Frin is drinking wine (It would be red if there were colors)
Isa drinking beer
Dile drinking entire bottles worth of vodka (because let's be real)
Mira is drinking a cocktail (it's barely alcoholic because they couldn't handle anything stronger and yet they're still somehow wasted)
Bonnie is drinking cherry juice (Siffrin lied to them saying it was the same thing as wine, which they completely and wholeheartedly believed, and now believe they are drunk)
Where's that video of skeletor being edited so that he's just giggling and giggling and standing up then sitting down again and rolling around and not saying anything
Funny that the stereotypical cynic is an idealist who aged out of it. In my experience, the reverse is true. I was an extreme cynic as a teenager and then I noticed how profoundly limiting it was, and also that "cynics are cool and smart" was a message that was being constantly reinforced by corporate media for some reason.
#yes! cynicism reads as very juvenile to me#and yes prev often stemming from teen pain
Yeah, like I see black-pilled people on here and my default reaction isn't "oh, these must be world-weary old warriors who've lost their faith in humanity", it's "these people are in their 20s and need a hobby"
I also think that the present era has proven that authoritarian leaders don't actually want a population of wide-eyed idealists, they want a population of jaded assholes who are convinced that everyone is lying, any resistance is either a scam or doomed to failure, and nothing can ever get better.
btw it's so fucking stupid you can be anxious physically in your body even after you've decided mentally you don't care. I'm supposed to be in charge here
A cis woman tells me that maybe she should transition to gain male privilege as I'm recovering from getting beaten up in the men's bathrooms.
I tell her to be my guest and give me a call when she gets her jaw broken, I always carry a first aid kit and a pepper spray.
She calls me a misogynistic asshole.
A cis man tells me that he'd sure love some T.
Gave him my prescription and best of luck with the constant shortages and getting denied.
He calls me a pussy.
I'm fighting for my life and reproductive rights. I get told to get off women's fights, that it's not about me, like I shed my womb after my first T shot.
I search for support groups for SA victims, and I'm stuck in the same āwomen/NBs onlyā. Still shooting my shot, send an application. I introduce myself. Never get a call back.
I go to a trans night. Say I go by he/him. Get told back āyeah, that's how we all start !ā by a trans woman. I'm too exhausted, I get up and I leave.
I hang out with my friends, one of them drunkenly says masculinity is a prison we must learn to escape. She gets rows of applause. Back to drinking alone.
Yes I could explain it. But who'd you rather be ? A delusional girl or a man made threat ?Or it could be better, I could just not exist ! And we'd bleach my corpse and I'd become a casualty. Not an F, ot an M, a W for Wound and for Wrong.
I put a candle on a single cupcake, 2 years on HRT. I blow it in the dark. Curtains closed like casket.
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.
this might piss some people off but I donāt think some of you actually ever tried to unlearn your hatefulness. you just came out as queer and decided your new targets really truly deserve it this time.
this might piss some people off but I donāt think some of you actually ever tried to unlearn your hatefulness. you just came out as queer and decided your new targets really truly deserve it this time.
this might piss some people off but I donāt think some of you actually ever tried to unlearn your hatefulness. you just came out as queer and decided your new targets really truly deserve it this time.
"why polyamorous people aren't valid" "mspec lesbians AREN'T okay actually" "aroallos are freaks" "he/him dni. cis men dni" "this post is for non-men only" yessss and the one with long hair goes in the girl box, then the one with short hair goes in the boy box!!
maybe I'm just a boring he/him white guy but inventing about 7 trillion terms to define "man" and "woman" so you can reinforce gender essentialism isn't very "love is love" of you. maybe i just don't have a sexuality but picking and choosing what sexualities are normal and which ones are "weird and predatory" sounds like we're all a bunch of republicans on fox news. if you attend your local pride parade and look REAAALLLYYY closely, you'll notice you can't actually tell if someone's gay or not from their appearance, and there's no way to know if they're "invading queer spaces". maybe it's just me, but when i attended my local gaybar last night for the drag show, they didn't ask for my gay-card with a peer reviewed diagnosis of faggot stamped on it. they just let me in the building. i live a life of bliss and luxury in not caring about any queer discourse ever, and just going "WHATEVER MAKES YOU HAPPY :-)" while booting up the latest cod game. and it seems much more fun than whatever the fuck you people are on about
As Google has worked to overtake the internet, its search algorithm has not just gotten worse.Ā It has been designed to prioritize advertisers and popular pages often times excluding pages and content that better matches your search termsĀ
As a writer in need of information for my stories, I find this unacceptable.Ā As a proponent of availability of information so the populace can actually educate itself, it is unforgivable.
Below is a concise list of useful research sites compiled by Edward Clark over on Facebook. I was familiar with some, but not all of these.
ā
Google is so powerful that it āhidesā other search systems from us. We just donāt know the existence of most of them. Meanwhile, there are still a huge number of excellent searchers in the world who specialize in books, science, other smart information. Keep a list of sites you never heard of.
www.refseek.com - Academic Resource Search. More than a billion sources: encyclopedia, monographies, magazines.
www.worldcat.org - a search for the contents of 20 thousand worldwide libraries. Find out where lies the nearest rare book you need.
https://link.springer.com - access to more than 10 million scientific documents: books, articles, research protocols.
www.bioline.org.br is a library of scientific bioscience journals published in developing countries.
http://repec.org - volunteers from 102 countries have collected almost 4 million publications on economics and related science.
www.science.gov is an American state search engine on 2200+ scientific sites. More than 200 million articles are indexed.
www.pdfdrive.com is the largest website for free download of books in PDF format. Claiming over 225 million names.
www.base-search.net is one of the most powerful researches on academic studies texts. More than 100 million scientific documents, 70% of them are free
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