ummm here have some random tomodachi life moments er .......
papyrus and rouxls have a thing going on and spamton and jevil want 2 get married 2 eachother now... alphys has a crush on queen but she hasnt done shit abt it bruh... some screenshots bellow
shortly after queen interrupted rouxls' failed confession to mettaton and got rejected, she ended up actually falling in love with mettaton
after a day of pining and seeing his face in clouds, she wanted to confess. despite still not even being friends with him yet
rouxls, still not over mettaton, showed up and tried his luck Again
(rudy did not show up this time, but earlier that day he'd moved in with noelle and subsequently remembered he's a dad, which further proves that his initial appearance was solely motivated by having nothing else going on in his life)
I fully expected this to go as poorly for them both as the first time. and yet...
their mutual love of making rouxls cry brought them together 💙
however. I am not convinced that this is true love.
this is clearly the island's two biggest celebrities faking a relationship so they can orchestrate the messiest, most dramatic break-up imaginable. and I love that for them 💕
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.
This is so, so important. I highly encourage everyone to read the full text under the readmore.
I also want to say that I feel like part of the problem with trying to explain this to a wider audience will be that most people don't know what stochastic means.
Well, in short, stochastic means random.
-via Merriam-Webster Dictionary, accessed May 26, 2026. Image description in alt.
So, that's what Google's lead of AI Ethics and her fellow leading AI researchers said about LLMs in 2021:
Generative AI is just random Random Parrots
ChatGPT is a Random Parrot, which is why it's literally incapable of giving you reliable answers to anything
Gemini is a Random Parrot, which is why it's literally incapable of giving you reliable answers to anything
Claude is a Random Parrot, which is why it's literally incapable of giving you reliable answers to anything
Deepseek is a Random Parrot, which is why it's literally incapable of giving you reliable answers to anything
They are very convincing parrots!
But no matter how impressive a parrot's ability to echo human words, you wouldn't let it write your contracts. Your court depositions. Your wedding vows. Your grocery lists. All your emails. All your papers for all your classes. All your thank you notes and letters. All your expense and budget reports at work. All the reports you send to your boss.
That's what people are doing.
They're trusting their entire lives - their grades, their decisions, their fucking wedding vows, half their fucking interaction time -
to a fucking random parrot
(that also tells suicidal people to kill themselves and tells recovering addicts to go do meth, btw)
Don't do that. Like, on top of all of the other issues like the massive environmental impacts, and modern slavery in mines in the Congo, AI psychosis, etc. etc. etc. etc.
Please don't let a random parrot that's wiretapping you for Amazon or whoever run any part of your life
jbbartram-illu
vaporwave
stormborns
theartofmadeline
ellievsbear
