bad ending: the farmer sells out to Joja
good ending: the farmer restores the community center and Pierre beats up Morris
bad ending++: Morris goes to law school and comes back 4 years later as a Monsanto goon and hits the farmer with a killer lawsuit
good ending++: same as above but the farmer teams up w/ Marlon and Pierre to disappear him in the mines
true ending: the farmer must enter the water purifier even though it’s been established that abigail is immune to radiation
we gotta get back to torrent distribution, i just watched someone eat eight grand in bandwidth charges because they ran a direct-download piracy site with local file hosting through cloudflare. torrents were invented literally for this exact reason
i have a file or folder on my pc that i want to share with other people. let's call it gayshit.mp3
unfortunately gayshit.mp3 is 750mb and im not paying for discord nitro so i need another way to send it
i put it into qbittorrent and it makes a torrent file. this is essentially a very small file that points to gayshit.mp3 so other computers can find it. kinda like a treasure map
i send this tiny file to my friend, who loads it into qbittorrent. their computer takes a moment to find mine over the vast expanse of cyberspace and then (as long as my pc is running and the file is still where it should be), it gets copied from my hard drive to theirs
this is the cool part: if somebody else loads that tiny file, they can download it from both of us. if i'm offline but my friend is on, the third person can still get it. this also means that if two people have separate halves of the file, they can download the other half from each other. as long as some combination of people have the pieces between them, they can all have the whole thing.
crucially this does not require a server!!! you can just upload the file to a few people and as long as they keep it, it's still accessible. as long as somebody, somewhere is still connected, it's available forever. the only way it goes away is if everybody disconnects from it.
Text of tweet under the cut because it is loooong.
But... Stochastic Parrots.
Timnit Gebru was fired from Google in December 2020 for refusing to retract a research paper, and every single warning that paper made about large language models has now happened at a scale the industry spent 4 years trying to make people forget about.
Her name is Timnit Gebru.
She co-led the Ethical AI team at Google. She co-wrote a paper called "On the Dangers of Stochastic Parrots" with Emily Bender at the University of Washington and two other researchers. The paper was 14 pages long. It was submitted to a top AI ethics conference. And it was the reason Google decided that one of the most senior Black women in AI research could no longer work there.
The story Google told publicly was that she resigned. The story she told, confirmed by 2,695 of her colleagues in an open letter, was that she was fired by email while on vacation because she refused to either retract the paper or remove her name from it.
The paper had not even been published yet.
Here is what she actually wrote, and why every prediction inside it has now come true.
The first warning was about scale itself. Bender and Gebru argued that training ever-larger models on ever-larger scrapes of the internet would produce systems that appeared fluent but had no actual understanding of language. They called these systems stochastic parrots because they would repeat patterns from training data with statistical confidence and zero comprehension. The paper predicted that this apparent intelligence would fool both users and developers into trusting outputs that were structurally incapable of being reliable.
This was 2020. GPT-3 had just come out. The paper predicted the hallucination problem before anyone had a word for it.
The second warning was about bias amplification. The paper documented in detail that internet-scale training data contains systematic overrepresentation of dominant viewpoints and underrepresentation of marginalized ones. The models would not just absorb this bias. They would amplify it, because the optimization process rewards confident outputs, and confidence in language patterns tracks frequency in the training set.
The prediction was that hiring tools built on these models would discriminate against women. That healthcare triage tools would underperform on Black patients. That loan approval systems would entrench inequality while presenting their decisions as neutral algorithmic judgment.
Every one of those things has now been documented in deployment.
Amazon's hiring algorithm penalized resumes that contained the word "women" in any context. Healthcare risk scoring algorithms used by major US hospitals were found to systematically underestimate the medical needs of Black patients. Apple Card's credit algorithm gave wives credit lines 10x lower than their husbands for the same financial profile.
The third warning was about environmental cost. The paper calculated that training a single large language model produced emissions equivalent to the lifetime output of 5 cars. The prediction was that the race to scale would create an environmental footprint that would eventually rival entire industries.
In 2024, Google's emissions were up 48% from 2019, and the company explicitly blamed AI infrastructure. Microsoft's were up 29%, same reason. Both companies have now quietly abandoned the climate commitments they were publicly celebrating the year Gebru was fired.
The fourth warning was about documentation. The paper argued that the training datasets being assembled were too large for anyone to actually audit. Nobody at Google, OpenAI, Meta, or any other lab could tell you with confidence what was in the data their models were trained on. This was not a temporary problem to be solved later. It was a permanent feature of the approach.
