I love this post so much. “we used to make posts about loki on here” is the gentlest way possible to describe this website’s history. It’s like saying einstein dabbled in science
The cops very clearly planted evidence on him because they had to make an arrest because all eyes were on them and whoever actually did the deed was making them look stupid.
Why would the real killer hero have kept the weapon on his person and traveled two states over while carrying it and a manifesto in his bag, conveniently turning the crime into a federal matter? The same guy whose bag they found in a park, filled with monopoly money? Why did the police turn off their bodycams, take Luigi's stuff, drive a block away, turn their bodycams back on, go back into the restaurant, and then arrest him?
From the moment of his arrest, even left-of-center media has been presuming his guilt without examining anything (e.g. calling him "the killer" instead of "alleged" or "accused") and then when I say he didn't do it, the nearest person chimes in with some quip that tells me they think he did do it but should go free anyway. Don't get me wrong, I would have the same attitude if he had done it. But he didn't. It makes me feel like the only sane person in the world, even among my staunchly leftist friends.
thanks for the advice tumblr but this post doesn't actually need to be seen i'm just trying to unburden my soul of it like it's some sort of dark passenger i need to exorcise out
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.
Martina McBride didn't win Country Music Association Song of the Year for a song about how burning your house down with your abusive husband still inside it is good, noble, and an allegory for the American Revolution for people to act like the genre belongs to bootlicking fucks
how the hell did I leave Morgan Wade off this list. wrote a song about being depressed, alcoholic, and suicidal and how mental illness stigma sucks, saw how much people connected with it, wrote a Part II of that song about how she's doing better now but you're never totally free of the risk of relapse. fucking icon.
I specifically curated this list so people couldn't be like "ah yes but you see here is my simple binary of good and bad country music which always works", I made sure to add different genders, eras, subgenres, etc and y'all are still pulling that shit in the tags!
listen. Alan Jackson, the archetypal mister big hat man sitting on a tractor singing about a pickup truck, wrote a shockingly normal song about 9/11 that was like "yeah I don't know jack shit about politics but my copy of the bible says we're supposed to love everyone" and then went on the radio and explained how he specifically wanted to write a song about that day that "wasn't vengeful". Miranda Lambert took the southern leftist slogan "y'all means all" and made it the title of a corny ass pop-country song for the Queer Eye soundtrack. Kenny Chesney stole a horse from a cop and Tim McGraw put the cop in a chokehold defending him, and I know that's not about their music but it is, and this is very important, fucking sick as hell
it's fine if you only listen to female country artists or pre-1990 country artists or whatever the fuck you want but stop acting like you've cracked the secret code to dividing a whole genre of art into good pure anti-establishment folk songs vs bad corrupted right-wing sellout pulp
Luke Combs covering Fast Car and keeping the line "I work in the market as a checkout girl" and doing an interview about how he couldn't change a single word because it's not his story. king shit
Morgan Wallen doing I Had Some Help, literally the first song that spoke to me as a male survivor of domestic abuse. also shoutout to the guy for getting caught saying a racial slur and responding by specifically telling his fans not to defend him and raising a bunch of money for the Black Music Action Coalition. bro had an engraved invitation to the culture war and said "nah I'd rather be normal"
Shaboozey just absolutely obliterating the drunk roadhouse anthem glass ceiling
Maren Morris and Brothers Osborne with a song that okay, released in 2019 but I didn't hear until recently, about how good friends mind their own business and let you love whoever you want and also get high with you when you're broke
Kimberley Perry! If I Die Young Part 2!! "actually I'm glad I lived, bitch" ass song that I bet is gonna mean a LOT to kids fighting depression
Kelsea Ballerini and Noah Kahan with Cowboys Cry Too. okay it's shallow and corny but genuinely a shallow and corny song about how men shouldn't be afraid to have feelings is what a lot of men need
If you haven’t heard, today PolyCystic Ovarian Syndrome has been renamed to Polyendocrine Metabolic Ovarian Syndrome. This change reflects that this is not a reproductive “problem” but a whole body disease.
(Text: PCOS affects an estimated 10-13% of reproductive-aged women. It is estimated that up to 70% of women with PCOS worldwide do not know they have this condition.)
everyone's talking about the ibs/autism haha funny comparison thing while I'm still stuck on the concept that hamsters exist in the wild. like naturally
tf do you mean they're a wild creature. you find those ankle-biters at the pet store
Not a biologist, but the evolution of mammals is way more granular than you might expect. Humans are the sole surviving species of the genus Homo, which was a real party before the other ones went extinct. You're in for a fun time.
Domestic cats are believed to be domesticated not from tigers, but from the African wildcat:
Which evolved to be small just because it's sometimes more useful to be small.
And no, hamsters are not off-brand rats. They're part of the rodent order, which includes beavers, moles, capybaras, guinea pigs (yes, also wild) and lots of other fun things:
The crazy thing is, ninety-nine times out of a hundred, if you asked me on any given day "Would like to see a picture of some genitals?" my answer would be "😰 No, that's... No, thank you. I'm okay, actually." I have nothing but the utmost respect for people who do engage with the penis side of the internet, but personally, I've spent the better part of two decades doing all I can NOT to have pictures of dick and balls or sexy bikini babe buttcheeks blasted onto my retinas constantly. And yet... to be denied the penis? To have a jumped up pile of javascript tell me, a grown adult with an air fryer and an outstanding council tax bill, that I cannot be trusted to withstand the sight of a bare nipple unless I let it scan my drivers' license? I will move heaven and earth to see that fucking nipple, friend. I will walk a thousand miles barefoot on hot coals before I give you big brother bitches my passport number. A thousand miles through the desert with five VPNs just to press my face up against the glass and see the last uncensored picture of two My Little Pony Characters sixty-nining each other, and I don't even want! to look at it! But I will! I must! for the sake of our fucking democracy!
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