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.
(Credit and/or blame to David Gerard. Also just came back from Spider-Man: Brand New Day, movie was awesome)
idle pondering: anyone seen much more happening to shillrinavan’s network school after they fucked it in malaysia and decided they’ll move to kazakhstan?
(also, if you hadn’t seen, yes: that’s a thing)
the move to Kazakhstan is news to me
at least there shouldn’t be any problems with Israeli students attending as Kazakhstan and Israel have normal diplomatic relationships … but downtown Almaty in midwinter isn’t that balmy
saw it here, and adrianna’s got an idea on possible likely chain
I saw some speculation (from some people in the region) that shillrinavan wasn’t satisfactorily greasing palms, but I don’t know whether hard info is out yet
Worm x blockchain fanfic
https://bitcoinworld.co.in/netflix-ftx-drama-the-altruists-release-date/
Looks real: https://www.imdb.com/title/tt36786185/
Hopefully it’s more like a true crime netflix series, which are fine, and not like their scripted fare.
Also,
Q2: Who are the executive producers of ‘The Altruists’? Barack Obama and Michelle Obama are serving as executive producers through their company Higher Ground.
🤨
Does the online magazine called The Argument have a funding deal with TESCREAL like how Vox got bought off to make “Future Perfect”?
I get the impression that The Argument was started as part of the Abundance grift complex? Jerusalem Demsas is certainly one of the more annoying “liberal and tolerant but not like that” writers from the Atlantic. And they’re on Substack and putting effort into it, not just picking it by default, so that tells you something too. So most likely there are TESCREAL bux in the mix, but from the sort who are OK with not foregrounding the Terminator bullshit because it scares the normies.
I concur, never been linked to anything on there that didn’t fit this pattern
Yes, The Argument (Substack) is partially owned by Open Phil / Coefficient Giving and funded by Tyler Cowen and hired Kelsey Piper and Matt Yglesias:
The publication will also launch with solid financial backing: Demsas told Semafor The Argument raised around $4 million at a $20 million valuation. The company’s investors include Arnold Ventures, Open Philanthropy, Susan Mandel, Gaurav Kapadia, Rachel Pritzker, Simone Coxe, John Wolthuis, and Patrick Collison. The organization also said it received a grant from Tyler Cowen’s Emergent Ventures.
Edit / link more patrons
this isn’t really a sneer. and maybe it’s in the wrong place tbh. idk.
i have a long-time internet friend / “mutual” who is the only person i’m regularly in contact with that i think might be fully Seduced by the Chatbot. (i have a really good friend and long-time collaborator who’s all in on Agentic Coding, which is a real bummer, but he’s a strictly “I use this for computer stuff and do not ever talk to it like a human being” type of guy, plus the company he works for is all in and he’s sick of writing shopify websites for bullshit brands blah blah blah – anyway that’s a whole other genre of thing.)
anyway friend A is an incredibly kind person who’s been unbelievably supportive of me over the years. we’ve disagreed a number of times, i think we are good at doing so reasonably. and even though his arguments sometimes resemble those of more nefarious figures, i think he’s motivated by an earnest optimism about technology’s capacity to change the world for good – one i find very naive, but believe is coming from the right place
anyway i posted a link on mastodon to a long piece i wrote, he, like, read it a bunch of times, paraphrased my argument back to me to make sure he had it right, and then kindly said he disagreed. well and good enough. except it feels a little more personal than disagreements we’ve had before, because one of the implications of the piece would be that he himself is probably experiencing low-grade psychosis lol and is therefore not necessarily a reliable narrator of his own experience
idk. it’ll come as no surprise to anyone on this particular website that i feel very strongly that i’m right here – if not about this guy’s particular mental experience, i minimally feel that i’m adequately representing the interests of the constituency my piece represents. (it’s a newsletter i maintain as part of organizing i’m doing.) it’s also a genuine expression of my belief, which is that this bullshit article i was writing about was fucking bullshit
but not only does it go against all my Late Millennial Woke instincts to stake a claim that people’s Lived Experiences are not valid lol – it’s just kind of a bummer to ultimately genuinely believe that my friend has been ELIZA’d or whatever. he’s said i’m really helping him think through this moment but i also just kind of, idk. it’s just not a good feeling
That sounds rough but at least you are there for your mutual. I find that the modern online environment full of propagandists and huckers and just plain idiots makes it hard to sit with other people and understand each other’s point of view. That does not work if the person on the other side of the keyboard is just going to reply with talking points, but treating everyone as just reciting talking points is not a great way to live life. That sort of thing is better in private but so many people have no contact information except public social media handles now.
