From the Nashville Zoo’s fb page! Here’s the petition, please please please take a moment to add your name (even if you’re not from Nashville!). If you are from Tennessee, contact your representatives and make it clear that the people do not want this data center. This is an AZA accredited zoo which is home to several species of critically endangered animals, we NEED to protect it. Make your voice heard!
I mean the french very much aren't getting away with it. Everyone else is taking their language and running off with it cackling with glee. We're all getting away with fucking up french words on purpose
#English loves french so much it steals the same fucking word a few centuries apart so it gets two words that have the same meaning#But different spellings -#Like guarantee/warranty#(aside: There was a w/g shift so you can see if the word showed up with the normans or got nicked later#Which is why for e.g. the english call it wales and the french call it pays de galls)#Catch/chase#Gender/genre
I'm so glad someone reblogged these additions while I was away from my puter, I absolutely love doublets (or twinlings as they are apparently called as well!! That's so cute!!)!
Gonna make a sci-fi entity that is an AI supercomputer which consumes a planet's worth of resources in order to run, like it is the entire planet, all just for one singular being and its calculations, and it's also stupid as fuck.
Like people regularly pilgrimage out to try and get it to calculate something for them despite the fact that it's widely known that this machine is dumb as bricks. People just refuse to believe that something this big and impression and that takes so much energy to run can actually just be stupid. There are whole entire cults on other worlds that are dedicated to puzzling out the secret actually "smart" interpretations of it's conclusions, widespread disagreements about what the culture of its creators was (if they existed) and how they might impact things like the translation of data submitted or received, there have been historical teams who have worked night and day to understand the planet brain's language and workings and solve this riddle of how it's secretly smart, but prevailing wisdom remains that it just actually, factually gets everything wrong like 99% of the time.
Some people are convinced there's some fundamental flaw to how the planet brain works, and that if this flaw could be fixed then it would become an invaluable resource. So yet more resources and genius have been poured into figuring out what it could be and trying to secure the necessary grants and access privileges to attempt repairs. The few times anyone has actually gotten in to try and change the brain, though, the effect on its output has been negligible, and the brain has gradually reversed those changes and reset itself over time.
It's estimated that multiple billions of resources have been poured into figuring out the planet brain over the years. Experts have dedicated their lives to trying to understand it. Impassioned devotees have ruined themselves and their communities attempting to follow its advice. Even people who agree that it's stupid tend to agree that it should still be preserved and studied, even though trying to recreate some of its systems or apply the super advanced technology involved in its creation to other tech has yielded negative results (it makes everything else dumber too).
Basically it's the sci-fi equivalent of a money pit. Even aside from the energy the planet brain consumes as a planet itself (it's eventually going to spiral into the sun and be destroyed btw), intergalactic civilizations just keep pouring more and more into it because of the conviction that no one would waste THAT much on a stupid machine that did nothing. With the plot twist being that this is exactly what happened. The original aliens who invented it poured a ton of their energy into it out of the belief that a machine intelligence could figure out how to solve all their problems. Over time the investments in the project mounted, the sunk cost fallacy kicked in, and the planet brain even became their last hope of saving themselves from extinction because they had invested too much into it to allow it to fail. Now it exists as an accidental trap, ensnaring those civilizations that discover it and share similar enough cultural flaws as its creators, that they take up the cause of chucking more resources into it.
med people are so annoying "This family's 8 year old child who was about to go through a major surgery and kept crying that she was hungry so they pitied her and gave her food, she then had a heart attack in the surgery. They're so stupid 😒" girl they didn't know that could happen or why it happens. it takes so little time to explain to them that will happen instead of telling them "no food" with no explanation 10 times
"Before surgery, your body’s reflexes that protect your airway are relaxed by anesthesia. If there’s food or liquid in your stomach, it will near certainly come back up and go into your lungs, which can cause choking, a severe lung / heart infection or even a heart attack. That’s called aspiration, and it is life-threatening. It's hard, but it's only a single day to prevent near certain death. Not eating or drinking beforehand massively lowers the risk and helps prevent these life threatening situations under anesthesia." <- TIP: patients have brains which allows them to receive information just like you
I have four kids. I’ve had one or another of them need some kind of surgical procedure that requires anesthesia four or five times over the past 15 years.
This Tumblr post is the first time someone has explained to me *why* I couldn’t feed them before those instances.
