The problem with AI is that, this time, nobody was caught off guard. From small startups to tech giants, everyone bet heavily on it. There are very good open-weight Chinese models, and even a French miracle. There is no winner-take-all.
So models are already a commodity, and will remain one for years. Companies must balance capex with very long payback periods against strict austerity everywhere else.
> From first principles I think youre right, but also Anthropic is making something like 80% margins.
I'm skeptical that they are operating at anything but a loss. 80% margins on a specific product (API) might still not cover the losses on the other products (Free tier, subscriptions) and their expenses (operating costs, training, research, etc).
Welp that’s not a good sign for the anthropic IPO. Curious what happens now that both OpenAI and Anthropic will face budgetary pressure. I don’t think they can raise prices, as it’d just open ppl to switch to Open source models.
It demonstrates why Anthropic has to IPO ASAP. Private investors are beginning to tap out. Anthropic is selling junior debt over 10% where it was about 8.5% last offer. If Anthropic wants to meet its compute purchase obligations (via actual business), it needs to start tapping public markets ASAP as its position is getting weaker. The size of the float and how much is primary vs secondary sale is the data we're missing right now. If the float is small and from secondary sales, the IPO is an exit and investors would be wise to stay away as Anthropic's runway stays where it is and therefore would require a re-acceleration of revenue growth to survive. If it is large and mostly from primary sales, it is a legit fund raise which extends the runway and revenue growth can be allowed to slow because of the pricing pressure you mentioned.
The work going on to improve things on single card like a 3090 is nuts. HyperQwen, other things. I have my subscriptions, but always good to explore options.
You have to understand that Strata and HyperQwen are giving you good looking tokens per second but are not giving you anything close to the bf16 model’s capability (they quantize, worse they quantize KV caches, they approximate expert routing etc.)
The models are so impressive that getting 70-80% of their capability can be helpful, but beware, you are using a significantly dumber model.
I have subscriptions for necessary work and even pay for api calls.
The machine with the 3090 I built years ago and suddenly it’s worth 4x plus what I paid. It is for testing, but I use the model I run on it and the model I run on an mbp M1 Max with 64gig as workers for specifically scoped work.
I’d love to have a few dgx sparcs or the like to do heavy local stuff, but that money is best paying the pimps for now.
Sure, but, in absence of money, where are the open models going to come from? They take a lot of effort and resources to train. The current ones have been made in hope the growth will lead to a payoff one way or another. With the two main giants struggling and the market cooling, that payoff becomes quite uncertain.
could be stone soup. a bunch of companies pitch in to train an open-weight model, a consortium or something. I think we need a return to something like the GPL for it to work, though. otherwise companies will take a good model and post-train it without contributing.
Selling the same product. It doesn't matter who is running the neural network, the utility derived from the neural network has nothing to do with the name of the company.
No, they sell different products in the same category. You are basically saying Google and Bing as the same product when Bing is superior to Google search in some non-critical metrics.
> No, they sell different products in the same category. You are basically saying Google and Bing as the same product when Bing is superior to Google search in some non-critical metrics.
In this case, it's pretty much the same product.
I mean, if you were to purchase electricity from two different providers (1x Nuclear plant and 1x Coal plant), would you actually care which one is being used to run your dishwasher on any given day?
Because they are? Google and Bing are the same product - search engines. Just like Ford and Ferrari both sell cars, whether you think one is "better" or not.
it’s kinda crazy but i do think we’re seeing a turn
my company was easily spending $1m/month on tokens
sonnet 5.5 drops - we barely cracked half this month
it has to go down too, carbon is interesting, china has qwen 4 soon
coding isn’t sustainable growth - RLRVF is really effective for software development - labs are cracking the code, these models will have to get better at other things to be worth it
How does this affect OpenAI's prospects in the next few quarters?
Unlike Anthropic, OAI does not have an S-1 to pore over. Their finances are shrouded in rumor and speculation. I can't assess how much of a death knell a ~15B financing shortfall is.
Nobody on the outside knows for sure, but two key signals to watch are project sunsets and brain drain.
