I’m guessing the lost funds are bleeding out to energy concerns. Correct? Asides from brief construction contracts for data centers, I’m unsure how one makes such large sums of money disappear.
Still supposed to be valued 1.500.000 Million dollars. Lol.
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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.
this goes in line with thier aggresive pandering to the govt to be used mass surveillance.
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.
Oh sure. Too bad the captive market here in the US wouldn’t allow it.
I’m totally spamming this across the thread with copy/vaste.
Oh yes I’ve seen that. He really did have a very high level of effortless explanation for it. Junkies fits perfectly.
A billion here, a billion there. Over some time it might become quite a sum.
I’m totally spamming this across the thread with copy/vaste.
Repeating the DotCom burst.
but worst. because some of those sites provided actual value, “AI” does not, most heavily used by Palantir/AI as mass surveillance and profiling people for bombings or harrasment.
I’m totally spamming this across the thread with copy/vaste.
Good.
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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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.
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.
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.
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.
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.
they have to pay off those datacenters somehow, the only one whos partially laughing to the bank is jensen.
What happens to Nvidia when the AI bubble pops though? They will lose so much revenue. Now they should be perfectly sustainable still given that they can sell GPUs to the same customers they used to. But will shareholders like that?
90% of Anthropic money is enterprise API use which is far less subsidised than their subscriptions being 10% of their income. OpenAI on the otherhand relies on the subs.
There is still going to be a big bubble bursting. It’ll be interesting to see how each company handles it.
Check out what portion of Anthropic revenues turned out to be processing distillation for others, namely Chinese market players.
A huge portion of their revenue basically came from their competitors using their horsepower against them to build the next, better mouse trap
