Goddamm… This could easily have housed every man, woman, and child in this country. But no, no free housing while we squander wealth with our stupid ideas.
Billion is officially the new million.
Why haven’t they just asked Claude how to make money with their business model? /s
They have.
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Wait for excited CEOs to fire all their staff.
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Crank up the prices.
2 only works if regulatory capture in place to prevent cheaper competition from open models.
That’s why they keep trying to play the “AI is so dangerous” narrative and why you keep hearing about “rogue AI agents” which in reality someone had to instruct to break the law, and they probably used some of their no-guardrails internal-use models (so Claude Mythos rather than Fable).
Claude Mythos and Fable are the exact same model, the branding only reflects which one has more restrictive classifiers in front of it during deployment. But the weights are identical.
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$8B real loss on $16B revenue. ($72B is a bondholder gain (accounting loss) from conversion). $9B in training costs not counted as loss, even though it is worthless whenever next model version is released.
$561B in forced spending on compute over next 10 years, with $750B total compute costs lined up. Structural losses are baked in for a few years.
But, when the word guessing program gains consciousness, it will be capable of doing the job of every worker in the world, and eager to do those jobs, and anybody who owns Anthropic shares will be a trillionaire in an economy that totally works and is healthy. So, better invest now!
Musk giving 1 share (about $160) to all US children with a Trump account, will make the next generation cheer for skynet genocide and oppression. “For a while, it added 10-20% to my net worth.”
even though it is worthless whenever next model version is released.
For most version releases I actually doubt that, I’m pretty sure they just keep training the model and release checkpoints every few months. Architectural changes, however, will indeed invalidate the previously trained models, and occasionally they have to do that to keep up with the competition.
But if you do architectural changes even just once a year, that means you’d have to depreciate those training costs over just that one year to be truthful. Meaning they might as well be losses rather than depreciating capital investments.
There is a genuine “training corpus” that is an accumulated asset and grows and feeds new models. The vast majority of training cost, that should be expensed, is the training time compute. Neither of these are expensed. There was about 13 major US model releases in September. At least 7 of these replaced a 1 month old previous model family. Open AI gpt sol went from 5.6 to 6 to 6.1 in about 2 months.
Fast model releases not only lock in structural losses, they juice revenue growth illusions. Model use rate generally drops by 66% 4 weeks after release, because of competition, and a surge of use on release for evaluation.
New models are trained on older models, so even if the older model is not longer at par, without it the new model couldn’t exists
I’m totally spamming this across the thread with copy/vaste.
And that’s without paying royalties to content creators as they should be required to do
also before court cases for defamation. Two cases in Germany hold Google executives responsible for false claims (by the Google AI) of sexual crime claims against an innocent man.
Good. If you want to make AI a form of communication then that’s the voice of your company. You’re endorsing whatever it says.
yeah. It should be the same with Facebook. Here in Australia, it seems like nothing is against the community standards anymore (not spam, porn or even violent threats)
Trash app, it’s why everyone should just stop using it. I ceased doing so, 6 years ago and it’s been bliss without it.
or counting the $1.5 trillion in debt the big AI players are hiding in subsidiaries
yeah the circle-jerk nvidia has created with coreweave and so many others just to wreck the gpu and memory markets, all so these hideously expensive AI racks can SIT IN THEIR FUCKING PACKAGING ON A LOADING DOCK because they don’t have power or cooling built is mindboggling
ITS THE FUTURE YOU JUST DON’T UNDERSTAND!!!
the future of aging like fine piss lol
“The court finds Anthropic guilty and orders them to relinquish the whole of their company to the Group Representing All Artists”.
Artists : “Wait -”.
Dario Amodei : “Fuck yes! Good luck paying back those 80 billions, losers!”
80 billion could have bought a whole lot of Chinese EV’s to resale and they could have made a profit.
All those loans are getting hot. They’re starting to toss them around and trying to hide them.
I have strong doubts they can ever make this particular approach to AI work at all, let alone in time to cover their bets.
This path looks like a dead end. But, I don’t know jack about shit.
The issue is they are too expensive, it’s not really a limitation of the technology, well it might be, but that’s not the issue here. They are paying Nvidia Billions for their entire 2026/27 GPU runs and they can’t get the customers to cover that. It’s like $200 pm for their max plan. It’s almost cheeper to hire a human in India.
There’s a reason so many AI projects have turned out to be Actually Indians.
