Please sign my choice my voice and allow women in the eu access to medical health care https://sign.myvoice-mychoice.org/forms/join-myvoice-mychoice?source=direct_link& Insta @voidwatchesback Art @voidwatches-art
cheese sits on the toilet while we take showers, and i like to stand on my tip toes and draw his silhouette in the steam from a high angle, then stand back to see how warped it is from his actual shape
so you're telling me the fifa world cup is all men? its all men's teams? and so is the superbowl? and all the sports teams that states are known for and make copious amounts of merch for are also men's teams? and only 5 women have ever entered formula one since its inception in 1950 and only two of them were able to compete? and this is normal? its acceptable?
i grew up playing backyard soccer on the pc as a child in the early 2000s where boys and girls would play on the same team and against each other and you're telling me that's still an unrealistic fantasy that can't happen in real life?
Heartwarming story: Little girl doesn’t have to do anything to fund her dad’s surgery because his expenses are covered by his country’s universal healthcare.
Human determination: Man bikes 18 miles to work every morning because he wants to and not because he can’t afford a car and would be fired if he’s late.
Spirit of Brotherhood: Neighbors host housewarming party for elderly resident who doesn’t need help in paying rent because his pension is more than enough.
SO INSPIRING: Local middle school students bake dozens of cupcakes because their home economics class is doing a baking unit. Their school is fully funded with everything they need.
As you know, counting sheeps is perfect for sleep. Sheeps take that job very seriously. But some are still learning. It’s fine, I don’t think Wolf Hunter minds. 🐑🐑🐑
reading progressive sex ed caricatures with accurate and detailed and realistic diagrams of sexual organs + shows their variation, but all i can think about is how there is no discussion of what srs is besides the fact that it exists
this one has been passed around recently from the mayo clinic and that actually makes me so happy because how many of transfeminine people are aware of what their options even look like?
there’s a diagram for phallo and meta from springer link(i believe) and. honestly i’d never seen these before and i dont think i’ve ever seen any diagrams. i know vaguely because of reading papers or listening to people talk about their experience but i’ve never seen it, yk? it makes me more confident in my choice to get meta when i’m older
There’s a website called Transbucket that has a whole archive of before and after photos, surgery costs, surgeon names and locations, and general feedback on complications, sensation, everything. It’s been around for at least a decade, and there are photos of some folks five or eight years down the line. It’s organized by procedure, and it’s very comprehensive. It’s NSFW of course but it’s an amazing resource!!!
Are you considering or have had transition care? | Transbucket.com
I made this series to share clear, no-BS info about abortion in a way that feels kind and easy to understand. Each post starts with a simple “Did you know?” fact — covering everything from how long a first-trimester procedure takes, to what recovery can look like, to the reminder that all kinds of people (not just women) have abortions. I wanted the tone to feel approachable and nonjudgmental, so I used soft, pastel rainbow colors and a clean layout to keep things gentle but informative.
joining the war on kids reading any book they want on the side of kids reading any book they want. simply you will be fine. it's even good to be confronted with things you don't understand and even find upsetting, uncomfortable and difficult. it's a surprise tool that will help you later.
literally ok so not a funny story but kind of funny? when I was nine I encountered rape in a book and I was like hey mom what’s this mean and she explained it and I was like oh. gross. and then like two weeks later a girl on the bus abruptly disclosed her csa and we were all like ????? what ???? but I was like wait hang on there’s a word for that ☝️🤓 and explained what it meant and that it was illegal and that you could talk to a teacher or my mom if it had happened to you and everyone was like ohhhhh I see I see and very somberly comforted the girl (she was safe she was removed from her home and living with my neighbor at the time so it wasn’t Urgent)
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.
IF YOU SEE ANY PAINTING BY "EMILE CORSI" ON HERE, DO NOT REBLOG IT THINKING IT'S REAL AND FROM THE 1800s. IT IS AI-GENERATED AND EMILE CORSI IS NOT A HISTORICAL FIGURE
And if you love the vibes and wish you could find something similar painted by a real person, let me introduce you to John William Waterhouse, on whose work the AI was definitely trained:
For anybody not caught up: Tennessee just passed a new map that pretty much makes it so black neighborhoods have no power in local votes. Two things about this. While protestors were chanting "No Jim Crow", white Tennessee lawmakers were caught laughing on video. On top of this, Representative Justin Pearson and his brother KeShaun Pearson were arrested for trying to give their takes on the matter (which is not only their legal right but literally his job). If you give a shit about black people, help fight this. We can't allow a return to Jim Crow.
A local paper had some great photographs, all taken by Nicole Hester:
The day before, Rep. Justin Pearson tries to attend a Senate Committee meeting and is barred access by the Sergeant at Arms.
Lawmakers and protesters link arms as the descend the capitol steps.
Once inside the chamber, Democratic representatives continued to stand together with arms linked.
They continued standing together with arms linked as votes were cast.
Democratic representatives take a group photo protesting the redistricting.
Rep. Justin Jones burns a photo of the Confederate flag with the words, We will not go back.
And stomps the ashes.
KeShaun Pearson being escorted from the building by the Staties.
KeShaun Pearson (left) being taken into custody. Rep. Justin Pearson (right) showing his support of his brother.
Additional information: State lawmakers have been gunning for Pearson and Jones nearly their entire terms. Most notably, in 2023, the House expelled them for participating in a protest at the Capitol. Their districts had to have special elections to have them reinstated.
Pearson is one of the plaintiffs of a lawsuit seeking an injunction against the redistricting.
The city most affected by the redistricting is Memphis, where locals are fighting against xAI's data center, which has been operating with very little oversight and is poisoning the people who live there. Here is a previous post on that with more information and more sources.
A little tiny microscopic dragon, rotifers passing by.
I've spent a lot of time peering down a microscope in the last few years, enjoying taking inspiration from the real tiny organisms to make one of my own.
yousharknotpass
turnnoffyourmind
jacobvanloon
romaincrisis
snowghoul
origamiaround
baratheonpilled