In 2023, researchers discovered that the LAION-5B dataset, used to train Stable Diffusion and other major image models, contained thousands of images of child sexual abuse material. The companies that had trained on the dataset had no way of knowing. The paper predicted that category of failure 3 years before it was found.
The fifth warning was the one Google cared about most.
Bender and Gebru argued that the deployment of these systems would centralize linguistic and cultural power in the hands of the small number of companies that could afford to train them. The internet would become a place where the dominant voice was a statistical average of dominant voices, presented as a neutral assistant. Languages underrepresented in the training data would degrade over time as more web content was generated by these systems and fed back into the next training run.
This is now happening in real time. A 2024 study found that 57% of new web content in English is AI-generated or AI-assisted. Researchers studying low-resource languages have documented active degradation in translation quality, because the synthetic content fed back into training is itself worse in those languages.
The paper Google fired her for predicted the model collapse problem before model collapse had a name.
The mechanism behind why this all happened is the part of her work that nobody quotes.
Gebru's argument was not that AI is dangerous in some abstract sci-fi sense. Her argument was that AI is dangerous in a very specific structural sense. The technology was being built by a small group of researchers who shared similar backgrounds, worked at similar companies, and were rewarded for shipping products faster than competitors. The incentive structure made it impossible for safety, ethics, and bias concerns to slow anything down. Anyone inside the system who raised those concerns was either ignored, sidelined, or removed.
She was making that argument from inside Google.
Then Google proved her right by removing her.
The team Google had built to make sure their AI was safe was dismantled in 90 days because they did the job they had been hired to do. Margaret Mitchell, the other co-lead of the Ethical AI team, was fired two months after Gebru for searching through her own emails for evidence of how Gebru had been treated.
Gebru did not stop. She founded DAIR, the Distributed AI Research Institute, in 2021. The mission is to do AI research outside the control of the companies that have a financial interest in not hearing the answers.
Every prediction in the Stochastic Parrots paper has now been validated by deployment. Hallucinations are an industry-wide problem the largest labs cannot solve. Bias amplification has been documented in hiring, healthcare, lending, and criminal justice. Environmental costs are larger than entire small countries. Training data audits remain impossible. Model collapse is an active research crisis at every major lab.
The question worth sitting with is the one almost no one in the industry will say out loud.
Every researcher with the technical credibility to call out these problems watched what happened to her in December 2020 and made a calculation about their own career. The number of people willing to speak publicly about safety and ethics issues inside the major AI labs collapsed after that firing and has not recovered.
The researcher Google fired for warning about exactly what is now happening was right.
The company that fired her is now the second-largest deployer of the technology she warned about.
And the people inside that company who agree with her are not allowed to say so.
I remember when the mall store I worked at got a bunch of "Mexican Jumping Beans" in to put up at the register as an impulse buy. I hadn't known that they were a real thing, I thought it was just a random nonsense joke from cartoons.
And then I had to sit in the back after closing, with the mall all dark and quiet as I counted out the drawers, listening to boxes and boxes of Mexican Jumping Beans clicking against their little plastic cases like rain against a window.
They "jump" - more of a wiggle that flips the wedge-shaped seed pod from one side to another - because a little caterpillar lives inside and they flop around partly as they eat and make a cocoon and partly in response to heat, so they'll eventually flop into the shade.
I don't know how many of them eventually emerged and flew away, unaware that they'd spent the majority of their little lives as a product, spending those few days they live as moths fluttering around some kid's bedroom or maybe even escaping out into the endless expanse of suburban sprawl.
These weren't my only moth co-workers; we also sold silkworms, and while technically the kit didn't include the silkworms themselves we mailed a certificate away so we'd have a demonstration silkworm. We named him Bucephalus, after Alexander the Great's horse.
Bucephalus would happily ride around on my shoulder, a gorgeous plump creature that felt like he was made of silk, rising up occasionally to look around and startling the customers. After making his cocoon and changing into a moth - even more beautiful, and still just as silky-soft - we'd walk around the store with him on our outstretched hands.
He'd face ahead, and flap his wings slowly. He probably didn't know why; silkworms have been domesticated for more generations that we can count, and any that remembered how to fly escaped into the wild long ago. Now they just walk, or - when you zoom them around a store in the mall like you're playing with a toy airplane - flap their useless wings gently thanks to some dim vestigial instinct.
Anyway, sometimes I wonder about the future that tech-bros want. A future where we mostly have a purpose as a product and a resource rather than as a person and spend our days sealed away. A future where people's minds are allowed to atrophy in deference to AI, until we've forgotten how to do anything for ourselves.
I hope, in some distant unimaginable future, whatever entity rules over the world our pathetic descendants inhabit still looks upon us with some form of affection.
