TO DUMP ALL OF MY (@/twipsai) REBLOGS!!!! NOT MY MAIN!!! I WILL STILL REBLOG ART TO MY MAIN FORMALITIES: IM TWIP, HETHEY PRNS, ADULT, I LIKE SPACE + ALIENS, ETC
i think i don't really vibe with most other fans of my favorite male characters is because they usually depict them too much of a man, and i am not interested in men, i am interested in The Character. and i am not saying that they should depict them as women, or nonbinary, or should depict them as feminine, no, not at all. but there's like, you know, you can depict a male character as The Character, and you can depict them as The Man. do you get me? like, i go to the fandom looking for art and fics, and it's just, regardless of his actual characterization, it's all just fantasizing about some kind of an abstract dominant patriarch, wearing my favorite character's face. it may be the most totally-wouldnt-have-normal-relationships (and sometimes even would-literally-abuse-you) kind of guy, and you join a dedicated space for his fans, and all they talk about is how they want to marry and start a tradcore 50s style nuclear family with him. it can be a guy who's arrogance and attempts of domination are explicitly shown to be a facade that hide the fact that he's actually kind of a massive pathetic wet loser, and you go to his fics, and they're all depicting him as a caricaturish daddy dom. at this point it's like, do you even like the character at all, or do you just like The Man, and project this man onto whatever character you find visually attractive? and these people kind of, really really poison actual discussion of the character, who is kind of a fucked up evil person (i only like *those* types, so im talking about them) because they see analysis of the actual character as an attack on their fantasized daddy dom husband, who is actually isn't The Character at all, and is simply a face of the day for The Man
🍖 How to Build a Culture Without Just Inventing Spices and Necklaces
(a worldbuilding roast. with love.)
So. You’re building a fantasy world, and you’ve just invented:
→ Three types of ceremonial jewelry
→ A spice that tastes like cinnamon if it were bitter and cursed
→ A holiday where everyone wears gold and screams at dawn
Cute. But that’s not culture. That’s aesthetics.
And if your worldbuilding is all outfits, dances, and spice blends with vaguely mystical names, your story’s probably going to feel like a cosplay convention held inside a Pinterest board.
Here’s how to fix that—aka: how to build a real, functioning culture that shapes your story, not just its vibes.
─────── ✦ ───────
🔗 Culture Is Built on Power, Not Just Style
Ask yourself:
→ Who’s in charge, and why?
→ Who has land? Who doesn’t?
→ What’s considered taboo, sacred, or punishable by death?
Culture is shaped by who gets to make the rules and who gets crushed by them. That’s where things like religion, family structure, class divisions, gender roles, and social expectations actually come from.
Start there. Not at the embroidery.
─────── ✦ ───────
2.🪓 Culture Comes From Conflict
Did this society evolve peacefully? Was it colonized? Did it colonize? Was it rebuilt after a war? Is it still in one?
→ What was destroyed and mythologized?
→ What do the survivors still whisper about?
→ What do children get taught in school that’s… suspiciously sanitized?
No culture is neutral. Every tradition has a history, and that history should taste like blood, loss, or propaganda.
─────── ✦ ───────
3.🧠 Belief Systems > Customs Lists
Sure, rituals and holidays are cool. But what do people believe about:
→ Death?
→ Love?
→ Time?
→ The natural world?
→ Justice?
Example: A society that believes time is cyclical vs. one that sees time as linear will approach everything—from prison sentences to grief—completely differently.
You don’t need to invent 80 gods. You need to know what those gods mean to the people who pray to them.
─────── ✦ ───────
4.🫀 Culture Controls Behavior (Quietly)
Culture shows up in:
→ What people apologize for
→ What insults cut deepest
→ What people are embarrassed about
→ What’s praised publicly vs. what’s hidden privately
For instance:
→ A culture obsessed with stoicism won’t say “I love you.” They’ll say “Have you eaten?”
→ A culture built on legacy might prioritize ancestor veneration, archival writing, name inheritance.
This stuff? Way more immersive than giving everyone matching earrings.
─────── ✦ ───────
5. 🏠 Culture = Daily Life, Not Just Festivals
Sure, your MC might attend a funeral where people paint their faces blue. But what about:
→ Breakfast routines?
→ How people greet each other on the street?
→ Who cooks, and who eats first?
→ What’s considered “clean” or “proper”?
→ How is parenting handled? Divorce?