My monthly salary as a software developer is 80 USD
Inference is cheap and getting cheaper. Not sure about training.
🐤
I hope it pops
Stop_trying_to_make_AI_happen.jpg
I’m doing my part by constantly asking chatgpt questions without ever logging in or paying them money. Eventually they’ll all go belly up and maybe we can ditch this shit.
Idk man, to me, it feels like we are further from AGI than fusion reactors actually being hooked up to the grid, considering LLMs are still just glorified autocorrects, needing a ton of prompt injections from their providers. And yet, the AI companies make it seem like it’s right around the corner (obviously, because $$$), whereas to me it feels like we are still at least 50 years away. Maybe AGI will be the next fusion generator chase.
Ironically there was notable news in the fusion reactor space this week as Gemini 4, building on the work of Matt Landreman and GPT-6 Astra a little while ago, expanded counterexamples to Grad’s conjecture which had claimed exact solutions for controlling a key aspect of fusion were impossible.
So fusion may actually be more around the corner thanks to the advances of capabilities of AI which helped prove that the fusion problems aren’t as hard as they were thought to be for decades.
And if you actually believe that, I have an amazing business proposition to you. So, there is a bridge in NY, and I can sell it to you for very little money…
Building on other people’s work to provide examples for something is actually one of the things an LLM can be good for.
Evidently, the only thing it’s good for is providing endless dribble for snake oil salesmen to scam people with. There is an endless barrage of “our latest and greatest magic just solved a problem” and when the dust settles it’s always some combination of exaggeration, lies, misunderstanding, and stolen work.
Even from my very limited understanding of high level fusion related math, I can bet it’s the same case here. At best they’re not lying and they provided a proof for some old math theorem. What I know is that fusion isn’t “one proven math problem away”, and I bet even if they’re not lying it will not help that much if at all.
AGI has been achieved more or less because it just means self sufficient at completing tasks. An LLM is just a component these days because they are Vision-Audio-Language-Models with multi frequency ‘thought’ loops. The next letter is A for action where they just have high frequency outputs for direct computer and robot use.
Just because it is bad AGI doesn’t mean it is not AGI right
See the problem is that people expect AGI to learn on its own. LLMs sorta do with big enough context and writing memories, but… They also don’t. They don’t get better at reasoning or anything, they only get better at solving the tasks they’ve written notes on. Which are themselves often pretty bad notes.
They do learn they use search tools and create long term memories. Mechanically that is just tool use it isn’t magic. Do you need these things as emergent properties for them to be real? That would be cool but I don’t think it takes away what is possible now.
They did manage to do something different, though. I thought at one point that proof assistants should offer to automatically upload your proofs to a central repository so everyone can benefit from them. But such a system would require many to opt in for it to be useful.
What AI does best is giving you existing solutions. It even adapts them if they don’t quite fit. Because many people now discuss their ideas with AI, ideas may spread the same way as well when the conversations are used as training data.
So no, definitely not AGI but valuable. Though as typical of explosively growing startups the value does not come from the technology but from activity bordering on criminal that lawmakers can’t keep up with.
This IPO is going to be one of the biggest rug pulls in history.
Yes. If you follow the money, investors in OpenAI are the usual suspects, a Kushner in there (admittedly the “best” kushner) and the early investors were guaranteed returns of up to 18% (bank CD currently around 5.3%) which stemmed from a $500B injection from the US government. Not only will it be a rug pull, but a government built one. Truly appaling, we let the fox in the henhouse.
Cant have Healthcare for our people, but can pump and dump the world economy.
So far
An entire industry built around burning cash, water, and electricity to generate questionable answers based on glorified autocorrect. It’s astounding.
Throw another few trillion and a couple dozen rain forests at it. Completely rational behavior.
glorified autocorrect and plagiarism/nonatribition.
Have you actually used it recently? It’s become incredibly good. Calling it a glorified autocorrect is like calling ASML’s lithography machines a glorified polaroid camera.
Now now this is the frediverse. Your only allowed to ignore facts and hate on ai around here.
There’s plenty of good reasons to hate AI but in case you missed the notice on the door your not allowed to have nuance. It’s all or nothing.
lol… it’s hardly limited to the fediverse bud, people are learning why the economy is fucked: AI
why can’t they buy a console? AI.
OR A GPU.
OR AN SSD.
OR RAM.