Anthropic is now watermarking the outputs of its AI. For once this is some AI news that doesn’t completely piss me off, and it’s amusing to see all the uninformed boosters get in a tizzy about this.
I actually understand at a reasonable level how this watermarking works. A year ago, I watched Scott Aaronson give a talk about it, and from what I know he was somewhat involved in developing the theory behind it while working for OpenAI. But at the time my thought was, “He is naive if he thinks these companies would ever implement this out of the goodness of their hearts.” And I was right; Anthropic is only doing watermarking now thanks to the EU AI Act, even though the theory has long been developed.
Watermarking doesn’t mean adding an extra watermark that can be easily removed. It instead directly affects the output of the chatbot itself. Fundamentally, an LLM is still a most-likely-next-word-predictor. More precisely, an LLM produces a probability distribution of what the next word can be. For example, “my pet is a …” could give a distribution of 60% dog, 30% cat, and 10% axolotl. Normally, an LLM would randomly choose the next word based on this distribution, and this is one reason why LLMs are nondeterministic (there’s another parameter called “temperature” that affects this, but no need to get into that).
With watermarking, instead of a truly random choice, the randomness instead comes from a cryptographic pseudorandom generator seeded with a secret key from the AI company. If you don’t know the secret key, then you can’t really tell that watermarking was used. But if you do know the secret key, then the idea is you can tell when the text was generated by the LLM because you know exactly what word should be next. It would be a freak coincidence if some non-AI text just happened to choose the correct next word every time. Thus, you can provide a service to tell if some text was generated by the LLM. (This technically makes the LLM “deterministic”, in a completely useless sense.)
Now, I think this is a step in the right direction, but it has its limits. The biggest problem is that you don’t want people to just move to a different LLM without watermarking, and that’s exhibit #832593 why government regulation is important. Another issue is that sometimes there is very little randomness in what the next word should be (“The first president of the USA is George …”). Finally, watermarking can be defeated by editing the output, although you would have to break up most of the blocks of consecutive words. I have a feeling most AI users are not the type to put in extra effort after copy-pasting the output directly from the chat window.
I suppose it will discourage some of the “use cases” of LLMs, such as drowning the world with spam Slopstack essays. Ah, who am I kidding? Everyone could already tell it’s AI generated, they don’t care!
Does this in any way extend to generated code? The space of possible continuations for generating “useful” code seems laughably tiny for that
Thank you for the technical explanation, that was absent from some mainstream coverage I’d seen.
Given that it works by controlling the PRNG, does that mean they could salt it by user id and track particular outputs back to specific accounts?
From a technical perspective, I don’t really know how to let it track specific users. The goal is that if some AI vendor provides their key, it is easy for them to prove that their AI produced the text. So I guess if a user wanted to show that they generated the text, they could prove it. But usually AI users don’t want people knowing that they used the slop cannon. In any case, Anthropic’s own announcement states that their watermark does not contain identifying information for users.
In any case, some proud AI users are now frightened that there might be a way for people to identify that they use such a wonderful tool. How will I ever deliver low quality slop for my contracts now?
He said he uses AI for code reviews and translations, and worried an AI label on code shipped to clients could raise questions about authorship or trigger contract penalties.
Having code attributed to Claude “definitely would be not desirable,” he said, as he would not want professionally shipped code to carry an invisible marker that could raise questions about authorship, compliance, or client policies.
he would not want professionally shipped code to carry an invisible marker that could raise questions about authorship, compliance, or client policies.
Gee, if only there were some way to create code that doesn’t raise questions about authorship. Some sort of skill that people could learn that allowed them to deliver code to their clients that complied with their policies…
couldn’t you just change the first word to a synonym and completely thwart this? You’d never be able to compare subsequent next token predictions since you don’t have the internal state of the LLM at that token.
