It seems similar to how GE under Jack Welch would use their rock solid financials to take on low cost debt that they could lend out to suppliers who needed finance to purchase their products.

The biggest difference here though is that most of these moves seem to to involve direct investment and the movement of equity, not debt. I think this is an important distinction, because if things take a downturn debt is highly explosive (see GE during the GFC) whereas equity is not.

Not to say anyone wants to take a huge markdown on their equity, and there are real costs associated with designing, building, and powering GPUs which needs to be paid for, but Nvidia is also generating real revenue which likely covers that, I don't think they're funding much through debt? Tech tends to be very high margin so there's a lot of room to play if you're willing to just reduce your revenue (as opposed to taking on debt) in the short term.

Of course this means asset prices in the industry are going to get really tightly coupled, so if one starts to deflate it's likely that the market is going to wipe out a lot of value quickly and while there isn't an obvious debt bomb that will explode, I'm sure there's a landmine lying around somewhere...

Except I'm guessing they are not selling their equity, they are making debt backed by their equity?

Yea this is speculation, you might be right. I'm not sure how exactly they're doing this but my thinking would be.

1. Selling equity (probably good).

2. Financed with actual profits over time showing up as lower margins on the income statement (probably good).

3. Issuing debt backed by their equity (possibly a dumpster fire).

> Financed with actual profits over time showing up as lower margins on the income statement (probably good)

would these equity investments only impact the balance-sheet as financial investments - why would they show up as lower margins on income statement ?

GE also created their "rock-solid financials" by moving money around as necessary to make earnings projections.

> debt is highly explosive (see GE during the GFC) whereas equity is not.

Not as explosive as debt but I'd venture to say that nowadays equity is a lot more "inflamable" compared to 2008-2010, as in a lot more debt-like (which I think partly explains the current equity bubble in the US).

As in, there are lots and lots of investment funds/pension funds/other such like financial entities which are very heavily tied to the "performance" of equity, and I'm talking about trillions (at this point) of dollars, and if that equity were to get a, let's say, 20 or 30% hair-cut in a matter of two-three months (at most), then we'll for sure be back in October 2008 mode.

Totally agree, it might not blow up in Nvidia's face, but there's a margin call sitting around somewhere in the pile.

> As in, there are lots and lots of investment funds/pension funds/other such like financial entities which are very heavily tied to the "performance" of equity, and I'm talking about trillions (at this point) of dollars, and if that equity were to get a, let's say, 20 or 30% hair-cut in a matter of two-three months (at most), then we'll for sure be back in October 2008 mode.

Just curious, can you detail how it would fail exactly?

Anytime there's a massive draw down equities an asset-liability mismatch shows up (margin calls) because someone was borrowing money to spend in the short term against the value of assets that have now disappeared.

It might not be the catastrophic cascading failure of the GFC, but someone somewhere in the pile will get exposed.

Ah yes I see. It's the idea that somewhere, somehow, there is debt that's funding all of this, even if it's very indirect.

But real GPUs are being built, installed and used. It's not paper money, it's just buying goods and services partly with stock. Which is a very solid and time honored tradition which happens to align incentives very well.

What revenues do these GPUs generate for OpenAI? OpenAI is not currently profitable, and it is unclear if its business model will ever becomes profitable -- let alone profitable enough to justify this investment. Currently, this only works because the markets are willing to lend and let NVIDIA issue stock to cover the costs to manufacture the GPUs.

That's where the belief that we are in a bubble comes from.

OpenAI is profitable if they stop training their next generation models. Their unit economics are extremely favorable.

I do buy that they are extremely over-valued if they have to slow down on model training.

For cloud providers, the analysis is a bit more complex; presumably if training demand craters then the existing inference demand would be met at a lower price, and maybe you’d see some consolidation as margins got compressed.

> OpenAI is profitable if they stop training their next generation models. Their unit economics are extremely favorable.

But OpenAI can't stop training their next generation models. OpenAI already spends over 50% of their revenue on inference cost [1] with some vendors spending over 100% of their revenue on inference.

The real cash cow for them is in the business segment. The problem here is models are rapidly cloned, and the companies adjacent to model providers actively seek to provide consumers the ability to rapidly and seamlessly switch between model providers [2][3].

Model providers are in the situation you imagine cloud providers to be in; a non-differentiated, commodity product with high fixed costs, and poor margins.

