Billion is officially the new million.
How have i never seen this before?
This is so on point.
Robin Williams is absolute treasure.
If any of these AI companies IPO, you could make a lot of money shorting them!
A billion here, a billion there. Over some time it might become quite a sum.
That is about what Taiwan just purchased in natural resources.
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.
80 billion could have bought a whole lot of Chinese EV’s to resale and they could have made a profit.
Forget resale, for 80 billion you could probably get BYD to produce custom vehicles under your own brand.
No wonder they’re panicking so hard over open weight Chinese models
I firmly believe OpenAI, Anthropic, etc., will all eventually collapse under their own weight, meanwhile open weight distillations of their models will become the de facto standard for AI usage. There’s just no way they can ever make up all the money they’ve burned in R&D, especially when distillations are right behind them.
Good.
Repeating the DotCom burst.
i wish them ruin, you made my day
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.
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.
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.
As a training data it’s possible less then useful, unsupervised data like that is actively harmful. As a central repository of everyone’s private conversations it can be in a way useful, but I can’t understand how anyone could be OK with a private company reselling your most private data.
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.
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.
So does Amazon every year, no?
No… The worst year Amazon ever had was a net loss of $1.4 Billion back in 2000. Most years in the early days they were at a loss of a few dozen million. At the time, they drew a lot of criticism for running red way longer. If Amazon ran at their worst year for 50 years, they still would have lost less money than Anthropic did.
They haven’t operated at a loss in over a decade.
$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.
I’m totally spamming this across the thread with copy/vaste.
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.
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.”
Impossible to imagine anything so extremely useful as AI not being profitable in the long run. No sarcasm.
Assuming your assessment of AI utility is correct for sake of discussion, it would not mean it is guaranteed to be profitable for any given company with any given strategy and spending.
Internet shopping and delivery is hugely profitable, but that’s of little comfort to pets.com and webvan.
If a company more responsibly managed their spend and commitments and still reached the same utility as Anthropic, then Anthropic would never see profitability.
It will definitely be profitable for the hardware makers. Companies whose entire value proposition depends on the model weights not leaking in an increasingly sloppy vulnerability-filled world of IT? Not so much.
In the long run you’d imagine that GPUs will become more affordable once these massive datacenters have been built. At that point it becomes far more profitable to run your own hardware. Especially if these AI companies need to increase their subscription prices by x10 to finance all this debt they’ve taken on.
Yeah AI is here to stay but these “founder” companies sure aren’t.
Public libraries are also very useful. Doesn’t mean they have to make money.
Bookstores, publishers, writers, etc etc are also very useful and profitable even with the existence of public libraries.
<ADAM DRIVER> MORE! </ADAM DRIVER>
