I think it would be healthy for everyone if the hype around this stuff would die down a bit. There's too much pressure to invest in hardware and too much uncertainty around the business case. I am excited to see what can be built but I hope a bunch of people don't have to get wiped out financially along the way.
You would think the effect was the opposite. I think this is worse for OpenAI.
So far, the circular financing from Nvidia has been peanuts for the company. It's roughly equal to giving 5% discount on hardware, not a big deal when the profit margin is 70%. Trying to prop up new neoclouds and competition is a good idea.
As I understand it, the OpenAI investment was much bigger effective discount but still safe because Nvidia invests gradually in installments only when OpenAI invests in data centers: tit for tat. Maybe OpenAI wanted to get the money now and invest it later, as they seem to be running out of cash.
> You would think the effect was the opposite. I think this is worse for OpenAI.
How do we know it wasn't? OpenAI isn't a publicly traded company, and I guess no one who dares writing anything here actually knows how the numbers look on the inside, so for what we know, it could very well have been worse for OpenAI than Nvidia.
You can make a good guess, though - OpenAI had a significant lead, its moat was being a generation or 2 ahead of the competition, and as of the end of 2025, OpenAI, Google, xAI, and Anthropic are pretty much neck and neck. Grok and Gemini are likely to be the top 2 within the next couple months, and the Chinese open models are hot on their heels.
OpenAI is going to be competing for third or fourth place with Anthropic unless one of them pulls off a big capabilities or efficiency leap while remaining believably as good as the other top models. Google and xAI have advantages that the others don't, and are capitalizing on them like crazy. It remains to be seen whether xAI can compete with the Google hardware advantage, but they have economies of scale, differences in mission, and Elon's billions on their side, so it's turning out to be a very interesting race.
Sama could also finagle a funding rabbit or strategic partnership out of his hat and also have the next top tier model, amazing everyone again and keeping a plausible "best in class" lead for a while; OpenAI would have to be down for at least a year before I counted it out completely. It's not looking very pretty for them right now, though.
No one believes Grok will be top 2 in a couple months. OpenAI and Gemini, in one of the two orderings, will continue to be far ahead of Grok in "the next couple of months". I encourage you to bookmark your claim here and return in 2 months to take stock in your ability to predict/bluff.
How do you know which two models are 'top 2' and how do you expect the parent commenter to know which are top 2 when he comes back to this comment and verify his prediction?
Even if OpenAI gets “better” than Google, it’s still a sharecropper on other people’s infrastructure and depending on more expensive Nvidia chips while Google has a real business that throws off 10s of billions a year in profit, it’s own infrastructure, its own TPUs, and actual customers with both search and related and GCP.
The open source models are showcasing a lot of cool research ideas that will undoubtedly end up in future frontier models from OpenAI and others. We're at a point where the big proprietary AI firms barely do any foundational research anymore, they're purely about incremental improvement. All the proven substantial progress recently has been coming from the open models side.
What I don't understand is why Gemini is not #1, other than that Google has no economic reason to have the same fire under its ass to be #1 as Anthropic and OpenAI. Or maybe they are correctly assessing that getting to good enough and out-building infrastructure is more valuable; they do have their TPUs as bets on their future and their search monopoly today to print nearly endless free cash flow. Perhaps Gemini is advancing at exactly the right rate for them.
I guess there is one thing that Gemini is objectively better at than either, which is long context, and it does seem to be by an order of magnitude. What boggles my mind is why Gemini is still not as good as the open weight frontier models yet. If they got just to parity with that along with their existing long context and strong token pricing, they'd be able to take over the coding market. Are they just biding their time to make their move? Hard to discern.
