my names buzz, bug/buggy and variants are also good (other nicknames also welcome if we're mutuals)
24
autistic, adhd + mentally ill, able-bodied with chronic pain
they/them
tme, nonbinary (agender - do NOT call me transmasc), no current sexuality label bc i don't really care at this point
on T since july '21
white
single
don't call me slurs (yes, including the q slur, no it is not an umbrella term and if you send me an ask about it i will just block you)
consistent interests:
amphibians (esp caecilians <3 if u couldn't tell <3), sculpting (portfolio blog @caeciliarts if u want to look), miniatures, clowns, semi-aquatic mammals (platypi and sea otters mainly), cats, fishing games, and minerals/rocks
past/present/cyclical interests (that i am still at least a little passionate about):
disco elysium, dimension 20/dropout, some streamers (namely rtvs, northernlion, occasionally jerma), riichi mahjong, katamari, metal gear solid, pikmin, the binding of isaac, fnaf, yo-kai watch, elder scrolls, rhythm games (namely taiko no tatsujin, parappa the rapper, and rhythm heaven), SCP, star trek tos (and tos movies)
dni if:
terf, transmisogynist, transphobe, truscum/transmed, "transmisandry" truther, "map"/pedophile, shipper/apologist of incest or abuse, fan of some bullshit (hp, homestuck, south park, vivziepop, whatever the fuck. you know who you are 🤨), or liberal/"vote blue no matter who" spouter.
resources:
at this time i'm going to focus on reblogging posts compiling fundraisers and news updates rather than trying to reblog every individual fundraiser, as my energy has been very low lately and i have very few followers who consistently reblog. here are a few links to resources for palestine, sudan, and congo:
Vetted fundraiser lists: The Butterfly Effect, list by el-shab-hussein & nabulsi, list for Palestine, Sudan, Congo, and other areas in crisis
eSIMs for Palestine: Gaza eSIMs, Crips for eSIMs
General fundraisers for Palestine: Gaza Funds, Help Gaza Children
General fundraisers for Sudan: Khartoum Aid Kitchen, post with several other organizations to donate to
General fundraisers for Congo: Focus Congo, The Panzi Foundation
Once when I was in undergrad, someone described something as “problematic” in class and our professor was like, “That’s cool, but ‘problematic’ doesn’t really mean anything. It means that the thing you’re describing has a problem, and in and of itself that’s not bad. Art, especially, should always have problems, or else it’s not interesting and not art, either. It sounds like you’re trying to say that this is bad, but you don’t want to say ‘bad.’ Is that right?”
So from then on whenever one of us called something problematic, he would make us talk it out until we could name the “bad” thing we were hinting at. In this particular class, 7/10 it was some type of oppression, and the remainder was like, “I’m uncomfortable because this is very new/confusing/pushing boundaries that made me feel safe.”
Once we stopped calling things “problematic” and stopping at that, class got way more interesting and... we all had to say, like, “that’s racist” or “that’s misogynistic” or “ew capitalism gross” out loud, which a lot of us had never done in a classroom before. Or we had to be like, “Uhhh... I’m not sure what’s so bad?” and confront our own beliefs and that was maybe even more useful.
Anyway. Whenever I see the word problematic, I can’t help but think of this professor being like, “Good starting point, now let’s get specific.” I think when we have to commit to saying “that’s ___” it requires a lot more careful thought about the truth and impact and complexities of whatever we’re claiming. Sometimes there really is some bullshit afoot, and also sometimes it’s art, and it should be full of problems, because that’s what art is.
It really is one of the best examples of them compounding. Cause when I was in a really bad spot housing wise, a few times I applied to those anyway and made a point about being like "oh I'm afab" and it felt so fucking gross. But I didn't wanna be homeless. So I made myself uncomfortable (and for nothing as it turned out, I would not do the same thing again if I went back in time)
But even then, and even more now, I was so conscious of the fact that, as uncomfortable and gross as it felt.... It was an option. And if I was a trans woman, no matter how desperate I was, it would not BE an option. It's a way of understanding privilege more people need to take on IMO, cause it's not about whether or not I think of it as a privilege. Course I dont. That's not the point.
You gotta be able to take an L if your moral and ethical belief systems are to be capable of guiding you. Otherwise you just have an idealized self where you get really mad and scared when anyone points out it isn't actually you. How the fuck are you gonna walk the walk if you can't handle being told when you are not, in fact, actually walking it
you cannot just socially transition into being a good person you are going to have to settle for being a messy human being who has to try and fail and keep trying to get better like everyone else. yeah even when it's embarassing and sucks for you a lot.
learning to notice an absence of people of color is crazy. you start seeing it everywhere. ill see a random pic of characters or people or whatever and be like "these are all white people. why"
all the babies in those baby youtube video memes. humanized character posts. like. its the little innocent shit. and like, the people making those baby memes probably arent seeking out white babies. maybe theyre just easier to find. but why are they easier to find? a complicated question, surely... but you know what it probably comes down to. someone, somewhere, maybe a lot of someones in a lot of places, made a choice. maybe knowingly, maybe not. but they made a choice. it starts to make you feel like a conspiracy theorist!!
its really funny that after 2 months this post is still making racists come into my askbox treating me like im a horrible person for pointing out that sometimes people of color are excluded from things in visible and offputting ways. cry about it
i've been obsessed with this video so i downloaded the video file off of youtube so even if the internet goes down i can always watch frogtimelapse.mp4
【Mayonnaise and the Checkered Sofa】
This is Mayonnaise, a dog sitting on a checkered sofa.
Every morning she eats yogurt with banana here.
After washing the dishes, she comes back to the sofa again.
Her favorite food is dumplings.
マヨネーズとチェックのソファ】
チェックのソファに腰掛ける犬のマヨネーズです。
毎朝ヨーグルトにバナナを入れたものをこのソファで食べます。
その後皿洗いをして、またこのソファに戻ります。
好きな食べ物は餃子です。
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.
tumblr you have to fix the ads autoplaying sound at 100 volume. i have reported like 20 ads by now and im still getting jumpscared when i scroll more than 2 inches. literally unusable
If someone is doing things that don't make Sense, try to understand that it is entirely possible that their brain is probably under an enormous weight and fracturing under the pressure. People who have been stabbed will sometimes talk a circle around the fact that they've been stabbed because stress and shock prevent you from recognizing the distress you are in and what you need to do to seek help for it. PTSD will do this also. You will find yourself repeatedly jamming a bag of frozen fruit into the same spot in the freezer where it doesn't fit and keeps falling, over and over and over, focused on nothing but that bag. You will decide that a beanbag chair is 10000% necessary to your life. You will lose your entire shit because you stubbed your toe on a table and that means the whole setup of your furniture is wrong. These are largely harmless examples. People under strain will also hurt themselves and others. Cornered animals bite. And it doesn't heal the bite to go "Hey, are you okay?" But it might get you to an animal that stops biting, so you can start to heal. And before you had an animal that bit, you probably had an animal that kept doing shit you didn't understand as stress signals
