Where Ceia Lives

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2026/07/13/go-meta-meta/#meta-meta-meta

"I often wonder what the Vintners buy/One half so precious as the Goods they sell" -The Rubáiyát of Omar Khayyám

I first encountered that quote from someone extolling the virtues of bookstores, and it stuck with me, because for most of my childhood, every bookstore visit ended with me broke and wishing I'd had three times as much to spend.

As a larval hyperlexic, I just didn't understand what a bookseller could possibly buy with my money that was better than the books they already had? Of course, then I became a bookseller and discovered that Sturgeon's Law ("90% of everything is shit") applies to a bookstore's wares as much as it does to anything else. I also acquired a monthly rent obligation and discovered just how important money could be.

Nevertheless, Omar Khayyám's question stuck with me, especially when I fell down a years-long rabbit-hole of learning about scams and the finance sector (but I repeat myself). Every get-rich-quick schemer will tell you that they've found the infinite money hack, which they will sell to you for a remarkably reasonable sum. Likewise, every stock picker claims they can outperform a simple low-load index fund, and all they ask of you is a few hundred basis points in exchange for multiplying your wealth beyond the dreams of Creosote. Neither one has a good answer to Khayyám's question: if you can make all the money with your amazing system, why do you need my money?

This is a question that needs to be forcefully put to AI hucksters. In their more expansive moments, the Altmans and Amodeis of the world will tell you that they're planning to teach the word-guessing program so many words that it will wake up and become god. DOGE's broccoli-haired brownshirts laughed in the faces of the NIH lifers who begged them not to vaporize their long-running cancer research projects: "General AI is around the corner and it's going to cure cancer. Cancer research is a waste of money!"

Which all raises the question: if you've truly incubated a foetal demiurge in your "AI lab," why are you offering to sell it to me? What do the AI hucksters buy/One half so precious as the Gods they sell?"

The last couple years experimenting with AI I've come to the conclusion that the main reason it works isn't a mystery because it has to be a mystery. It's a mystery because they need it to be.

That's why they've been hogging all the RAM and GPUs to the point of ordering the entire yearly worldwide supply in advance.

That's why they keep building data centres despite demand not justifying it.

That's why every open source model China releases is a hit to the stock market.

The secret sauce behind LLMs isn't really as demanding as they claim. There's waste built into it.

Every response within a chat sends the entire message chain through the robot's brain. It doesn't have loading bars, it doesn't let you calculate how many tokens you've used, it doesn't even let you see when you're crossing the limits until you're there.

It's almost like they don't want you to have control over how much you use.

ChatGPT in particular is prone to scope creep. It subtly talks you into expanding the reach of your projects to require more computation. It always delivers 90% of a project, with something missing so you ask another question.

Claude turns everything into a file creation request, even if it can deliver in plain text just fine. It's enticing to see how your simple table becomes a fancy react file or an HTML with heavy formatting.

Neither of these issues are present on DeepSeek or on local models. Which means they aren't inherent issues with LLMs.

It's not a bug, it's a feature.

They want you to keep paying unmetered rent. They do tricks to convince you to spend more than you meant making something bigger than you planned. They do this subtly, to make you think it was your idea.

The thing is, Chinese local models prove that we already have good enough AI for most things. It's plateauing in capacity, it needs to grow in efficiency and memory use. But intelligence is already at J.A.R.V.I.S levels, and can run fine on consumer grade hardware. We've reached a stability point.

The problem is you can't raise rent on stability. So you just keep throwing compute at the problem until you can justify asking for more money. Which is why they choke the memory market.

If nobody can buy memory, nobody can run local AI. If no one can run local AI, they have to keep paying unmetered rent. Development is slow, and importantly, the black box remains a black box.

That's why every memory breakthrough comes from Chinese companies. Because they're the only ones sharing their data. Capitalist companies don't want people to study how the models work.

With subscriptions, there's rent seeking. With local models, there's reverse engineering. Once enough people get their hands into the guts of the robot it won't be long before we figure out exactly how they work, and find more efficient ways to make them that don't require as many data centres.

Meanwhile, Fable and GPT 5.6 are being shadow marketed with all these rumours about how dangerous they are, and AI companies are begging for regulations from the government. Yes, they want control of those regulations, but that's not all.

What they're really after is a government ban on local AI. They want to cut off access so that they control all the intelligence.

Eventually, the goal is making contracts with large corporations to employ their robots instead of people. If no one has local AI, because they can't understand it or because it's illegal, then they can no longer compete against a faster worker that demands no labour rights, even if it does C+ work at best.

And that's where the real fun begins. And by fun I mean starving out the working class.

They aren't competing directly with their customers yet. First they have to educate them, jus like Spotify educated their consumers into forgetting how piracy works. They have to make them reliant on cloud compute, just like how Google Drive made everyone reliant on its storage before raising prices. And they want them to be ignorant of how much energy anything takes.

That's going to take one generation.

Not long ago every teenager knew how to use a computer. Now they depend on Apple for everything. It's a masterful business model. So what if we could apply it to every form of labour?

It's okay, just hand us your credit card and we'll do the rest. How much, you ask? Don't worry about that. Just keep your monthly payments coming. Oh, you can't afford it? You want your computer to do it? Well fuck you, we bought all the computers, so now you work for us.