My best guess is that Nvidia is unhappy with how OpenAI is fishing for compute with its competitors (Jensen had some opinions on the AMD-OpenAI deal when it was announced). If this actually becomes a feasible reality, it gives OpenAI (and co) negotiating power - which is bad for Nvidia
Nvidia might have wanted more exclusivity/attachment. And OpenAI still seems to have no problem raising money. So maybe there was just a commitment mismatch
>It's roughly equal to giving 5% discount on hardware, not a big deal when the profit margin is 70%.
using your numbers, Nvidia didn't drop 70%, it's more on the order of the 5% so at least from that angle, the news narrative holds together superficially.
the hit to microsoft the other day was pretty interesting
I saw reports attributing it to a miss on earnings from Azure but they were off by 0.4% on 39% growth. That's 39% instead of 39.4%. And the company stock dropped 10%. This is all of Microsoft - 10% down (!).
It has to tell you there are a LOT of people primed to sell in a hurry on bad news. The "bubble" talk subsided a lot after nVidia smashed earnings last quarter, but largely overlooked how much their whole situation is based on pent up demand. It completely masks the fundamentals.
I still feel like we're sitting on a volcano and seeing puffs of smoke and feeling earth tremors.
I thought this was already revised? Jensen Huang said they’ll be investing more than ever:
> Nvidia is likely set to make its “largest ever investment” in ChatGPT firm OpenAI, despite reports that the deal may be under threat in recent weeks. The chip giant’s CEO, Jensen Huang, didn’t say exactly how big the investment would be, but said it would be “nothing like” the $100 billion figure mentioned in the September partnership agreement.
Microslop CEO begging for AI $$$ because astronomical overprovisioning is becoming obvious, all big spenders frantically trying to hide CapEx from their books and hallucinate revenue projections like its Enron reloaded and Oracle is already getting sued by bondholders over AI spend [0].
To me CoreWeave is the one to watch. They have to actually bring all these promised datacenters online, operational, and profitable. They basically got a $2B bailout from Nividia a week or so ago but they're back to sinking.
Consumer can eat all the GPUs they have and more if we stop trying to force B2B
Right we have a loop where AI is so expensive (because it's priced to feast on B2B margins) that the best consumer experiences aren't affordable, and they're not affordable so they don't go mainstream, and they're not mainstream so no one is willing to take less money and bank on the incredible volume that would emerge if it went mainstream.
If we can get model pricing cheaper AI entertainment alone will probably carry things (I'm 99% sure NovelAI is already one of their largest customers outside of major AI labs)
Even if consumer can eat all the gpus, it cannot have the margins (as you say), and thus won’t sustain the current valuations all these companies have and which fuel the (necessary) investments.
> Consumer can eat all the GPUs they have and more if we stop trying to force B2B
You should really crunch the numbers on buying and then running enough compute to run a leading edge model. The economics of buying it (never mind running it) just dont add up.
You still haven't factored in "training", the major problem right now that every one remains head in sand about.
I dont need a model to know who Tom Cruise is or how to write SQL if I am asking it "set up my amazon refund" or "cancel xyz service". The moment someone figures out how to build targeted and small it will take off.
And as for training, well having to make ongoing investment into re-training is what killed expert systems, it's what killed all past AI efforts. Just because it's much more "automated" doesn't mean it isnt the same "problem". Till a model learns (and can become a useful digital twin) the consumer market is going to remain "out of reach".
That doesn't mean we dont have an amazing tool at hand, because we do. But the way it's being sold is only going to lead to confusion and disappointment.
Literally all the cloud providers have been reporting severe capacity crunches for the past few quarters -- to the tune of backlogs of triple-digit billions each. As a reminder, a backlog or "Remaining Performance Obligation" (RPO) is money their customers have committed to them but they could not realize because they didn't have enough capacity to serve their workloads. Which is why they are all committing to double-digit billions each in AI CapEx spend over the next few quarters.
And most of them (aside from Oracle, which is trying to borrow its way into this gold rush) are investing money from their double digit billions in profit (per quarter!) into this spend... money that they could have otherwise comfortably held on to for something more palatable to share-holders.
Revenue and return on investment is a valid concern to bring up in this whole GenAI shebang; demand is not.
If you truly believe this, slowly divest everything into cash, wait for the crash, then buy back in. Even buying in slowly over the course of a crash, on the way down, will save you a ton of money if you're out before it hits.