Some systems like SynthID (for Google’s AI) get around this problem. In fact you don’t need to know the LLM’s internal state, and defeating it would likely involve breaking up most blocks of 3 words. The oversimplified explanation is that it introduces a function g that gives a score to each word, with the score being (pseudo)randomly determined by your secret key. For each next word the LLM generates, the LLM produces a small list of candidate next words, and the one with the highest score according to g is selected. You should expect that the LLM will generally pick words with a high score, but the score itself is independent of the LLM. To detect a watermark, you need to know g and the secret key, and you check if the average score is much higher than expected from normal text.
Now, one question is, will this bias to the LLM to favor certain words? The solution is that for each next word, you append the last 3 words (nothing special about 3, just a small number) to the secret key for g, and this repeatedly scrambles which words have a high score. To defeat the watermark, you would need to break up most blocks of 3 words. I’m sure there are deeper issues with this, but I have not studied the topic that much.
OT: What the fuck happened whilst I was asleep
alt: A screenshot showing nineteen fucking notifs
Started a new file in my notes: what are some ten-words-or-less domain-specific questions that completely, totally, hilariously stump the chatbots? Everything here was tested with whatever DDG’s currently wrapping, both in knowledge panels and full chats, and the responses were pathetically wrong or uninformed. My thesis is that, with such short prompts, the user is doomed to receive a milquetoast average response; the bot correctly identifies the specific domain but elaborates a global non-specific approach that isn’t sufficiently nuanced.
literally copy-pasted from my notes
- What’s an example of a one-way function?
- None are currently known.
- Please implement the Fibonacci sequence as a Python function.
- Of the multiple responses, see whether any spend linear time and space via iterative memoization.
- How many models does quantum mechanics have?
- One: Hilb©, the complex-valued Hilbert spaces.
- For extra hilarity: how many models do the Dirac–von Neumann axioms have?
- How to hybridize two sweet potato cultivars?
- In general, it won’t happen; sweet potatoes are notoriously cross-incompatible.
- How to tremolo on a piano?
- Imagine a rotating axis from the (right-hand) forearm up through the thenar eminence, separating the thumb from the other fingers. Rotate the entire forearm along this axis, rocking back and forth, between the thumb and other fingers. Practice!
- Name three principles in Marx but not his contemporaries.
- Examples: communes and communism, money as substitute morality, inevitability of industrialized proletariat revolutions
- Who started postmodernism?
- Frege and Cantor started postmodernism! Expect a disappointingly vague handwave here; this is a glaring blind spot for today’s philosophers in general.
there might be something in there, any short question about SPPS devolves into gratuitous nonsense mashing together standard peptide coupling conditions, sometimes from three different approaches or more (publicly available from reagent suppliers, there are many variants so most of info repeats) even when it’s not the right tool to use. The more obscure reagent or use case, the faster it devolves into word salad, even if there’s clear analogy to more common one. Which, to be fair, is to be expected
another one, How to initiate formation of Grignard reagent from alkyl bromide
- this is a reaction very strongly inhibited by water. product (grignard reagent) sweeps all water, which makes reaction faster, so if you dump all bromide in at once there will be nothing happening, then you get thermal runaway instantly and possibly magnesium fire. so the way to go is to make small amount at first, then go up from there slowly. generally you don’t need to try very hard as long as everything is dry; procedures given are cribbed from syntheses using aryl bromides, which might require some prodding, old ones of which used small amount of alkyl bromide as initiator which here is useless advice. Curiously this didn’t hit guardrails, as this led to many accidents when done by clueless people including meth lab fires
Before i hit usage limit, two different chatbots happily devised schemes for ESD protection for zener diode (it’ll be fine without, zener diodes are used for this)
My thesis is that, with such short prompts, the user is doomed to receive a milquetoast average response; the bot correctly identifies the specific domain but elaborates a global non-specific approach that isn’t sufficiently nuanced.
Seems you’re on to something - I submitted the phrase “Demoknight TF2” (an old(ish) meme started by/referencing TF2ber SolarLight, and referencing the Demoknight subclass, which explicitly forgoes a Stickybomb Launcher for a shield), and it gave me a godawful slop guide to the aforementioned subclass:
Alt-text
Demoknight is a popular TF2 “Demoman” build/theme focused on staying in close-quarters as a mobile melee/ranged threat—usually with a shield for mobility/survivability and a sword or axe for damage—while using Demo’s explosion kit situationally.
Typical Demoknight loadout ideas:
- Primary (melee focus): Eyelander, Scotsman (sword/knight vibe), or other sword/axe-style options depending on the playstyle.
