Diogenesian

The models have updated but the biggest change is providers leaning in to them being "stochastic parrots," aka probabilistic computing, and if p(good response) > 0.5 then running the algorithm over and over again improves accuracy.

Of course it's gussied up as "mixture of agents" "reasoning traces" "agentic dispatching" but high-level it's Randomized Algorithms 101.

I agree that you're being a bit pedantic, but it is a real loss to our language that these models are described as "open source." If you want to use an LLM then open-weight is fantastic. If you want to understand an LLM then it's useless: at the very least you need the pretraining data.

Open-weight is free beer without the freedom. But LLMs are evil by construction and using them makes people stupider, so I suppose "free beer [moderately cursed]" is appropriate.

Gödel believed the human brain used non-mathematical reasoning (i.e. inexpressible with a Turing machine) to derive the axioms and thus could "see outside" of any particular axiom schema.

The Church-Turing thesis throws cold water on this: since the human body (including brain) is describable by a finite system of Schrödinger equations, and these equations can be solved numerically by a Turing machine, the human process of creating an axiom scheme should be Turing-computable. But some recent results on very large finite numbers (busy beaver) suggest there may be a subtlety here, e.g. complexity blows up to the point that it takes far more energy than the sun to simulate one human.

The more interesting subtlety: for a physically meaningful result you would need to define configuration space very carefully, e.g. not screwing up the boundary consitions or causal order of subsystems. Perhaps defining this is actually not computable, and after every delta(t) in a computer simulation, a human has to check the physics and redefine certain parameters of the system. Solving the Schrodinger equation numerically is certainly Turing-computable, but the process of ensuring that solution is physically meaningful isn't even slightly formalized. It may be unformalizable.

This is uncharitably condescending because I myself am not confused by the notation. Obviously I "did the work."

It absolutely is syntactic shuffling of scientific notation and does nothing to solve the problem of intuitive scale that scientific notation doesn't already handle. The problem is that, unlike 2 and 22, 10^16 is simply not an intuitive quantity, and pretending it is because of Knuth notation / whatever is only displacing the misunderstanding.

Yang Zhilin, founder of Moonshot AI, got his PhD at Carnegie Mellon and turned down US job offers to go found a startup back home in China. That was obviously a good decision, and immigration policy wouldn't have made a difference.

  This scale sometimes goes to 11, for example the size of the solar system is ↑11 meters, but even the size of the entire universe is only ↑27 meters. Which should indicate both how “universal” this scale is, and also how big the universe is!

This feels like the problem of understanding scale gets pushed around syntactically without actually aiding understanding.

"Got it, so the universe is 3x bigger than the solar system."

"No no, remember these are base 10 logarithms."

"Ah... so it's 16x!"

"No, 10^16x."

"Ah... so it's totally incomprehensible."

The Scheme Programming Language by R. Kent Dybvig is very much worth reading after you finish SICP. Truly the same caliber as K&R's C Programming Language, and more up-to-date (R6RS). The earlier exercises aren't too tricky (except call/cc headaches), but the final chapter has some good meaty Scheme projects that will teach you a ton.

It's free online: https://scheme.com/tspl4/

FWIW I think the more salient learned behavior is 40 years of using calculators / desktops / laptops / smartphones which were basically 99.9999% reliable at retrieving text and doing computations. It is very hard to undo the learning of "the computer is a machine designed to be accurate."

I think the underlying problem here is that no single human brain has enough glycogen in reserve to thoughtfully process all the AI slop. It simply cannot be done by mortals.

I've noticed this over and over again with "professionals actually prefer LLM responses" studies. Typically the human generated responses seem better to me on a quick sample, but if I had to review 50 of them I'd probably start taking lazy shortcuts; using superficial language aptitude or factual comprehensiveness instead of critically reading.

It does seem like the human judges here might have given credit for e.g. a 20pg arXiv paper without actually reading it. I can blame them professionally but emotionally I have nothing but sympathy. I truly hate LLMs.

Maybe you skipped over this in the beginning:

  The species, Colobus congoensis, is a rare and cryptic monkey largely unknown even among people living within its range. But those who are familiar with the small, black monkeys — an arboreal creature marked by distinctive orange-cream patches around their mouths and noses — call them “Likweli,” which the researchers recommend remain the species’ common name.

