So, about 2 years worth of operations based on alleged $14 billion burn rate projected for 2026.
What an absurd amount of money - if only this was invested in energy sector scientific research and development, or healthcare or anything else practical.
I really hoped to see compact molten salt nuclear reactors in operation before 2030.
I don't understand how this is the top comment. LLMs have unlocked a lot of value for me personally, and arguably for the society as a whole. They are also one of the coolest technologies I've tried in years. As a technologist, I'm really glad that money is pouring in and allowing us to find its limits.
2020s ai could be the first systemic stall I see. Let's assume agentic could really be a force for improvement but the cost model is unsustainable and will choke.
This .. doesn't seem like such a terrible deal? At the purported growth rates, you'd expect OpenAI to reach 60-100 billion revenue by 2028. This is more or less the equivalent of building a new AWS.
Provided they keep cost growth slower than revenue and don't get disrupted by another model provider/commodification etc.
Nonsense. To give you a sense about how much $100B in revenue is, that would be the equivalent of every person in the United States paying $25/mo. Obviously that’s not happening, so how many businesses can and will pay far more than that, when there’s also Anthropic and Gemini offerings?
Well, i wished you actually donated the money you spent for pizza/coffee or all your savings towards hungry kids as well. How does it make you feel? why are you obsessed with how other people allocate their money?
We should all care how resources are used, even if don't own them. That investment is going to make things more expensive for everyone. See RAM, SSD, and GPU prices.
LLMs will create the pitch deck for molten salt reactors, provide progress reports, plans, and documentation, accept payment for delivery, and disappear into the night.
A major cost in building and operating datacenters is energy, so it does mean that significant share of those money would go into energy development. Large demand is one of the best things for stimulating technology development, and in this case we'd definitely see investment in solar and compact/safer nuclear of which MSRs are a part of.
xAI already brings gas turbines on-site, and i think the trend of on-site energy generation will grow, which will open opportunity (by providing well finaned demand) for compact/mobile/safer nuclear, and BigTech companies are among the best for any new tech development. I expect nuclear engineer positions get opened with Google and the likes :)
All of these things can be simultaneously true (and I would say, are true):
1) We are in a huge investment bubble right now and it's going to burst.
2) LLMs are extremely useful right now for certain niche tasks, especially software engineering.
3) LLMs have the potential to transform our world long-term (~10 yr horizon), on the order of the transformations wrought by the internet and mobile.
4) LLM's don't lead directly to AGI (no continuous learning), and we're not getting AGI any time soon.
This is an extremely obvious point, but bears repeating. I feel the assumption of an implicit link (in both truth or falsehood) between these fairly independent assertions can cause people to talk past each other about the really important questions in play here.
Regarding The Great Bubble, I am very very bearish about OpenAI in particular. They've had a good run for three years with consumer mindshare due to their first-mover advantage, but they have no moat, trouble monetizing most of their users, not much luck building out products that stick among consumers that aren't chatbots, and their models are no better than Anthropic's, Google's, or even the best Chinese open weight models 6 months later.
My bet would be on Google and Apple together (with Gemini powering Siri, for now) destroying OpenAI in the consumer AI market over the next 2-3 years. Google has first-rate models... but more than that, both Google and Apple have the enormous advantage of owning underlying platforms that they can use to put their own AI chat in front of consumers. Google has a mobile OS, the leading browser, and search. Apple has the premium hardware and the other, premium, mobile OS. They also have the advantage of the current regulatory climate being less antitrust than it was. And they don't have to monetize their AI offerings (no ads in gemini; ChatGPT is adding them) and can run them at a loss for as long as it takes to eat up OpenAI's market share. If they partner up, as they seem to be doing, OpenAI should very very afraid.
At ~$100B in AI funding, the question isn’t capital—it’s physical constraints.
Data centers need power (H100s are ~700W each), and recent capacity additions were mostly pre-allocated. Chip supply is also constrained by CoWoS packaging, not fab capacity, and expansions take years.
If power, packaging, and GPUs are fixed in the near term, does $100B mostly drive inflation in AI infrastructure prices rather than materially more deployed compute? Are we seeing the real cost of a usable GPU cluster rise faster than actual capacity?
Has anyone modeled what $100B actually buys in deployable compute over the next 2–3 years given these constraints—and whether that figure is shrinking as more capital piles in?
> as part of the startup’s [OpenAI's] efforts to raise up to $100 billion
At this stage, why not go public? Yes, they would need to manage quarterly financial reports and answer to shareholders, but they have reached a size where they are in the top 20 range on the NASDAQ. These public companies doing well, so it seems like a logical next step.
Okay, but I don't think we can call OpenAI a startup until it has reached the number one spot on NASDAQ with a $5 trillion valuation. Therefore, I believe now is a good time to focus on more realistic fundamentals, rather than fueling the hype by burning even more cash on the way to the absolute top, which is typical bubble mentality.