So my beta reader for the Big Fics is an astrophysicist, right. Who is currently also writing a hard sci-fi novel about the exploration of Phobos (more power to them, I cannot with the physics required for that, best I can do is soft sci-fi/fantasy and that reminds me I should finish that story).
Anyway I was bitching about how hard it is to come up with feasible planets in Star Wars because sometimes you need a new planet from scratch and sometimes you need to know more about a planet than the 'has jungles, is probably a moon technically' than Wookieepedia will give you, and they're like 'oh yeah I can do something about that'.
So they've written (in Matlab but they swear it will run as a .exe as well and I may be conscripted to embed it as a web tool at some point) a star system generator.
You input what you know about the planet (ecosystem, population, sun colour, does it have liquid water, does it have a moon or moons, is it a moon or moons, temperature averages, atmosphere, you get me) and it will give you the... everything else about the star system, in obedience to real-universe physics. And if you input nothing you get a randomly generated star system.
And I’m like oh I know people who will be into this with a vengeance, and they're not on Tumblr, so this is me seeing who exactly would be keen on, and I cannot stress this enough, a real-physics comprehensive star system generator.
It's still in the debugging phase (last error fixed: every planet wants to have a population of exactly 5000 regardless of other factors, turned out to be a missing equals sign somewhere), but I'm psyched for this and trying to gauge interest for how high a priority 'make this an accessible web tool' needs to be.
One of the quiet background realities of the Star Wars galaxy is that it is spectacularly bad at labor. Not just “late-stage capitalism” bad, but structurally, culturally, and institutionally allergic to the idea that workers should have enforceable protections. You’ve got child soldiers, child labor, debt slavery, corporate fiefdoms, and a Republic that can field a galaxy-spanning bureaucracy but somehow never gets around to standardizing “maybe don’t enslave people.” The Empire of course doesn’t fix this; it industrializes it.
So in that environment, formal labor law is either nonexistent, unenforced, or actively hostile. Which means if you’re operating in a sector where the state either can’t or won’t protect you, you get a classic historical pattern: workers build their own rules.
Enter the gray economies.
Groups like the Smugglers' Alliance (Legends) and the Bounty Hunters' Guild (new canon) look, at first glance, like professional associations for criminals. But if you squint at them through a labor history lens, they start to look a lot like early, proto-union structures — especially the kinds you see in maritime or extralegal industries on Earth.
Think pirate codes (yes actual ones, Pirates of the Caribbean didn't make that up). Think matelotage agreements. Think dockworker brotherhoods that predate formal unions.
Because what do these groups actually do?
They:
set norms for compensation and contracts
regulate competition to prevent destructive undercutting
provide a framework for dispute resolution
establish reputational systems (“you don’t honor contracts, you don’t get work”)
That’s industry self-governance in the absence of law.
Take bounty hunting. Without something like the Bounty Hunters' Guild, the field collapses into chaos: clients don’t pay; hunters underbid each other into oblivion; jobs get duplicated, interfered with, or sabotaged. And nobody trusts anybody!
The Guild steps in and says: here are the rules of engagement. Here’s how claims work. Here’s how you get paid. Here’s what happens if you break contract.
That’s basically a union crossed with a licensing board and a regulatory agency, just without any moral pretense.
Same with the Smugglers' Alliance. Smuggling is inherently risky, decentralized, and dependent on trust networks. If everyone is constantly betraying everyone else, the whole system stops functioning. So instead, you hash out agreed-upon routes and territories, informal protections against betrayal, mechanisms for information sharing, and consequences for breaking the code
Again: not altruism. Stability.
And the reason this emerges specifically in gray/illegal sectors is because they have to. The Core Worlds might pretend they have laws, but those laws don’t meaningfully protect the people actually doing dangerous, itinerant, high-risk work. So the margins of the galaxy — where enforcement is weakest and risk is highest — become the places where labor organization evolves first.
Which is very historically grounded.
On Earth, some of the earliest labor protections didn’t come from governments; they came from workers in dangerous, decentralized industries—sailors, pirates, miners—who literally wrote their own rules because no one else was going to save them.
Pirate codes, for example, often included:
compensation for injury
shared distribution of loot
limits on captain authority
Which is … shockingly progressive compared to a lot of contemporary working conditions (cough Amazon cough).
So in the galaxy far, far away, you end up with this ironic inversion:
The “legitimate” systems — Republic, Empire, megacorporations — are exploitative, inconsistent, or indifferent.
The “illegitimate” systems — smugglers, bounty hunters — are the ones building functional labor frameworks, because they need to survive.