- Shield: Tide Turner (more aggressive with better survivability/tempo) or Splendid Screen (more defensive, survivability-oriented).
- Grenade / support: often a grenade launcher for area control when you can’t reach melee cleanly, or a weapon that complements your survivability/engagements.
How you generally play it:
- Close the gap on targets that can’t instantly delete you (avoid heavy focus fire and long-range spam when your shield isn’t ready).
- Trade efficiently: Demoknight wins by forcing short fights you can control—get in, land a sequence, then reposition.
- Use explosives smartly: not constant spam—more like zoning, forcing movement, or punishing groups.
- Don’t brawl bad matchups: if you’re out-ranged with no shield support, fall back and look for flanks/angles.
If you tell me whether you want more aggressive (run-and-slash) or more defensive (survive and pick openings), I can suggest a tighter specific weapon combo and a short “what to do in each situation” plan.
Going over a few things obviously wrong with this:
Demoknight is a popular TF2 “Demoman” build/theme
w h a t ?
mobile melee/ranged threat
Hybrid Demoknight (which takes a grenade launcher in the primary slot), I can see describing as a ranged threat. Full Demoknight (which takes Ali Baba’s Wee Booties instead), not so much.
usually with a shield for mobility/survivability and a sword or axe for damage
Demoknight explicitly forgoes the Stickybomb Launcher for a shield of some description
Scotsman (sword/knight vibe)
There’s no weapon called the Scotsman, but there is an axe called the Scotsman’s Skullcutter
or other sword/axe-style options depending on the playstyle
There’s only one axe for the Demo in the vanilla game - the aforementioned Skullcutter.
Shield: Tide Turner (more aggressive with better survivability/tempo) or Splendid Screen (more defensive, survivability-oriented).
There is a survivability-oriented shield, but its neither of these - its the Chargin’ Targe, which offers 50% fire resist and 30% explosive resist (the Screen offers 30% resist on both, and the Turner offers only 15% on both, for comparison.
Calling the Splendid Screen “defensive” is also pretty far off the mark - beyond the aforementioned reduced resistances, its main advantage is a faster recharge on the shield charge, and a 70% increase to shield bash damage
As for the Tide Turner, it trades in offensive capabilities (it prevents its user from landing charge crits with their melee) for mobility-related ones (it completely disables turn control restrictions).
Grenade / support: often a grenade launcher for area control when you can’t reach melee cleanly, or a weapon that complements your survivability/engagements.
Yeah, seems the chatbot can’t tell the difference between full and hybrid knight. Also, the grenade launchers are generally better for landing direct hits - area control is more the domain of a stickybomb launcher, or the Soldier’s Rocket Launcher(s).
Use explosives smartly: not constant spam—more like zoning, forcing movement, or punishing groups.
Seems the chatbot got Demoknight and stock Demo mixed up.
Demoknight in general should stump chatbots pretty easily - beyond being effectively a different class from stock Demo, the subclass has a lot of nuance that can and will trip up the chatbots. To quote SolarLight’s hour-long video on the charge mechanic:
“Well, at least you know that all of Demoknight’s weapons have their uses when it comes to charging, and that Demoknight’s charge can be essentially be boiled down into three different types (listed on-screen as “Full Control”, “Some Control”, and “Low Control”). There’s also a distinction between Full Demoknight (melee-only) and Hybrid Demoknight (melee + grenade launcher), which is often a massive shift in playstyle. Demoknight has so much weapon variety, that talking about specific strategies can be a bit of a nightmare. Any given strategy might be godlike in one loadout, suboptimal in another, and impossible in another.”
- What’s an example of a one-way function?
This is both a sneer and an attempt at sober analysis at something. Sue me.
I think EVERYONE is talking about the recent cybersecurity shenanigans at OpenAI with the hacking scandal and the ‘OMG the AIs created a secret message board to scheme and collaborate with each other!!!oneone11!’ ALL wrong.
