Hello! I've finally gotten around to making one of these. Yay i guess, this can be taken off of the "I'll get around to it" list.
Call me Lepidop or Leppy (He/She/They), and this blog exists. Formerly Moth. I don't really post often, but when I do it's usually art or analysis of whatever I'm obsessed of at the moment. Reblogs are slow as well but not as slow as original posts though, so that's something if you follow me for whatever reason.
Edit: the tags with apostrophes seem to be misbehaving?? I'll fix this another time, making this edit just to note that they don't seem to display everything
My tags:
For my art: #my art
For analysis and discussion posts (i have not made these in a while.. also have not gotten around to retroactively tagging these): #leppy’s thoughts
For my OC related stuff: #leppy’s ocs
For non OCs but original designs (eg. fanart for nonvisual media or alternate outfits): #leppy’s design attempts
For my personal posts: i just realized i probably don’t want a public list of that
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.
Yippee!! New Gym Leader OC! Meet Tyfo, the Water-type Gym Leader of the Kapula region.
Tyfo was a workaholic who was sent to a resort (which happened to host a league gym as well) to chill out due to overworking herself. it did not work, she got herself hired, worked her way up the ranks, and became a director of the resort and the gym leader. She’s at least she’s been taking better care of her health in her current occupation.
Her partner Pokemon are Fakemon which I haven’t figured out the designs for yet, so instead she’s accompanied by a Greninja. Her team in general is composed of Pokemon that are supposedly chill and zen which are supposed to help her chill, but she still interprets this as discipline herself for her to work even more.
Concept art can be seen here. First picture is of Typho herself, second is of her gym and gym trainers, and third was a much earlier concept of her that has been retconned to be her younger self. She’s meant to evoke Psyduck and Goldduck much more in that one, to symbolize that she’s serious at her core but a bit neurotic.
I have yet to finish twining threads (busy) but the one Fauvist gallery they give us does a really good job at not only portraying what I think is the most common flaw in the works of Fauvist students but how Émile Benoît subverts this by, to be succinct, Giving A Shit
(long and a bit image-heavy below)
It's been established time and time again that, culturally, Fauvists—if they want to be successful in portraying "fauve"—need to lean into the aesthetics of one singular animal. The animal that they connect most closely with on a personal level—though, I presume this is because of the passion that forms from that connection rather than anything thematic that goes into the works, considering how Fauvism is more a celebration of the animal than a representation of the piece's creator.
However, the passives of the Students paint, to me, a strikingly different picture. Their tendency toward concepts more divorced from the animals they choose as ingredients leaves their works feeling only superficially beastly.
A focus on the self in relation to an animal is closed-off: what best represents you while making a piece you are, by the standards of Fauvism, not connected to. Chasing "ferity" is closer, but to dilute the presence of any individual creature misses what makes them significant enough to survive.
Both of these ideals lead to a passive consumption of animal aesthetics. They are fauve because of their star power: massive claws, elongated teeth, imposing stature. Only the most surface-level beastliness—that which makes them different from us—is portrayed in their works.
This consumption is seen in the pieces themselves, such as the bear's leg with arbitrary feathers or the quadrupedal creature on the far left, constructed with enough parts to obscure most of its original form. Even if these pieces display technical skill—the capability to stitch together at least five different creatures in a manner that stays together is impressive—what do they say about the animals themselves and, how they interact with the world around them that makes the uniquely fauve?
Rodion is able to, partially, subvert this. She displays a more thorough understanding of her chosen animal's behavior, allowing her to use more diverse imagery in her portrayal of the wolf:
Looking at some of her other lines, though, she's still following conventions. She understands subversion enough to land her the role of Docent, but doesn't value the creation of art enough to go truly in-depth.
This is where Émile differs from every other Fauvist shown: she purposefully, frequently explores the intricacies of different creatures enough to seemingly dedicate every (or near every) piece to something different. Both how the Docent in Rodion's uptie story speaks about her and her design indicate that her interests span widely—her boa, from the hides that can be identified, uses at least mammalian and avian ingredients—yet, despite this, she is a Maestro.
With the above context, it becomes clear what has allowed her to create works influential enough to give her this position: a genuine care for the animals she uses. Judging by her serpent example, she has not only identified the underlying flaw in the Students' works but put effort into subverting it. Even in one example there has been a more acute demonstration of anatomical understanding than what is seen in any other explanation of Fauvist works (that I know of, I could be wrong here. Maybe Rufo says something profound).
This all makes the choice to give Meursault a Fauvist identity very interesting. He is very obviously an identity of the Impulsive Fauvist Student—they're near indistinguishable when he's masked—yet "impulsive" is far from how Meursault could be described.
His voice lines and uptie story largely support this. He follows an instruction manual, perfecting technique in an art form where the replication of something technically competent without deeper meaning is quick to become stale—see Corporism—and going as far as saying his subjective interpretations do not matter.
Though, the end of his uptie story implies something much more bleak: he does possess this "impulsivity" of sorts, but actively suppresses it in favor of something that is more surface-level palatable.
My character analysis is certainly limited by having yet to read The Stranger, though. This is all rather easy stuff to point out, how he's entirely opposite to the philosophy Émile has. I will read it soon!
in conclusion... I LOVE THE RING!!! pleeaase tell us about Cubits KJH! I'll pick apart their students too! Show us artworks from every school!