Culture is what happens between plot points. It should shape your character’s assumptions, language, fears, and habits—whether or not a festival is going on.
─────── ✦ ───────
6. 💬 Let Your Characters Disagree With Their Own Culture
A culture isn’t a monolith.
Even in deeply traditional societies, people:
→ Rebel
→ Question
→ Break rules
→ Misinterpret laws
→ Mock sacred things
→ Act hypocritically
→ Weaponize or resist what’s expected
Let your characters wrestle with the culture around them. That’s where realism (and tension) lives.
─────── ✦ ───────
7.🧼 Beware the “Pretty = Good” Trap
Worldbuilding gets boring fast when:
→ The protagonist’s homeland is beautiful and pure
→ The enemy’s culture is dark and “barbaric”
→ Every detail just reinforces who the reader should like
You can—and should—challenge the aesthetic hierarchy.
→ Let ugly things be beloved.
→ Let beautiful things be corrupt.
→ Let your MC romanticize their culture and then get disillusioned by it later.
─────── ✦ ───────
📍 TL;DR (but like, spicy):
→ Culture is not food and jewelry.
→ Culture is power, fear, memory, contradiction.
→ Stop inventing spices until you know who starved last winter.
→ Let your world feel lived in, not curated.
The best cultural worldbuilding doesn’t look like a list.
It feels like a system. A pressure. A presence your characters can’t escape—even if they try.
Now go. Build something real. (You can add spices later.)
—rin t.
// writing advice for worldbuilders with rage and range
// thewriteadviceforwriters
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“The LEGO Movie was my favorite movie of 2014, but it strikes me that the main character was male, because I feel like in our current culture, he HAD to be. The whole point of Emmett is that he’s the most boring average person in the world. It’s impossible to imagine a female character playing that role, because according to our pop culture, if she’s female she’s already SOMEthing, because she’s not male. The baseline is male. The average person is male. You can see this all over but it’s weirdly prevalent in children’s entertainment. Why are almost all of the muppets dudes, except for Miss Piggy, who’s a parody of femininity? Why do all of the Despicable Me minions, genderless blobs, have boy names? I love the story (which I read on Wikipedia) that when the director of The Brave Little Toaster cast a woman to play the toaster, one of the guys on the crew was so mad he stormed out of the room. Because he thought the toaster was a man. A TOASTER. The character is a toaster. I try to think about that when writing new characters— is there anything inherently gendered about what this character is doing? Or is it a toaster?”
— Bojack Horseman creator Raphael Bob-Waksberg commenting on how weird gendered defaults in entertainment are, and why we should think twice about them. Excerpted from this longer original post.
(via 360degreesasthecrowflies)
i am of the sincere belief that if ur on ur computer a lot you should visually customize it to high hell and back not just for funsies but also because it has literally made me less depressed before. its kind of like how rearranging your bedroom is good for your brain, yknow. i do stuff like this every few months
LIVE WALLPAPER: wallpaper engine. only thing on here that costs any money (its like 5 bucks on steam). im sure theres free alternatives but this one has a lot of presets and stuff so its less hassle and its what i use. might be a bad idea for lower end pcs tho
CUSTOM TASKBAR: retrobar on github (lots of different options)
CUSTOM CURSOR: theres a lot of places to find these, but rw-designer open cursor library is a good place to start
DISCORD: betterdiscord, im using the clearvision v7 theme with a custom background
EXTENSIONS (these are for firefox, might or might not exist on other browsers):
tabliss for the new tab theme
stylus for tumblr -> specifically the 'tumblr - custom dashboard pallette' theme for colors + bg, and this for the pre-twitterifcation layout
enhancer for youtube for custom youtube colors
the browser theme is just one i found on the firefox theme 'store'
My desktop background is still a picture of the front of the local shop I got it from, with tweaks to make the neon signs pop and to make sure there's absolutely no dark shadows. It's a very vibrant image, a local store, and kiddos tech savvy friend works there.
But I'm absolutely doing this when it's time to change.
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 know we’re both just messing around pretending to be whole but look at me. if the train was coming would you move. if the ground was falling from under your feet would you even notice or would it just be another tuesday for you. if somebody stabbed you could it hurt worse than you already do. what i’m saying is that i love you but i think we both drive over the speed limit when it’s raining. what i’m saying is that i want to hold your hand and i understand about how you sometimes have to sit down in the shower. what i’m saying is that i’m here for you and if the train comes please move.
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