every major structural social problem right now is basically "we don't have enough skilled workers on the ground" and the reason is always "well we've been intentionally underpaying and understaffng them for decades to increase corporate profits" and somehow the news always just mentions the "shortage" without digging into the cause
air travel is a mess? shortage of air traffic controllers - for some mysterious reason
logistics a mess? shortage of truck drivers - for some mysterious reason
public transit can't meet demand? shortage of bus drivers - for some mysterious reason
We even mysteriously have shortages of doctors, nurses, teachers... FOR SOME MYSTERIOUS REASON
The destruction of public and higher education and the degradation and subjugation of workers has been an active part of conservative policy for more than fifty years.
Related: when conservatives say "no one wants to work anymore", what they mean is "no one wants to give up a substantial portion of the fruits of their labor in order to enrich an idle capital-holding class".
Good to see San Antonio’s queer community saying HELL NO to Greg Abbott’s absolute fucking loser behavior. Rainbow crosswalks aren’t allowed anymore? Okay, let the LGBTQts take the whole sidewalk then, dickmunch!
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.
The Necron army I painted that was raffled off for charity this weekend. Painted over the last month, apart from the Nightbringer, which I painted in January.
Next year, I’ll do it over again with a new army. This is the 10th time I’ve done it, and I love doing it. There’s something special about creating something like this, trading it off for charitable donations, and releasing it into the world. I’ll likely never see it again, and there’s a bit of magic in that.
"There are legends of people born with the gift of making music so true, it can pierce the veil between life and death. Conjuring spirits from the past and the future."
SINNERS (2025) dir. Ryan Coogler
SpaceX shared new details about a crewed Mars flyby in the lead-up to Thursday's Flight 12 launch attempt.
"During the live webcast, SpaceX played a video of cryptocurrency billionaire and civilian astronaut Chun Wang speaking from Bouvet Island in the South Atlantic Ocean. Wang, who has gone to space one time before, explained that he will embark on a Starship flyby of the Moon and Mars."
Ah, yes, the crypto dipshit who rode in a rocket once is going to *checks notes* command a mission to Mars.
SpaceX is such a fucking joke. I don't know how anyone with self respect can work there.
I will vote for any candidate who promises to go scorched fucking earth on every tech company. Break every single one of them up into companies based around a single product and then split those in thirds. Weaponize existing antitrust laws to the hilt and pass the most draconian versions of them ever seen on this planet. Nationalize google search specifically. Pass consumer privacy protections strict enough to kill the data harvesting industry for good. Make all of these fuckers go bankrupt for this rent-seeking shit
Under Virginia law, a month had to elapse before the death sentence could be carried out. Governor Wise resisted pressures to move up the execution date because, he said, he wanted everyone to see that Brown's rights had been thoroughly respected.
Brown made it clear repeatedly in his letters and conversations that these were the happiest days of his life. He would be publicly murdered, as he put it, but he was an old man and, he said, near death anyway. Brown was politically shrewd and realized his execution would strike a massive blow against Slave Power, a greater blow than he had made so far or had prospects of making otherwise. His death now had a purpose. In the meantime, the death sentence allowed him to publicize his anti-slavery views through the reporters constantly present in Charles Town, and through his voluminous correspondence.
Before his conviction, reporters were not allowed access to Brown, as the judge and Andrew Hunter feared that his statements, if quickly published, would exacerbate tensions, especially among the enslaved. This was much to Brown's frustration, as he stated that he wanted to make a full statement of his motives and intentions through the press.[54]: 212 Once he had been convicted, the restriction was lifted, and, glad for the publicity, he talked with reporters and anyone else who wanted to see him, except pro-slavery clergy.[46]
Brown received more letters than he ever had in his life. He wrote replies constantly, hundreds of eloquent letters, often published in newspapers,[133]: 43 and expressed regret that he could not answer every one of the hundreds more he received. His words exuded spirituality and conviction. Letters picked up by the Northern press won him more supporters in the North while infuriating many white people in the South.
Just a couple of the quotes about him that I like:
“His zeal in the cause of freedom was infinitely superior to mine. Mine was as the taper light, his was as the burning sun. Mine was bounded by time. His stretched away to the silent shores of eternity. I could speak for the slave. John Brown could fight for the slave. I could live for the slave. John Brown could die for the slave.”
-Frederick Douglass
"That new saint, than whom nothing purer or more brave was ever led by into conflict and death, — the new saint awaiting his martyrdom, and who, if he shall suffer, will make the gallows glorious like the cross."
I still can't believe, that in the evil vampire season, which confirmed the presence of malevolent ghosts and literal bigfoot, the real villain is the illusion of choice in a two-party political system.