And that feeds back into why the galaxy feels so unstable overall. There’s no universal baseline of rights. Everything is hyper-local, network-dependent, and contingent on whether you’re inside a system that has rules you can rely on.
If you’re a clone trooper? You are literally property.
If you’re a factory worker on a corporate world? Your protections are whatever your employer feels like offering.
But if you’re a smuggler or a bounty hunter?
You might actually have clearer expectations about your pay, your risks, and your recourse — because your “union” is the only thing standing between you and total chaos.
So yeah: the Smugglers’ Alliance and the Bounty Hunters’ Guild aren’t just flavor. They’re a glimpse of what labor organization looks like in a galaxy where the state has fundamentally failed to provide it.
why is it always a male character going mad avenging his dead wife and never a female character cradling her dying pure of heart husband in her arms then dragging the whole world down with her
I don't know where it came from, but several years ago this idea popped into my head unbidden, and for some reason it tickles me. I don't know if it's funny, but I like it and I made it into a zine, I hope you enjoy it.
It lays out really nicely as 3-up spreads on A4 paper, so you can print, staple and fold it, then cut it into 3 zines. It made it really easy to print up 20 of them to trade at this art social thing I went to
micron, rotring and sharpie on printer paper, coloured and screentoned digitally, 2024
Imagine you get a personal external hard-drive (handheld size) that has every public/account-available post on a site to date (nothing from the future or that has been deleted prior to the download process). You only get to pick one website for it. Which would you pick?
Wikipedia
Reddit
Tumblr
TikTok
“Fanwork” website (e.g. AO3, FFN, Live journal, Wattpad)
Webtoon
Instagram
Twitter
Internet Archive
A (1) non-YouTube streaming service (which one?)
A less legit streaming service 🏴☠️
Other (comment? Or if you really just want YouTube lol)
Voting ended onMay 4
TMI notes:
The posts downloaded have to be uploaded/native to the site; external links to elsewhere will not be saved to the drive (this is why no search engine was included…it’s just links to other places lol)
Private posts won’t download unless you personally have access or could get access personally logged in.
YouTube is a bit of an outlier— if that’s your #1 I’d like to know what your second pick would be, if you would want anything else
There’s a few others I would have liked to list but options were limited 🫡
idk what neurodivergent young adult needs to hear this but you are NOT supposed to give 100% at your job. I've gotten more promotions and raises since I started giving 40-60%, which my evil CEO uncle informed me is what bosses actually expect when they say 110%. My mental health has improved tremendously. I've spent 2 out of 5 workdays secretly writing my novel for the last 2 years and I've never been more respected and appreciated. Also--when you see glaring wasteful errors in the company's operating systems, say absolutely nothing! Embrace inefficiency. It is your friend in this capitalist hellscape.
@sparrow-va Seen a lot of people asking this and here's a starter-pack, which others have also added in the comments:
Start on day one. It's almost impossible to scale back if you started out giving 100% —it might be possible though, so don't give up hope.
If you can get away with it, 'waste' roughly half of your time. You can work on a personal project if IT won't clock you, or go for long walks if you can sneak out of the office. I walked 3-4 miles every day when I started my current job. I also walked to Barnes & Noble to sit on the floor and read comics. I've spent a few days just watching TikToks or Fall of Civilizations. If you have Work From Home days, buy a mouse jiggler! (Don't install mouse jiggler software, that shit's traceable.)
If you're still not sure, pay close attention to how much work your worst coworker is doing, and copy that. I bet you it will be 40-60% of what you feel you could easily do, especially if they are 50+.
Never finish anything immediately. If you want to get a project done, knock it out, and then set a reminder to send it at least 2-3 days later. I fuck this one up the most, if I'm honest, 'cause shocking people with how fast I can accomplish things is like a drug.
Remember!!!! Being the fastest and the best will get you NOTHING—except possibly the kind of attention that gets you abused and fired. Promotions for hard work are a myth. It's capitalist propaganda you MUST expunge from your brain. Aim to be the worker your manager expects, not the one they're impressed by—except in a social sense. I got a $2 raise for singing in 3 part harmony with my bosses once.
I'll also make sure to honestly say during check-ins with my boss that I've "got some extra bandwidth if there's anything anyone on the team needs help with" because it:
1. Proactively keeps them from asking which lets me keep it vague and not have to say "I've got about 30 hours of my 40 hour work week free actually and I've mostly been working on my hobbies".
2. Makes me look like a team player and genuinely lets me be one since honestly I'd rather help out other people than have more projects that are directly mine anyway.
3. Rarely results in more work, or if it does they're super grateful and it's just a tiny bit more so whatever.
origamiaround
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