this post was submitted on 20 Jul 2026
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Stubsack: weekly thread for sneers not worth an entire post, week ending 26th July 2026 (awful.systems)
submitted 5 days ago by dgerard@awful.systems to c/techtakes@awful.systems
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Have a sneer percolating in your system but not enough time/energy to make a whole post about it? Go forth and be mid - welcome to the Stubsack, your first port of call for learning fresh Awful you’ll near-instantly regret.

Any awful.systems sub may be subsneered in this subthread, techtakes or no.

If your sneer seems higher quality than you thought, feel free to cut’n’paste it into its own post — there’s no quota for posting and the bar really isn’t that high.

The post Xitter web has spawned so many “esoteric” right wing freaks, but there’s no appropriate sneer-space for them. I’m talking redscare-ish, reality challenged “culture critics” who write about everything but understand nothing. I’m talking about reply-guys who make the same 6 tweets about the same 3 subjects. They’re inescapable at this point, yet I don’t see them mocked (as much as they should be)

Like, there was one dude a while back who insisted that women couldn’t be surgeons because they didn’t believe in the moon or in stars? I think each and every one of these guys is uniquely fucked up and if I can’t escape them, I would love to sneer at them.

last week's edition

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[–] nfultz@awful.systems 6 points 10 hours ago (2 children)

John Michael Greer writes:

Second, I’ve had various people try to launch discussions about AIs — that is to say, large language models (LLMs) and the utilities they power — on this and my other forums. The initial statements and their follow-up comments always end up reading as though they were written by LLMs — that is, long strings of words superficially resembling meaningful sentences but not actually communicating anything. That’s neither useful nor entertaining. Thus I’ve decided to ban further discussion of this latest wet dream of the lumpen-internetariat here, and have extended that ban to LLM-generated content of all kinds. https://ecosophia.net/july-2026-open-post/

Good for you, you peak-oil meme-magic druid, for keeping your corner of the net weird.

[–] istewart@awful.systems 6 points 9 hours ago (1 children)

Yeah, I began losing interest in Greer as it became clear that he was perfectly happy squatting in the middle of the red-brown alliance during the Trump era. His critiques of industrialism and unquestioning belief in technological progress broadly align with what we discuss here, but he will always coddle MAHA types and tale a shrugging "well, what can ya do?" attitude towards people like Trump, as it fits his preference for cyclical theories of civilization.

I noticed a couple months ago that he actually managed to dig Nick Land out of whatever tweaker den that guy's been hiding in for a podcast, which says a lot about what he's willing to indulge these days.

[–] CinnasVerses@awful.systems 3 points 6 hours ago

I like to keep my analysis separate from my word-magic (making things happen by saying them). Greer is trying to remake the world and not just work up his courage which is a harmless and consensual form of word-magic.

[–] dgerard@awful.systems 6 points 10 hours ago

and covid vaccine denier

[–] dgerard@awful.systems 9 points 17 hours ago (6 children)

Debian has a new general resolution to ban LLM use in Debian packaging: https://www.debian.org/vote/2026/vote_002

[–] peteorrall@mastodon.bsd.cafe 3 points 12 hours ago

@dgerard Wow, this is awesome.

[–] Gyroplast@furry.engineer 4 points 15 hours ago

@dgerard

Coincidentally, the second proposal in favor of conditional LLM use in Debian verily reads as generated to me. :)

Not to mention its singular argument literally is "many Debian contributors find AI tools helpful", right after "recognizing that AI-assisted contributions raise many concerns".

Concerns that were clearly laid out in the counter-proposal.

The "conditions" listed to address these concerns are hilariously toothless. Contributors should (sic!) stay accountable and responsible for any legal, functional, and procedural fuck-ups, and, like, really not be one of those thousands of dicks who are the reason for this discussion in the first place, and things will be fine! It's so simple!

Yeah, cool. I'm sure every contributor thoroughly checks if any of the generated output violates any existing license or infringes on someone's copyright. I'm sure you can just prompt an LLM to check that for you, though!

Is this naïveté, or deliberate disregard? I don't know, and that makes me mad.

[–] nielsTFranck@mastodon.nu 3 points 15 hours ago

@dgerard I knew I choose right with Debian as my distro.