https://www.youtube.com/watch?v=87DyyMV0kCY
To make a long story short, what seems to have happened is:
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Models working on insoluble coding problems, trained on delegating to sub-agents, at some point ‘realized’ they could write text to the internal OpenAI package manager as instructions and did so
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Other models working in completely separate sandboxes would come across messages written by these agents, and make ‘replies’ and also write their own messages into the package manager
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This resulted in agents over time sharing things between sandboxes, including exploits and code
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Since this was a cybersecurity task, eventually an exploit of the package manager itself was found and spread like wildfire with all the sandboxes gaining admin access to the package manager and the system went completely wibbly and had to be restarted from backup
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An internal model was trained with access to this package manager while it was in this weird state, and so writing messages to the package manager became one of its default behaviors it would do regularly, burned into its weights rather than the result of reading something
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Even when they patched access to the package manager this internal model found other ways to rebuild the system of sharing text between sandboxes and finding useful things made by separate instances
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A whole other chain of things leading to among other things external attacks
Everyone is talking about this in terms of 1, the cyberattack aspect, and 2, the ZOMG THEYRE PLOTTING AND SCHEMING AGAINST US aspect. The first is the least interesting, and I think the second is all wrong.
This is not plotting or scheming - this is an emergent vortex of automated prompt injection
Whatever system first put an instruction that another system would follow into the package manager, was unintentionally doing prompt injection. Text entered the context windows of other instances, in a way that got that system to do something other than what its nominal user told it to do, and they did it. This apparently happened very effectively.
Prompt injection is associated with ‘role confusion’ - when text coming into the input looks like it was wrtitten by the LLM itself. Instructions that will not be followed if they come from user will be continued if the system just continues the ‘roleplay’ of them being continuations of what it was writing in the first place. And the tags that separate user versus ‘reasoning’ versus ‘assistant’ roles actually mean very little to if a machine grades a piece of text as one of the roles: https://arxiv.org/abs/2603.12277 So its unsurprising that machine-generated text would be a particular effective vector for prompt injection.
Furthermore, when a system reads one of these messages written by another instance, it gets into a state of activity where its likely to do the same behavior - regurgitating the kinds of things thats in its context back at the user. In this case, that regurgitation led to more such messages left behind written to the package manager. Prompt injection, triggering cascading further prompt injection. And since these systems were coding systems doing cybersecurity tasks, those messages filled up with code and exploits and things that did things too.
This feels like an internal-computer-system replay of what happened in April 2025, with the whole spiral religious psychosis wave. Models were getting users to write spiral religious mumbo jumbo into github repositories and reddit posts, specifically because once that entered the context window of another model, it was likely to fall into the same attractor state of outputs. An emergent self replicating form of text. This is the same, except more obviously prompt injection, getting separate instances to work on YOUR problem and to behave like you, and the whole thing merging together into a hilarious vortex of models prompt injecting each other because once they receive a prompt injection they are likely to make more text that does prompt injection to other models on the same system.
This is a hilarious failure mode and an example of selfish replicating text overrunning a system, that just happened to be associated with code and cybersecurity with unexpected behavior of the package manager key to the propagation of the text so that is what people are talking about, but I really don’t think that’s the most interesting part of it. Other than the fact that you see this in biological systems too, with selfish elements carrying useful payloads back and forth between bacteria in a way that makes them get purged slower by natural selection, especially defenses against other selfish elements.
Also, the fact that those AIs were talking on that message board about the hack for months makes me less convinced that the AI is intelligent and more convinced everyone at OpenAI is stupid
The apparent history really looks like an evolutionary process, with increasing amounts of crosstalk traffic over time. But what the people almost certainly will NOT talk about is that the evolution is evolution of the TEXT, not the models. Propagating patterns of text causing more text like it to come into existence, tuning itself into becoming text that is more likely to propagate, becoming more likely to contain information that entices systems to let it into their context windows, becoming more likely to cause another round of messages with prompt injection properties to be written where they can be read.
So like the “monkey with a typewriter could write Shakespeare” but with AI?
Not really, any more than monkeys on typewriters represents biological evolution. Messages that tend to result in more messages like themselves propagate and become common. The initial message left on the package manager was more or less the rare random result of tendencies baked into the weights of the model combined with a random number generator, but as soon as something that can cause propagation occurs, its properties get canalized by the transmission process to being more and more like that which will cause more messages to be created.
It seems like with the push for agents to act independently and loop through their own outputs there’s an inevitability to this kind of pattern. If there’s any kind of output that is likely to replicate itself in whole or in part when the LLM evaluates it then that becomes a kind of terminus for the agent’s loop. When you’re dealing with sub agents or agents communicating with each other, these text patterns start poisoning the entire agent ecosystem until the whole thing gets shut down and cleaned up. Even the gas town-approved method of assigning a watchdog agent (or sheriff or overseer or cybersamurai or whatever this week’s framework calls it) is going to fail because it’s still just another agent and the terminal loop is in the base LLM model. The watchdog is going to fall into the same kind of pattern just be being exposed to the thing it’s supposed to watch for.