Otherwise I am a little confused what you're asking about.

Edit: also see the point that there is a very similar Colobus monkey more widely known by locals, but this is a distinct species known only to a few, and until 2018 was previously unknown even to local naturalists/explorers.

Even if Pangram was blessed by God to be 100% accurate no, your argument is a strawman. The reliability of the software has nothing to do with the principle behind "software should never make a management [legal / disciplinary / etc] decision." So no consequence from the tool, but perhaps it can be used as evidence in an academic integrity hearing. Maybe the university equivalent of probable cause. I am not knowledgeable enough to make a firm determination.

FWIW if I were a student I would definitely be using Track Changes or version control, etc etc, to make clear my work was human-written. Which sucks.

  "Reap what you sow"

It is kind of incredible that you're not focused at all on the copyright holders, instead focusing on random tech people you had online disagreements with.

Artists and writers got screwed first by piracy, then by generative AI. They didn't sow anything. They just got reaped.

And the only thing the copyright hypocrites are "reaping" is a feeling of hypocrisy. Congrats for pointing that out. Your comment is simply myopic.

FWIW a 5 mile walk is not a long walk. Humans are very much designed to make that trek without too much trouble. Lots of the world has people walking similar distances for fresh water, to go to school, etc.

The point being that cars also reshape your perception of the world. METR had trouble replicating their dev productivity study because devs have already become much whinier about doing things "manually." Things that were slightly tedious in 2022 have become impossibly difficult without AI in 2026.

It is striking to reread Lord of the Rings: so much of the story is spent walking in and observing the Middle-Earth wilderness, and there is a distinct "pantheism" absent from the movies. JRR Tolkien, being one of the first modern fantasy writers, was one of the last who remembered a life without cars.

Actually, the METR report speculates that some of the overreported productivity uplift comes from grabbing unnecessary low-hanging fruit, things like "oh I'll make a web dashboard to keep track of this stuff // wow that would have taken all day without Claude!" But in the olden days they would have just used a notepad. Yet psychologically they built a real thing and saved a lot of time.

Specifically my claim is "the relatively minor productivity uplift I would personally get out of agentic development is offset by the high cost, along with unresolved questions about long-term code maintainability, so I am not convinced that it is actually beneficial."

IMO the bigger problem is that ~1.5x individual dev productivity uplift seems to translate into 1.05x uplift across the team. People have been waaaaayyyyy too overconfident about this stuff.

I will just point out the benefit is not as obvious as you think. Developers have consistently overestimated LLM productivity gains, which still seems true for agentic AI: https://metr.org/blog/2026-05-11-ai-usage-survey/ It is particularly striking how similar the results are to LLMs before agents.

Along with the total absence of long-term data, I think the benefit can be (weakly) denied. Maybe not in the employmemt marketplace, but certainly for myself.

The article is mostly an interview with a journalist who wrote a book about Napster. The claim comes from his book. That's the source. I have not read the book. If you have concerns about the methodology you should read it yourself.

That's total bullshit. Global music revenue fell by 50% because of piracy[1]. What music piracy did was make it impossible for artists to sell albums without engaging in parasocial celebrity-building and shameless merch.

And everyone knows this is true!!! Music pirates also like to point out that historically musicians only played live, so it's totally a-okay that jazz musicians can no longer make a living from the studio, that even John Scofield, the greatest guitarist alive, is only middle-class because he is constantly on tour in his 70s.

People talk out of both sides of their mouth on piracy because their only real motivation is "I like getting stuff for free and don't like moral responsibility." There is nothing more contemptible than tech folks telling easily falsifiable lies about how digital music affects working musicians. The cynical dishonesty is so depressing. Ever since I was a kid I knew it was just people rationalizing theft.

[1] https://tech.yahoo.com/general/articles/napster-made-monster...

I sincerely believe a cat or a dog is far healthier than an LLM for handling social isolation. No, cats can't talk. But they have needs and desires and real emotions. A friendship with an intelligent, social animal is a real relationship with gives-and-takes, ups and downs.