If the rumors of fundraising difficulties are true, OAI will have to prioritize its most profitable projects, potentially slowing down new training runs and optimizing existing models for efficiency at the expense of user experience.
Insiders are also the first to sense internal trouble, so if top talent starts leaving for competitors preparing to go public, it won't bode well for the company.
The amount itself is probably meaningless. The fact that there was a shortfall at all is, for me, the signal.
Not too long ago, people were fighting to throw money at them. That might be the sign that we're past the peak of inflated expectations and going down towards the through of disillusionment .
> The amount itself is probably meaningless. The fact that there was a shortfall at all is, for me, the signal.
It is a signal, but I am not sure what it is signalling...
It could be signalling that all surplus money has been consumed already (i.e. the investment class has no more money left to invest).
It could signal that the specific class of investment is no longer desirable (i.e. the investment money is there, but has no appetite for token-providers).
It could mean that OpenAI, specifically, is considered not worth committing to anymore.
We should be looking at how the entire class of token providers is doing; if the rest are still getting interest from investors but OAI is not, then it's just OAI that is in trouble. If the entire class is not getting the money they are asking for, then maybe the peak of the bubble is reached (or the surplus money is all invested).
If this is being announced here, it was probably started at least a few months ago, and at that point funding was likely looking a lot more forthcoming, so it would make sense to try to raise more than is strictly necessary if the price is good. On that basis, it might not be a problematic shortfall.
If an open source model locally does one job correctly, lets say writing the code, then what really do we need OpenAI and Claude for? But I guess there might be some time in that.
That’s why the Mac mini and studio are selling like hotcakes. Massive unified memory with massive cpu performance, with a solid hardware. If I had 3-4K burning a hole in my pocket I know what I’d be getting.
What depreciation? I bought a DGX Spark a month ago for Qwen Flash Next (excellent model, by the way - using it basically exclusively at this point). The hardware has gone up in value 55% since I bought it. I just wish I had bought two of them.
> Why do I sense a schadenfreude here? It's like people are rooting for their failure.
You sound surprised. Why?
After all, they have been selling their product on the basis of driving the value of human labour as close to zero as possible (your labour included). Why wouldn't people want such an endeavour to fail?
Among other reasons, because it's been evident that the numbers won't add up from the beginning. It's always delicious when reality catches on a major scam.
Guess they'll just have to tighten the belt and follow through on their promise to revolutionize work, capitalism, government, and everything by building AGI. Lol. Lmao.
It's frightening to me that single companies' valuations can vary by that much. The stock exchange is the Adam Smith way of directing the assignation of resources to the most efficient company, and it's supposed to be liquid enough to allow fine-grained decisions.
> The directors with of such [joint-stock] companies, however, being the managers rather of other people's money than of their own, it cannot well be expected, that they should watch over it with the same anxious vigilance with which the partners in a private copartnery frequently watch over their own.... Negligence and profusion, therefore, must always prevail, more or less, in the management of the affairs of such a company.
This Adam Smith?
Adam Smith was against Joint Stock Companies (aka: the predecessor to the modern company). Specifically, he believed that shareholders will never watch over the money with the same care as a merchant who watches his own money.
> The stock exchange is the Adam Smith way of directing the assignation of resources to the most efficient company, and it's supposed to be liquid enough to allow fine-grained decisions.
So? OAI isn't on any stock exchange right now. Their value is not determined purely by supply and demand.
MSFT isn't laying off 60k people. It's offering voluntary severance, which will have a sub-10% take-up (for reference at GOOG it was low single digits).
I think Microsoft laying off 60,000 people was going to happen regardless of this AI boom or even the economy being in the absolute shitter it's in right now.
When the economy was much stronger in 2018 their headcount was around 131,000 people. By 2020 that jumped to 163,000, and by 2022 it reached 221,000. I have personally heard of employees feeling like they had nothing to do.
With their current head count at around 218,000 employees (I'm excluding their Activision head count here), bringing things back down to 160,000 or so employees sounds a bit more realistic, especially given that Microsoft has not been expanding its range of products significantly. They're building out more in the spaces they're in, but they've been pretty conservative on new product launches compared to others.
