[quotes--and--lyrics]

“A ghost can be a lot of things. A memory, a daydream, a secret. Grief, anger, guilt. But, in my experience, most times they’re just what we want to see. Most times, a ghost is a wish.” 

― The Haunting of Hill House (2018) dir. Mike Flanagan 

[noknowshame]

resurrected dead wife watching her own montage: wow I looked so hot in that

[despazito]

Sometimes I'll be looking at bullshit online that I know will just rile me up and I have to think of this image to get myself to stop

[kiefbowl]

I saw on insta this morning a reel of a woman who's been hosting a dinner party for friends for the past two years show snap shots of the parties each month for the last year. and I'm interested in that in general, I'd like to start hosting more. so I go into the comments and there are just some rank ass ppl saying things like "oh so you're rich rich" and "some of us don't have money." Is it fun living so miserably?

[kiefbowl]

maybe this is abstract but I think this is fallout from phone addiction fr. it's easy to say "well I'm burnt out at the end of the day" about scrolling on your phone rather than doing hobbies if you're so addicted you'd be doing it anyway. and it will suck up time. you will lose skills. and I'm not saying this on a high horse, we're all struggling with it right now including me. But if you're not deliberately working on distancing yourself from phone addiction, you will spend your life watching other people have lives and think that the only barrier is your own unavoidable situation in life. girl I think it's you actually. you can make some sandwiches and ask some friends over.

[basslinebutch]

Wet Leg live at Øya Festival in Denmark

photos by Johannes Andersen

[64mpg]

thank you for misunderstanding me even though i took the time to over explain myself in a very articulate way

[accordionlover]

cross stitch, words from Jenny Holzer's Livings, 1980-1982

[justalurkr]

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.

[hildegardavon]

Adolph Hirémy-Hirschl, 1860-1933  

The birth of Venus, n/d, oil on canvas, 109x227 cm

Private Collection

[lustingupon]

[sosuperawesome]

Vincent Giarrano on Instagram

[aghostisawish]

i haven't finished florescence yet but i am confused by the mixed reception. my only complaint i guess is that i maybe miss some of the more pop bops from the good witch. otherwise it feels like a very strong follow up to me.

[ceruleanwhore]

To everyone in Massachusetts: If you don't know this already, Alex Rikleen is probably the candidate you actually want for senate! If you, like me, have felt stuck between a rock and a hard place because Markey is way too old and Moulton is a centrist corporate sellout, Rikleen is literally the solution. He's truly left-of-center (like he's calling what's happening in Palestine a genocide and all his stated policies are liberal) but he's like 40(?) instead of being an octogenarian who shouldn't even be allowed to drive anymore. The problem is that the Big Money that wants Moulton to replace Markey so they have more control over our state has also been getting their grubby fingers in the media, so Rikleen has been fighting like hell but is barely getting any coverage at all.

They want us to feel like it's Markey vs. Moulton and push us to vote in Moulton, but Rikleen is very much a viable option. I just talked to him and he told me there was just a poll that showed that, even though only like 15% of people in the state have heard of him, half of everyone who has would like to vote for him, which is insanely huge. He could win this yet, if the delegates know to consider him as an option and if people start talking about him so he can't keep getting relegated to the side and silenced. This is literally our chance to vote for a candidate we actually want instead of picking between the two options the billionaires backing the party want to force us to choose from, so take it! I encourage you to do your own research, reach out to him, whatever you want but do consider Alex Rikleen as a candidate and, positive or negative, talk about him!

[massachusetts-official]

Official Post of Massachusetts

[senatortedcruz]

Have you thanked god for making you a coastal elitist today?

[userfish]

[signedthemoon]

— isa b. i dream of a home

[peachbecreative]

[8nin]

so done with tumblr. see u all in two minutes