I actually think the public markets have a lot less faith in openai than softbank does. They need these crazy investors. Public markets would not value openai at $1.4trn. So they can't go public. It would reveal how bad things are.
It can be also just a trade part of a deal; like in YC companies, where investor Y buys company A from investor Z, and in exchange investor Z buys company B from investor Y, so the choo-choo train keeps running.
I'm pretty sure I could become a billionaire just by meeting Masayoshi Son and having a chat for 15 minutes. I've never seen a better case for a fool and his money being parted.
I think it should be 70 billion, scratch that, 125 billion, scratch that - 180 trillion. I'd rather have pictures of crocodile Trump on the Moon than a warm house, scratch that, rather than kids, scratch that, rather than any decent future at all. Great move, guys, can't get enough of it.
Not even close. The 2008 financial crisis is better comparison. And even then I think most negative effect will come from investors pulling money away from everything non-AI, than OpenAI/Anthropic/Oracle crashing and burning.
https://archive.md/uc1G9
So, about 2 years worth of operations based on alleged $14 billion burn rate projected for 2026.
What an absurd amount of money - if only this was invested in energy sector scientific research and development, or healthcare or anything else practical.
I really hoped to see compact molten salt nuclear reactors in operation before 2030.
> invested in (...) anything else practical.
I don't understand how this is the top comment. LLMs have unlocked a lot of value for me personally, and arguably for the society as a whole. They are also one of the coolest technologies I've tried in years. As a technologist, I'm really glad that money is pouring in and allowing us to find its limits.
To be fair Softbank really likes to invest in lemons, so you know, let them do what brings them joy.
Love this for them.
"90% of VCs quit investing right before hitting the jackpot"
- Softbank's motto
> if only this was invested in energy sector scientific research and development, or healthcare or anything else practical.
Haven’t you heard? AGI is going to solve every problem for us!!!
> $14 billion
Incidentally that’s how much SoftBank lost on WeWork.
2020s ai could be the first systemic stall I see. Let's assume agentic could really be a force for improvement but the cost model is unsustainable and will choke.
This .. doesn't seem like such a terrible deal? At the purported growth rates, you'd expect OpenAI to reach 60-100 billion revenue by 2028. This is more or less the equivalent of building a new AWS.
Provided they keep cost growth slower than revenue and don't get disrupted by another model provider/commodification etc.
“My 3-month-old son is now TWICE as big as when he was born. He's on track to weigh 7.5 trillion pounds by age 10”
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> At the purported growth rates, you'd expect OpenAI to reach 60-100 billion revenue by 2028.
I hope that’s “real” revenue and not the cyclic quid pro quo that seems to be propping the whole thing up.
Nonsense. To give you a sense about how much $100B in revenue is, that would be the equivalent of every person in the United States paying $25/mo. Obviously that’s not happening, so how many businesses can and will pay far more than that, when there’s also Anthropic and Gemini offerings?
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> At the purported growth rates, you'd expect OpenAI to reach 60-100 billion revenue by 2028.
I hope that’s “real” revenue and not the cyclic quid pro quo that allegedly seems to be propping the whole thing up.
Well, i wished you actually donated the money you spent for pizza/coffee or all your savings towards hungry kids as well. How does it make you feel? why are you obsessed with how other people allocate their money?
>why are you obsessed with how other people allocate their money?
I suggest you stop viewing the actions of multi billion dollar multinational corporations as anything similar to individual action.
Tu Quoque AND false equivalency. Impressive.
We should all care how resources are used, even if don't own them. That investment is going to make things more expensive for everyone. See RAM, SSD, and GPU prices.
What made you think that I'm "obsessed" with how other people spend money?
Because Softbank are really bad at it, and they have lots of it.
https://www.reuters.com/business/softbanks-wework-once-most-...
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I suppose the idea is that the LLMs will invent the compact molten salt nuclear reactors. Double win.
LLMs will create the pitch deck for molten salt reactors, provide progress reports, plans, and documentation, accept payment for delivery, and disappear into the night.
That's just magical thinking.
And Ethiopia couldn't get US$5 billion loan for a dam to service 60 million people.
The world is sick.
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A major cost in building and operating datacenters is energy, so it does mean that significant share of those money would go into energy development. Large demand is one of the best things for stimulating technology development, and in this case we'd definitely see investment in solar and compact/safer nuclear of which MSRs are a part of.
xAI already brings gas turbines on-site, and i think the trend of on-site energy generation will grow, which will open opportunity (by providing well finaned demand) for compact/mobile/safer nuclear, and BigTech companies are among the best for any new tech development. I expect nuclear engineer positions get opened with Google and the likes :)
All of these things can be simultaneously true (and I would say, are true):
1) We are in a huge investment bubble right now and it's going to burst.
