As you know, counting sheeps is perfect for sleep. Sheeps take that job very seriously. But some are still learning. Itâs fine, I donât think Wolf Hunter minds. đđđ
I travel to France quite often, but I have a special love for the south and its lavender fields. Whenever I think of France, those endless purple landscapes are the first thing that comes to mind. Iâm sure there are lavender fields in other regions too, but itâs the ones in the south that have stayed with me the most.Three years ago, I traveled through southern France, visiting Montpellier and several beautiful towns along the coast. I also visited a monastery, wandered through the lavender fields, and came home with hundreds of photographs that I later shared on my social media.Some time later, those memories inspired this painting. Of course, I didnât paint the scene exactly as I saw it. I made the colors richer, the sunset brighter, and the atmosphere more expressive. Thatâs what I love about Impressionismâit isnât about copying reality perfectly, but about capturing an emotion. Perhaps this wasnât the exact feeling I had at that moment, but itâs the emotion that remained with me as a beautiful memory of that journey.
Real thing that changed how i write: I started asking "what does this character think is wrong with them" and separately "what is actually wrong with them." Those two things are almost never the same. She thinks she's too much. She's actually terrified of being too little. He thinks he's bad at commitment. He's actually just never met someone he trusted enough. The gap between their diagnosis of themselves and the real thing, that's your character arc right there. you don't have to explain it. just write both.
Ooooh, we have a bunch of really fancy pedestrian traffic lights in Germany! I need to share:
Starting off with the difference between formerly Eastern German traffic lights (upper images) and formerly Western German traffic lights (lower images):
The city of Erfurt had some additions, like an umbrella or a heart:
Same sex love in Marburg (upper image) and Frankfurt (lower image):
Traffic light lady in Bremen:
Karl Marx light in Trier:
Face of Friedrich Engels in Wuppertal:
Elvis in Friedberg (Hessen):
A sparrow (for the Golden Sparrow film awards) in Gera:
Winemaker in Bad DĂŒrkenheim:
MainzelmÀnnchen (mascot of the public broadcasting service ZDF) in Mainz:
is anyone else annoyed that "ai" encompasses both chatgpt and tools we train to do repetitive tedious work for us. and by the ripple effect of articles like "scientists develop ai to detect cancer early" that make people argue for the merit of chatgpt or become anti-medicine. and by the general state of the world and society
can we bring back the term "fair-weather friend" bc I feel like if fair-weather friends got called that more this whole argument about whether or not you should be there for your friends when it's inconvenient/at what point of personal inconvenience it's ok to bail on your friends would kinda fall apart bc like. we literally have a word for "friend who's only there when you don't need something from them" because the baseline expectation is that a friend should be there even when it sucks. like we used to make fun of people for bailing on their friends.
âFor me this glass is already broken. I enjoy it; I drink out of it. It holds my water admirably, sometimes even reflecting the sun in beautiful patterns. If I should tap it, it has a lovely ring to it. But when I put this glass on the shelf and the wind knocks it over or my elbow brushes it off the table and it falls to the ground and shatters, I say, âOf course.â When I understand that the glass is already broken, every moment with it is precious.â
all i want for 2026 is that gigantic rancid AI bubble to finally burst in such a catastrophic way that the consequences will be so good and i'll never have to see another AI generated image ever again
this is a loving reminder that you can use tumblr on your browser with an ad blocker for a better quality of life, I'm of the opinion you should never be forced to see anything ever
Consider this (based on a conversation I had with some friends a while ago): Pride and Prejudice and Zombies for people who actually like Pride and Prejudice.
LookâI tried to read Pride and Prejudice and Zombies and I got about 20 pages in before I came to the conclusion that the person who wrote it did so out of the belief that the original Pride and Prejudice was stuffy and boring. There were out of character vulgar puns. And the trailer for the movie did not convince me that I had missed anything by cutting short my reading experience.
So, what Iâm talking about here is this premise: the world of Pride and Prejudice, but if you die, itâs highly likely, almost certain that your corpse will get up and try to eat people.
But no one dies in Pride and Prejudice, you might say. In fact, few or no people die in any Jane Austen novel.
This is true. But people do get sick with some regularity. Imagine the tension added to Jane getting sick after going to visit Bingley if there was the chance that she would become a zombie after she died. Becoming a zombie in an eligible bachelorâs house probably would have seriously wrecked any chances of any of the living sisters ending up with him.
