"It would be a shame if protesters started wearing safety glasses, hard hats, respirators, and gardening gloves, all of which can be found at the hardware stores. It would be a shame if they started using traffic cones (the kind without the hole in the top), upside down buckets, or other improvised lids to contain teargas by placing them over the canisters.
It would be a shame if protesters learned that police scanners are legal to own in the US, allowing them to learn where police are moving, and what routes they intend to take. It would be a shame if they discovered that these scanners can be used to send as well as receive, allowing them to flood the scanner frequencies with noise.
All of this would be a terrible, terrible shame.
“It would be an awful shame if you copied and pasted this, so that they couldn’t delete the original and all linked posts (again).”
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alright I've got to do some quick math to explain attitudes towards AI to my boss.
we're looking to create an AI policy, and when we were talking about this, my boss (older millennial) was genuinely shocked to hear that younger people do not (seem) to view AI positively (a la the recent commencement speakers being booed)
please rb for larger sample size!
Question 1/3
What is your age, and do you feel AI is a net positive or net negative in our lives today?
Further context: Durham city council (Reform UK) cut funding and support for Pride. The Durham Miner's Association and other trade unions raised enough money for Durham Pride 2026 to go ahead - a direct call back to when Lesbian and Gays Support the Miners (LGSM) raised money for mining communities when Margaret Thatcher seized union funding during the miner strikes of 1984-85.
At the 1985 Labour party meet, the motion to support LGBT rights as a party was passed due to a block vote from mining unions.
Stephen Guy, the chair of the Durham Miners’ Association, said that when it became apparent Durham Pride was under threat, he took it upon himself to “encourage the trade union movement to step up and do the right thing, and stand shoulder to shoulder with the LGBT+ community […] They not only raised funds for us, but came to our communities, uplifted our spirits when they were down, and showed their solidarity.”
im posting this here despite the website being extremely white centered, I want people to understand how in this country it's basically ok to murder and victimize black people, especially women and children in the name of "self defense" and white America will reward you for your antiblackness.
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for those wondering why they're free to take now, it's because the company that made those "chicken soup for the soul" books bought them a few years ago and then completely collapsed so bad they couldn't afford to dispose of or even take the blu rays and dvds out of their kiosks all over.
so any of them is free game because they're all located on other business' property and they usually don't want to have to pay to get rid of them either. so asking the store manager usually gets you the ok to pull it out and keep it.
there was a period of time right after their bankruptcy where you could put in any debit or credit card and it would spit out movies without charging you. you could even put in like an expired or deactivated card, or a visa gift card with a $0 balance, didnt matter, they'd just start spitting discs out. a lotta people raided redboxes for movies for a couple months, with some people doing what me and my brother and my dad did here, taking the whole box and signs and marquees as well. because managers sure as hell don't want a big abandoned piece of trash on their sidewalk disappointing customers. BUT they're also often too cheap to pay someone to remove it. so they just sit there.
luckily there are no shortage of freaks like us who will just take them away on our own volition. we did it all "by the book", too: we set up cones and caution tape, disconnected electricity properly, used an angle grinder to grind down the bolts in the concrete so nobody would trip on them, then cleaned everything up afterward and sealed off the electrical panel so the store would know everything is safe and tidy. though they were hesitant when we were first contacting them, they were honestly very relieved and grateful when we finally took it away, especially once they saw that we "knew what we were doing" (we don't) and look like we've "done this before" (we haven't).
the fun part: the reason why this redbox, in particular, was completely full and unraided is because the computer hardware inside had failed some months before the bankruptcy, and a failing company sure as hell wasn't gonna send a tech out to our podunk dipshit city to fix it, so it was impossible to rent movies or take any discs out. plus, for who knows how long, people were returning old redbox discs to this machine and not taking any out, leading to a much higher variety of movies than your average redbox.
there is a thriving community of redbox hackers and modders out there, as well, creating open-source software for repurposing the machines and not letting their very interesting and robust disc-management hardware go to waste. this one belongs to my brother (who was very annoying persistent and did all the legwork of contacting managers and securing permission) who is a programmer by trade and will be hacking it into a family-access movie library, with whatever discs we want. i mean the machine is completely weatherproof and has a built-in AC unit, it would be such a waste to not try to turn it into something cool.
if we get another one, i'm gonna try to mod it into some sort of art or zine vending machine. the disc boxes are just the right size for small print art or stickers. would make a great "little free library" too.
remember: the rules are made up. act like you belong there and you can get away with anything. this applies to your own life
She got the idea for the study while walking with her advisor at Stanford to discuss her thesis topic, and the paper she eventually published in the Journal of Experimental Psychology in 2014 is sharp enough that it should have ended the seated meeting on the day it came out.
She ran 4 experiments on 176 people. Same person tested twice. Once sitting, once walking. The creativity tasks were the standard ones psychologists have used for decades to measure how good a brain is at generating novel useful ideas.
81% of participants in the first experiment produced more creative ideas while walking than while sitting. In the second experiment, 88%. In the third, 100%. Every single person walked into a more creative version of themselves. On average, people generated 60% more novel useful ideas the moment their legs started moving.
The skeptical question is the obvious one. Maybe it was the fresh air. Maybe it was the scenery passing by. Maybe it was the change of environment doing the work, not the walking itself.
Oppezzo killed every one of those explanations with one experimental decision. She put people on a treadmill facing a blank wall. No scenery. No fresh air. No environmental change. Just legs moving in place while staring at white drywall. The 60% boost held.
Then she ran the experiment that closed the case completely. She took participants outside in two conditions. Half of them walked through a Stanford courtyard. The other half were pushed through the exact same courtyard in a wheelchair. Same outdoor stimulation. Same scenery passing at the same speed. The only difference was whether the legs were moving.