But you're more likely to just cash out early, lose a bunch of gains, then buy back in later at higher prices.
If you can time the crash you can make a shitload of money. But you can't, so you'll come out better if you just keep buying in every paycheck and ride it out just like you have been.
It doesn't have to be 'ride it till it dies' or 'sell everything'. The AI bubble is almost exclusively contained to the US stock market and a few east Asian manufacturers.
You're right that selling everything and 'going to cash' would be a mistake, but diversifying away from US large cap growth absolutely wouldn't. I'm 60/40 stocks/bonds. My stocks and bonds are 50/50 us/intl. ~ 10% of my us portfolio is small cap value.
What's funny to me is that nobody learns from the past. This is far from the first tech bubble we've had even before the .com crash (canals, railroads, radio...). The answer, every time was diversification.
The east Asian semiconductor manufacturers are selling shovels in the gold rush and being very cautious about expansion given how capital-intensive the whole sector is. It's hard to come up with a scenario where they outright lose, even with the bubble popping.
I mean there's also a cost to not expanding too, in that you're leaving money on the table. I doubt they've really been able to resist the siren call of basically being able to print more money, but if the AI bubble collapses and they're left selling most of their production to consumers, they're gonna have a lot of stranded capital. Here's hoping they're smart enough to build a big war chest to weather the storm, but in my experience, companies rarely do.
Invest into stuff that people will need regardless of the bubble popping like medicine, food, internet access, energy, ... . Stay away from luxury/travel stuff.
Also, during a crash there is the so called "flight for quality" where people cash out from risky assets and invest in stable ones that can weather the storm. So, try to invest in assets that are A or above (https://en.wikipedia.org/wiki/S%26P_Global_Ratings). The chart is for countries, but analysts grade companies as well in case you want to stay away from treasuries/national bonds.
Also diversify geographically. US will likely take the biggest hit if the bubble pops, so perhaps European markets that lagged behind in adopting the technology are safer (IMHO).
Personally, I am preparing by moving money from growth items to stable ones a bit at the time. To diversify even further I am using ETFs that, in addition to what mentioned above
1) pay dividends (whether these distributed or reinvested doesn't really matter)
2) are denominated in or hedged in safer currencies (CHF especially, but also Euro)
You definitely get smaller returns, but the name of the game is to maintain what you have, not to make heaps of money.
Finally, I am not a financial advisor, so do your own valuations/risk assessment analysis.
Primarily the fault of our governments not using anti-trust laws for real in, like, decades.
Governments actually do have the power to regulate the economy and to prevent catastrophic crashes from occurring. The warning signs for the AI bubble have been visible for well over a year now, when the entity relationship map between the major players began to resemble a Habsburg family tree... and yet, nothing was done.
It isnt God - Sam went a little overboard with his pushing that.
AI still isnt just hype tho and remains the greatest digital tool ever made by people.
The reality remains that if you adopt AI into your workforce, not replace your workforce with AI, use AI to help with your work - you can do a lot more and faster too.
I just downloaded deepseek on my Win 11 PC - Copilot is obviously more integrated but its not that bad at all. Copilot is very limited in the boxes Microsoft built into it but it is a great tool for average people that only need to interact with AI occasionally to search the internet.
1. Clueless: AI is the future, grant it access to everything and let it do everything, from management to execution.
These engineers will be unemployed and companies go bankrupt. This is the majority of the market right now, look what is happening to them from companies to the products themselves.
2. Smart: AI is a tool to improve my work so I can spend less time doing the boring stuff and more time learning and doing cool stuff.
This is the minority and the only companies thriving right now.
So far, the circular financing from Nvidia has been peanuts for the company. It's roughly equal to giving 5% discount on hardware, not a big deal when the profit margin is 70%. Trying to prop up new neoclouds and competition is a good idea.
As I understand it, the OpenAI investment was much bigger effective discount but still safe because Nvidia invests gradually in installments only when OpenAI invests in data centers: tit for tat. Maybe OpenAI wanted to get the money now and invest it later, as they seem to be running out of cash.