I’m not stupid. I understood that just fine. Hell, my kids would have understood that just fine. But no one bothered to tell us.
i did know this before having kids (i have six). we have a kid that's needed multiple procedures requiring anesthesia. and every single time, i am asked multiple times if i'm sure he was not given any food or water after a certain point.
every single time i have had to say, "i understand that if he had food or water, he could aspirate it into his lungs under anesthesia. i am not lying to you." THEN someone would make a little note and i would stop being repeatedly asked.
not a single time was that risk explained to me. the only reason it came up was because i already knew. i still don't understand why it isn't standard pre-op counseling or pre-op check information, when me as a parent acknowledging the actual risk also put THE MEDICAL STAFF at ease because i conveyed that i had informed understanding as reason to not lie about giving my kid food.
"maybe some people will get nervous and refuse surgery" okay so they need more counseling about risks and anxiety, not less information in a way that actually does endanger their child or themselves!
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?
One hot and cool writing tip that I wish more people knew is... you don't have to write out people's accents phonetically. You just don't. You are not Dickens. You are (hopefully) not Rowling. There are so many other ways you can make someone's speech feel authentic to their background, or just make it clear that they're speaking in a certain accent, not limited to:
literally just saying 'he spoke with a Welsh accent'; sure, it's a bit blunt, but it gets the job done in a pinch. "He's completely drunk," he said, his southern drawl lingering on the final syllable as if to highlight the extent of the offence. Y'know, something of that ilk, but not as shit.
learning the specific vocabulary and syntax that someone with that accent might use. Sticking with the Welsh theme, because it's objectively the best accent*, there's a bunch of things that differentiate a colloquial South Walean accent, outside of our famed tendency to elongate a vowel to the point of death. The way we use prepositions (where to by is he?), the vocabulary borrowed from Welsh - saying that someone daft is twp, or something small is dwty - can easily signpost our speech as being from that specific area, without needing to type something like "'e's absolutely 'angin', man, pissed as a faaht 'e is!" Something less jarring, such as "He's absolutely hanging, he is." is just as clear. A character who says "Do you want a cuppa?" is coded or located very differently to one who says "You'll have a cup of tea, so you will."
ditto if there are specific ways that someone from a certain area might refer to a well-known concept. Regional words for mother and father, for example, or words that are class-specific; your character who calls his parents 'mater and pater' is likely inhabiting a different socioeconomic strata than your character who calls them 'mam and dad'. See if there's a colloquial way of saying 'yes' and 'no'; a lot can be signposted if your character says 'nah' rather than 'no', or 'aye' rather than 'yes'. A character saying 'couch' is inherently coded differently to one who says 'sofa'.
The reasons that writing accents phonetically is Generally Ill-Advised, In My Opinion are as follows:
quite simply, you're probably not being as clear in conveying the sounds of the accent as you think you are. Taking JK Rowling's work as the best possible example of this, her attempts at writing a Cockney accent phonetically come across like someone is chewing a mouthful of cheese curds and struggling to contain them. There's no consistency, no proper understanding of how to transcribe syllables into writing in a way that coherently conveys the accent she's trying to portray. I mean this so seriously, but what the flying fuck is: 'Well, 'e 'ad these 'ead pains and 'e was def'nitley nervous. Depressed maybe.' It's a crime, is what it is.
it's just plain hard to read. Trying to wade through sentences full of apostrophes and elision, parsing what's actually being said, gets tiresome. It asks the reader to do work that you're actively making harder for them. And that's not always a bad thing! Making readers Put Some Fucking Effort In can be very fruitful! But do you really want them to be struggling to understand every single thing that your Character B is saying for 350 pages?
which leads me onto the last point, and the most important in my mind: writing out accents like this always, always affects accents that are already in some way Othered. They're either racialised or working class, or associated with certain local regions that have negative stereotypes - think the deep South of the US, or the Welsh Valleys. They're never the 'default'. And this raises thorny questions about what the default is, what the standardised accent is, the accents that do and do not merit differentiation from the norm. You're relegating Character B to being hard to read because he's from, idk, Sunderland. You've decided that he isn't speaking 'properly', and therefore the reader needs to understand that other people think he's speaking weirdly. That, to me, is the principle issue. Because returning to JK Rowling (a sentence I hoped never to type), the only characters who speak like this in her work are working class, or they're from other countries. They're never from, you know, Surrey. Wonder why that is. And it's easy to be glib about it, but I do think it reifies class and regional boundaries in a way that's ultimately harmful.