Imagine Mr. Collins, as a minister, having the duty upon someoneâs death of severing their head with a ceremonial plate or something that would prevent the corpse from rising. Obviously important, but this only makes him more self-important and obnoxious.
And dangerous.
For you see, in this version, Mr. Bennett, who stays in his office all the time, whose life is the only thing allowing Mrs. Bennett and her daughters to stay in the houseâMr. Bennett is definitely a zombie. He died at home, and Mrs. Bennett decided that, no way were they dealing with this, and soâŠjust started faking it. Jane and Elizabeth know. The younger sisters donât.
In this universe, I think we have to go with zombies that are not any faster or stronger than the humans they were, and in fact tend to get weaker as time passes because their flesh is rotting. AndâŠhmm, okay, how about they are pretty violent upon rising, and for about a week afterward, trying to bite people and spread the infection (even though most people are carriers anyway, but getting a nasty bite from a corpse will give you other stuff that will have you die while carrying the virus). But then they calm down and basically just start sort of attempting to act like they did in life, that is, taking habitual actions with no consciousness, in a depressing and desiccated way.
So Mr. Bennett is a zombie, and Mrs. Bennettâs number one goal is to get her daughters married before anyone finds that out. And this, actually, makes Elizabethâs refusal of Mr. Collins more frustrating for Mrs. Bennettâobviously Mr. Bennett didnât tell Elizabeth that she could refuse Mr. Collins, because Mr. Bennett is dead, but Mrs. Bennett canât say anything or the game would be up.
Another question in this versionâdoes Mr. Darcy find out about Mr. Bennett being a zombie somehow? Does Elizabeth find out that he knows and didnât say anything and this is something that helps repair his earlier actions?
Anyway, this is the Pride and Prejudice and Zombies that I was looking for.
Okay also: in the original, when Elizabeth walks through the rain all the way to bingleyâs to care for Jane while sheâs sick, itâs a very dramatic expression of both Elizabethâs love for her sister and her penchant for flamboyant rebellion, but consider, if there is a chance Jane will wake up a zombie and Elizabeth knows it, how does that change the dynamic? Elizabeth might be going to help take care of Jane, or to *take care* of Jane should things take a more morbid turnâŠby killing her zombie sister.
This works especially well if zombieism is communicable prior to death; if mr. Bennett is a zombie and only the elder Bennetts know, that means Jane has been pre-exposed and is almost certain to wake up as a zombie should she die in the Bingleysâ careâ which the Bingleys do not know. Elizabeth has to forge through the rain to be there in case things get ugly, because she knows that the Bingleys arenât prepared.
And I think you pretty much HAVE to make Mr. Bennettâs zombie status play a role in how and why Darcy separates Bingley from Janeâthe heavy implication behind Darcyâs line about the want of propriety shown even by her father hits Elizabeth like a ton of bricks as she realizes he knowsâhe knows, and he thought Jane lying to Bingley about it was evidence that Jane didnât love Bingleyâbutâbut Darcy must not have told Bingley that part of it. Bingley couldnât keep a secret on his life; if he knew, his sister would know, and word would already be out and theyâd have been ruined by nowâ
And of course, not only does the fact that Darcy, who owes their family nothing, has kept and continues to keep this secret for them even after Elizabethâs refusal deepen the gratitude she begins to feel for him after the letter of explanation, but it also liberates Elizabeth to fall in love with him. Because Elizabeth-who-wants-to-marry-for-love would never be happy marrying someone who didnât know the family secret in advance. She had resigned herself to spinsterhood because she couldnât be satisfied with having to hoodwink someone to have their hand, but also couldnât put her family at risk by trusting someone who wasnât bound to them by more than an engagement. (Maybe she was even tempted to confide in Wickham at one point, and hasnât Darcyâs letter proven she was absolutely right not to yield to that passing thought.) But Darcy figured it out himself, and heâs kept her trust, and she could fall in love with him without guiltâif she hadnât already turned him down.
AND THEN LYDIA HAPPENS. And Darcy realizes immediately that Mr. Bennett canât do anything to recover herâand if Mr. Bennett doesnât do anything about Lydia, Mr. Collins might become suspicious, or even just officously involve himself, so find out the while thing. When Darcy blames himself for not revealing Wickhamâs character, itâs with a much more immediate sense of urgency. Itâs not that the other sistersâ marriage prospects being ruined may impoverish them down the roadâit might immediately drag them all into destitution. Thatâs why he rushes off to go look for Lydia himself.
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.
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