there’s a used bookstore in rural western massachusetts (the montague book mill) whose motto is “books you don’t need in a place you can’t find” and i just feel like that summarizes tumblr too
You'll have a single mother of three who's fleeing a DV relationship. She has no recent work history because her ex kept her barefoot and pregnant. She's struggling with depression+PTSD while trying to find work in a horrific job market.
Now I have to be the one to tell her "Dept of Social Services insists every child over the age of 5 have their own bedroom, so you'll have to get a 4 bedroom, which will likely cost $5000/mo. You will get a housing voucher that covers 50% of the cost, so $2500/mo. You will need to make $90k/yr to comfortably afford this"
You and her both know a full-time minimum wage job comes out to $32k/yr in your area and most of that is going to go towards child care so she can work a job that will never pay enough to cover her living expenses. Even if she worked two full-time jobs, she'd still be ~$30k/yr short of the required income.
She can do everything right, she can work her ass off, she can get benefits, and it still won't make a difference. Her abusive ex is going to get the kids in the divorce simply because he has a steady income and home.
You see, in that moment, the woman start to consider going back to a guy who'll probably kill her and/or the kids someday and there's really fuck all you can do. Like " uhh I can help you apply for SNAP, you'll probably get $200/mo. Sorry for all the systemic issues"
As a Child of the 'Burbs, Driving = Emancipation. My first car was the first place that was completely my own. 1964 Pontiac LeMans, $500.00 for my high school graduation.
The sooner you start, the sooner you'll be done with it and the sooner you can stop thinking about it. Go on, up you get, it won't be as bad as you think.
You won't want to do it later either. You might as well just do it now. Even if you don't finish it all, anything you manage to get done now is something you don't have to do later (when you still won't want to do it)
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.
Today we present some fancy Caslon capitals, borders, and ornaments from The Manual of Linotype Typography, printed by the Plimpton Press for the Mergenthaler Linotype Company in Brooklyn, New York, in 1923. William Caslon (1692-1766) famously introduced the first superior British Roman font in his 1734 specimen sheet. Various iterations of the Caslon typefounding house persisted until the 1930s when it was acquired by Stephenson Blake, but the Caslon Roman typeface remains the classic British font.
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.
Genuine question: how do you make so much stuff (collective term for art, stories, blog posts, and other misc. creative things) and not get burned out? I love making stuff and love the idea of making stuff for work, but when I’m busy, I can make maybe a couple of stuffs a week, sometimes a month before getting burned out. I love being creative but this part is really hard for me because it feels like I’m failing at the one thing I really love. How do you do it and still have so much joy left?
I build and maintain my life around making things.
It is really that straight forward, if unsatisfyingly lacking in drama or strategy.
I work out physically to build and maintain muscle and flexibility, I read intellectually stimulating things similarly so.
I also occsaionally say "ah hell it's time for salt water taffy and root beer while watching ultra cheesy movies" because is as important to embrace the high-brow as the low-brow.
My personal relationships are similarly treated. Am I making your life better, are you making mine? Yes? Great we continue, let's be weird together. No? I wish you well and I remove myself.
I work until I can't then I don't until I can again.
When I am feeling toasted on the burnout scale, I look to become an audience member. Not in hopes of recreating the work, but in the raw enjoyment that it exsits. It is as important to experience and enjoy things as it is to make them. Two sides, one coin.
My life is a series of side quests. There is no main goal, no main purpose.
I make small things, without apology or remorse that they will never be large or complex, they'll never make me famous, they will never win awards or get written up in prestigious publications.
I want to revisit something because in re-reading I missed something really, really, really important.
I was writing the intial reply at 3 AM before coffee and now that I've had coffee and a giant bowl of stir fry it is time to
Properly answer your question this time
YOUR COMMENT: "...this part is really hard for me because it feels like I’m failing at the one thing I really love."
Look at me.
Look into my beautiful eyes.
YOU.
CANNOT.
FAIL.
AT.
CREATIVITY.
THAT.
IS.
NOT.
A.
THING.
You can fail at capitalism.
That's not necessarily a bad thing
considering what winning at capitalism looks like.
tw: jeff bezos
The history of life --
and I'm going to assume you're alive -- if you are a sentient AI then fuck off, if you're a human or other, stay --
-- revolves around SURVIVING and THRIVING.
Guilt you feel, negativity you feel, anything other than desire to make more you feel is a systematic vice gripping around you by some mother fucker with more resources than you have attempting to squeeze juice from your bones so they can have even more resources.
Every
time
you make
something
you win.
Devil bless my beautiful boobs bones heart and soul.
You cannot fucking fail at creativity.
Your role in this world, in this life, is not "make creativity machine go brrrrr."
Your role is to live the most fulfilled life possible.
As your non-doctor non-professor art doctor professor, I diagnose you with
HAVING SEEN GENERATIONAL WEALTH IN ACTION-ITIUS
I do not have generational wealth.
I am in my middle age. It's beautiful and I love it here.
I started working in my early teens and have only recently started relaxing to the point where my office is (figuratively) a swim-up pool bar where I drink pineapple juice and tell embarrasingly cheesy jokes as I make mocktails for everyone.
It has taken me decades to achieve things that people with generational wealth achieve nearly immediately.
People with generational wealth -- and assholes -- love to say shit like "as an artist you should sacrifice--"
how about... no...?
People whom make work explicitly to sell at galleries -- and assholes -- love to say shit like "You can't do [whatever metric I personally deem not worthy] and be an artist."
how about... no...?
There are no guards.
I checked.
there is one
just one
singular metric
DO YOU MAKE ART?
if so: you are an artist
if not: you can become an artist if you want to, go on, go make art
IF YOU ARE AN ARTIST, DO YOU WANT TO MAKE MORE ART? BETTER ART? MORE BETTER ART BETTER MORE?
congrates babe we all do
that's like
the whole thing
we are all trying to figure out how to make more, better (however we specifically define it) art
I have had friends whom have painted things so fucking incredible I kissed them on the goddamn mouth to celebrate this artistic accomplishment.
I have had friends who then stopped painting at all and got desk jobs because they didn't want to make art anymore and I have kissed them on the goddamn mouth to celebrate our friendship.
I guess my point is I'll kiss you on the goddamn mouth if you're into it
i guess my point is that art is a core component to some lives, but it's not everything.
If it was everything, we could outsource it to robots to generate automatically to our tastes, instead of going through the glorious ordeal of figuring out how to make it, how to experiment, how to learn
the entire point of all of this is you are a tiny fragment of the universe figuring out what it means to be energy and matter comprised in your current form
dededos
turnnoffyourmind
origamiaround
snowghoul
discoholicmusic
jbbartram-illu
yousharknotpass
areudirty