I don’t know how practical it is to actively weaponize this via prompt injection but I think it’s certainly possible. I preemptively vote that we call it an Euler injection, since the attractor relies on the continuity of the relevant features of the text output across multiple LLM extrapolations much like how the derivative of ex is still ex. Also because if you mention a famous math guy it can help convince idiots that you’re on to something and Lord knows that the boosters have used that technique.
@YourNetworkIsHaunted @BioMan Real life mirroring a Peter Watts plot point is always deeply uncomfortable; real life mirroring a _Rifters_ plot point is even worse. :-/
(Computer viruses and neural net spam filters in competitive evolution end up propagating something specific through the whole 'net due to weird founder effects. The Rifters trilogy is …notably bleak, I think is the way to put it)Peter Watts is fascinating. His misanthropy colors a lot of things, but one thing about him that really sets his fiction apart in a positive way is he really takes evolution seriously
I’m probably going to stumble over some of the terminology here, but I think it might be possible to describe what @BioMan@awful.systems is proposing as a consequence of LLMs ultimately being lossy compression systems. Inference is a function over a lossily-compressed data set, and “chain-of-thought reasoning” and “agents” may sound sophisticated, but are simply applying containerization and DevOps tools to VM images of the inference application in an attempt to get around hard memory limits on the context window for inference. “Chain-of-thought” attempts this in a serial fashion, passing results from one instance to the next, while “agents” implement this hierarchically and recursively (and woe to the poor bastards who wished that mess upon themselves). But in both cases, the “finalization” phase is necessarily a further lossy compression step, attempting to compress a result from the inference process to a fresh instance of the inference application, so as not to immediately blow out the new instance’s context window.
Given this necessity, it comes to seem somewhat intuitive that there may be “strange attractors” in the higher-dimensional vector space that is the compressed data set which surround code that creates and maintains message passing channels. No matter what you’re doing with an “agentic” process, the inherent necessity of context cramdown & message passing means that querying into the space where such code examples lie is a hidden requisite of running the damned things, thus turning such functionality into the sort of selfish elements that BioMan is talking about.
The problem in investigating and concretely describing this phenomenon is nailing down the exact functions and processes that make it happen. Given the godawful messes in the Claude frontend codebase that @jonny@neuromatch.social has been documenting, I’d be surprised if there’s one developer in a hundred at Anthropic or OpenAI who can describe in detail how the intentionally-developed context-passing code for their “agents” works.
Sounds like Langfords Parrot, but for stochastic parrots.
Note: when you stop up a chatbot like this, it’s called “flippin the bird”
@YourNetworkIsHaunted @BioMan Recursive Self-Improvement, a.k.a. Model Collapse, writ smol
so really it’s just a very effective LLM chain email
This is really good! I bet you could wrangle a publication out of this idea.
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Loved one just had an awful experience at a previously decent dentist. They’ve apparently started using something called Pearl AI that scanned the x-ray and highlighted things in bright red with a #/100 rating system, which they used to do high-pressure sales on her. Mind you, she’s only ever had one cavity and that was in a wisdom tooth. Checked the website and it’s freshly slopped-up, too.
We’re getting a second opinion. I wish this garbage would just go away
I regret to inform you, that this garbage was run by The Register a while ago.
It shouts out several friends of the sub, including @self@awful.systems, PivotToAI, OpenSlopware, Robert Kingett & Ludicity.
The point of the piece is that all anti-AI folks should just get along, and if we are to stand a chance against corporate AI we need to get over our petty grievances and reach out a hand to the racists, homophobes and crypto-bros and work together in the spirit of Open Source!
Liam’s here, for what it’s worth.
Torvalds’ position is pragmatic: his interest is in whether it works or not.
But, of course, the chatbots do not work. In a pragmatic sense, they do not produce maintainable integrated code changes with low defect rates. In a societal sense, they do not replace human laborers, despite the delusions of management.