Maybe at first, but server hardware doesn't stay deployed tooo long and ends up liquidated. That was always a looming problem with this rapid buildout. Some hosts like OVH or Hetzner might swipe up some second hand gear, they're not afraid of renting old hardware. But eBay will be flooded once the DCs upgrade / downscale. And it wont be cheap at first either I bet. Everyone will try to cash in on the secondary market hype.
> No no no, don’t burst that AI bubble just yet. I haven’t finished all my side-projects.
You'll be fine; the GPUs will be sold off for pennies on the dollar, and if you can't run one at home there are plenty of people who will buy them to host for cost of hosting +5% markup.
Inference will keep getting cheaper and cheaper though. Perhaps model releases will be fewer and farther between because these groups can't affording paying out a billion or more in training each generation
Yeah, but Wright's law (cost of making the n^th something (like a token) being exponentially less than the cost of making the first) strongly suggests that post-bubble inference will be significantly cheaper the longer the bubble lasts.
Whether that's a good thing considering the other things those dollars could be going towards...
I mean I'm happy for better but it might start grounding the industry where 1.6% better on some benchmarks doesn't justify hundred million investments.
Over last 3 years on HN I have seen such low quality comments : prophesizing the end of times - the bubble will burst and we will all be so happy after that.
Any tiny news article that indicates even a modicum of challenges for OpenAI will be met with slurry of such comments.
Perhaps it’s good to keep a good epistemic hygiene in all this. OpenAI isn’t going away anywhere soon. AI isn’t going away, in fact we haven’t even started yet.
It's a reaction to the constant drum beat of doom marketing:
- "our product is too dangerous to release but we can't be bothered to prove its capabilities working in public hacking competitions"
- "our product is going to kill everyone"
- "our product is going to take all the jobs"
- "we have a $40T addressable market"
- "in a few days AI will be able to improve itself without human intervention and it's capabilities will hocky stick to infinity!!!"
Followed by absurd financials that spin massive losses as "getting in on the ground floor" before historic profits arrive based on the doom marketing above.
No one is saying AI is going away soon). But OpenAI and Anthro will go the way of Netscape when the market finally stops blindly accepting the doom marketing. Anyone with eyes can see LLMs will create historic increase in productivity among knowledge workers AND it will be a commodity. The massive profits frontier labs need to justify valuations are not coming.
There are AI bears and AI bulls. It's easy to cherry pick extreme and clearly wrong statements from each. But if you actually believe the bears are the more extreme/wrong overall you just aren't paying attention to what the bulls are saying.
You have conflated two completely unrelated concepts. LLMs aren't going anywhere, but what good does that do a company burning hundreds of billions to do 20% better than Chinese models trained with millions? The economics don't economic.
It's far too late for a prescription now because they're already committed to hundreds of billions in spending they don't have, but the reason Chinese companies will win the long game is because they are serious and the Americans are deeply unserious. From the beginning, Chinese labs have viewed LLMs as software tools and developed efficiently. Conversely, Americans are selling a fantasy about creating the machine god if they just throw another hundred billion at it every few months. Altman, Amodei, and Musk are all pathological liars who have oriented their entire companies around deceiving investors and marketing hype rather than engineering principles. They are unbelievably successful at what they set out to do, but what they set out to do was not to build a long-lasting foundation for success.
They successfully turned the entire tech sector into a giant pyramid scheme. That's one hell of an accomplishment. I hope history forever remembers the names of everyone who aided and abetted them.
There's no should, only what economics incentivize. Right now we're not paying for the upfront training costs-it's great, the Millennial subsidy continues. But if, and big if right now, the infinite money font dries up and they have to recoup training investment direct from customers then that looks to be a huge price increase on the ground which makes cheap to train and good enough even more attractive than it already is.
Can also be read as observation, as I have observed that many colleagues haven't started yet using AI on a daily basis and I myself is still using methods from months ago (no agent orchestration).
Sure, but both can be true. The internet bubble bursting did not kill the internet. All that investment in severs and fibre was still there, and still got used. A lot of investors lost their shirts, but the Internet future still happened.
OpenAI going bust would not cause those data centres to cease to exist, they’d still be there just owned for cheap by someone else that can run them at cost.
