i think we should be ridiculing them more for this. you don't get to try and go all "queer website" when your staff likes to go on nuking sprees targeting the trans fem users
would be remiss not to mention that the rainbow notably straight up just removed the trans flag colors from it. like they’re gone. it’s the progress flag minus the trans flag colors.
i've started reading star: strike it rich, a manga i can only describe as "three underground fighting ring promoters seek out stronger and more insane women to appease the bottomless appetite of the world's most terrifying schoolgirl".
i absolutely love it. just a bunch of deranged women beating the shit out of each other.
969 (nice) words. Probably could have done more this week if I had been a little more consistent across days, but still not a whole lot for having started since Monday. Maybe I'm just expecting too much of myself though - I'm so used to just blitzing through thousands of words when the stars align just so and I'm feeling I should probably work to cultivate a more diligent, consistent work ethic, even if it's irritating and slow.
Not even really finished the first of likely five scenes, but that's probably okay. I'm not super confident on some of the characterization I've got so far, but this is probably the first time I've written these two specific characters and I should probably worry about that when I'm actually finished and get to rewrites.
im just so happy i live in a time period where actual meaningful biological transition is possible. even if we lose rights or the ability to exist in public, nothing can turn back the clock on that, and just by having any sort of access to that our lives are made immensely better. millions of our sisters throughout history would never have dreamed of a day where they could have what HRT does for us.
please don't lose the plot of this. if you're a trans person on HRT you're a living miracle, the dream of hundreds of millions of your ancestors. your lives are all deeply meaningful no matter what anyone says.
Cursed be the one who announced to my father:
“It’s a boy!"...
...How could he twist the course of the stars so much?
How could he have erred so in his astrology?
A lying tongue, a fool’s mouth it had given him
For he foolishly transformed justice to poison
He altered the law and transposed the lines
Oh, but had the artisan who made me created me instead – a worthy woman...
...I would say "how lucky am I"
Father in heaven
who did miracles for our ancestors with fire and water...
...Who would then transform me from a man to woman?
Were I only to have merited this being so graced by goodness...
What shall I say?
why cry or be bitter?
If my father in heaven has decreed upon me
and has maimed me with an immutable deformity
then I do not wish to remove it.
the sorrow of the impossible is a human pain that nothing will cure
and for which no comfort can be found.
So, I will bear and suffer until I die and wither in the ground.
Since I have learned from our tradition
that we bless both, the good and the bitter
I will bless in a voice hushed and weak:
blessed are you [HaShem] who has not made me a woman.
Gooooood evening!! ✨ Today's illustration from LAM-sensei for the BLEACH x LAM Soul Art Showcase 2026 collab is Renji's wifey, Rukia!!! 😍 Aaaaa she's so gorgeous!
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.
did you know the cops once found a fully functioning movie theater with a well-stocked bar inside the catacombs and they when they tried to go back later to formally investigate it was completely emptied out save for a note that read "don't search for us"
my little bro is part of the catacombs community and yeah, it's basically a fully autonomous society! enough that when my bro goes in on a friday night, they don't come out until monday for work- sometimes longer if they took days off.
some of the rooms have fully stocked pantries with cooking equipment, some have movies like the one described above, some have books you're allowed to just take but people always put back- every day people bring things from the outside. artists often set up galleries there. there are rooms with mattresses and hammocks set up for people to sleep. one of the room is just a place where people leave shoes for the fun of it.
this is Known, it's not a secret by any means. the catacombs are as big as paris itself, and people live there just as people live above. it's wonderful when you think about it.
germansingergirl
izzy806
baratheonpilled
snowghoul
titsay
yousharknotpass