[1] https://www.wheresyoured.at/why-everybody-is-losing-money-on...

[2] https://www.jetbrains.com/help/ai-assistant/use-custom-model...

[3] https://code.visualstudio.com/docs/copilot/customization/lan...

That's why we are seeing these insane numbers. The competition is "do or die" right now.

Zuckerberg said in an interview last week he doesn't mind spending $100B on AI, because not investing carries more risk.

This only applies if you think one of two things; First, that it is guaranteed that this specific line of inquiry will lead to development of a form of superintelligence or otherwise broadly applicable development; or second, the form of machine learning technologies that unlocks or otherwise enables a market which would otherwise be inaccsesible that justifies this investment.

To date, no evidence of either even exists. See Zuckerbergs recent live demo of Facebooks Ray Bans technology, for example.

I agree the market dynamics are weird now, I disagree that says much about the existence of other equilibria.

For example, inference on older GPUs is actually more profitable than bleeding-edge right now; the shops that are selling hosted inference have options to broaden their portfolio the advancement of the frontier slows.

Cloud providers are currently “un-differentiated”, but there are three huge ones making profits and some small ones too. Hosting is an economy-of-scale business and so is inference.

And all of these startups you quote like Cursor that are not free-cash-flow positive are simply playing the VC land grab game. Costs will rise for consumers if VCs stop funding, sure. That says nothing about how much TAM there is at the new higher price point.

The idea that OAI is un-differentiated is just weird. They have a massively popular consumer offering, a huge bankroll, and can continue to innovate on features. Their consumer offering has remained sticky even though Claude and Gemini have both had periods of being the best model to those in the know.

And generally speaking there are huge opportunities to do enterprise integrations and build out the retooling of $10T of economic activities, just with the models we have now; a Salesforce play would be a natural pivot for them.

> Cloud providers are currently “un-differentiated”, but there are three huge ones making profits and some small ones too. Hosting is an economy-of-scale business and so is inference.

Anybody who has worked in a compliance heavy segment (PCI-DSS, HIPAA, etc.) will tell you the big 3 clouds have very significant differences from the smaller players. The differentiation is not on compute itself, but on the product. It's partially why products like AWS Bedrock exist and are actively placing model providers both in competition with eachother and AWS itself which is exactly the market dynamic they should seek to avoid.

> The idea that OAI is un-differentiated is just weird. They have a massively popular consumer offering, a huge bankroll, and can continue to innovate on features. Their consumer offering has remained sticky even though Claude and Gemini have both had periods of being the best model to those in the know.

This is exactly where this line of reasoning goes off the rails. The consumer market is problematic (see the recent post about the segment its growing in; basically young women of limited spend in low income countries); a huge bankroll is also a huge liability, model providers are on a clock to get huge or die, and the innovation we are seeing is effectively attempting to "scale-up" models, not provide novel features.

> Their consumer offering has remained sticky even though Claude and Gemini have both had periods of being the best model to those in the know.

This isn't a good thing with current market mix.

> And generally speaking there are huge opportunities to do enterprise integrations and build out the retooling of $10T of economic activities, just with the models we have now; a Salesforce play would be a natural pivot for them.

Do you have any indication these are achieving buy in or profitable? Most significantly, we have seen a recent study by MIT that 95% of generative AI pilots fail. The honeymoon period is rapidly coming to a close. Tangible results are necessary.

OpenAI generates plenty of revenues from their services. Don't conflate revenues with profits

I don't believe I am. Investors (value investors, not pump and dump investors) provide capital to companies on the expectation of profit, not revenue.

Sure, and as long the expected profit keeps increasing investors are happy. They don't need to make an actual profit yet.

The counter point to this is that while not profitable, the cashflow is real, and inference is marginally ROI positive. If you can scale inference with more GPUs then eventually that marginal ROI grows large enough to cover the R&D and other expenses and you become profitable.

"Marginally ROI positive" works in a ZIRP environment. These are huge capital investments; they need to at least clear treasury return hurdles and importantly provide attractive returns.

I am fundamentally skeptical of "scaling inference". Margins are not defensible in the market segment OpenAI is in.

For some of these tech companies their valuations let them go to the market with their equity in way that is basically a ZIRP environment. In a way you could say this is a competitive advantage someone like Nvidia has at the moment and so they are trying to push that.

