes that do not require hundreds of extra pounds of propellant are definitely plausible. They were extremely common in the early days of spaceflight and plagued most of the very first moon exploration attempts. Again, with modern RCS this is unlikely. But reentry is still incredibly tight and dangerous. Apollo famously had a +-1° safe entry corridor, and Orion is way heavier and coming in even faster. If their perigee was off they could’ve easily burned up or doubled their mission time, which they may not have been able to survive.

related git repo: https://github.com/ByteDance-Seed/In-Place-TTT

Isn’t this what AGI is by design? People CAN learn to become good at videogames. Modern LLMs can’t, they have to be retrained from scratch (I consider pre-training to be a completely different process than learning). I also don’t necessarily agree that a grandma would fail. Give her enough motivation and a couple days and she’ll manage these.

My main criticism would be that it doesn’t seem like this test allows online learning, which is what humans do (over the scale of days to years). So in practice it may still collapse to what you point out, but not because the task is unsuited to showing AGI.

Disagree on the last statement. Makie is tremendously superior to matplotlib. I love ggplot but it is slow, as all of R is. And my work isn’t so heavy on statistics anyway.

Makie has the best API I’ve seen (mostly matlab / matplotlib inspired), the easiest layout engine, the best system for live interactive plots (Observables are amazing), and the best performance for large data and exploration. It’s just a phenomenal visualization library for anything I do. I suggest everyone to give it a try.

Matlab is the only one that comes close, but it has its own pros and cons. I could write about the topic in detail, as I’ve spent a lot of time trying almost everything that exists across the major languages.

Some quick napkin math: AI energy usage for a chat like that in the post (estimated ~100 Wh) is comparable to driving ~100m in the average car, making 1 of toast, or bring 1 liter of water to boiling.

I’d wager the average American eats more than 20 dollars/month of meat overall, but let’s say they spend as much as an OpenAI subscription on beef. If you truly believe in free markets, then they have the same environmental impact. But which one has more externalities? Many supply chain analyses have been done, which you can look up. As one might expect, numbers don’t look good for beef.

Exactly the same as pointing out that LLMs use energy. That whole conversation probably used as much energy as making a piece of toast.

Indeed, the original comment you replied to actually made no sense in this case. But there seemed to be some confusion in the thread, so I tried to clear that up. I hope I’ll get to talk with one of the cerebras engineers one day, that chip is really one of a kind.

There’s an expected amount of defects per wafer. If a chip has a defect, then it is lost (simplification). A wafer with 100 chips may lose 10 to defects, giving a yield of 90%. The same wafer but with 1000 smaller chips would still have lost only 10 of them, giving 99% yield.

This is precisely the matter, I wholeheartedly agree. The metacognition that we have, that only humans are likely to have, is the root behind the millennium-long discussions on consciousness. And the hard problem stems from whatever was left of traditional philosophers getting hit by the wall of modern scientific progress, not wanting to let go of the mind as some metaphysical entity beyond reality, with qualia and however many ineffable private properties.

The average person may not know the word qualia, but “is your red the same as my red” is a popular question among kids and adults. Seems to be a topic we are all intrinsically curious about. But from a physical point of view, the qualia of red is necessarily some collection of neurons firing in some pattern, highly dependent on the network topology. Knowing this, then the question (as it was originally posed) is immediately meaningless. Mutatis mutandis, same exact argument for consciousness itself.

If you let the computer run for long enough, it will compute any atomic spectrum to arbitrary accuracy. Only QFT has non-divergent series, so at least in theory we expect the calculations to converge.

There’s an intrinsic physical limit to which you can resolve a spectrum, so arbitrarily many digits of precision aren’t exactly a worthy pursuit anyway.

“There’s plenty of space at the bottom” only really took off in popularity decades later. Feynman’s accomplishments are undeniable, Nobel prize and all, but his celebrity status is given by other aspects of his personality. No Feynman equivalent I can think of is alive today. Perhaps Geoffrey Hinton and his views on the risk of AGI? He’s far from the only one of course.

Said by the man himself no less

Feynman is indeed often quoted among the first people to propose the idea of a quantum computer! This talk he gave in ‘81 is among the earliest discussion of why a quantum universe requires a quantum computer to be simulated [1]:

> Can a quantum system be probabilisticaUy simulated by a classical (probabilistic, I'd assume) universal computer? In other words, a computer which will give the same probabilities as the quantum system does. If you take the computer to be the classical kind I've described so far, (not the quantum kind described in the last section) and there're no changes in any laws, and there's no hocus-pocus, the answer is certainly, No! This is called the hidden-variable problem: it is impossible to represent the results of quantum mechanics with a classical universal device.

Another unique lecture is a 1959 one [2] about the potential of nanotechnology (not even a real thing back then). He speaks of directly manipulating atoms and building angstrom-scale engines and microscope with a highly unusual perspective, extremely fascinating for anyone curious about these things and the historical perspective. Even for Feynman’s standards, this was a unique mix of topics and terminology. For context, the structure of DNA has been discovered about 5 years prior, and the first instruments capable of atomic imaging and manipulation are from at least the 80’s.

