Personal blog of @bootsssss. Musical theatre, linguistics, medieval art, Jewish things, squeaky animals, mental health stuff. Artist. Fandom old. Queer. ey/em or he/him.
I honestly think being intersex is WAY more common than a lot of people realize.
Like, not just 1.7%-2% kind of common. I mean like 10-20% kind of common. That's how common I actually think intersexuality is, especially when I hear all these stories about people who just realized they had vulvar hypospadias, since they thought it was perisex-typical. Or all these people who just realized that PCOS and NCAH are intersex, since they thought those were perisex-typical. Or all these people who are starting to accept that their micropenises are intersex traits instead of feeling ashamed about them. And on and on.
You ever see something innocuous, minding its own business on the clearance shelf at Michael’s and before you know it, it takes over your life for a few weeks?
So it was with this desktop greenhouse.
I took it home and after taking an appropriate time to “season” my idea in my mind (read: a month or two) I set to make my vision of a mini botanical garden a reality.
I started by removing the heavy glass panels and building a raised floor above the latch. I wanted to use the base as a foundation on the building.
I wrapped the foundation in plastic stone textured flooring (meant for Christmas villages) and built a pond at one end of the same. I then gave it a more realistic paint job and designed a rough layout for my plants and displays.
I also knew I wanted to make the ironwork significantly more intricate, but I wasn’t sure how just yet…
Up next - PLANTS! I went wild making all kinds of plants. Some were specific species and some were more conceptual.
I made several trees with polymer clay and moss, cacti out of beads and flocking, cattails out of raffia, hot glue and coffee grounds, and giant monstera leaves out of paper and wire.
This part should have taken me a long time, but it really came together fast. I loved finding ways to replicate natural shapes and patterns using bits of this and that.
I did make adjustments to my plans as I went like eliminating benches in favor of a simpler overall design.
Then I needed to fill my pond with water. For this I used resin. Lily pads were added to the top layer, and I wired in simple LED fairy lights. The batteries are kept in the box under the foundation.
In a weekend frenzy I added more plants, metal (paper) steps, new (plexi)glass windows, a roof, wrought-iron vines (paper again), doors that open, and a hose reel disguising the latch. Suddenly, a project I thought would take months was finished…
I love my desktop botanical garden. Right now it sits on a simple lazy Susan in my office. But I’d love to get it a proper display box to protect from dust.
Thank you for coming on this little journey with me. This piece packs a lot of joy into a tiny space. I always love building miniatures, and I’ll be doing more in the future I’m sure.
given the current climate this pride especially i feel i must mention that i love my trans friends, i stand with trans people in the fight against transphobic legislation and those who would enforce it, and this blog is not a good place for you to be if you do not vibe with that
One of my biggest projects - an entire Hydrapple, with all the syrpents included! There's toothpicks in the main head's horns for rigidity, while every syrpent has armature wire inside them for poseability. And...
...that includes the two tail syrpents! All six syrpents other than the main one are completely removable along with the apple top, which has little hooks to hold it in place when it's on there. The apple base also has a plastic pot inside it, to help it hold all that weight.
The one thing they can't do is fold the bonus heads flat against the apple like the ingame model does, but they can get... some of the way there? although it does require something of a Noodle Vortex on the inside for all those tails to still fit in the apple.
Very proud of these good apple noodle friends and how well they turned out!
~~~
my commissions are open - see my pinned post for more info.
(I don't offer things this big and elaborate (yet...?), but I can make you something simpler!)
like people are just going to keep saying “theyre only queer because they want to be/because it gets them off/because they think it’s fun/because they saw a queer person and thought it sounded like a good idea/etc. theyre gonna keep saying it
and we are going to have to stop desperately scrambling to say noooo, they have to be like that, they have no choice, they wouldn’t be like this if they didnt have to. we HAVE to stop falling all over ourselves assuring straight people and transphobes that we hate being us as much as they hate us being us, that we are suffering and that’s why we deserve this decadence and deviancy. we HAVE to start saying “yeah ok and?”
being queer is a delight. deviant sex makes people really happy. being genderfucky is joyful. queerness CAN actually be an option you can choose, and that doesn’t make it worth less than if you only picked it with a gun to your head, because it is a good option and there are good reasons to pick it.
frankly i hope straight people are straight because they think it’s fun and it makes them happy! the implication that one should not pursue happiness is so frustrating!
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.
Register now for Being Aro: A Conversation on crowdcast, scheduled to go live on May 27, 2026, 03:00 PM EDT.
And here's tomorrow's book tour event for Being Aro--I'll be included in the conversation on this one. You can register for free and pop in from anywhere to check out our chat about aromantic stories and their importance!
