I'm Trying

Lumi, 34, Autistic. Disabled artist.

[ex0skeletal-undead]

Waldinneres (In the Forest), 1933 painting by Hans Emmenegger

[ex0skeletal-undead]

Thank you @nuka-rockit I was actually going to ask if anyone spoke German and if that translation, which came from Wikipedia, was any sort of accurate. Fascinating. Titles are so important.

[aidashakur]

Wishing you a relaxed nervous system

[phantomrose96]

That thing where milkmaids were often immunized against small pox because they'd already contracted the weaker cow pox earlier in their lives. That's Tumblr, to me, against whatever the hell social media landscape is happening in 2026.

[phantomrose96]

"TikTok Instagram Youtube-Shorts Share-Your-Whole-Life Influencer Social-Media Online Online Online" it cannot affect me. I was already a weird online 16-year-old all so many years ago. You cannot grab me raw and unfortified with these poisons. I inoculated myself when glomping was a thing. I am still on Tumblr making text poasts.

[sparrowposting]

"if you worry, you suffer twice"

Brother, I am inventing new types of worry and ways to suffer thrice. Perhaps even FOUR times.

[great-and-small]

The stubby legs of a sanderling may not look like much at first, but boy can these babies skedaddle when they need to

[roswellsoup]

bonus/proof:

we tipped her well dw. best waitress ever 🍒

[maidthings]

"this is unbecoming of me" is genuinely a useful thing to have in your mental toolbox

[fake-lancelot]

[loveridden1999]

top 3 hobbies for young adults:

1. borrowing misery from future

2. carrying grief of the past

3. agonizing over the present

[nattousan]

ok so, I approached my local library with a proposal to donate a mural as a way to A: build portfolio/gain practical experience and B: give back to a beloved public institution. The director was very enthusiastic about it and i've been working on it since the beginning of March. Come with me as I endeavor to paint what is in all honesty an excessive amount of birds

I wanted the birds to look like they were actually in the space so first thing after doing the draft was to do a lighting study

after that I covered the walls in letters in lieu of a projector/vr headset bc i have neither of those :) Then i take a picture of the section of wall and superimpose the lineart over top of it so I can pencil in the lines

et voila

and that was a whole week on it's own so next comes the paintin' >:)

[prokopetz]

This is 100% me being a crank, but I'm getting real annoyed at seeing Ancient Traditional Crafts™ videos that depict people grinding minerals to make pigments with no respiratory protection. Like, yeah, an N100 mask isn't Authentic and shit, but do you know what powdered mica does to your lungs?

[prokopetz]

@sawdust-emperor replied:

Watching any green or blue-green mineral being ground to make pigment in these, praying it's just rough glass or some shit and not any of the almost always notably poisonous green minerals:

Being as I've also seen examples where the craftsperson is handling what appears to be raw cinnabar with their bare hands, I wouldn't say the odds are good there.

[ajaxgb]

[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.

[mckitterick]

definitely read under the cut for the full overview

essentially, everything Gebru warned about LLMs in her paper has come to pass, including "model collapse," the issue where LLM datasets grow worse as more of their training data - the internet - becomes AI-generated slop, degrading the LLMs more and more as time goes on

because LLMs aren't really artificial intelligence and cannot understand anything - they're just really good at sounding like the dominant language - their "hallucinations" (nonsense and lies) will continue to worsen. they're not even really algorithms anymore, just "Stochastic Parrots"

the human, cultural, and environmental cost is awful and building. when these LLMs become unusable and all the hundreds of billions of dollars invested evaporate, the economic collapse will be unimaginable

[squeakitties]

"do it scared" gets exhausting when you're The Fearful Afraider and everything is scary even when you're in your 30s

[bird-gifs-collection-agency]

this baby tawny frogmouth is hungry hungry hungry! hes taking it all!

[drumlincountry]

Why do they even make apps for ADHD. You want me to use my 24/7 handheld immediate distraction device? To manage my 'gets distracted too easily' disorder? Ooooh we developed the perfect tool for managing your anemia. Its hosted in Dracula's castle. 👍

[shortshortking]

Picked up my phone to consult my task list for today and now I'm reblogging this instead, case in point

[lycanr0t]

comic about determination and hope

[necromancelena]

Computer loves to be like "fuck! You sure you want to shut down? Youve got volume mixer open"

[crossconnectmag]

Crocheted Leaf Sculptures by Susanna Bauer

To truly appreciate the delicacy of Susanna Bauer‘s leaf sculptures, think of crunching a dead leaf in your hand, how it disintegrates into dust with the slightest effort. To work with dry and fragile leaves as a medium for crochet seems nearly impossible, but Susanna somehow manages it with ease, turning leaves into cubes, tunnels, and geometric patterns with techniques that might be more appropriate for the durability of leatherwork. She lives and works in Cornwall, England. You can see more on her website and Facebook. 

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