I'm also pretty skeptical, and could imagine this whole thing blowing up, but it's not like this a big grift that's going to end up like the GFC either.

I think it's possible we are in datacenter GPU overcapacity already, and NVIDIA is burning its stock to avoid the music stopping.

It's already happening in China that datacenters are at GPU overcapacity. I wouldn't be surprised if it occurs here.

Wow, diluting stock during a bull run is incredibly short-sighted. NVIDIA is betting there will never be a downturn. If there is, the dilution causes late investors to either be left holding the bag or be forced to sell (potentially at a loss), meaning the stock has the potential to drop like a stone at the first sign of trouble.

I guess that’s why they would be gaming their numbers: to convince the next greater fools.

They're doing about a billion per month in revenue by running proprietary models on GPUs like these. Unless they're selling inference with zero/negative margin, it seems like a business model that could be made profitable very easily.

Revenue != profit, and you don't need to become net negative margin to be net unprofitable. Expensive researchers, expensive engineers, expensive capex, etc.

Inference has extremely different unit economics from a typical SaaS like Salesforce or adtech like google or facebook.

> Revenue != profit

Indeed. And even if that revenue is net profitable right now (and analysts differ on whether it *really is), is there a sustainable moat that'll keep fast-followers from replicating most of OpenAI's product value at lower cost? History is littered with first-movers who planted the crop only to see new competitors feast on the fruit.

All of those expenses could be trimmed in a scenario where OpenAI or other big labs pivot to focus primarily on profitability via selling inference.

Currently, selling LLM inference is a red queen race: the moment you release a model, others begin distilling and attempting to sell your model cheaper, avoiding the expensive capitalized costs associated with R&D. This can occur because the LLM market is fundamentally -- at best -- minimally differentiated; consumers are willing to switch between vendors ("big labs", as you call them, but they aren't really research labs) to whomever offers the best model at the lowest price. This is emphasized by the distributors of many LLMs, developer tools, offering ways to switch the LLM at runtime (see https://www.jetbrains.com/help/ai-assistant/use-custom-model... or https://code.visualstudio.com/docs/copilot/customization/lan... for an example of this). The distributors of LLMs actively working against LLM providers margin provides an exceptionally strong headwind.

This market dynamic begets a low margin race to the bottom, where no party appears able to secure the highly attractive (think the >70% service margin we see in typical tech) unit economics typical of tech.

Inference is a very tough business. It is my opinion (and likely the opinion of many others) that the margins will not sustain a typical "tech" business without continual investment to attempt to develop increasingly complex and expensive models, which itself is unprofitable.

I don't disagree but you're moving the goalposts. I never said that they could achieve the profits of a typical tech business, just that they could be profitable. Also, the whole distilling problem doesn't happen if the model is proprietary.

> I don't disagree but you're moving the goalposts. I never said that they could achieve the profits of a typical tech business, just that they could be profitable. Also, the whole distilling problem doesn't happen if the model is proprietary.

In the absence of typical software margins, they will be eroded by providers of "good enough" margins (AWS, Azure, GCP, etc.) who gain more profit from the bundled services than OpenAI does from the primary services. This has happened multiple times in history, either resulting in smaller businesses below IPO price (such as Elastic, Hashicorp, etc.) or outright bankruptcy.

Second, the distilling happens on the outputs of the model. Model distillation refers to the usage of a models outputs to train a secondary smaller model. Do not mistake distillation for training (or retraining) to sparse models. You can absolutely distill proprietary models. In fact, that is how DeekSeek-R1-Distill-Qwen and the DeepSeek-R1-Distill-Llama are trained. This also happens with Chinese startups distilling OpenAI models to resell [2].

The worst part is OpenAI is already having to provide APIs to do this [1]. This is not ideal, as OpenAI wants to lock people into (as much as possible) a single platform.

I really don't like OpenAIs market position here. I don't think it's long term profitable.

[1] https://openai.com/index/api-model-distillation/

[2] https://www.theguardian.com/technology/2025/jan/29/openai-ch...

And even if they are selling inference at negative margin, they'll make it up in scale!

These kinds of phrases are...eerily similar to the phrases heard right before...the .com bust. If you were old enough at the time, that's exactly what the mindset was back then.

The classic story of the shoeshine boy giving out stock tips...and all that.

We all know how that turned out.