This isn't to say that there's never a place for eye dialect in writing - Trainspotting (edit to respond to some legitimate comments in the reblogs: I bring up Trainspotting because it's written in Scots and Scottish English, not just Scots, but I agree that this isn't the best example as the Scots portions are not part of this conversation in the same way; consider Their Eyes Were Watching God by Zora Neale Hurston as a better example, and apologies for the confusion!) wouldn't be what it is without it, and there's definitely a different conversation to be had when it's your own accent and you're making a deliberate point about identity by differentiating through eye dialect - but I think that the blanket assumption of 'oh shit, my character is from Ireland, I'd better type that out phonetically!' can actually be both damaging to your writing and to your character representation, and I think that instead doing the work to really understand the vocabulary, speech patterns and unique aspects of a language or dialect always makes a work feel more authentic and lived-in.
To wit, less of this shite:
There’s mony a slip, an’ I’m no losin’ sight o’ any o’ my suspectit pairsons, juist yet awhile. (One of the Lord Peter Wimsey novels by the very English Dorothy L. Sayers, if you were wondering, and yes, that's supposed to be a Scottish accent; I'd not be bringing it up if it were a Scottish author writing in Scots)
and more of this:
"Are we straight so?"
"Aye, we're straight," said Jim.
"Straight as a rush, so we are." (Jamie O'Neill, Irish, from At Swim, Two Boys)
*objective determination made via a sample size of one: me, in an elaborate hat.
tumblr I swear to god if your ads on mobile keep opening popup webpages because my FINGER touched them while I was SCROLLING because they are SO BIG that they FILL THE SCREEN AS I SCROLL PAST THEM I am going to MANIFEST SNAKES IN YOUR WALLS
text: [ “Some of you have forgotten that only three years ago you were perfectly capable of writing an essay, writing a eulogy, telling a bedtime story to a child, and it should worry you that powerful companies have convinced us we can’t do things we’ve been doing for 5000 years.” ]
And they're absolutely specifically pushing it, make no mistake. It's not just a matter of "it's there, it's convenient, so people are going to take the path of the least resistance", it is a legitimate and concerted effort on the part of these companies to get people to outsource all these things to their models.
They're preying on insecurities to do it. Yes, you can write an essay - but can you write a good essay, they ask you. Do you not want to improve your output? Do you not want people to think of you as competent and very clever? Why go through the mortifying process of failing and failing and failing until you succeed if you can just skip the "learning" part of doing, and simply generate a ready-made product?
I'm preaching to the choir here obviously but it's a concerning thing to witness nonetheless. My kid is 6 next week and I've been teaching her that failing at things is morally neutral and in fact necessary even before the advent of AI, but it's becoming ever more important that we teach the kids that criticism and failure and discomfort aren't necessarily bad things, but just a part of the growth process.
AI companies are heavily invested in making themselves relevant. They want people to believe they can't do the things they have done unaided before and to make them become reliant on the AI models, so the AI models' existence is artificially justified.
it saves your life in a situation where no one else would have been fast, strong, agile, and composed enough to do so.
your security team is immediately more alarmed by its presence than the attack that is obvious to you as the bigger issue at the moment
they insist it's dangerous and struggle to relax enough to take their weapons off of it
then a combatbot attacks your group
somehow this secunit, much smaller than the bot, unarmored, without any heavy weaponry on its person, manages to take it down. some real jaw-dropping action, all over in less than a minute
then it leaps into a room with two combatbots and not only survives, but it gets your unconscious friend out alive
then it immediately comes to your own rescue, disabling impressive combat armor
it then is dead-set on killing your attacker who is already immobilized and harmless
clearly this is an incredibly competent and dangerous and powerful person
then miki tells you that it IS rin and you finally put it together that not only is this person competent in the field, but it is also calling all its own shots and has truly come here all on its own and volunteered its services to help and protect you without needing to be asked or ordered
so this person is incredibly competent, dangerous, powerful, AND kind, AND fiercely protective, AND reassuring, AND intelligent, AND selfless
and it's still coming up with great ideas and still thinking proactively about how it's going to face down or distract another combatbot as though there's no doubt in the world that it, still bleeding heavily, still unarmored and barely armed, is ready for another round with a terrifying machine that appears to be nothing BUT armor and weapons
so you step forward to help treat its injuries
and it jerks back a step with the single most frightened face you've ever seen, as though you had lifted your arm to inflict pain and it was helpless to stop you
behind you, even miki can read the devastating expression that's breaking your heart and says "abene won't hurt you, secunit"
where did the fearsome fighter from moments ago disappear to?
