Been on Tumblr since 2010 but haven't been active in years; they still don't let us transfer main blogs status so I made this whole new thing to escape the hellblog of my past.
I am also, like, SUPER sus about anyone randomly DMing me so I probably won't respond to random "hey"/"hi"/"hello" anymore. It's a much better time for both of us if you randomly open with like topical statements or questions that aren't seeking personal info 😅
My Interests
Skyrim / The Elder Scrolls
Star Wars
Writing & Worldbuilding
Fantasy Storytelling
Dungeons & Dragons
The Empyrean Saga
The Dragonriders of Pern
Live-Action Roleplay
Weapons & Combat Training
Space, Astronomy, Astrophysics, Cosmology
History, Archaeology
This blog will contain, along with fandom and writing stuff, political reposts and discussion, commentary on religion, war, and current events, and potential NSFW content. I don't intend to make them the core theme of the blog, but please be aware you may encounter these topics here.
My Creative Areas
(may update with tags later)
Worldbuilding
Original Writings
Fanfiction
Photography
Electronic/Synthesised Music
Crappy Art (affectionate)
I don't use AI in any of my creations, I'm just Autistic 😂
CW under the cut: Mental Health, Controversial Topic links
My Uniquenesses
AuDHD
Anxiety
Dissociative Tendencies
Physically Disabled
Heart Condition (undergoing diagnostics)
Recovered from Depression
Former DID
My Stances
Where a link does not exist, it means I haven't made a post yet - you can either wait or harass me in Asks, about these or literally any other topic, just make sure you mention you want my opinion because unless you specify that I might skirt the question.
Abortion || Artificial "Intelligence" || Democracy || Disability || Entertainment || Health & Fitness || LGBTQIA+ || News Media || Oxford Comma || Parents || Politics || Racism || Religion || Sexism || Social Media || Therapy || Transgender || Trauma || Vaccines
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my corner store guy is a 50 year old man who's my best friend in the world and recently he was like "you're too pretty to be single I have some nephews you should meet. very handsome!" and I was like "a niece might be more up my alley" and he just got more excited and said "ah even better! I was overselling my nephews but my nieces are very beautiful"
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They taught us in physics that an object in motion stays in motion unless something acts on it and i didn't care at the time but as a writer i think about this constantly. your character cannot just stop. something has to stop them. something external, something internal, something that costs them. a person doesn't change direction for no reason. a story doesn't either. newton was writing craft advice and nobody told him.
🔪 3 Plot Twists That Slap (and 1 that should be arrested) 🔪
hello and welcome back to me yelling on main about storytelling crimes. today we are talking about plot twists. specifically: the good, the god-tier, and the why-would-you-do-this-i-trusted-you tier.
let’s go.
✨ The Twist That Reframes Everything ✨
a.k.a. the “wait. WAIT.” twist.
This is when you drop a twist that doesn’t just add drama - it recontextualizes the entire story. It makes the reader go back and reread earlier scenes like “was this character ALWAYS sketchy or am I just stupid??” It retroactively changes the emotional weight of everything that’s happened. Suddenly that offhanded comment in chapter three hits like a brick. The romance subplot becomes 500% more tragic. The villain’s motive makes SENSE now. Delicious.
✅ Best used when: the breadcrumbs are subtle but real. The twist shouldn’t come out of nowhere - it should feel inevitable in hindsight. Like Sixth Sense, Knives Out, that one betrayal in your favorite anime you still haven’t recovered from.
2.🧨 The Emotional Betrayal
It’s giving: “i would’ve died for you” energy. This is the kind of twist that hurts. You thought they were loyal. You thought they cared. They did care - and still did it anyway. Or they never cared, and now you’re spiraling. This twist slaps because it’s not just about plot, it’s about trust. It stabs the characters AND the reader in the same motion. Bonus points if it’s a slow burn betrayal. Bonus bonus points if the betrayer feels genuinely torn up about it.
✅ Best used when: the reader is emotionally attached. Don’t waste this one on a side character we barely know. Save it for the love interest. The best friend. The mentor figure with dad energy. Make it personal. Make it RUIN lives.
3. 🧊 The “They Were Dead the Whole Time” but Make It Interesting
Listen. This one’s risky. It’s a classic for a reason but also easy to flop. But when done well? Haunting. Creepy. Unhinged in a gorgeous way. It doesn’t have to be death either - maybe the character’s been possessed. Or they’re not real. Or the narrator’s memory is lying. The KEY is to not lean too hard on the shock. Lean on the vibes. Give it eeriness. Make it a slow unraveling. Give us dread. Give us melancholy. Give us psychological decay with a side of unreliable narrator.
✅ Best used when: you’re writing something surreal, gothic, speculative, or emotionally weird. This twist isn’t about plot logic, it’s about atmosphere and emotional rot.
🚨 The Twist That Should Be Arrested: “It Was All a Dream” 🚨
I’m sorry but. no. if I read 80k words of someone’s descent into madness just to find out it was their stress dream and now they’re normal again?? I will throw the entire book into a lake. This twist erases tension instead of escalating it. It invalidates everything the reader emotionally invested in. It’s the narrative equivalent of gaslighting. don’t do it. UNLESS - and this is a big unless - you’re doing it with INTENT. Meta intent. Dream-within-a-dream psychological horror intent. If you’re gonna do it, it better haunt me. It better RUIN me. Otherwise? Into the lake.
okay that’s all. go forth and commit plot crimes responsibly. bonus points if you use all three Good Twists in the same story and then look me in the eye like “oh was that too much?”
it wasn’t.
tag me when you emotionally destroy someone with it.
🕯️ download the pack & write something cursed:
A gothic prompt pack for writers who love cursed universities, secret societies, and scholarly rot.✎ Write the Darkness ✎A 75-prompt horror
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.
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realizing many people don't know about infinity train creator owen dennis' among us show from years ago, which has been trapped in unreleased limbo all this time and was just dumped on streaming this morning with no advertisement. they don't even know about its weirdly stacked cast
The European Union already forced Apple to abandon its proprietary charging port and adopt USB-C across its entire iPhone lineup. It just did something bigger. A new EU mandate requires every smartphone sold in Europe including Apple devices to feature a battery that can be replaced by the user without specialist tools, without voiding a warranty, and without sending the device to a manufacturer approved service center. Batteries must maintain a minimum capacity threshold after a set number of charge cycles and replacement parts must remain available for up to ten years after a model goes on sale.
The consumer electronics industry built its current business model around batteries that degrade, cannot be replaced at home, and create a natural upgrade cycle every two to three years. The EU just legislated that model out of existence in the world's largest regulatory market.
Apple, Samsung, and every other manufacturer now faces a choice between redesigning their devices for the European market or accepting that their current hardware architecture is no longer legally sellable there.
Given that no company walks away from European consumers voluntarily the phones are going to change and once they change for Europe the rest of the world will ask why theirs still do not.
Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
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Friendly reminder that you are worthy, no matter what your parents or siblings or society says. We are one tiny little speck in the universe and the world is better with you in it 🫶🏻