||-terfs kick rocks-|| ||-🏳️⚧️building a better boy🏳️⚧️-|| ||-24- (he/they)-|| ||-i like birds a normal amount and mostly vultures-|| ||-pfp by @reidspng on IG-||
Ozempic scares the shit out of me. You're telling me there's a drug that takes away both the craving side of hunger and targets the brain's rewards center for eating. You're telling me it takes the joy out of eating and it turns you into a skeleton. Why did we turn The Curse of the Black Pearl into a drug. What the fuck.
I actually want to thank the diabetics coming on this post like "actually it genuinely is a great treatment for diabetes and it hasn't affected my mood or my enjoyment of food. The real issue is it's getting abused as a weight loss drug which also makes it scarce and more expensive for those who can genuinely benefit from it." Kind of reminds me of the time my brother got permission from our family psychiatrist to try my ADHD medication and his reaction to it was "what the fuck are you on. WHAT THE FUCK ARE YOU ON. WHY DO I FEEL LIKE CRYING. YOU'RE ON THIS EVERY DAY!?!"
Body chemistry! It makes a big difference in how your body processes a drug! What can be genuinely helpful for some folks is The Curse of the Black Pearl for others!
i think stories without a romantic subplot are so important actually because i didn’t even realize how much internalized aphobia i had rolling around in there until i saw ryland grace be genuinely happy and fulfilled by platonic relationships
It has been literal years but every time I see Martin’s tweets posted somewhere and his word is shared as truth while her post is not shared it sort of reiterates the fact that we trust men to speak about feminism more than we believe women who experience it.
Reading her account of how their boss treated her blows me away. Men are so emboldened that they will literally admit to illegal discrimination casually and face no consequences.
Adding screenshots of her post. His whole post is there without needing a link. Hers should be, too.
Also, she posted this is 2017! It’s fucking 2020 and I’ve seen his side of this for years, but it took 3 years for her side to make its way to my dash…
Eva and Grace’s dynamic is so important to me. They’re in love platonically. Like, that’s not a common dynamic. She put the way he likes his coffee into the ship’s computer. He follows her around like a puppy. In the book, she cracks jokes with him and him only. She cares about his opinion. He was the only one she asked about the coma gene, wondering if it was worth it.
He’s her best friend, and she doesn’t even know it. They’re so close, that in the book, people think they’re sleeping together, and poor Grace is so confused because he thought that was his platonic work wife, wdym people think we’re sleeping together, that’s my person that I crack jokes with and then she glares at me because they’re not funny.
She’s softer with him than anybody else and is only ever vulnerable around him. We see in the movie, he’s the only one who ever gets her to smile, and sometimes even laugh, and then she serenades all of them, but mainly him, and he stares at her with those big, shiny eyes so lovingly, and she points at him when she sings, “everything’s gonna be alright”, and then she gives him those eyes, so loving.
And then she’s trying to stop herself from crying when she’s sending him away because, against her will, he’s become her person, and somewhere along the way, she’s become his, and they will have forever ended this relationship on bad terms, and nothing can fix that.
It’s a platonic tragedy. It’s a platonic love story. This is something we don’t get often, or, like, ever, and it’s deep and it’s tragic and it’s sad.
But even after, Eva’s still taking care of him. Packing clothes she knew would bring him comfort. Programming the ship to know how he likes his coffee. And Grace is still watching out for her, speaking to her directly in his video logs, with that same lopsided smile he used to throw her way.
He uses Rocky’s sign for goodbye, and she uses it back, and how did this book and movie give us such a deep platonic friendship because, guys, this NEVER HAPPENS.
Eva and Grace, the platonic male/female friendship of all time.
does anyone have that gif of a penis growth ad thats a guinea pig that stretches out rly long and a girl says “hot!” and the guinea pig spins around pls i need it
You literally cannot find this type of community interaction on twitter or instagram or any other app. Look at the support, the gratitude, the absolutely incomprehensible shared knowledge of this most cursed, most rare gif.
as a lover of Women Fighting & Killing media it's so important to me when they actually let the women look like shit. you know what i mean. like im so bored when a woman is in what's supposed to be a brutal fight and her hair is just aesthetically tousled or something and her makeup is still pristine. fuck offfff. if she's beating the shit out of someone and fighting for her life she should be covered in blood n bile she should look like she got hit by a truck and the truck exploded
duuuuuude you have GOT to come out tonight we're enacting cruelty upon those who have transgressed so badly that we can justify any act against them... and you KNOW we're interpreting our delight as moral righteousness... Yeah it's fucking crazyyyyyyy get an Uber
love seeing revisionism in the wild “free the nipple never meant you can walk around topless every where that’s still sexual harassment it just meant for like breastfeeding and stuff”no it literally means you should be able to walk around topless anywhere because get this. breasts aren’t fucking sexual organs.
I remember when I was about 12, I watched a show on TLC that followed people as they got somewhat uncommon medical procedures.
There was one episode with a trans woman getting different gender-affirming operations, including breast implants. It showed the procedure, and (what I found so fascinating that it's stuck with me for decades), as soon as the doctor put the implant in, a censor blur popped up on the nipple.
And you just know there was a meeting between the TLC lawyers and the editors and producers of the show to discuss what the difference was between a "man nipple" (can be shown) and a "woman nipple" (no no must obscure, 'tis naughty). And they decided that as soon as the implant goes in and the nipple has more mass behind it, that's the moment when it becomes a woman's nipple and must be hidden to comply with TV rules.
But it's the same nipple. On the same person. I know what it looks like; I just saw it. But TV and obscenity rules are rules, and the rules say woman nipple = sexual and therefore explicit, but man nipple = neutral, just fine.
"Free the Nipple" was calling out arbitrary bullshit like that, because someone just existing with their body parts should not be considered obscene, and the double standard that men can be topless but women can't is so blatantly ridiculous. All nipples are just nipples. If you get turned on or bothered by them, that's on you.
idk why people are still trying to do "hear me out"s on tumblr
you could talk about wanting to fuck the space needle on here and people would still call you a poser for insisting on fucking "conventionally attractive architecture" as if that's a coherent, easily-recognizable category
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.