She played bass on 10,000 songs, including the most-played track of the twentieth century. She was paid $55 per session. Her name never appeared on the albums.
Gold Star Studios, Los Angeles, 1964. A woman in a cardigan walks past the receptionist, a Fender Precision bass in her hand like a briefcase. She doesn’t sign autographs. She signs a timesheet.
Her name is Carol Kaye. In three hours, she will record what will become the most-played track of the twentieth century. She’ll pocket fifty-five dollars and head to another studio, on the other side of town, for the next session.
The record label will never put her name on the album.
Between 1957 and 1973, Carol Kaye took part in roughly 10,000 recording sessions. Not as the featured artist, not as a guest, but as a hired hand. She was part of an anonymous collective nicknamed The Wrecking Crew—elite studio musicians who actually played the instruments on your favorite records while the famous bands posed for promotional photos.
The work was relentless. Three albums before the day was over. Stale coffee in paper cups. No rehearsal. The charts arrived minutes before the tape rolled. If you couldn’t read a chart and nail the take in two tries, you didn’t get called for the next session.
Carol could do it on the first try.
She started playing guitar in grimy bars at fourteen because her family couldn’t pay the electric bill. Music wasn’t a romantic dream for her. It was survival. It was a job—factory work with better acoustics and lower pay.
But she was faster and sharper than almost everyone else. She corrected charts in pencil while the producer was still explaining what he wanted. In one session in 1968, she told a famous producer his arrangement sounded like a dying dog. She chose her own line. They kept her version.
That descending bass line that drives the Beach Boys’ “Wouldn’t It Be Nice”? Carol Kaye. The propulsive groove of “These Boots Are Made for Walkin’”? Carol Kaye. The acoustic-guitar intro to “La Bamba”? Carol Kaye. The iconic theme from Mission: Impossible? Carol Kaye.
She invented techniques on the spot, out of sheer necessity. When the bass sound was too muddy for AM radio, she stuck felt under the strings and used a hard pick instead of her fingers. The tone cut through the static like a blade. It became the sonic signature that defined 1960s pop.
Bassists spent years—decades—trying to crack the secret of the Beach Boys’ gear to get that sound. They were studying the wrong people. They should have been studying Carol.
She received no royalties. No residuals. No gold-record ceremony. No credit on the album sleeves. When “You’ve Lost That Lovin’ Feelin’” hit number one, Carol was already back in a studio cutting a soap jingle.
The biggest bands mimed her bass lines on TV variety shows. New York marketing departments decided a mom in classic clothes didn’t fit the rebellious-youth image they were selling. So they simply left her name off the album credits.
For thirty years, almost no one cared. The truth only began to surface in the late 1990s, when music researchers found the same union contract numbers on thousands of hit records. The very documents meant to preserve studio musicians’ anonymity betrayed them.
Think about it. Every time you heard “Good Vibrations,” “River Deep – Mountain High,” the Righteous Brothers, Nancy Sinatra, or Sonny and Cher, you were hearing Carol Kaye. She composed the soundtrack of an entire generation’s youth.
And yet the records still say nothing. She’s now over eighty. She wrote instructional books. She trained countless bassists. She is finally starting to be recognized by music historians who uncovered the truth about The Wrecking Crew.
But she never got what she deserved: her name on those albums. Credit for the music that defined an era. Recognition that those bass lines everyone associates with the “Beach Boys” were, in fact, Carol Kaye’s.
Fifty-five dollars a session. Ten thousand sessions. The most-played track of the twentieth century.
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.
In case you just skimmed the post above and missed it, I want to reiterate and highlight Gebru's current position as Executive Director of Distributed AI Research Institute. If you're curious about what AI technology might look like when not applied in the horrifically unethical and damaging way it's currently applied, please check them out.
If we want to have nice things, decentralization is essential, and if we want to decentralize, we need to have our eyes on things that are beyond the scope of the current Big Tech narrative.
The Distributed AI Research Institute is a globally distributed organization of academics, activists, and engineers conducting community-roo