The walkers produced dramatically more novel high-quality ideas than the wheelchair group. The outdoors did almost nothing on its own. The walking did everything.
She also tested the opposite kind of thinking. Convergent thinking. The kind where there is one right answer and you have to narrow down to it. Word puzzles where 3 words share a hidden fourth word that connects them. The seated participants did slightly better on these. Walkers got slightly worse.
Walking is not a general intelligence enhancer. It does one specific thing. It opens up the divergent search inside your brain. The part that generates options. The part that produces unexpected connections. The part that takes a problem and finds five ways into it instead of one.
When you need to converge on the single right answer, sit down. When you need to find the answer in the first place, get up.
The mechanism is now well understood. Walking selectively activates what neuroscientists call the default mode network, the system inside your brain that runs when you are not consciously focused on anything. The DMN is where mind-wandering happens. Where memories cross-reference each other. Where ideas that have been sitting in separate folders inside your head finally bump into each other.
When you sit at a desk and force yourself to concentrate, you suppress the DMN. When you walk at a natural pace, the executive part of your brain gets just busy enough handling the walking that the DMN comes online and starts doing the work that focus was blocking.
The most useful finding in the entire paper is the one almost nobody quotes. The boost did not turn off the moment people stopped walking. Participants who walked first and then sat back down stayed elevated. Their next round of seated creativity work was still significantly better than people who had been sitting the whole time. The rest lingered for at least several minutes after the legs stopped moving.
You do not need to do creative work while walking. You need to walk before the creative work. The brain holds the state.
The biggest misconception in public schools is that literary analysis is about proving you can be right or wrong about a book you read
Literary analysis isn’t about the book
It’s not even about being right
It’s about performing an investigation and presenting your case to the jury
It doesn’t matter if your defendant killed that guy or not. If you can convince the jury he didn’t, you’ve won
And the incredible life skill of spinning bulletproof bullshit out your ass with a handful of facts and a prayer is soooooooo much more valuable than anyone’s ever gonna tell you
If the average tweenager knew that good media analysis meant you could force your English teacher to admit that fuckin- (rolls dice) What’s Eating Gilber Grape is a metaphor for (rolls dice again) Why the crack cocaine epidemic is good actually- we would have far better literacy and critical thinking skills as a nation. And I stand by that
You could develop the magical psychic and illusory power to force the middle aged bitchfuck who makes you raise your hand and beg for permission to take a shit accept the premise that Cocomelon is a subversive and scathing artistic commentary on the pitfalls of modern democracy. Chat GPT essay engines are stealing this from you
The most significant lesson I ever received in Literature classes was that everything is actually about abortion.
My regular teacher was out for the day, so the “this guy works here but nobody quite knows what he’s supposed to do” substitute was in for her. His name was Mr. Moony. I suspect, knowing more now, that Mr. Moony was the special education coordinator for gifted and talented students. But that’s all besides the point.
The only thing that mattered about Mr. Moony for this story is that every student knew you never learned anything when he was in, because he was always batshit insane. He would completely disregard plans, throw them away, and tell us to do something different.
When he came in, we had just finished reading Waiting for Godot. We were well on our way to an AP Lit exam, tired and worried, and we had a practice essay coming up based on this play. And he said, “you’re all burnt the hell out, so I’m going to write an essay for you.” We all cheered because, hell yes, a lecture day. We didn’t have to do shit. We could all tune out and stop caring.
And then he started going.
We were enraptured. This man deconstructed the two act play into a masterpiece, quoting ancient literature on theology and God, as well as personal details about the author, to reveal to us all that, actually, Waiting for Godot was the author’s roundabout way to show the anguish behind the politics of the pro-life/anti-choice movements, and the author’s criticisms of abortion.
He went on for a half hour, writing faster than we could really keep up with. By the end of his rant, we were all nodding along. At the end, he slammed his hand on the board and shouted “ABORTION” to really make his point.
“So, do you all think that’s what this story is about?”
The majority of us nodded, myself included. And this man looked at us, scrunched his face like Kermit the Fucking Frog, and went, “no the fuck it’s not. I made all that up.”
There was a beat of everyone feeling like their time was wasted. Some students very frustrated because they were trying to take notes and just realized it all was fabricated. One or two who were angry about being woken up to him shouting abortion.
And then he looked at us. “How many of you only believe it’s about abortion because that’s what I just told you to think?”
Quite a few raised their hands.
“Then I did English good.”
The rest of the time of class was spent with him teaching us various styles of analysis, though sadly my amnesia has claimed most of this part from me. I remember my belief in English being entirely shaken at this point. But at the same time, I also got what he was saying, and it opened my eyes to new things.
There is no right answer in literary analysis. There’s just answers people want to hear, or answers that are compelling, or answers that aren’t those things. The answer that Waiting for Godot was about abortion was not something all of us wanted to hear, but he made the answer sound compelling — and so we were riveted.
My next essay I wrote for that class was about the setting of the play, and how the entirety of Waiting for Godot centers on the anxieties of losing the modern family — and even modern life as we know it — to technology, and via that idea, the climate crisis.
I got a 100%. My teacher highlighted my (thankfully anonymous to the class) essay, particularly because the first sentence was “compelling,” due to my absence of proper grammar rules; I’d started it off by just saying, “trees.”
That was the day I really knew I loved English — not just enjoyed reading and writing, but genuine love of playing with the language. And it’s this love that I try to instill into my students.
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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The mandatory evacuation zone stretches from Ball Road to the north, Trask Avenue to the south, Valley View Street to the west and Dale Avenue to the east. That includes parts of Garden Grove, Cypress, Stanton, Anaheim, Buena Park and Westminster.