A crash would drastically cut investment and research funding, but research would still happen. New companies would rise from the ashes of the old. It might still trigger a recession though.
> OpenAI going bust would not cause those data centres to cease to exist, they’d still be there just owned for cheap by someone else that can run them at cost.
Someone would have to see value in that. Right now the value prop of AI is that maybe someday it'll get better and we'll be able to build useful, profitable consumer products on it. That's not really a great investment thesis, unless you're drunk on the hype.
Now that the market is sobering up a bit, will operating a "cheap" GPU datacenter at cost be worth anything? Not "future value", but present value. Can you turn a healthy profit running a GPU datacenter today? I doubt it.
At this point AI company valuations only make sense if each of them captures most of the value of the entire IT sector. Soon. If that doesn’t happen, it’s a matter of time before reality catches up, but how much time? Who knows. It could be years still.
Or AI could in the next few years generate more value than the whole IT sector a few times over. That would be cool.
I’m not touching any of that stock, most likely ever.
There’s so much money that has been poured into this, with absolutely no revenue to justify it. Trillions of investments generating billions of losses.
Now they’re looking for retail and retirement funds to pay off the debt.
This is not to say that no one will make a profit; I’m sure some people are _very_ happy.
This is really fascinating, I'm thinking of putting a significant chunk of my net worth into the four AI labs (maybe 40/30/20/10% across Anthropic/OpenAI/Google/Meta, alongside another large investment across the chip supply chain).
It seems obvious to me that we will get superintelligence in the next 5 years, and that is a winner take all race. Who knows to whatever extent money will matter after this.
There is nothing to indicate that they will achieve general intelligence. Their models have stagnated and are incapable of continuous learning, so the architecture is a dead end.
The mistake is assuming that science is linear. You could give me a trillion dollars, there’s still no guarantee I’ll invent cold fusion. You can’t predict or guarantee inventions.
I don’t believe in betting on single companies but I’d be more inclined to bet on Amazon and Google. Most AI deployments go through bedrock, and Google has their own cloud business and other businesses to make money. That means they can win regardless of who develops the next cool model.
So models are already a commodity, and will remain one for years. Companies must balance capex with very long payback periods against strict austerity everywhere else.
Good news for customers, BTW.
All the more reasons for us to figure out how to keep getting open models, or we are subject to the will of the the few frontier labs.
I'm skeptical that they are operating at anything but a loss. 80% margins on a specific product (API) might still not cover the losses on the other products (Free tier, subscriptions) and their expenses (operating costs, training, research, etc).
The models are so impressive that getting 70-80% of their capability can be helpful, but beware, you are using a significantly dumber model.
The machine with the 3090 I built years ago and suddenly it’s worth 4x plus what I paid. It is for testing, but I use the model I run on it and the model I run on an mbp M1 Max with 64gig as workers for specifically scoped work.
I’d love to have a few dgx sparcs or the like to do heavy local stuff, but that money is best paying the pimps for now.
In this case, it's pretty much the same product.
I mean, if you were to purchase electricity from two different providers (1x Nuclear plant and 1x Coal plant), would you actually care which one is being used to run your dishwasher on any given day?
Those two are very different cults. Cultures, I mean.
My only request is to keep Opus 5.5 alive
my company was easily spending $1m/month on tokens
sonnet 5.5 drops - we barely cracked half this month
it has to go down too, carbon is interesting, china has qwen 4 soon
coding isn’t sustainable growth - RLRVF is really effective for software development - labs are cracking the code, these models will have to get better at other things to be worth it
It’s not clear whether people are being more careful, or if the price per effort is in free fall.
Unlike Anthropic, OAI does not have an S-1 to pore over. Their finances are shrouded in rumor and speculation. I can't assess how much of a death knell a ~15B financing shortfall is.
If the rumors of fundraising difficulties are true, OAI will have to prioritize its most profitable projects, potentially slowing down new training runs and optimizing existing models for efficiency at the expense of user experience.
Insiders are also the first to sense internal trouble, so if top talent starts leaving for competitors preparing to go public, it won't bode well for the company.
