World's Coolest Uincron And Homosexual Commentator
@elf-pet
Follow for inconsistent mixes of several types of tumblr posts and rainbow showers! Hi, I'm the coolest uincron you'll ever meet. You will notice that I am a uincron (pronounced "oyn-kron") not a stupid unicorn. The difference is that uincrons are FAR gayer and WAY more awesome than unicorns. Also, uincrons ACTUALLY exist, unlike that mythical lame-ass "unicorn" you all are so familiar with. My icon is a uincron like myself roaming the skies, blessing the world, casting its homosexual rainbow all across the land as we are commonly seen doing in the wild. Uincrons plague tumblr and spread their homosexual content, humor, and fight off bigotry.
dick makes people mentally ill. dick havers, dick wannabes and dick lovers are all insane. it's like toxoplasmosis, you have compulsive need to defend and push and worship dicks all the time and spead your dick mania to everywhere you go.
this seems rational and grounded in empirical evidence
its so weird like this dog is truly so... like no dog is perfect. or rather, no dog perfectly and easily fits into the modern expectations of an unchallenging housepet without some training/guidance, I should say. there's some stuff about her that is going to be somewhat challenging probably at some point, because she is a dog. but largely I just keep being like "she's fine"
like she's just ... fine? she is fine.
loose in a weird place and heavily pregnant? worried but fine. seeing strange person emerge from car nearby? fine. be captured by this person happily and allow them to put you places and do stuff to you? fine. be contained on a back porch alone much of the day where all your needs are met but there's not a lot of room to roam and people aren't there with you 24/7? fine. being leashed up and walked? fine. being put in a car and taken around to various locations? fine. getting her jabs at the shelter clinic? fine. having the shelter employees bring out another intact female pitbull to see how she would react (OH MY GOD WHY DID THEY DO THIS WHY WOULD ANYONE DO THIS? BUT--) somehow fine. see a loose cat walking around in the parking lot near you? fine. get an X-ray at the vet? fine. techs even remarked that she was unusually cooperative, like to a notable degree. jumpscared by a random malamute emerging from a room right in front of your nose? fine. see some kittens thru a glass window? fine. being left alone all night with just the radio on? fine. have people nearby when you have a REALLY good chew? fine. in fact actively wants to share.
like who is this dog. she immediately loves and trusts every human she meets. she gets worried about stuff but then she looks at her person and sees if they think it's a big deal or not and if they don't think it's a big deal she shakes it off. I opened an umbrella in front of her like people do for puppy temperament tests, and she just startled back a bit in surprise, glanced at Ship and at me, saw that we didn't think it was a threat, and dismissed it. she was just like "OH GOHS WHAT IS THAT, hey new friends what is that is it ok?" and we said "it's ok, I am familiar with this object and it is not a threat" and she said "oh okay phew thanks for telling me, now I know this object is safe :)"
^ translation of our nonverbal conversation translated into Human Words :)
I'm high and I'm just like thinking about how much I love talking to animals
bc you are always talking to them with your body language and if you do it on purpose, they will understand you and they will talk back to you. and you can understand them and talk back to them and they will understand you :) I love learning and knowing about dogs and how they communicate because it makes these conversations even clearer to me because it means I am learning their language better! and I can tell because of their behavior! i love nonverbal communication so much I LOVE DOGS I LOVE DOGS I LOVE DOGS.
Analyzing the politics of a work that's meant to be apolitical is actually a really interesting exercise because it asks you to critically examine what the creator considers to be "political" in the first place. Which ideas are just How Things Are, and which ones are Political, and how is that influenced by the creator's beliefs?
Angrily lashing out at the suggestion that it's possible to do basic media analysis was foundational to the ragebait ecosystem of the 2010s, from which we got basically the entire culture of modern far right politics, btw.
I went outside and got an education, that's where I learned that you can obtain knowledge and insight through analytical methods, then noticed that some people who sit on the internet yelling at strangers get really mad about that constantly.
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 normally tag these posts “specific ass machines” after a minor meme that blew through Tumblr, but I was tempted to tag this one “specific boob machines”.
So one of the things that can apparently contribute to kidney issues in cats is if they eat too much dry food and don't drink enough water; cats are adapted to get a lot of their water from their food since they're originally desert animals, and might not get enough water if they don't eat wet food. Unfortunately, Dozy won't eat wet food no matter what; she categorically refuses to touch the stuff. So a few months ago, we were looking for ways to get Dozy more fluids, and my wife noticed at the pet store a cat drink--basically meat broth with some floaty bits in--that was low-protein and meant for cats with kidney issues. So we figured, worth a try, right?
Great news: she loved it. Super tasty apparently. Great success. Along with the kidney-sensitive treats we found, it was a nice way to supplement her diet. Unforseen long-term consequence though: she loved it so much she began demanding it throughout the day. Like, would come up to us and meow, and meow, and meow, and not stop, until we got up, went to the kitchen, and got her some cat drink.
And by doing so on demand, we have unfortunately created a monster: no matter what we are doing at home, Dozy knows that if she sits next to you and meows, 1) you know what she wants, and 2) you know that she will not stop until you get it for her now. And when you do get it, she gets extremely excited. She will bum rush the kitchen door as you enter. She will run around your feet as you open the can. She will let out the creakiest, crunchiest, most nails-on-the-chalkboard meow you've ever heard if she thinks you're not going fast enough.
I do not begrudge her this. It is gratifying to care for a creature whose most ardent desires are so simple that it is this easy to fulfill them. But I am a little sad, because I know in my heart that I have never loved any comestible as much as she loves this cat drink. She has a pleasure of a purity and intensity that I will never know.
[the creacher in question]
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