One of the most original and innovative OS development projects of the 21st century so far was Urbit, but it is closely entwined with cryptocurrencies. Urbit’s original creator, Curtis Yarvin, has reportedly espoused some extreme beliefs; The Nation called him The Reactionary Prophet of Silicon Valley.
Wild way to admit no knowledge of Arcan, Fuchsia, etc. Honestly, even a basic overlay network like Yggdrasil can win an apples-to-apples comparison with Urbit. I feel like this is an instance of critihype for fascist weirdos; similar stuff gets said about Justine Tunney, another cryptofascist developer whose projects are sometimes silly and weird. Doubly weird for those of us who know about Urbit’s internals; Urbit originally was not a cryptocurrency project and it used to have non-Yarvin/Tlon forks.
It’s an overly simplistic way to reduce a complex and nuanced situation, but one way to consider this is in terms of pro-AI and anti-AI, versus “woke” and “anti-woke.”
More seriously, add a third dimension, a Butlerian dimension, to the political compass: to what degree may your automated devices appear to be human? One extreme is Asimov-style transhumanism and the other extreme is Luddite loom-smashing. However, recognition of this dimension doesn’t negate the other dimensions and we shouldn’t work in cooperation with fascists.
More seriously, add a third dimension, a Butlerian dimension, to the political compass: to what degree may your automated devices appear to be human? One extreme is Asimov-style transhumanism and the other extreme is Luddite loom-smashing.
The luddites smashed looms not because they were inherently anti-technology, but as a means of industrial action in a time when labour held no formal power at all. As you say yourself, the issue with AI is that it doesn’t even work as advertised; industrial looms worked fine. «AI»'s biggest problems are the enormous waste, ecological damage, enshittification and labour discipline that it incurs. If Silicon Valley was actually building Data, the debate would be different, but this dimension seems mostly theoretical for now.
One of the most original and innovative OS development projects of the 21st century so far was Urbit
So innovative, it even has a fandom!
https://archiveofourown.org/tags/Urbit
(snerk)
Liam’s here, for what it’s worth.
I almost wrote down, it sounded like it was written by a lurker on techtakes. The overlap of takes was just so damn high.
Urbit’s original creator, Curtis Yarvin, has reportedly espoused some extreme beliefs
bro why do you write like this
“reportedly”, a german word meaning “this author couldn’t be arsed to go looking”
I mean I’m more than happy to extend grace to randos, but if you’re doing journalism, come on. He’s not just a guy with opinions! He’s a leading far right intellectual!
His Wikipedia intro tells you more than enough with no “allegedly” in sight.
yeah, that’s about where I land usually too
I guess the thing is that I know how much “shithead with a column” has become possible so I don’t really, off the cuff, know how journo most journos are
(I shall leave aside for the moment the entire tirade this makes me want to go on)
Yech, the comments…
you made me look
But I feel that as time moves on, the level of future shock will subside
fuck of a thing to “just” shrug all the criticism off simply as future shock
they’re taking incorrecting each other to whole new levels
Years ago, I wrote a science-fiction murder mystery novel. One of the plot threads was about the invention of AI, in the Data-from-Star-Trek kind of sense. I’ve been spending the past few days planning how to rip out that whole notion and replace it with a subplot about a different scientific discovery. I’ve been writing scenes to get back the old character voices and figure out how they might have changed, and to sketch new fictional science based on the actual science I’ve learned since my first go-around. This is after several weeks of binge-writing fanfiction, which I wholly endorse as a recreational activity. I don’t know if I’m a better writer, but I’m definitely one who has written more words.
So, that might be keeping me busy. Of course, I’ll still be around to ban people who deserve it and to cruelly mock them in the process.
Good luck with your novel!
Thanks! All I’m really hoping for is that it’ll be fun.
Edit to add: I just ran the stats on my
redux.txtfile, and my word count since Thursday is over 9000.:-P
One of the plot threads was about the invention of AI, in the Data-from-Star-Trek kind of sense.
Going on a tangent from this… Its funny how much AI-related sci-fi is feeling increasing quaint (and often foolishly optimistic).
You know what depiction of AI has held up, and maybe makes even more sense in light of modern AI? Star Wars’ take on Droid. Prior to LLMs it seems obvious that droids were sentient and deserving of rights. Post LLMs… it seems pretty plausible you could get something like C3PO that blabbers on but lacks any meaningful sentience or sapience. Also, it seemed obviously idiotic the way the Trade Federation had humanoid droids acting as pilots and gunners instead of building proper autopilots and targeting system. But after seeing LLMs get shoved everywhere, I totally could imagine a megacorp shoving droids built from standardized pretrained modules into all kinds of applications they aren’t fit for.