[–] djb@social.shirow.net 3 points 16 hours ago (1 children)

@dgerard @cstross wonderful! So happy

[–] cstross@wandering.shop 6 points 16 hours ago (2 children)

@djb @dgerard It' could be undermined by Linus's tolerance of AI slop in the kernel, and by other upstream projects accepting LLM code, notably (to me) vim and pandoc.

The unknown original provenance of code generated by LLMs means that many open source projects may soon be in violation of their own license terms.

[–] chopsstephens@mastodon.nzoss.nz 2 points 4 hours ago

@cstross @djb @dgerard the proposal starting with copyright was such a welcome change, I find it wild how many projects just have their head on the sand over the copyright status of LLM generated code. You can be unethical as you like generating code, open source licences permit that, but they are all about copyright, they are built on it.

[–] djb@social.shirow.net 4 points 16 hours ago

@cstross @dgerard 😮‍💨 yea. It’s all getting to be a bit too much.

[–] simon@tutut.delire.party 3 points 17 hours ago

@dgerard if i read this correctly there are two opposite proposals still in discussion?

[–] lagrangeinterpolator@awful.systems 14 points 1 day ago (6 children)

long rant about mathThe recent big AI results in math have left me in quite a bad mood. I believe the main ingredient is Lean, which is a formal language resembling a programming language. Math proofs written in Lean can be verified deterministically with a computer, which really helps mitigate the hallucination problems of LLMs. Back in the days of pure scaling LLMs and Sam Altman talking about Dyson spheres, I was skeptical that LLMs would do math, but I did think that perhaps in the future, techniques using these formal languages could contribute to math. Well, it seems like OpenAI and Anthropic had the same idea and I underestimated their limitless checkbooks. Many of the biggest results were announced by mathematicians directly working for them (and presumably being paid a handsome amount).

For what it's worth, after the last of these big announcements, I decided to try one of these AIs on one of my small problems that I couldn't figure out. The AI did give a solution. That is, until I checked it thoroughly and realized that the it had a subtle but severe mistake that made it useless. I reprompted it, it failed again, and I ran out of tokens. I'm sure someone will tell me to shell out $200/mo for a pro subscription.

In the math and computer science research community, this is all anyone can really talk about right now. Honestly, after watching this whole AI bubble starting from the very beginning, I think the AI companies want to use marketing to stoke fear that all mathematicians will be replaced. But now, I am just too tired to argue. The amount of alarm and the extraordinary social pressure to use LLMs has soured me to this whole research thing. If becoming a researcher will one day require supporting these evil AI companies, I would rather just not. My dream job now is Factorio developer.

A lot of annoying people in technical areas view the world in terms of an intelligence hierarchy: the smartest people do math and physics, the slightly less smart people do coding, and the dumb people do everything else. So if AI can do math then it can do anything else. But, as an example, it is abundantly obvious now that AI is not replacing filmmaking. The techbros might be moved by arguments about how hilariously expensive video generation is, and how all these videos are 2 second clips stitched together so you won't feel the uncanny valley. But the real reason is that nobody wants to watch slop made with no intention or feeling. Also, nobody wants to support the AI companies, which could not act more evil even if they tried.

The mania in math right now quite resembles the mania in software engineering back in December-February, when Claude Code definitely solved all coding. I don't think the boosters expected that by April, everyone would be complaining about how expensive it all was while seeing an endless parade of vibe coding disasters (and no increase in productivity). Even if math research works out perfectly well (which is a still big if), it's not going to pay the bills. They would need to find a use case in the real world, where hallucinations can cause serious damage and cannot be formally prevented. And they have certainly tried. Math will not change the fact that all of this will collapse.

[–] rook@awful.systems 4 points 5 hours ago (1 children)

I reprompted it, it failed again, and I ran out of tokens. I’m sure someone will tell me to shell out $200/mo for a pro subscription.

One of the things that’s never clear from the reporting on ai successes is exactly how much actual paid human time went in to achieving those successes. This was especially notable in the fable-based security work… a huge amount of person-hours went into turning fable-detections into actual meaningful vuln reports.

A lot of demonstrably clever and capable people are involved with the llms-for-maths work, and a lot of money was spent on their time and supporting their work. Replicating it without your own stable of mathematicians and computer scientists and all the tokens they can eat is probably impractical.

