when youāre a gay lion and you accidentally tried to introduce your lesbian lioness friend to one of her own exes at a gay bar and she goes into the bathroom and bitches you out for not being able to tell her endlessly rotating cast of girlfriends apart which isnāt really fair because first of all they all keep dyeing their hair different colors and second of all she keeps getting back together with different ones at different times and meanwhile youāve beenĀ āsingleā for like 8 months but are spending a lot of time with one specific guy who works at your old co-op and were going to excitedly tell her about it tonight but now youāve ruined the whole subject of dating by trying to introduce her to her own ex at a gay bar (which is a watering hole. because youāre lions.)Ā
HOLY SHIT GUYS, I WAS INSPIRED BY THIS POST TO TRY MAKE THE SONG AND YOU WOULD NOT BELIEVE THE SCREAM I SCRUMPT WHEN I DRAGGED THE TRAINING AUDIO OVER THE BACKING TRACK AND IT LINED UP PERFECTLY
what the fuck did the producers inject into Help Me, ERINNNNN! to make it so stupid catchy???? it's stuck to my brain like a parasite god that chorus is impossible to not hum or sing at random it's been years please let me go
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.
In case you just skimmed the post above and missed it, I want to reiterate and highlight Gebru's current position as Executive Director of Distributed AI Research Institute. If you're curious about what AI technology might look like when not applied in the horrifically unethical and damaging way it's currently applied, please check them out.
If we want to have nice things, decentralization is essential, and if we want to decentralize, we need to have our eyes on things that are beyond the scope of the current Big Tech narrative.
The Distributed AI Research Institute is a globally distributed organization of academics, activists, and engineers conducting community-roo
so im insane incredibly normal about chants of sennaar and this fic, 'on exile, and the things we call god' by kirta (@aurore-parle-de-ses-idees @thalion71) in particular and decided i needed a hand-bound, (faux) leather, embossed, illustrated version of it.
and by the power of pva glue, janky translating, and homosexual audacity, i have one :D
š Artists and titles will be revealed after the poll closes, so check back for results! Until then, please don't mention the song title in reblogs! (Guesses about everything else are fine and encouraged though; have fun!) š
House of Leaves is a book about a man trying to explore the inside of his new home, which proves substantially more difficult than should be possible, due to its non-Euclidean dimensions.
Except that House of Leaves is actually about a documentary about a man trying to explore the inside of his new home, which proves impossible to document properly, due to its non-Euclidean dimensions.
Except that House of Leaves is actually about an academic paper, which itself is about an alleged documentary about an alleged non-Euclidean home, but none of this can be verified.
Except that House of Leaves is just, like, this fucking stack of papers I found in this old dead guyās apartment, and, like, I donāt even know if its his or what because like both his eyes were gone and he didnāt have any degrees or anything. I tried asking my friend from the tattoo shop about it but she was fixing up this thumper tattoo right above a girlās pussy the whole time we were talking; like Thumper from Bambi, and Iām not gonna lie man I was pretty distracted and I just couldnāt [XXXXS XXXX XXXX. XXXX XXXX XXX X XXX XX XXXXXXX XXXXXX XX XXXX XX XXXXXX XXXX XXX]^*
āāā
* Editorās Note: House of Leaves is a metatextual examination of the ability for a minor inconsistency in measurement, which might have been ignored by a normal person, to cause an all-consuming obsession spiral in the sort of person who is academically trained, obsessed with documentation, or overtly pedantic, and-
āJohnny, please, Iām your Mother; I know I have a lot to apologize for but I canāt, not unless you return my letters; are you even getting my letters? I send one every week you know, but I think that nurse keeps them from you, keeps you from getting my letters, because I know, I know my sweet Johnny would never leave his poor old mother rotting away by herself in this horrible drafty ward if he was getting his motherās letters, would you, sweet boy? I know sheās stealing my letters from you, sheās always touching my things, even though they havenāt moved I know sheās touching them I know she keeps you from me I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know [thereās a limit to what you can know. Some folks bump up against that limit and bounce right off and keep swimming, and some folks, well. Some folks SPLAT]I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know [they just gotta keep digging away at it. Even when itās not that deep, they justā¦ grab a shovel and keep digging. Lord knows what motivates them. A kind of Madness I suppose. Some folks find GOD in that madness. Not much of a believer myself]I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know I know
I know
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I know youāll visit me for Motherās Day, wonāt you?
was thinking about how the fandom used to have Bridgette and Felix be Marinette and Adrien's cousins who used to be LB and CN before them. and them it hit me like a brick that specific headcanon was popular 10 years ago.
do you read fanfic for a fandom you haven't engaged with otherwise?
no and I wouldn't
no but I'd try
yes and I liked it
yes but it's not for me
I don't think ppl should read fanfic without understanding the source material
Walter White
Voting ended onMay 27
just stumbled across a video of someone asking for fic recs and when asked what fandom they replied 'any' and my mind short circuited, pls add your thoughts in the tags
playing the world ends with you for the first time... does Neku stop being an insufferable asshole or am i saddled with an unlikable MC for the entire game
quick update neku got slightly better he's actually bearable now . my new enemy is mingle mode. open pictochat on my ds lite -> open twewy on my 3ds -> keep opening and closing mingle mode for 20 PP per time. i know this was surely cooler back in the day but right now it just looks like a baffling design choice to me.
Unstuck in translation @minothtime - Tumblr Blog | Tumgag