How do we know it wasn't? OpenAI isn't a publicly traded company, and I guess no one who dares writing anything here actually knows how the numbers look on the inside, so for what we know, it could very well have been worse for OpenAI than Nvidia.
OpenAI is going to be competing for third or fourth place with Anthropic unless one of them pulls off a big capabilities or efficiency leap while remaining believably as good as the other top models. Google and xAI have advantages that the others don't, and are capitalizing on them like crazy. It remains to be seen whether xAI can compete with the Google hardware advantage, but they have economies of scale, differences in mission, and Elon's billions on their side, so it's turning out to be a very interesting race.
Sama could also finagle a funding rabbit or strategic partnership out of his hat and also have the next top tier model, amazing everyone again and keeping a plausible "best in class" lead for a while; OpenAI would have to be down for at least a year before I counted it out completely. It's not looking very pretty for them right now, though.
Genuine question.
I guess there is one thing that Gemini is objectively better at than either, which is long context, and it does seem to be by an order of magnitude. What boggles my mind is why Gemini is still not as good as the open weight frontier models yet. If they got just to parity with that along with their existing long context and strong token pricing, they'd be able to take over the coding market. Are they just biding their time to make their move? Hard to discern.
Nvidia might have wanted more exclusivity/attachment. And OpenAI still seems to have no problem raising money. So maybe there was just a commitment mismatch
Pure speculation though
using your numbers, Nvidia didn't drop 70%, it's more on the order of the 5% so at least from that angle, the news narrative holds together superficially.
Enron thought the same thing. Until they had a closer look at what their middle managers were actually doing to the books.
I saw reports attributing it to a miss on earnings from Azure but they were off by 0.4% on 39% growth. That's 39% instead of 39.4%. And the company stock dropped 10%. This is all of Microsoft - 10% down (!).
It has to tell you there are a LOT of people primed to sell in a hurry on bad news. The "bubble" talk subsided a lot after nVidia smashed earnings last quarter, but largely overlooked how much their whole situation is based on pent up demand. It completely masks the fundamentals.
I still feel like we're sitting on a volcano and seeing puffs of smoke and feeling earth tremors.
https://medium.com/@Arakunrin/the-post-ipo-performance-of-y-...
Did Oracle spin off Cerner yet?
> Nvidia is likely set to make its “largest ever investment” in ChatGPT firm OpenAI, despite reports that the deal may be under threat in recent weeks. The chip giant’s CEO, Jensen Huang, didn’t say exactly how big the investment would be, but said it would be “nothing like” the $100 billion figure mentioned in the September partnership agreement.
https://www.pcmag.com/news/nvidia-ceo-well-make-our-largest-...
Microslop CEO begging for AI $$$ because astronomical overprovisioning is becoming obvious, all big spenders frantically trying to hide CapEx from their books and hallucinate revenue projections like its Enron reloaded and Oracle is already getting sued by bondholders over AI spend [0].
It will be worse than the dot com bust.
0: https://www.reuters.com/sustainability/boards-policy-regulat...
https://ts2.tech/en/coreweave-stock-slips-as-class-action-no...
Right we have a loop where AI is so expensive (because it's priced to feast on B2B margins) that the best consumer experiences aren't affordable, and they're not affordable so they don't go mainstream, and they're not mainstream so no one is willing to take less money and bank on the incredible volume that would emerge if it went mainstream.
If we can get model pricing cheaper AI entertainment alone will probably carry things (I'm 99% sure NovelAI is already one of their largest customers outside of major AI labs)
You should really crunch the numbers on buying and then running enough compute to run a leading edge model. The economics of buying it (never mind running it) just dont add up.
You still haven't factored in "training", the major problem right now that every one remains head in sand about.
I dont need a model to know who Tom Cruise is or how to write SQL if I am asking it "set up my amazon refund" or "cancel xyz service". The moment someone figures out how to build targeted and small it will take off.