Not too long ago, people were fighting to throw money at them. That might be the sign that we're past the peak of inflated expectations and going down towards the through of disillusionment .
It is a signal, but I am not sure what it is signalling...
It could be signalling that all surplus money has been consumed already (i.e. the investment class has no more money left to invest).
It could signal that the specific class of investment is no longer desirable (i.e. the investment money is there, but has no appetite for token-providers).
It could mean that OpenAI, specifically, is considered not worth committing to anymore.
We should be looking at how the entire class of token providers is doing; if the rest are still getting interest from investors but OAI is not, then it's just OAI that is in trouble. If the entire class is not getting the money they are asking for, then maybe the peak of the bubble is reached (or the surplus money is all invested).
You sound surprised. Why?
After all, they have been selling their product on the basis of driving the value of human labour as close to zero as possible (your labour included). Why wouldn't people want such an endeavour to fail?
> The ChatGPT maker’s latest funding round values it at $1.25 trillion, less than its $1.4 trillion target
Number go down, or even not go up as much as expected, is not good. These valuations are entirely matters of confidence. When that goes away…
I always kind of suspected that those are somehow derived numbers, but arbitrary for the most part.
The implication is they had to sell more of the company for cheaper than they wanted if they only hit 1.25 instead of 1.4.
This Adam Smith?
Adam Smith was against Joint Stock Companies (aka: the predecessor to the modern company). Specifically, he believed that shareholders will never watch over the money with the same care as a merchant who watches his own money.
So? OAI isn't on any stock exchange right now. Their value is not determined purely by supply and demand.
If you have a billion users and 90% + are freeloaders, you need social media style ads to support growth, which no one likes.
Plus they are all out of data training sets, they are buying zombie companies for their data.
There are dozens of distillated clones, which are getting better every release.
The only moat is expensive data centre builds with on-loan Nvidia inference and the Chinese embargo fears.
Good luck out there.
When the economy was much stronger in 2018 their headcount was around 131,000 people. By 2020 that jumped to 163,000, and by 2022 it reached 221,000. I have personally heard of employees feeling like they had nothing to do.
With their current head count at around 218,000 employees (I'm excluding their Activision head count here), bringing things back down to 160,000 or so employees sounds a bit more realistic, especially given that Microsoft has not been expanding its range of products significantly. They're building out more in the spaces they're in, but they've been pretty conservative on new product launches compared to others.
You'll be fine; the GPUs will be sold off for pennies on the dollar, and if you can't run one at home there are plenty of people who will buy them to host for cost of hosting +5% markup.
Suppose OpenAI goes bust tomorrow and all those data centres get sold for pennies on the dollar. Whoever buys them can operate them at cost.
Whether that's a good thing considering the other things those dollars could be going towards...
If you're talking about free tiers, yes, that might change as marketing budgets will shrivel up.
Any tiny news article that indicates even a modicum of challenges for OpenAI will be met with slurry of such comments.
Perhaps it’s good to keep a good epistemic hygiene in all this. OpenAI isn’t going away anywhere soon. AI isn’t going away, in fact we haven’t even started yet.
- "our product is too dangerous to release but we can't be bothered to prove its capabilities working in public hacking competitions" - "our product is going to kill everyone" - "our product is going to take all the jobs" - "we have a $40T addressable market" - "in a few days AI will be able to improve itself without human intervention and it's capabilities will hocky stick to infinity!!!"
Followed by absurd financials that spin massive losses as "getting in on the ground floor" before historic profits arrive based on the doom marketing above.
No one is saying AI is going away soon). But OpenAI and Anthro will go the way of Netscape when the market finally stops blindly accepting the doom marketing. Anyone with eyes can see LLMs will create historic increase in productivity among knowledge workers AND it will be a commodity. The massive profits frontier labs need to justify valuations are not coming.
There are AI bears and AI bulls. It's easy to cherry pick extreme and clearly wrong statements from each. But if you actually believe the bears are the more extreme/wrong overall you just aren't paying attention to what the bulls are saying.
You have conflated two completely unrelated concepts. LLMs aren't going anywhere, but what good does that do a company burning hundreds of billions to do 20% better than Chinese models trained with millions? The economics don't economic.