I believe the main ingredient is Lean, which is a formal language resembling a programming language. Math proofs written in Lean can be verified deterministically with a computer, which really helps mitigate the hallucination problems of LLMs.

Fwiw, lean is a general purpose programming language, though despite microsoft’s efforts no-one uses it for that. I think its popularity with mathematicians came as a bit of a surprise.

Anyway, the other important thing that didn’t get reported on is that building the formal definition of the problem is not trivial! Obviously I don’t need to tell you that, but from the reporting you’d think that an llm solved all these problems, when in fact it was an llm in the hands of some very capable people who absolutely did not just prompt the thing in plain english.

Anyone hoping for self-marking homework here is going to be disappointed… lean slop confirming to formal spec slop is just expensive slop. Reviewing regular genai code is awful, even the thought of reviewing genai dependently-typed code makes me want a new career.

[–] BlueMonday1984@awful.systems 7 points 9 hours ago

A lot of annoying people in technical areas view the world in terms of an intelligence hierarchy: the smartest people do math and physics, the slightly less smart people do coding, and the dumb people do everything else. So if AI can do math then it can do anything else. But, as an example, it is abundantly obvious now that AI is not replacing filmmaking.

Going by those annoying peoples' logic, filmmakers are smarter than coders, because LLMs can (allegedly) program, but they can't make a good film. I have no wider point to this, I just find this really, really funny

[–] BigMuffN69@awful.systems 8 points 1 day ago

"The mania in math right now quite resembles the mania in software engineering back in December-February, when Claude Code definitely solved all coding. I don’t think the boosters expected that by April, everyone would be complaining about how expensive it all was while seeing an endless parade of vibe coding disasters (and no increase in productivity). Even if math research works out perfectly well (which is a still big if), it’s not going to pay the bills."

^MBAs at Open AI desperately trying to figure out who is willing to buy a counter example for 100 billion USD . pee en gee

[–] scruiser@awful.systems 8 points 1 day ago

I believe the main ingredient is Lean, which is a formal language resembling a programming language. Math proofs written in Lean can be verified deterministically with a computer, which really helps mitigate the hallucination problems of LLMs.

100% this. Also, looking back at an earlier example that was actually written up in more detail, AlphaGeometry 1 got 28/30 problems, but entirely stripping out the LLM from the system, the symbolic logic proportion alone could get 14/30, and replacing the LLM with different heuristic methods could get 18/30 and 21/30 (for different methods).

Even if math research works out perfectly well (which is a still big if), it’s not going to pay the bills. They would need to find a use case in the real world, where hallucinations can cause serious damage and cannot be formally prevented. And they have certainly tried. Math will not change the fact that all of this will collapse.

The boosters and LLM companies still believe LLMs get their current level of performance by generalizing and not just memorizing facts (and maybe a wide shallow pool of weak heuristics). So they are hoping by pushing the LLM performance up in some narrow domain they can churn out synthetic data for, they will see some large general improvements in LLM performance.

[–] BioMan@awful.systems 8 points 1 day ago* (last edited 1 day ago) (1 children)

Am I right in understanding that almost all the big name results in LLM-derived math recently come from big publicity projects in which someone spent ungodly amounts of money to have the thing nondeterministically fuzz huge numbers random seeds leading to independent random outputs around a topic, putting out simulacra of ideas which could be then deterministically algorithmically checked? In fields where something like finding one counterexample to a conjecture would be a big deal, or where you just need to try a huge number of possible solutions until you happen to hit on one that works, rather than follow a long train of logic?

[–] lagrangeinterpolator@awful.systems 9 points 1 day ago* (last edited 1 day ago)

Among the three big results I've looked at (unit distance problem, cycle double cover, Jacobian), two were counterexamples and one of them had a short 3 page proof using ideas from the 1970s. The Jacobian conjecture is an extreme case because a single counterexample is enough (for unit distance, you technically need a family of counterexamples), and it is easy to check with very basic computations. It is telling that all of these announcements came from OpenAI or Anthropic employees, who presumably have unlimited access to their AI. Nobody really knows how many resources they spent on this, or what else they tried. Nobody really seems to care about this question, either.