2) LLMs are extremely useful right now for certain niche tasks, especially software engineering.
3) LLMs have the potential to transform our world long-term (~10 yr horizon), on the order of the transformations wrought by the internet and mobile.
4) LLM's don't lead directly to AGI (no continuous learning), and we're not getting AGI any time soon.
This is an extremely obvious point, but bears repeating. I feel the assumption of an implicit link (in both truth or falsehood) between these fairly independent assertions can cause people to talk past each other about the really important questions in play here.
Regarding The Great Bubble, I am very very bearish about OpenAI in particular. They've had a good run for three years with consumer mindshare due to their first-mover advantage, but they have no moat, trouble monetizing most of their users, not much luck building out products that stick among consumers that aren't chatbots, and their models are no better than Anthropic's, Google's, or even the best Chinese open weight models 6 months later.
My bet would be on Google and Apple together (with Gemini powering Siri, for now) destroying OpenAI in the consumer AI market over the next 2-3 years. Google has first-rate models... but more than that, both Google and Apple have the enormous advantage of owning underlying platforms that they can use to put their own AI chat in front of consumers. Google has a mobile OS, the leading browser, and search. Apple has the premium hardware and the other, premium, mobile OS. They also have the advantage of the current regulatory climate being less antitrust than it was. And they don't have to monetize their AI offerings (no ads in gemini; ChatGPT is adding them) and can run them at a loss for as long as it takes to eat up OpenAI's market share. If they partner up, as they seem to be doing, OpenAI should very very afraid.
At ~$100B in AI funding, the question isn’t capital—it’s physical constraints.
Data centers need power (H100s are ~700W each), and recent capacity additions were mostly pre-allocated. Chip supply is also constrained by CoWoS packaging, not fab capacity, and expansions take years.
If power, packaging, and GPUs are fixed in the near term, does $100B mostly drive inflation in AI infrastructure prices rather than materially more deployed compute? Are we seeing the real cost of a usable GPU cluster rise faster than actual capacity?
Has anyone modeled what $100B actually buys in deployable compute over the next 2–3 years given these constraints—and whether that figure is shrinking as more capital piles in?
> as part of the startup’s [OpenAI's] efforts to raise up to $100 billion
At this stage, why not go public? Yes, they would need to manage quarterly financial reports and answer to shareholders, but they have reached a size where they are in the top 20 range on the NASDAQ. These public companies doing well, so it seems like a logical next step.
The reporting creates "transparency" - there are 1000s of analyst ready to pounce on this (with AI assistant). What skeletons would they find?
I think they are still crazy r&d heavy, which it's not what investors like to hear. Investor pressure would make them stagnate from r&d side
On the other hand they would probably set things up in a way where they still control all the voting power
Okay, but I don't think we can call OpenAI a startup until it has reached the number one spot on NASDAQ with a $5 trillion valuation. Therefore, I believe now is a good time to focus on more realistic fundamentals, rather than fueling the hype by burning even more cash on the way to the absolute top, which is typical bubble mentality.
I actually think the public markets have a lot less faith in openai than softbank does. They need these crazy investors. Public markets would not value openai at $1.4trn. So they can't go public. It would reveal how bad things are.
I used to hold this theory, but apparently Anthropic are planning to IPO, and surely both of them would be valued similarly?
Anthropic don't have all the free users, but they're also raising absurd amounts and have similar costs.
It can be also just a trade part of a deal; like in YC companies, where investor Y buys company A from investor Z, and in exchange investor Z buys company B from investor Y, so the choo-choo train keeps running.
I'm pretty sure I could become a billionaire just by meeting Masayoshi Son and having a chat for 15 minutes. I've never seen a better case for a fool and his money being parted.
That may be true, but in order to meet Masayoshi Son, you have to be a billionaire to begin with.
Is this pre or post hyperinflation 30 billion? As things might be heading there and that might make a difference.
I think it should be 70 billion, scratch that, 125 billion, scratch that - 180 trillion. I'd rather have pictures of crocodile Trump on the Moon than a warm house, scratch that, rather than kids, scratch that, rather than any decent future at all. Great move, guys, can't get enough of it.
So ... will the crash be bigger that the one causing The Great Depression or smaller? Any bets?
Not even close. The 2008 financial crisis is better comparison. And even then I think most negative effect will come from investors pulling money away from everything non-AI, than OpenAI/Anthropic/Oracle crashing and burning.
The Great Depression saw 25% unemployment and a third of farmers losing their land. Millions could die if it gets that bad today.
This sounds good to the "earth is overpopulated" crowd.
Before 2030, especially if the frontier AI labs begin to IPO before then.
I'm really eager to see how Anthropic's IPO this year (if it even happens) will pan out.
hahahah, have fun with that