You can’t realistically stop all of your bad habits at once. So like. Pick one. Pick one thing in your life to work on. Eating slightly more vegetables or being slightly nicer to your coworkers or reducing the amount you drink. Something. And once that’s easy try something else.
oh and when i was a year old, after i got my foot amputated my parents were pushing me around in a stroller at a street festival in miami and i was chewing on my foot or whatever and this street performer came up to us and was like “aw i bet that tastes good!!” and my dad was like “yeah look at what she did to the other one!!!!” and pulled back the blanket covering my left leg to show a stump with a huge scar on it and i’m pretty sure my dad terrified that poor man
When my sibling was about 4 years old our grandmother came to visit and took her own dentures out to clean them. My sister watched in abject astonishment until my grandmother noticed, turned, and said, “Shall I do yours next?” at which point the kid slapped both hands over her face and yelled, muffled, “MINE DON’T COME OUT!” and ran away.
Many lgbt teenagers and young adults growing up on the internet today have socially conservative beliefs that they voice at all times that they got from their conservative parents which they’ve never challenged because they think the life experience of being gay or trans makes them politically progressive
This is why I hate it when people say something homophobic and then go “so you’re really accusing me, a whole ass lesbian, of being homophobic 🙄” like yeah
you ever get so into the whole "it would have been good if it was good" thing that it gets kind of embarrassing. it would have been good if it was good but it's Not and in fact it's maybe worse than anything else but unfortunately. it still could have been good. if it was 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.
It is not nearly common enough knowledge that most Native tribes in the U.S. don't actually own all of the land within their reservation. There are millions of acres of reservation land that tribes don't legally own and they have no control over how that land is used. Like, there are a lot of different concepts tied in with the land back movement, but a major one is literally just getting reservation land back into tribal ownership.
hi, filipino here. just want to say that our independence day is june 12, not july 4. july 4 is when the united states government decided that they would recognize our freedom, specifically because it is your independence day and they wanted to cement their cultural hegemony over our country. and because of their influence on our country this was recognized for a time as our independence day. we still commemorate it, but i hope you can understand why we don’t want our independence day to be associated so closely with our former colonizer. it wasn’t even a work holiday for us.
june 12 is the day that we filipinos declared our own independence for ourselves, and that is what we celebrate as independence day
I saw this when running newpipe. But wait, it gets deeper. I clicked on the details buttons and it said as of today, we have 83 days left until Google rolls out this new requirement for apps inside and outside of the google play store. If any developer disagrees with their new terms and fees, they will be blocked!
I'll share some of the info below:
Looks like they're trying to nuke the remaining privacy and freedoms we have left on the internet.
What to do?
-Get your developer friends to not comply to their new guides
- Sign the open letter on the site and take action by checking out the full resources list on their website as well!
To summarize, this is all daunting especially when you feel all alone with unfair and inhumane regulations comming out faster than improvements but we got this working together!
Share the link with your friends, family and anyone who will listen!
Your phone is about to stop being yours. In September 2026, Google will block every Android app whose developer hasn't registered with them.
“Why don’t you use ai” idk man beyond the obvious environmental and “this machine causes psychosis and encourages people to kill themselves” thing I think asking the equivalent of a solid D student who is also a pathological liar if they can answer my question/do the work for me seems pretty fucking stupid
This morning I finally saw a bee on my melon plants trying to pollinate the flowers but the flowers were too small for his whole body so he was just shoved by his head in there and kicking his little bee legs trying to get in there to the yummy yummy pollen and it was so cute.