OR A FUCKING SPINNING DISK HDD.
why does the food in the adverts look like nightmare fuel? AI.
why does the president think he’s popular? AI.
Tim Sweeney castigates Kenny - why? AI.
Musk can’t synthesize a personality so he snorts ketamine and AI.
where’s the upside, ASSHOLES? Your garbage is fucking up the entire planet, great fuckin work FANBOYS, shove that up your ass for NUANCE
In 20 years - if there’s still a civilization - they’re all gonna look back and wonder how so many were so fuckin dumb.
In 20 years we ALWAYS look back and wonder how so many were so fucking dumb. Thats literally history. Theres never a point where there isn’t some major fucking bunch of absolute idiots trying to ruin everything.
Ai is just this decades attempt at ruining everything.
ok, so it’s like asbestos and nuclear waste runoff, that’s not enough reason to hate AI for you?
instead of stopping the stupidity you’re like: find the nuance.
[email protected] - lol doubt [email protected] -
listen kids, if you’re not brave enough to let chatgpt give you a riposte don’t fucking participate ya little shits
That’s entirely enough reason to hate it.
But it’s also objectively fucking stupid to act as if this is some new historic event in human history and not just yet another dumb fuck move in a long line of dumb fuck moves.
Plenty of good reasons to be pissed off. You don’t have to lie and bullshit to make up more is what I’m getting at.
yep. roided up eliza’s
bUt It CoUlD cUrE cAnCeR
alphafold actually COULD have and still got dissolved https://www.aimodeling.com/en/news/slug/deepmind-dissolves-alphafold-team-anthropic-pivot
Not with an LLM you won’t.
You act as though those billions of dollars spent towards other things (like cancer research) would somehow be better.
?
Fucking yes it would be better to put hundreds of billions of dollars every year into curing cancer/HIV/ Type 1 diabetes/alzheimers, literally any disease. Curing a major illness like those would actively help hundreds of thousands or millions of people around the world every year.
What does AI help? My fucking manager in sending cryptic emails that raise more questions than answers?
Dump a few hundred billion into disease research, or fusion power, or just into housing for all of us.
AI helped me with my voting ballot. I asked Kagi’s AI to research the ambiguous candidates and propositions. I had it put them into a political alignment chart - left/centrist/rightwing. Addendums for candidates included things like whether they had criminal convictions or corruption, stance on vaccinations, how they feel about “tough on crime”, the homeless, ect.
For propositions, the political alignments had a fourth entry added, where the yes/no included the wealth level of backers for a position.
This is very useful, completing in a hour what would have taken a week of research. Very useful for digging into the mechanical details of a proposition, like whether it prevented the replacement or supplementing of a measure.
How do you know that anything it displayed was accurate for those candidates? Every single time I’ve asked it to include source links, those source links don’t actually support the AI’s statement.
My experience too. The source never backs up what the AI claims. It always just makes shit up.
One of the candidates was appointed to their office by a Republican governor, and elevated more recently by a Democratic one. The AI referred to official government records.
Well, that’s one candidate. And a reference to an official gov doc doesn’t meant the info was extracted or summarized accurately.
How about the others?
…yes?
Remember to never miss the /s
Marking your sarcasm is the coward’s way out
With a .ml account you need to. I’ve heard way more absurd statements said with a straight face from .ml users
It’s cowardly to be understood?
Okay, boss. 👍
obligatory…
But have you considered that it’s like REALLY good at programming? /s
What’s stupid is, you could even just keep just the programming part, and it would become much more efficient and not ramble on with explanations etc.
If an LLM was something you could train on your GitHub repo or an internal knowledge base, and ask it natural language questions about that, AND it didn’t need an 800 acre datacenter to do it, I wouldn’t have so many hang-ups about it. Or maybe even train a model in a programming language and have a model that’s tailor made for writing C, or LISP, or Brainfuck or something.
But that’s not what they are. They only function if you hoover up everything the light touches and feed it to the machine, to the point where rare, irreplaceable literature is being shredded apart for training data. And god help you if you try to take your ball and go play somewhere else as the AI boosters profess you must do, they will follow you there and scrape you anyway
You are describing local models and they’re getting pretty damn good, especially at coding.
I mean, local models with RAG exist.
The ai crash of 2026 can’t come soon and fast enough
The RAM cartel is figuring out a new excuse for a price hike before allowing it.
Repeating the DotCom burst.
i wish them ruin, you made my day
