Bi Black Over 20 Cis GNC (She/her, He/him very close friends only) Minors DNI. I have ADHD so i am very prone to reading things and comprehending things wrong. (UNTAGGED SPOILERS) “Who else could it be. None other than the fandoms most obnoxious and biggest dumbass fucking Stephanos Space Opera.” Media Critic blog, usually for animation, sometimes Launchpad is here.
fellas imma need some help, not for me, but for my younger sister. she needs to pay back her loans of a total $20k and she needs $700 for her electricity bills. If $20k isn't possible then she says $700 is fine while she figures out the loan issue. The $700 seemed more urgent. She's epileptic and the stress is causing more and more seizures to occur.
so, i noticed that in “sinners,” remmick is portrayed as playing a banjo when he performs. that piqued my interest because i know somebody, hannah mayree, who runs something called the “Black banjo reclamation project” which aims to educate people about the banjo’s african origins and history in Black music, accepts donations of banjos to be distributed for free to Black folks who are interested in playing, and offers shows and events oriented toward helping Black people reconnect to their roots through this instrument.
there’s a campout that starts tomorrow, june 4th, and an online study group that starts this weekend, june 6th, and some events and shows this summer that look really fun. there’s also a newsletter for any future events!
looks like i can’t put the link to the website, but it’s just the name of the project dot org
I have always loved a good banjo. It's crazy bc it's from Africa, but it always gets a bad rap as a Southern White Hick stereotype. Which, interestingly enough, is probably why they gave it to Remmick. A sort of sign that even in this, he's trying to use Our Music to get Inside to Us. But anyway, somebody shredding on a banjo is 🤌🏾🔥
I'd actually love to participate in something like that, because I gave up on this guitar 😭 I don't have the memory and focus anymore to teach myself music.
This seems like a great place to plug the full-length documentary about the all-Black old-time string band Carolina Chocolate Drops:
They formed at a Black Banjo Gathering in North Carolina in 2005 and have been a big influence in the revival of Black traditional/string band/old-time/folk music in general but also from the Piedmont region of the Carolinas.
I especially like this documentary because they talk about how you take a style of music that's been whitewashed/repressed and bring it back for a modern audience, while repairing its ties to and honoring the Black ancestors who played it first. The origins of the banjo are a huge part of that and a huge part of the documentary.
lol, so I got kicked off the wifi and I need 40 dollars to pay my phone bill in the next few days; I wont. e able to post or do art or contact anyone at all unless I get this sorted asap.
I have commissions open if youd like to help otherwise please boost.
making this a general dono post bc I need help w a lot of things lol, in a v toxic living situation rn that is wearing on my patner and i's mental health a lot and growing progressively more hostile.
Please donate or commission me so I can get my life sorted so I can move out please.
Compilation of Racial Demographic Polls on this app
The current ongoing one:
Some ones from the past:
I'll keep digging on my end to see what else. But again... 65-75%, nearly every time. I want to see if we can record the pattern so we can stop doing this and pretending to be surprised.
I looked up the percentages from the #CBC poll event, specifically the character design ones. This page has a bias due to me having an actual relationship in the space with my Black peers and peers of color... And it STILL was showing 50-60% white on most every single poll.
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.
Shit that I'm sure will turn me into a villain if this keeps on happening:
Looking up the cast of a predominantly Black movie, and for whatever reason the white actors (no matter how small their roles are), are displayed first
The actual protagonist, who is a darkskinned Black girl, is way at the bottom once you press "Show more" btw
They'll have that Circus Digital finale playing in all these theaters, but I have to practically hunt down for the one showing of Is God Is in a late night time slot
all that money goin to a racist white woman, defending a racist white woman and her racist friends when u could be uplifting black trans women just saying. donating to them. reading their stories. watching their animations.
hey this post is almost a year old and all of these ladies still haven't reached their goals yet. please keep this going instead of news story number 900 about the british terf in chief.
I suffer from severe OCD, depression, flashes of fatigue that throw me in short blackouts, and live in an abusive household where my freedom is severely restricted. I therefore find myself dependent on communal aid to get going. Right now, I urgently need to take care of a couple of lingering debts, buy new clothes, and buy groceries. I set myself a goal of 650$, but as time passes, my needs keep growing with very little income coming in, so I now set my goal at 900$.
I am currently dragging a collective debt of about 300$ (this covers phone bills, impromptu repairs, and recurring payments). I truly live within the urgency of financial instability and consistent abuse (my mother installed a camera in the kitchen) which means I'm grateful for all communal support.