If you’re captivated by this last one as I was, I can also recommend Greg Bear’s novel “Blood Music”. It doesn’t explore the nanotechnology side much, but the main hook is biological cells as computers. Gets very crazy from there on.

1. https://s2.smu.edu/~mitch/class/5395/papers/feynman-quantum-... 2. https://www.zyvex.com/nanotech/feynman.html

You seem to be familiar with the field, yet this is a very strange view? I work on exactly this slice of solid state physics and semiconductor devices. I’m not sure what you mean here.

The way we construct Hamiltonians is indeed somewhat ad hoc sometimes, but that’s not because of lack of fundamental knowledge. In fact, the only things you need are the mass of the electron/proton and the quantum of charge. Everything else is fully derived and justified, as far as I can think of. There’s really nothing other than the extremely low energy limit of QED in solid state devices, then it’s about scaling it up to many body systems which are computationally intractable but fully justified.

We don’t even use relativistic QM 95% of the time. Spin-orbit terms require it, but once you’ve derived the right coefficients (only needed once) you can drop the Dirac equation and go back to Schrödinger. The need for empirical models has nothing to do with fundamental physics, and all to do with the exorbitant complexity of many-body systems. We don’t use QFT and the standard model just because, as far as I can tell, the computation would never scale. Not really a fault of the standard model.

I think most of them are valid questions!

(1) is perhaps more of a question requiring a strict definition of consciousness in the first place, making it mostly circular. (2) and especially (3) are the most interesting, but they seem part of the easy problem instead. And I’d say we already have indications that the latter option of (4) is true, given your examples from (5) and things like sleep (the most common reason for humans to be unconscious) being in distinct phases with different wake up speed (pun partially intended). And if you assume animals to be conscious, then some sleep with only one hemisphere at a time. Are they equally as conscious during that?

My imaginary timeline of the future has scientific advancements would lead to us noticing what’s different between a person’s brain in their conscious and unconscious states, then somehow generalize it to a more abstract model of cognition decoupled from our biological implementation, and then eventually tackle all your questions from there. But I suspect the person I originally replied to would dismiss them as part of the easy problem instead, i.e. completely useless for tackling the hard problem! As far as I’m concerned, it’s the hard problem that I take issue with, and the one that I claim isn’t real.

This is not as good a refusal as you think it is. To me (and I imagine, the parent poster) there is no extra logical step needed. The problem IS solved in this sense.

If it’s completely impossible to even imagine what the answer to a question is, as is the case here, it’s probably the wrong question to pose. Is there any answer you’d be satisfied by?

To me the hard problem is more or less akin to looking for the true boundaries of a cloud: a seemingly valid quest, but one that can’t really be answered in a satisfactory sense, because it’s not the right one to pose to make sense of clouds.

You also don’t consciously use your senses until you actively think about them. Same as “you are now aware of your breathing”. Sudden changes in a sensation may trigger them to be conscious without “you” taking action, but that’s not so different. You’re still directing your attention to something that’s always been there.

I agree with the poster (and Daniel Dennet and others) that there isn’t anything that needs explaining. It’s just a question framing problem, much like the measurement problem in quantum mechanics.

You’re free to vote towards your goals, or move to countries which invest basically nothing in research. There’s plenty of them. I suspect you may not enjoy such great quality of life there.

In case it wasn’t a rhetorical question, they’re in your interest because through the process of building them we improve our understanding of the world, develop new technologies which the industrial system wouldn’t have backed, educate the next generation of engineers and scientists, and inspire the kids that will form the second next generation.

Private research already exists and works well in some fields, mine included. But public research is just as important since it can afford higher risk and longer scope. You can’t begin to count the startups that were created as spin-offs of university research groups.

In a few cases and in a simplistic sense, yes. But the point of the comment you’re replying to still stands completely. Quantum tunneling is nothing exotic and we have plenty of devices exploiting the principle (e.g. tunnel diodes). It was basically fully understood the moment the Schrödinger equation appeared.

These accelerators are as large as they are to try and find mismatches between theory and experiment. And even then, we can explain virtually every experiment that the LHC has conducted. If we did find something unexpected with one of these colliders, it would only really apply to experiments made in the collider. Particle physics is irrelevant for everyday stuff since we already fully understand everything involved.

This was such a big pain for me when switching back to windows / Linux. I’m not sure why it’s not talked about more. 4 modifiers is much better if you are a keyboard “power user” but don’t want to spend days crafting and maintaining a bespoke input system.

A more general point: you can be a “power user” and not have the time to learn about the absurd stack of technologies that is a Linux DE. You may even be a “power user” and not have a job / education related to computers! Shocking!

I have more or less the same views, although I can’t formulate them half as well as you do. I would have to think more in depth about those conditions that you highlighted in the GP; I’d read a book elaborating on it.

I’ve heard a similar thought experiment to your bitterness one from Keith Frankish: You have the choice between two anesthetics. The first one suppresses your pain quale, meaning that you won’t _feel_ any pain at all. But it won’t suppress your external response: you will scream, kick, shout, and do whatever you would have done without any anesthetic. The second one is the opposite: it suppresses all the external symptoms of pain. You won’t budge, you’ll be sitting quiet and still as some hypothetical highly painful surgical procedure is performed on you. But you will feel the pain quale completely, it will all still be there.