And as for training, well having to make ongoing investment into re-training is what killed expert systems, it's what killed all past AI efforts. Just because it's much more "automated" doesn't mean it isnt the same "problem". Till a model learns (and can become a useful digital twin) the consumer market is going to remain "out of reach".
That doesn't mean we dont have an amazing tool at hand, because we do. But the way it's being sold is only going to lead to confusion and disappointment.
???
Literally all the cloud providers have been reporting severe capacity crunches for the past few quarters -- to the tune of backlogs of triple-digit billions each. As a reminder, a backlog or "Remaining Performance Obligation" (RPO) is money their customers have committed to them but they could not realize because they didn't have enough capacity to serve their workloads. Which is why they are all committing to double-digit billions each in AI CapEx spend over the next few quarters.
And most of them (aside from Oracle, which is trying to borrow its way into this gold rush) are investing money from their double digit billions in profit (per quarter!) into this spend... money that they could have otherwise comfortably held on to for something more palatable to share-holders.
Revenue and return on investment is a valid concern to bring up in this whole GenAI shebang; demand is not.
But you're more likely to just cash out early, lose a bunch of gains, then buy back in later at higher prices.
If you can time the crash you can make a shitload of money. But you can't, so you'll come out better if you just keep buying in every paycheck and ride it out just like you have been.
You're right that selling everything and 'going to cash' would be a mistake, but diversifying away from US large cap growth absolutely wouldn't. I'm 60/40 stocks/bonds. My stocks and bonds are 50/50 us/intl. ~ 10% of my us portfolio is small cap value.
What's funny to me is that nobody learns from the past. This is far from the first tech bubble we've had even before the .com crash (canals, railroads, radio...). The answer, every time was diversification.
Also, during a crash there is the so called "flight for quality" where people cash out from risky assets and invest in stable ones that can weather the storm. So, try to invest in assets that are A or above (https://en.wikipedia.org/wiki/S%26P_Global_Ratings). The chart is for countries, but analysts grade companies as well in case you want to stay away from treasuries/national bonds.
Also diversify geographically. US will likely take the biggest hit if the bubble pops, so perhaps European markets that lagged behind in adopting the technology are safer (IMHO).
Personally, I am preparing by moving money from growth items to stable ones a bit at the time. To diversify even further I am using ETFs that, in addition to what mentioned above
1) pay dividends (whether these distributed or reinvested doesn't really matter) 2) are denominated in or hedged in safer currencies (CHF especially, but also Euro)
You definitely get smaller returns, but the name of the game is to maintain what you have, not to make heaps of money.
Finally, I am not a financial advisor, so do your own valuations/risk assessment analysis.
https://www.investopedia.com/your-s-and-p-500-index-fund-mig...
https://www.cnbc.com/2025/10/22/your-portfolio-may-be-more-t...
And whose fault is that?
However, the consequences are always applied to everyone but the executives and board.
Primarily the fault of our governments not using anti-trust laws for real in, like, decades.
Governments actually do have the power to regulate the economy and to prevent catastrophic crashes from occurring. The warning signs for the AI bubble have been visible for well over a year now, when the entity relationship map between the major players began to resemble a Habsburg family tree... and yet, nothing was done.
AI still isnt just hype tho and remains the greatest digital tool ever made by people.
The reality remains that if you adopt AI into your workforce, not replace your workforce with AI, use AI to help with your work - you can do a lot more and faster too.
I just downloaded deepseek on my Win 11 PC - Copilot is obviously more integrated but its not that bad at all. Copilot is very limited in the boxes Microsoft built into it but it is a great tool for average people that only need to interact with AI occasionally to search the internet.
1. Clueless: AI is the future, grant it access to everything and let it do everything, from management to execution. These engineers will be unemployed and companies go bankrupt. This is the majority of the market right now, look what is happening to them from companies to the products themselves.
2. Smart: AI is a tool to improve my work so I can spend less time doing the boring stuff and more time learning and doing cool stuff. This is the minority and the only companies thriving right now.
(Something concrete)