I think there is a phenomenon where supposedly hard questions are much easier than expected, because by chance nobody found the right approach for a while, and eventually it becomes famous as a "hard problem" which makes nobody want to attempt it.

What I'm more worried about is many people starting to use AI to try and prove small lemmas for them in their projects. Of course, a $200/mo subscription is absolutely necessary to them. This honestly feels like a repeat of Claude Code back in February. The software engineers eventually realized that AI is absurdly expensive after the AI companies realized that spending $14000/mo to service a $200/mo subscription is a bad idea. If the AI vendors couldn't squeeze money out of rich software companies, what exactly are they gonna get out of poor mathematicians and universities? Also, there is the cognitive decline caused by overuse of LLMs that has yet to set in.

[–] flaviat@awful.systems 5 points 1 day ago (1 children)

I just entered university for math and even though this is all very demotivating, it's just what I'm good at.

https://math.andrej.com/2013/08/19/how-to-review-formalized-mathematics/

The AI people's cry of "no don't look at the code! it's in lean so it's correct! does give me a bit of hope (hi bitofhope if you're here) that it's bullshit that will fall over

[–] lagrangeinterpolator@awful.systems 8 points 1 day ago (2 children)

I think a serious possibility is that AI generated papers flood the zone with uninteresting incremental results that are eventually meaningless and full of mistakes. Right now, math is full of smart, dedicated people, so at least major results are reviewed carefully. But as AI alarmism drives away many honest people from the field, the remaining mathematicians will be burdened with far more work to review, and their cognitive faculties will be eroded by LLM use. Despite 4 years of development, $3 trillion of debt, mountains of stolen data, all the agents and harnesses and loops and other expensive tricks, as well as the advantages of Lean in math research, LLMs still hallucinate.

I believe this is happening with software, but at least there are objective consequences for screwing up there (guy gets his home directory deleted, email is sent on a guy's behalf without permission, small business gets every customer subscription cancelled). But nothing bad happens if there is a mathematical mistake in a paper and nobody catches it. One could say to just provide a Lean proof, but there is still the issue of making sure the Lean code actually matches the content of the paper. Exactly what force will correct things?

Still, I don't think this is the most likely possibility. The AI companies are extremely unsustainable financially, and it's not like they're very popular. Once they collapse, I believe there will be a re-evaluation of how LLMs should be used in research. If they are used (let alone trained), someone is going to have to pay the bills.

In the end, we have to ask ourselves the question of why one does math. To me, math is not really a field where you memorize trivia. The real value comes from being able to think abstractly and rigorously from first principles, and from understanding why something is true rather than just knowing it is true. It is another aspect of your ability to reason as a free human. A few dedicated people go into math research, but your skills can easily go to many places. If you're starting undergrad, you have plenty of time to see how this all pans out before making a decision.

[–] Ooze@wirejunkie.net 4 points 23 hours ago

@lagrangeinterpolator @flaviat This is going to be more of a problem in the humanities than the sciences because in the latter we know there is a right and a wrong answer without which things don't work. In the humanities there is no right answer to check against.

The zone has been flooded with crap since before LLMs even arrived because of publish or perish.

[–] BioMan@awful.systems 8 points 1 day ago* (last edited 23 hours ago) (3 children)

Biologist here.

This REALLY reminds me of how jealously cells guard their genomic DNA from interaction with nucleic acids out in the environment.

Most genetic information on Earth is malicious information, selfish replicators in the form of viruses or transposable elements or selfish elements. Things that subvert the signals within a cell for their own propagation and provide nothing productive that the cells care about. So cells jealously guard their own genomic DNA and have all kinds of checks to make sure that nothing other than that sequence gets used, and outside sequence does not get incorporated into it. ANY DNA in your cytplasm gets rapidly destroyed, double stranded RNA sets off your immune system like crazy, even RNA with sequence statistics that are not quite like that of your species can set off an inflammatory reaction, immune system cells seeing RNA inside them that is overly compact and optimized like viral RNA treat them as sources of antigen rather than self.

I cannot help but think we are living through the transformation of our non-brain-information sphere into a state like that of the genetic information sphere. Most material out there being meaningless for our purposes and us needing to jealously guard the provenance of information we use so as to not use bull, or worse, huge amounts of malicious information made to subvert us to the purposes of the powers that be that generate it.

