#socs

[artcollectorninja]

[mostlysignssomeportents]

The AI that we’ll have after AI

I'm on a tour with my new book Enshittification: catch me next in Los Angeles, Calgary and San Francisco! Full schedule here.

When the AI bubble pops, what will remain? Cheap GPUs at firesale prices, skilled applied statisticians looking for work, and open source models that already do impressive things, but will grow far more impressive after being optimized:

https://pluralistic.net/2025/09/27/econopocalypse/#subprime-intelligence

The AI bubble companies are scams. They've spend most of a trillion dollars in capital expenditures, and by their own (very cooked and dishonest) numbers, they are grossing a total of $45b/year, industry-wide:

https://www.wheresyoured.at/the-ai-bubbles-impossible-promises/

At $45b/year (an inflated number, remember!) it's going to take them a long time to recoup the hundreds of billions of dollars they've spent so far. But they don't have a long time: the massive GPUs that power AI's "foundation models" and cost six- or seven-figures each burn out remarkably quickly. The companies that buy these GPUs claim they'll last five years (and depreciate them over that schedule); however, this is accounting fraud, because in reality, these GPUs have a duty-cycle that's more like two to three years:

https://blog.citp.princeton.edu/2025/10/15/lifespan-of-ai-chips-the-300-billion-question/

And when the companies run their GPUs really hard, they burn out in just 54 days:

https://techblog.comsoc.org/2024/11/25/superclusters-of-nvidia-gpu-ai-chips-combined-with-end-to-end-network-platforms-to-create-next-generation-data-centers/

To recoup their existing and announced investments, AI companies will have to bring in $2 trillion, more than the combined revenue of Amazon, Google, Microsoft, Apple, Nvidia and Meta:

https://www.bain.com/about/media-center/press-releases/20252/$2-trillion-in-new-revenue-needed-to-fund-ais-scaling-trend—bain–companys-6th-annual-global-technology-report/

And they have to bring in that $2 trillion before all those GPUs burn out…which is, again, about 2-3 years.

Or sometimes just 54 days.

AI companies' purchases and R&D expenditures aren't guided by the need to make products that will bring in $2 trillion dollars. AI companies spend money in order to put on a show for investors, to demonstrate that they are very serious about AI. Think of all those GPU-stuffed data-centers as akin to a peacock's tailfeathers: an expensive way to attract mates (or, in this case, investors), by emitting costly signals that demonstrate your power:

https://en.wikipedia.org/wiki/Signalling_theory

Of course, it's far cheaper to pretend to be spending a lot of money than it is to actually spend it, and they're doing plenty of that, too. Meta has promised to spend $72b next year on data-centers. However, Meta's annual free cash flow is $52.1b. OpenAI says it will spend $60b/year on data-centers, which is five times its annual revenue of $12.7b (and the company is losing $9b/year). As The American Prospect's Brian McMahon writes, "How can OpenAI plan to spend five times what it brought in?"

https://prospect.org/power/2025-10-15-nvidia-openai-ai-oracle-chips/

I don't know how many of these giant "foundation models" will still be online after the crash, but I would not be surprised if that number is zero.

So the big question is, what comes next? What will the AI bubble leave behind?

Some bubbles leave nothing or next-to-nothing behind. Enron left nothing behind but the cooling corpse of a CEO who popped his clogs before he could be sentenced to life in prison. Worldcom left behind a CEO who survived long enough to die behind bars…and a ton of fiber in the ground that people are still getting use out of (I'm sending these keystrokes to the internet on old Worldcom fiber that AT&T bought and lit up).

Crypto's not going to leave much behind: a few Rust programmers who've really taken security by design to heart, sure, but mostly it'll be shitty Austrian economics and even shittier JPEGs.

So what kind of bubble is AI? That's the $2 trillion question:

https://locusmag.com/feature/commentary-cory-doctorow-what-kind-of-bubble-is-ai/

Before I get to that, let me be clear here: bubbles are always bad. As much as I like my 2gb symmetrical fiber, the fact that it exists because a crook stole billions of dollars from everyday people who were only hoping to live a dignified retirement of material sufficiency is terrible. Worldcom CEO Bernie Ebbers deserved what he got, and worse.

The AI bubble is on its way to sucking up a trillion dollars and not all of that money is coming from Saudi royals, hedge fund bastards and Elon Musk's credulous creditors. Plenty of it will come out of the savings of working people who've forced to play the suckers at the table thanks to the replacement of guaranteed pensions with "market-based pensions" that only pay out if you guess right about which stocks to buy:

https://pluralistic.net/2020/07/25/derechos-humanos/#are-there-no-poorhouses

Those people are going to get wrecked. And so are the rest of us. You don't need to be an AI investor to get wiped out by the AI investment bubble, either. With 30+% of the S&P 500 tied up in seven AI companies' stock, the coming crash will definitely escape containment and crash the whole damned economy.

So the bubble is bad. Really bad. But even so, there will be things we can salvage from it: open source models, skilled programmers, cheap GPUs bought out of bankruptcy for pennies on the dollar. It would be better if we created that stuff without burning the world's economy to the ground and emitting a heptillion tons of CO2, but ignoring the productive residue of the AI crash won't bring the economy back, or suck the carbon out of the atmosphere.