I like it because it highlights the tension in the supposed platonic essence of qualia. We can’t possibly imagine how either of these two drugs could be manufactured, or what it would feel like.

Would you classify your view as some version of materialism? Is it reductionist? I’m still trying to grasp all the terminology, sometimes it feels there’s more labels than actual perspectives.

I didn’t make it up, it’s a well known talking point around string theory. I think it was first mentioned by a practicing string theorist. Of course it’s not a novel critique, but I’ve read about putting data centers in space on this website, so I think it’s worth trying to teach people how to do these sort of Fermi problems quickly.

I did indeed miss your point, it was well hidden under a lot of sarcasm. I think it is of course completely valid. People should be free to research what they want, and I’m sure string theory must be beautiful mathematics.

But if your goal is unifying QM and GR, and/or achieving a theory of everything (as is for most theoretical physicists), then me and a growing fraction of physicists think that it’s not a promising avenue. I’m not advocating for only working on “useful” things, because such a theory is not likely to yield much profit to anyone in the foreseeable future anyway. But if you state that a unifying theory is your goal and seek funding for that goal, then string theory should move to the backstage. The mathematics department would rightfully be happy to house you otherwise.

You may be understating how much 15 orders of magnitude are.

The only truly exponential technological progress we’ve ever had, transistors, only scaled by ~5 orders of magnitude in feature size. Thermal engines went from maybe 0.1% to ~50%, less than 3 orders of magnitude, in about 200 years. There’s very fundamental physical laws that suggest that engines are done, and transistor scaling as we have known it for 30 years is also done. Perhaps very clever things might give us 5 more orders of magnitude? E.g. truly 3D integration somehow? Then we’re still 5 orders of magnitude off from our target. I can’t think of any technology that ever improved by more than 10^6, perhaps 10^9 if you count some derivative number (like “number of transistors on chip”, rather than actual size), and that’s from literally zero to today. Not from already-pretty-advanced to Death Star scale.

Another perspective is that, to get to those kinetic energies, we need accelerators as large as the solar system. Possibly the galaxy, I can’t quite remember. Will you concede that galaxy-wide objects are so far from current reality that there’s no point seriously talking about them?

Bad article. The thesis may even be valuable, but it’s riddled with falsehoods trying to prove the point. It reads more as the usual person disliking the idea of IQ and trying to bash its foundation. Some actual facts are:

1. Einstein was a great student (as common sense would expect) [1]. Top in his class in ETHZ, and the supposed failed exam is because he tried to do the exam earlier than intended. He had great, although not flawless, grades all the way through. He wasn’t a mindless robot and clearly got some feathers ruffed by not showing up for classes, but his academic record is exactly what you would expect from a brilliant but somewhat nonconformist mind. He may not have been Von Neumann or Terence Tao, I suppose.

2. The main “source” of the article is an even more flawed blog post [2], which again just bashes on IQ with no sliver of proof that I can see other than waving hands in the hair while saying “dubious statistical transformations”, as if that wasn’t the only possible way to do these kinds of tests. Please prove me wrong and show me some proper study in there, I can’t see it but I’m from mobile.

Disappointing. What’s the point of it? Quote actual scientists, for example Higgs, who are on record saying that modern academic culture is too short term focused. Basically everyone I’ve ever spoken to about it in academia agrees. Might be a biased sample, but I think it’s more that everyone realizes we’ve dug ourselves into a hole that’s not so easy to escape.

[1]: https://m.youtube.com/watch?v=2zwZsjlJ-G4

[2]: https://www.theintrinsicperspective.com/p/your-iq-isnt-160-n...

They’re trying to sell their product, which seems like a new language + runtime inspired by matlab. Reinventing Julia perhaps? It will be missing all the things that make matlab unique, as you point out.

You do realize how many arbitrary words and concepts that are nowhere to be found in “conventional” math there are here, right?

I know what all of these do, but I just can’t shake the feeling that I’m constantly fighting with an actual python. Very aptly named.

I also think it’s more to do with the libraries than with the language, which I actually like the syntax of. But numpy tries to be this highly unopinionated tool that can do everything, and ends up annoying to use anywhere. Matplotlib is even worse, possibly the worst API I’ve ever used.

For once, the Italian fascination with grammar and sentence analysis comes useful.

For some context, when moving abroad I felt that most other countries don’t really teach grammar and language analysis to the point that we do in Italy. I did attend a language-focused school, which obviously leaned even more towards this tendency; but I get the impression that most competent teens graduating italian schools have a more extensive grammar-related vocabulary than other cultures.

It makes sense then that Italian learning books would be more focused on grammar compared to other languages. I felt it extended to how we were taught English as well (i.e. the opposite direction). I don’t think it is the absolute best tactic for language learning, but perhaps it is the best one when restricted to purely written exercises.

I’d be curious to know whether you had a similar impression. My evidence is all anecdotal, mostly from talking to various people around Europe.