What is your prescription if I may ask? Don’t invest in research? Let China do it?
OpenAI going bust would not cause those data centres to cease to exist, they’d still be there just owned for cheap by someone else that can run them at cost.
A crash would drastically cut investment and research funding, but research would still happen. New companies would rise from the ashes of the old. It might still trigger a recession though.
Someone would have to see value in that. Right now the value prop of AI is that maybe someday it'll get better and we'll be able to build useful, profitable consumer products on it. That's not really a great investment thesis, unless you're drunk on the hype.
Now that the market is sobering up a bit, will operating a "cheap" GPU datacenter at cost be worth anything? Not "future value", but present value. Can you turn a healthy profit running a GPU datacenter today? I doubt it.
2. Claude Code limits tightened. A commenter expects the bubble to pop, while arguing AI will succeed long term. https://news.ycombinator.com/item?id=44599297
3. GPT-5 disappoints. "Teetering on the edge of a huge bubble pop." https://news.ycombinator.com/item?id=44966583
4. DeepSeek releases a cheaper model. A commenter expects excess data-centre capacity when the bubble bursts. https://news.ycombinator.com/item?id=45413548
5. AMD signs an OpenAI chip deal. A commenter predicts a bubble pop and a flood of cheap GPUs. https://news.ycombinator.com/item?id=45491514
6. Discussion of AI-assisted open-source contributions. A commenter says models must improve soon or the bubble will pop. https://news.ycombinator.com/item?id=45745326
7. Discussion of Opus 4.5 coding. A commenter advises using cheap AI tools before the bubble bursts. https://news.ycombinator.com/item?id=46521192
8. GitHub Copilot moves to usage-based billing. "The bubble has burst." https://news.ycombinator.com/item?id=47929404
9. DeepSeek runs on one AMD accelerator. A commenter predicts a bubble pop will flood the hardware market. https://news.ycombinator.com/item?id=49166790
10. Same DeepSeek thread. "AI is overvalued, so it WILL pop." https://news.ycombinator.com/item?id=49167787
Edit: more examples
1. AI on an old CPU: coding gains don’t justify investment; bubble will burst. https://news.ycombinator.com/item?id=48938412
2. Nvidia–OpenAI deal stalls: GPU bubble, inflated demand. https://news.ycombinator.com/item?id=46834749
3. Lisp machines retrospective: AI bankruptcies and another bubble. https://news.ycombinator.com/item?id=45990309
4. Nvidia customer concentration: AI bubble will pop despite useful technology. https://news.ycombinator.com/item?id=41411258
5. DeepSeek open-source announcement: inflated AI valuations will collapse. https://news.ycombinator.com/item?id=43126535 https://news.ycombinator.com/item?id=43126619
6. OpenAI–AWS deal: spending commitments could bring everything crashing down. https://news.ycombinator.com/item?id=45802550
7. Anthropic funding: final big push before the bubble bursts. https://news.ycombinator.com/item?id=45105333
8. Enterprise AI adoption: disappointing returns will pop the bubble within two years. https://news.ycombinator.com/item?id=48025025
9. OpenAI cash burn: railroad-style bubble and massive investment downturn. https://news.ycombinator.com/item?id=46439964
Or AI could in the next few years generate more value than the whole IT sector a few times over. That would be cool.
as a litmus test: would you turn down the opportunity to buy OpenAI shares at this current valuation?
There’s so much money that has been poured into this, with absolutely no revenue to justify it. Trillions of investments generating billions of losses.
Now they’re looking for retail and retirement funds to pay off the debt.
This is not to say that no one will make a profit; I’m sure some people are _very_ happy.
It seems obvious to me that we will get superintelligence in the next 5 years, and that is a winner take all race. Who knows to whatever extent money will matter after this.
The mistake is assuming that science is linear. You could give me a trillion dollars, there’s still no guarantee I’ll invent cold fusion. You can’t predict or guarantee inventions.
I don’t believe in betting on single companies but I’d be more inclined to bet on Amazon and Google. Most AI deployments go through bedrock, and Google has their own cloud business and other businesses to make money. That means they can win regardless of who develops the next cool model.