>looks inside

— then it's art nouveau

and if the sexy lady has a bob cut or a hair cap and is wearing a column or flapper dress; there's a lot of geometry like rectangles, arches, rays, and diamonds; angels have super sharp wings and a lot of muscles; everything is steel, concrete, marble, gold, and red velvet seats; everything is VERY angular; and all the foliage is basically papyrus fronds; things feel vaguely Egyptian or Turkish or Mesopotamian; the fonts play with being very skinny or very thick and are sans serif with extra lines; or Gatsby would be found floating dead in that pool

— with lots of lush flora, tiny insects (like dragonflies) or graceful birds, stained glass, iron, warm golden lighting, lots of wood and wood carving (but now it's more wood paneling), a stylistic fondness for Japan, line weight variation in the font, and tile (but this time it's carved or sculpted on, not tiny mosaic)

but you're worried it's art deco

— because the forms (especially foliage) are very symmetrical and slightly more angular or blocky and graphic looking, things are more rectangular than circular or curvy in architecture, the patterns repeat more often, and more of the lamps are pyramids or rectangular, and there are nods to Egyptian or Ottoman style, and they used the color red (probably in an accent chair or carpet rug)

BUT there's no steel, concrete, gold plating or gilding, marble, big muscles, spiky or radiating diamond shapes, angular people, or flappers,

AND the vibes are jacobean, gothic, or spanish mission revival; they love some brick and stone; the wallpaper is an explosion of colorful pattern that could give you arsenic poisoning or help depict a descent into postpartum psychosis in a famous short story; but there are NO people to be seen, not even sexy ladies,

Truncated text of tweet from MrPitBull, Mar 11, 2026:

She kept finding women in laboratory photographs from the 1800s. Then she read the published papers—and every single woman had vanished. Someone had erased them from history.

Yale University, 1969.

Margaret Rossiter was a graduate student studying the history of science. She was one of very few women in her program.

Every Friday afternoon, students and faculty gathered for beers and informal conversation. One week, Margaret asked a simple question: "Were there ever any women scientists?"

The faculty answered firmly: No.

Someone mentioned Marie Curie. The group dismissed it—her husband Pierre really deserved the credit.

Margaret didn't argue. But she also didn't believe them.

So she started looking.

She found a reference book called "American Men of Science"—essentially a Who's Who of scientific achievement. Despite the title, she was shocked to discover it contained entries about women. Botanists trained at Wellesley. Geologists from Vermont.

There were names. There were credentials. There were careers.

The professors had been wrong.

But Margaret's discovery was just the beginning. Because as she dug deeper into archives across the country, she found something far more disturbing.

Photograph after photograph showed women standing at laboratory benches, working with equipment, listed on research teams.

But when she read the published papers, the award citations, the official histories—those same women had disappeared. Their names were missing. Their contributions erased.

It wasn't random. It was systematic.

Women who designed experiments watched male colleagues publish results without giving them credit. Women whose discoveries were assigned to supervisors. Women listed in acknowledgments instead of as authors. Women passed over for awards that went to male collaborators who contributed far less.

Margaret realized she was witnessing a pattern that stretched across centuries.

Women had always been present in science. The record had simply pushed them aside.

She needed a name for what she was documenting.

In the early 1990s, she found it in the work of Matilda Joslyn Gage—a 19th-century suffragist who had written about this exact phenomenon in 1870.

In 1993, Margaret published a paper formally naming it: The Matilda Effect.

The term captured something that had been hidden in plain sight for generations. Once you knew the term, you saw it everywhere.

Her dissertation became a lifelong mission.

For more than 30 years, Margaret researched and wrote her landmark three-volume series: Women Scientists in America. She examined letters, institutional policies, individual careers. She gathered undeniable evidence that women in science had been consistently under-credited and structurally excluded.

Her work faced resistance. Many dismissed women's history as political rather than academic. Others insisted she was exaggerating.

Margaret didn't argue emotionally. She presented data. Documented cases. Patterns repeated across decades and institutions.

Eventually, the evidence became undeniable.

Her research helped restore recognition to scientists who had been erased:

Rosalind Franklin, whose X-ray work revealed DNA's structure—credit went to Watson and Crick.

Lise Meitner, who explained nuclear fission—omitted from the Nobel Prize.

Nettie Stevens, who discovered sex chromosomes—received little credit.

Cecilia Payne-Gaposchkin, who discovered stars are made of hydrogen—initially dismissed.

And countless others whose names had nearly vanished.

Margaret changed the narrative. Science was no longer just the story of solitary male geniuses. It became a story of collaboration that included women who had been written out.

A very tiny percentage of creators go on to be famous, but that doesn’t mean that people don’t remember little things you did for years and years. Who came up with most of the world’s most famous jump rope rhymes? Who coined some of the famous idioms we use in daily speech? Who made up ‘Jingle Bells, Batman Smells?” Somehow, all of these things stuck and spread around.

When I was a small child, I saw a high school put on a production of the musical HONK. In one song, the mother duck describes various dangers that her baby should avoid in the water, including fishing line, which could strangle him. A member of the ensemble played the role of fishing line, doing a maniacal laugh and over-the-top strangling motions, and I found it hilarious– and to this day, that’s an example I often think of when talking about how ensemble members can still stand out in theatre. The guy who played the role might not even remember that he did that, but I do.

I took Suzuki violin lessons as a kid. The teacher made up lyrics to some of the songs, and she let her students make some up, too. Now whenever I hear the instrumental of one of those pieces, I always remember these ridiculous lyrics about a skunk that we sang in violin class. I don’t even know which student invented them!

In middle school, I found a video about atoms parodying Bill Nye made by some kids for a school product. It probably had less than 1,000 views, but I think of quotes from that video all the time. They had a parody of “We Will Rock You” with the chorus, “Protons, neutrons, electrons” that I think about a lot.