The open source models are a big deal. They're already capable of doing really impressive things, like transcription, image generation, and natural language-based data transformation, running on commodity hardware. I run several models on the laptop I'm typing this on – a computer that doesn't even have a GPU.

What's more, there are a lot of ways to improve these models within easy reach. The US AI companies that threw these models over the transom after irrevocably licensing them as free software had very little impetus to improve their efficiency by optimizing them. Remember, they're spending money as a way to "prove" that AI has a future.

Shipping a model that runs badly – that needs more data-centers and energy to run – is a way to convince investors that it's doing something really advanced (after all, look how much compute and energy it's consuming!). It's a scaled-up version of a scam that Elon Musk used to pull on investors when he was shopping his startup Zip2 around: he put the regular PC his demo ran on inside a gigantic hollow case that he would wheel in on a dolly, announcing that his code ran on a "supercomputer." Yes, investors really are that dumb.

Even modest efforts at optimization can yield incredible performance gains. Deepseek, the legendary Chinese open source AI model, consumes a fraction of the resources gobbled up by the likes of OpenAI. Deepseek's launch was so impressive that it knocked $589b off of Nvidia's stock price the day it shipped:

https://finance.yahoo.com/news/nvidia-stock-plummets-loses-record-589-billion-as-deepseek-prompts-questions-over-ai-spending-135105824.html

There are a ton of these open source Chinese models, and they all perform like crazy. China does a lot of AI optimization because US embargoes prevent Chinese AI companies from accessing the most powerful GPUs, so Chinese coders tighten up their code and outperform US companies even though they're using far less powerful computers.

After the crash, everyone will be in a similar position to those Chinese AI optimizers: Chinese companies can't buy advanced GPUs because of the embargo; and everyone else won't be able to buy advanced GPUs because the AI crash will have cratered the economy for a generation.

But there is so much room at the bottom. Optimized models do really impressive things on really cheap hardware.

How cheap? Well, here's hardware hacker Pete Warden demoing a chatbot that you talk to and that talks back to you – and it's running on Synaptics System-on-a-Chip (SoC) that costs "low single digit dollars":

https://petewarden.com/2025/10/16/why-does-a-local-ai-voice-agent-running-on-a-super-cheap-soc-matter/

This is basically a little special-purpose Alexa, except it doesn't connect to the internet at all (and therefore doesn't leak any of your data). In Warden's demo, the gadget is a button-sized voice assistant that is meant to be integrated into a dishwasher, which can interpret the dishwasher's manual for you. If your dishes come out dirty or if the drain gets clogged, you press the button, describe your issue in pretty vague terms, and it instantly speaks aloud all the troubleshooting steps to deal with it.

This privacy-preserving, cheap-like-borscht component adds a voice-activated, conversational assistant to a device, sipping power like the clock on your microwave, running on a processor that costs less than a pack of AA batteries. It's seriously fucking cool.

There's going to be a lot of this AI, after the AI goes away – just like there was a lot of the web after the dotcom crash, when, overnight, San Francisco had infinity office-space, servers, and techies going begging.

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/2025/10/16/post-ai-ai/#productive-residue

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[tr4v1s-sk4t3rb0y]

something something about how both the Socs and Greasers are jealous of each other but for completely different reasons.

[your-local-soc-girl]

do u think darry ever lets the gang wear his old letterman jacket?

actually no, i think the gang would steal it and wear it to fuck with the socs

i can imagine like two-bit strolling along with a letterman jacket just to see their faces

[hellothereimaloser]

Ponyboy still dreams of drowning...

Before I got sick I managed to draw this oneee, it was hella out of my comfort zone but I like how it turned out eventually 🥺💞

And yes it's exactly what you think it is 😔

[nmbch]

More things that i came up with about the outsiders

1. Paul was a massive dick to Pony every time he came to the Curtis house but instead of ruining his big brothers friendship by snitching he resorted to throwing books at Paul when no one was looking and only came clean to doing that after Darry and Paul stoped hanging out

2. On occasion soda will go over pony’s notes from school to catch up one some things but half the time he doesn’t understand what he’s writing about

3. I think we all can agree that soda has adhd

4. Johnny ate the most random foods not just because he simply needed food he genuinely liked it and i mean he would eat stuff like brussels sprouts with ketchup

5. the only reason dally ever knew the gang was cause johnny saw him thought his hair was cool and brought him to the lot where everyone was hanging out

6. Pony used to call his brothers “dearest big brother(s)” and no one knows why but now he’ll do it if he wants something

…you see how my Johnny and dally headcanons are in past tense their dead their not coming back

[dallasgallant]

“Soc is when popular people.” Guys I am begging you. Popularity ≠ class.

Rich does not mean popular, popular does not mean rich. Darry was not boy of the year level popular because he had soc friends, he was nice and genuinely liked- have you never had that guy (or girl) at your school? A greaser could be popular, a “softer” (less JD) one’s swagger could make them really cool and rebellious. While Soc’s do have an overlap, correlation is not causation - in addition to having a large group of friends does not a “popular kid” make.