There's a guestbook and buttons to click and a webring with a bunch of other funky websites and some pictures of Minu and dice and @flibbertiggibit's tarot decks it's really fun there's a whole world wide web out there why not explore it I promise it's fun.
I'm just saying, if you're going to worldbuild magic being a "raw, primal force, akin to and interweaving with nature itself" you gotta explain to me why animals don't use it
I know the normal answer is "they just aren't smart enough for it" but idk I've seen enough media where a character uses a spell in a moment of brain-off panic ilI feel like animals could probably stumble into a spell or two like, accidentally
group of wizards who ask this in-universe, and after extensive study learn to their surprise that animals are casting spells all the time, just that their magic is so fundamental as to be unrecognizable to humans. turns out the only reason acorns grow on trees is because squirrels keep wishing for them.
Sisko whenever Garak does something like blow up his shop, trip someone on the promenade cause he's feeling silly or hack the system to Fuck with dukat by turning off his hot water while he's in the shower
Okay but imagine being the team of Eridian scientists tasked with keeping Erid's Only Human alive for as long as possible while the whole planet's environment is literally trying to kill him. And then Rocky shows up and is like:
“Grace says he would like half of dome to be water.”
“Oh, is necessary for humans to have large amounts of water question?”
Small Eridian equivalent of a sigh. “No. Not needed for life. In fact Grace will die if he falls in water and does not get out.”
“Tell him we give him water in containers that won't kill him. Lots lots lots of water on Erid for Grace to drink.”
“No. Grace say he want water on ground. Also want it with excess sodium chloride compound so it will be unhealthy for drink.”
To celebrate Erid getting their sun back on track, Grace asks for some alcohol. There's a small amount left from the Hail Mary and Rocky offers to take it to the science Eridians to see if they can synthesise more.
“Grace want this liquid for celebration.”
“Of course.” They scan it. “You have wrong liquid. This contain compounds which are poisonous for humans.”
“Yes yes yes. Grace say humans like feeling of being slightly poisoned.”
quirky fourth wall breaking character but theyre just fucking. wrong about the medium theyre in. they keep making references to cinematic techniques and directorial styles and the other fourth wall breaking character is like "dumbass we're in a fucking comic book" and they are in a video game.
excuse me, but goofy and pluto are like humans and other apes. closely related species but not the same. this can be seen in how goofy walks plantigrade and bipedally, while pluto is digitigrade and quadrupedal
are you going to argue that they’re different versions of the same species, which has different types of walking? when dogs and wolves are generally regarded as different species? and wolves and coyotes are different?
Sorry, gang, gotta weigh in on this one.
Pluto and Goofy are both cartoon dogs. The idea of them being different species of cartoon dogs doesn't hold water for a few reasons.
- Pluto does not have digitigrade legs.
Here's a real dog with real digitigrade legs.
We should all know how that works. The weight rests on the 'toes', the bones which parallel our ankle joints are positioned higher and act as locomotive joints as opposed to weight-bearing joints, and the knee/hip are similar to ours.
Okay, so here's Pluto:
Pluto puts his weight on his ankle, and his knee is the main locomotive joint. He's plantigrade. I'm actually finding it impossible to grab examples of him walking in a such way that doesn't suggest that he and Goofy have extremely similar anatomical structures, (minus Goofy doesn't have a tail and Pluto has less digits* - but those can be chalked up to individual variation.)
*Sometimes Pluto summons a thumb out of nowhere in order to complete a gag so who knows.
Walking comfortably as a quadruped is not evidence of him being a different species; some humans can do that. He can otherwise emote as well as Goofy, shows as complex an emotional range as Goofy, is as much a character as Goofy is. Rarely we get Pluto's internal monologue, and it is complex and very human. The only reason he is considered less anthropomorphic is because he acts less anthropomorphic. And doesn't wear clothes; lots of cartoon animals don't wear clothes, though.
But, I mean, Goofy can talk. Pluto can't talk. Right?
- Pluto Can Talk
Pluto only speaks in barks and some maybe human-sounding interjections (huh, yeah, woah), but his earliest incarnations delivered some dialogue. He could, once upon a time, speak some english and communicate with Mickey. His lines were brief, and his character's ability to talk was phased out pretty early.
It may be worth noting that 75% of his spoken dialogue was racist enough that The Walt Disney Company went back and redubbed those few lines with barking. So, I mean. That might explain why they don't let him talk anymore.
I think I started replying to all this with a different point, but now I guess my point is that the Goofy/Pluto situation raises so many questions that after taking the time to read more about Pluto and draft this reply, I am more convinced that Goofy and Pluto are the same kind of cartoon dog, and I have even more questions about what the hell is going on here.
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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