Hey, I'm Erin, and I tend towards the medieval, tea and the occasional obsessive spiral. First & Last & Always: Poe, terrible puns, Tolkien rated r for explicit language, scenes of sci-fi/fantasy violence and gore The Tags Page
Kind of obsessed with this woman's freakishly modern jacket from 1904.
The complete lack of shoulder definition gives it the silhouette of an MA-1 bomber jacket, but bombers weren't even a thing yet. The Wright brothers barely achieved powered flight in 1903. The ribbing on the shoulder and the angular cutouts with the hexagonal mesh are so futuristic and cyberpunk, but even art deco wouldn't be a thing for another 15 years. The color is like a dusty NASA flight suit. All together it's giving lone spacefarer crash landing their tiny rustbucket ship on Mars.
Hey guess what i saw this a few days ago when i was in an absolutely scary slump and then i spoke to my counsellors and did what they told me to do and now i feel so much better. So this is true. Reblogging for more good luck
Because the essence of humanity and life as a whole is a constellation of connections with one another. We are all here in this cosmos together, from the tiniest creatures to the distant stars.
2 hours of bad sleep will have you thinking things like 'i am a stranded whale and i need to be covered in dynamite in an ill-advised attempt to clear the beach'
Fear of what the dead might do to us didn’t start with Dracula, and it didn’t end with him, either.
I’m reading this book rn. Definitely worth it if you’re interested in vampire history, although History Today called its approach “exhaustive and sometimes exhausting” so do be prepared for that
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.
older lotr illustrations sometimes depict éowyn wearing ridiculously small armour. apart from the problem general sexualisation of the only female character (who really does anything), there’s another hilarious thought:
éowyn pretended to be dernhelm, a man. to fit in, she must have worn men’s armor. so the armor in the illustrations is normal for rohirrim.
therefore, all the rohirrim rode to war just like that:
there’s a thundering sound in the distance as the rohirrim ride into war but rather than hoofbeats it’s the collective sound of all their cheeks clapping
Frank Frazetta was the reason He-Man was designed like that; the producers conduct a study to see what art appeal the most to children, and Frank’s work came out on top in popularity. So everyone in He-Man is dressed the way they are directly because of Frazetta.
Ah, it has been too long since I have seen the no pants post on my dash. And yes, this is a rare case where it wasn’t some sexist nonsense but an egalitarian No Pants Agenda.
“I am definitely an ass man. It blows my mind. Talk about simple shapes. Two very simplistic curves. It’s so dumb, but they are fascinating as hell. It’s more than that. It’s the way the rest of the anatomy ties into that area — incredible beauty”
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