Hey, That's Pretty Neat

Skylar  ||  he/they  ||  late 20s  ||  🏳️‍🌈♠️  ||  meowwied to @hajinjin13  ||  blog is nsfw  ||  Message me if you want something tagged (or if you want to talk!)

[okay-sky]

hello and welcome to my main blog! my name is sky, pronouns are he/they, and im american. currently into hp/drarry but also fuck jkr

you can find all of my artwork under #okaysky art

↓  tag directory & shippy sideblog links below the read more  ↓

TAG DIRECTORY

#fma for fullmetal alchemist

#hp for harry potter

#witcher for the witcher (primarily the witcher 3)

#detroit for detroit become human

there’s probably a ton more sowwy these are just the fandoms i post the most in!

#p3,  #p4,  and #p5 for personas 3 thru 5

#vocaloid

SHIPPY SIDEBLOGS

@skys-royed-sideblog for all my Roy/Ed shit. also features just general fma stuff sometimes but most of my gen fma posts are on @okay-sky under #fma

@okaysky-drarry-sideblog for all my Harry/Draco and hp stuff. there is a small amount of hp content on @okay-sky under #hp but lets be real its 2022 im keeping this stuff quarantined

@skys-hankcon-sideblog for Hank/Connor, all gen DBH content is on @okay-sky under #detroit

[momento-more]

@elodieunderglass - This made me think of you.

[elodieunderglass]

Thank you so much for this

[jaubaius]

[nabi3000]

[narcissistcookbook]

the second eel at the end in its little cuck shelter 💜

[derinthescarletpescatarian]

eel deets from @whitefangthefightingwolf

[reikomakoto]

[dragon-in-a-fez]

when an eel lets you skritch

his most vulnerable bits

that’s amore

[crowlines]

NEW: Dawn Sparkle! 100% cotton, XS-4XL Part of the Sparkle With Pride collection releasing Tuesday June 9~ ✨ shop ✨

[hydrattan]

I was feeling agitated and artblocked yesterday so I decided to give my brain a rest by watching TV and then the next thing I knew these were in front of me

[phineas-and-ferb-heritage-posts]

phineas and ferb heritage post

[kafkasapartment]

artistsuniversum: “Kathin Marchenko is a textile artist and designer known for her expressive embroidery on delicate tulle fabric.

Using a "painting with thread" technique, she creates portraits, anatomical forms, and ethereal figures that seem to float within wooden hoops, blending craft with fine art.”

Artist: @kathrin_marchenko

#art #embroidery #artist #textileart

[systlin]

Every time I see bullshit about women never EVER being able to beat men in any sport, I think about how in martial arts classes I, a cis woman, 5' 8" and 145 pounds, regularly beat the tar out of 6' 2" 230 pound cis dude weightlifters. One guy ragequit class. He came in cocky as hell and talking the standard bs line about how a woman simply never could beat a man in a fight because they're physically weaker and our instructor was like. Okay. Put the pads on you're sparring her. Yes, her, the one 4" shorter and 100 pounds lighter than you.

It wasn't close I beat the pants off that man, and others like him. I did it more than once. Some guys got humble and stayed. One guy got angry and stormed out.

And I think about that every fuck damn time I hear that bullshit, which seems to be all the fuck over the place these days. Oh, women are just fragile little soft delicate flower creatures who can't do ANYTHING and could NEVER compete with big strong manly muscular strong MEN.

I think about driving that dude into the mats and seeing the brutal reality of this big dude's misogany meet the realization that a woman was beating his ass literally that second, that none of his strength could stop the fact that I'd just hip thrown him facefirst into the mats and that had I actually connected with the axe kick to his neck I would have crushed a bunch of important shit and he could not stop me, and his whole psyche collapsing like a dying star in that moment.

Anyway, don't ever fall for it, ladies, and there's absolutely no goddamn reason to get your knickers in a twist about trans people in sports.

[i-suggest-larp]

Fight people of every gender!! Kick their asses!! Get your ass kicked!! You will find gender is not correlated to ass-kicking!!

[lilu-the-horse]

when horses do the big doggie stretch and go allll the way down…

Yeag

[chestnut-horse]

can I add to this?

[lilu-the-horse]

absolutely you can

[horsefigureoftheday]

If I may add

And let's not forget about

[voidthing]

happy month, fellow slurs.

[yardsards]

but i stay silly! *←said in the most world-weary voice you ever did hear*

[fizzlepop-frog]

“but I stay silly!”

[sensiblereblogifposts]

Reblog you stay silly

[depsidase]

[jerreeeeeee]

not every mutual fits neatly into an archetypal medievalism but there are some mutuals that im like yeah addressing you as “my liege” would come strangely naturally

[jerreeeeeee]

what mutual is prev

my liege lord

my loyal knight

my wise wizard

my evil advisor

my brother in arms

my lady muse

my wild mermaid friend

my fellow alchemist

my dashing rapscallion

my monstrous foe

Remaining time: 17 hours 32 minutes

[3000s]

[thriron]

[binturong-of-the-day]

The binturong of melancholy

[pavizi]

in honor of tdov here's a short comic about my transition

[caviar-and-cigarettes]

@this-is-trans-joy !!!!

[this-is-trans-joy]

This is trans joy!!!

[justalurkr]

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.

[irispurpurea]

This is the paper. It's excellent, highly recommend reading it.

I remember reading about Gebru's firing but I had no idea this was the paper she was fired over.

[brucebocchi]

sorry to post facebook videos on main but the sound of jello going through an industrial shredder is both mesmerizing and horrible