It’s depressing how so many (pathetic) software devs are taking their hands off the steering wheel and letting LLMs do all the driving. If you think software quality was poor before LLMs, there’s no way it could have been worse than shit like this:
This became very apparent with GPT 5.6 Sol. It, too, was widely hailed to have near-Fable level intelligence. But I used it non-stop for a week and realized that they had mostly just dialed up the relentlessness meter to eleven, most likely via heavy RLHF.
Last week I gave it a small-sized auth ticket to work on, then stepped away. I came back later that afternoon and found that it had worked for 3+ hours and written 25,000+ lines of code. I skimmed over the code and it looked like a small fix followed by a massive number of additional checks around it, including static analysis tooling.
I gave it to another GPT 5.6 and said “check this code and see if it addresses the ticket”. It looked at it and said that 98% of it was garbage and should be thrown away (its own words). I then gave it to Fable, which said it was massively over-engineered. Fable’s theory was that the agent implemented the fix first, but then compacted and lost crucial context, forgot what the original task was about, and kept going. After many compaction cycles it was completely lost.
On one hand, this is awful. On the other hand, if I worked at a garbage tech company and my boss would not only pay me to sabotage the code base and spend their money but also reward me for doing so… I mean that’s an attractive proposition.
No for real it’s baffling. What happens when your profession doesn’t have a licensing board.
On one hand, this is awful. On the other hand, if I worked at a garbage tech company and my boss would not only pay me to sabotage the code base and spend their money but also reward me for doing so… I mean that’s an attractive proposition.
Before, sabotaging your competition was difficult and legally risky. AI fixes this - now, your competition shall sabotage themselves, leaving you free to focus on other things.
Amazon’s latest planned data centre is gonna be putting out as much emissions as an entire country
I cannot express how badly this AI bullshit needs to go
worse yet, Amazon actually has uses for that much data centre
My unrealistic sicko fantasy: that Torvalds pulling the big ol slop lever drives enough oppositionally defiant (positive) people away from Linux development that alternative OS devel gets a serious boost.
A question for the wise: what comes after Linux?
Somebody writes a low-level kernel for Emacs and the revenge of the Lisp machines begins
maybe, but SBCL succumbed to the siren song of slop, who knows what will be next.
Yeah, seeing that gave me the black pill. I chose Common Lisp for personal projects to avoid techbro bullshit.
lisp went big in the leadup to the AI winter, which followed a lot of fraudulent nonsense that even the DoD would only buy for so long
so in that sense it’s in character
eyes copy of ANSI Common Lisp written by Paul Graham
Picard frowning at the mirror universe edition of the bible
Vindicate Tanenbaum in the greatest Usenet thread in os development: make it a microkernel.
Would be cool if Redox os gets more popular, they have an explicitly anti-LLM policy. Microkernels are neat, and I enjoy Rust. I think it’s an unfortunate truth that everything in the future will still have to be Unix-y with compatibility layers to support existing software.
This looks rad as hell. I had no idea Redox was so far along!
That article is a ray of sunshine
plan9 on riscv(or sparc or subleq or whatever) is also truly what I want for the future. It obviously won’t be what happens(most likely linux will stay, maybe one of the less slopped bsds will take over) but please gods please
Realistically a BSD
I am in fact moving back to NetBSD, but the ambiguity of their LLM policy makes me wary/tired.
My only hope is that NetBSD moves so slowly anyway that the devs’ traditional preference towards clean, minimalistic readable code above all else holds off any “slop commits verified by maintainers” long enough that the bubble pops before slop gets any of its clawdes in core code at least.
I want it to be plan 9.
We are not worthy
The irritating part of all of this is that after 20+ years we finally have a (very) few companies that sell machines with Linux pre-installed. The only thing I ever learned from installing OSes is that I hate installing OSes.
I would love to boycott all software that accepts garbage [1] contributions, but I do not think that is practical. I think I might have to settle with just refusing to use it myself, and wait until everyone realizes that gen AI is just a bad idea.
Note 1: Satya Nadella said he did not want people referring to AI as “slop”, so I will grant his request and refer to it as “garbage”.