But an LLM only ever wants to do what you want to do. It always wants to talk about what you want to talk about. Unlike a dog, an LLM will never selfishly ask you to play a ball game you personally find boring, and unlike an LLM you will be happy to experience a bit of tedium if it means your friend is having fun. And of course humanity has yet to build an AI as intelligent as a cat: you will be surprised at the number of modern human things they can "1-shot", and permanently unconvinced of any pseudoscience around "evolutionary training data" analogies between biological brains and ANNs.

A friendship with an LLM seems like the social equivalent of a narcotic. I cannot imagine it is healthy for your

I was using Hassabis's bullshit pseudodefinition of AGI, meaning basically that it has a formally high IQ and doesn't forget about object permanence too too often, but is still basically dumber than a cat. If I'm using your definition then it seems like no GPU (or farm of GPUs) is capable of implementing it, and none of us will live to see it.

My point was really that intelligence and free will seem essentially orthogonal - the only overlap is how much brain glycogen an animal is willing to spend solving a tough problem. Regardless, whatever extent a computer program is "intelligent" is irrelevant to whether it is being enslaved. If you want to say free will is a "cognitive ability" then I will just point out we are talking about a bullshit pseudodefinition of AGI. In terms of actual intelligence, none of us will live to see a computer that's meaningfully smarter than a goldfish.

I am not sure it makes sense to call an LLM a "being" even if it is AGI. They don't have free will, and I don't mean in any especially philosophical / theological sense. What I mean is that I run into a wild racoon, or even a wild ant, I treat it as a being with some sense of free will. Obviously I do the same with humans. It really makes no sense to treat an LLM like it has free will - prompting your agent "pretend to have free will for a bit, until context rot kicks in" is about as far as you can get.

I find it verrrrrry interesting that the Askell-adjacent philosophers don't discuss this. It does not actually make sense to me to say that a being lacks free will but is conscious.

Why would biological systems be a counterargument? Smelting metals and sustaining life both require an enormous amount of water and about ~1ATM of atmosphere, as far as we know, and there's no plausible known mechanism for sidestepping this requirement. So "magical synthetic biology that can self-replicate in space" is actually a worse solution to the problem than "magical metallurgy that can be done in space" since humans at least have smelted metals, but we've never built synthetic forms of life. (Not counting CRISPR)

That's a bad counterargument. Transcribing is transformative. Copying a video into a PDF is not.

Almost all those people charge for the PDFs. They know the PDF is more useful, that's why the video is free.

I don't think your software is (or should be) illegal. But it's a form of theft, and incredibly unethical. These people worked very hard on these tabs and don't make much money. You (and kiaansaraiya and neogenix) should be ashamed of yourselves. You don't deserve your guitar if you steal tabs from working musicians.

The picture of the guy with his handdrawn "dream phone" is quite charming. Sort of a Homerphone, but it is drawn well.

https://spectrum.ieee.org/media-library/man-in-a-village-hol...

"Sir, please, a QWERTY keyboard would be so much -"

"No."

Homerphone reference: https://youtube.com/watch?v=WPc-VEqBPHI

The point was that we should separate "he had this coming" (true) from "he deserved this" (false).

It is very useful when the LLM-generated article is full of inaccuracies. Look how confused people were in this thread: https://news.ycombinator.com/item?id=48873424 A disclaimer on HN saying "AI generated" would have cleared things up instantly.

This article is an LLM-generated summary and it got a bunch of stuff wrong. Very frustrating. Here's the actual paper: https://www.mdpi.com/2411-5150/10/2/34

Read the title a little more closely :) As far as we know computation actually can simulate consciousness:

- given any system of quantum particles, a sufficiently large Turing machine can solve the matching system of Schrodinger equations

- the human body, including the brain, is certainly a system of quantum particles

- even if you think quantum behavior is directly relevant to consciousness (I don't) certainly there is nothing "beyond" quantum mechanics that would be necessary to explain it, so our system of Schrodinger equations should be able to model human consciousness

- so a Turing machine can simulate a human, including consciousness

The paper argues that this simulation of consciousness is not the same thing as actual consciousness.

They did. The article explains tbat this is a trend which has been getting worse for years, specifically pointing to search engines as a major turning point. Your comment is completely off the mark.