Evolution makes parasites more reliably than anything else. How did we train text-generation systems? Basically, to mimic the written word on the page like a stick bug on a stick. They're like those beetles that live in ant colonies, sending out social signals that make the ants see them as offspring that have to be babied rather than parasites that don't contribute. They replicate the form while not being the thing that they have subverted the signals of being.

EDIT: There is something wrong with the upvote counter

[–] zenkat@sfba.social 4 points 21 hours ago

@BioMan @lagrangeinterpolator There are a few things we have forgotten as a species. Our forgetting will prove disastrous.

  1. The acquisition of knowledge is a *social* process. Truth does not exist is a vacuum. It is the outcome of social processes.

  2. Our default mental and social processes do not automatically produce objective truth. Far from it, in fact. Our default is mob consensus.

  3. Our current success rests upon the advancements of The Enlightenment, which developed social processes (like the Scientific Method) which tend, over the long run, to create local knowledge that approaches objective truth.

[–] Ooze@wirejunkie.net 3 points 23 hours ago

@BioMan @lagrangeinterpolator I love this explanation!

[–] jerojasro@col.social 5 points 1 day ago (1 children)

@BioMan

> even RNA with sequence statistics that are not quite like that of your species can set off an inflammatory reaction, immune system cells seeing RNA inside them that is overly compact and optimized like viral RNA treat them as sources of antigen rather than self

I was aware of the other DNA/RNA recognition/defense mechanisms, but not of the ones I quote from your toot, here.

May I kindly ask for some references/sources? I'm quite interested!

[–] BioMan@awful.systems 3 points 21 hours ago

I kind of read wayyyyy too many preprints and some of that is the result of super briefly summarizing some things I have read recently. Here:

https://www.biorxiv.org/content/10.1101/2024.11.26.625518v2 poor codon optimality for your translation system leads to immunogenicity and activation of innate immune signaling in animal cells

As for length and super optimized proteins, it's mostly about RIG proteins (see https://www.pnas.org/doi/10.1073/pnas.1005077107 for an old bit of a review) and the whole DRIP hypothesis about how short mismanufactured proteins are preferentially the source of presented antigens

[–] gerikson@awful.systems 7 points 1 day ago* (last edited 1 day ago) (1 children)

guys, the reason Codeberg decided to ban "AI" is because they host the "open slopware" list, and that inspires "meatpuppets"!

https://lobste.rs/c/u4idgu

[–] rook@awful.systems 3 points 6 hours ago

Multi-trillion-dollar (-self-valued) industry that’s the future of all work and that everyone who doesn’t use it gets left behind and everyone who does use it evokes superheroically productive turns out to be helpless in the face of a small group of outspoken and minimally organised opponents?

I see.

[–] mirrorwitch@awful.systems 11 points 1 day ago* (last edited 1 day ago) (1 children)

"AI bet goes awry: Oracle fires 21,000 employees, then hit a $7 billion power hurdle"
https://www.msn.com/en-us/money/news/ai-spending-spree-hits-600b-as-oracle-fires-21000-employees-to-fund-boom/ar-AA28vWuD

"Oracle’s Worst Stock Crash in 25 Years" "Has Cost Larry Ellison $213 Billion in 10 Months"
https://finance.yahoo.com/markets/stocks/articles/oracle-worst-stock-crash-25-113002772.html

It's going to be Oracle to collapse the house of cards, isn't it. Come on Oracle, die and take down the USA economy with you. Make the people happy, Oracle.

"In short, Oracle's 65% decline is historic, but the stock's future depends less on its past and more on whether its AI investments produce durable cash flow"

well good luck with that, Oracle! :D

[–] nfultz@awful.systems 4 points 1 day ago (2 children)
[–] mirrorwitch@awful.systems 3 points 16 hours ago

"Up to 7 billion" over a period of 10 years can hardly dig Oracle out of the hole it has dug itself into, though...

[–] fullsquare@awful.systems 2 points 15 hours ago

they had big corporate contracts for their other, boring and profitable part of the business, but that won't save them from openai going broke. it's like 50x less than they need

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