Amazon lost money every year for the first 9 years of it's existence and people said it was a bubble the entire time.

Amazon was gross margin profitable -- and significantly so -- the entire time.

It just turns out they were a server farm subsidizing a gift shop.

Yeah this.

Ultimately the marketplace was just an investment that had embedded within it a real option for AWS. Magical really.

> OpenAI is not currently profitable, and it is unclear if its business model will ever becomes profitable -- let alone profitable enough to justify this investment.

Well, yes. Which again is how venture capitalism has worked for ... is it decades or centuries? There is always an element of risk. With pretty solidly established ways to handle: expected value, risk mitigation etc.

I haven't lived through the dot com bubble (too young) but i've read about it. The absolutely insane ways they were throwing money at startups were... just insane. The potential of the technology is the same now and then: AI vs Internet. It wasn't the tech that failed the last time, it was the way the money was allocated.

The math is actually quite mathing this time around. Most AI companies have solid revenues and business models. They aren't turning a profit because (like any tech startup) they chose to invest all their revenue plus investments into growth, which in this case is research and training new models. They aren't pivoting every 6 months, aren't burning through cash reserves just to pay salaries, and they've already gone through train/deploy cycles several times each, successfully.

Are they overvalued? shrug that's between them and their investors, and we'll find that out eventually. But this is not a bubble that can burst as easily as last time, because we're all actually using and paying for their products.

No one's implying it's fake money or resources, only that will no clear path to profit eventually the money will stop flowing and valuations will implode.

It’s a global AI race, there is more at stakes than profit.

There was also a global AI race in the 80's...

> But real GPUs are being built, installed and used.

At this moment they could as well be called bitcoin or tulips....No different from Chinese ghost towns. Real houses being planned and built... And let's not talk to accountants about the depreciation rates on GPU Hardware that is out in 8 to 12 months...

But GPUs are a depreciating asset - if there's a bubble burst and your 5 million GPUs are idle for the next few years before demand picks up again, they'll be pretty outdated and of limited use.

Infrastructure tends to have much longer lifetimes. A lot of the telco infrastructure "overbuilt" during that boom is still used today - you can always blow new fibre, replace endpoints and all that without digging everything up again, which was the largest cost in the first place. Sure, in the above example you'll still the datacentre itself (and things like electricity connections and cooling) that can be reused, but that's a relatively small fraction of the total cost comparitively.

Going to leave this link here: https://www.hussmanfunds.com/comment/mc250814/

By many different measures, we are at record valuations (though must be said, not P/E however). Tends not to end well. And housing prices are based on when mortgages were at 3% and have not reset accordingly. We are in everything bubble territory and have been.

> Tends not to end well.

I'm no financial guru but this time around the boom/bust cycle, there's a new, additional factor that's concerning. Even though I sold my individual tech company shares a few years ago and diversified all my equity holdings in broad market ETFs like VTI, the so-called "Magnificent 7" tech companies have inflated so much, they now occupy a disproportionate percentage of even broad market ETFs which hold ~5,000 stocks based on their market caps. The obvious issue being their share prices all having a significant component elevated by the same thing - unrealistic AI growth expectations.

Two words. Passive flows.

Where do you think your 401K money is going...right into the S&P 500...and who gets the lion's share of allocation out of that? The Mag7 et al.

If you chart the last 25 years, Gold (yes, that one...the useless metal) has outperformed the S&P (and it's making new highs even today). What does that say about hard assets vs these companies?

Housing prices have not reset because of supply and demand. People are sitting on those 3 percent mortgages and not selling.

People are quite bearish and the stock market is making all time highs. This is actually a very good sign, because we are far from any euphoria.

Always keep in mind the old saying: pesimists get to be right and optimists get to be rich.

Only if they're optimistic at the right time and not the wrong one.

Timing the market is a fallacy. Time in the market is what builds wealth.

You're treating a statistical tendency as immutable law. It's true that attempting to time the market is not generally a good investment strategy, but every investment is made at some time, and some of those are very bad times to put money in the market. That it'll probably recover eventually doesn't much help if you've lost everything in the interim.

Which is why you invest a percentage of your paycheque not wait to time the market.

That quote definitely has some insane survivor bias in it.

Optimists go bankrupt or something and you blame them on their work ethic or something and you discard any of those optimists who didn't really succeed and cherry pick those optimists which went right...

Its a classic survivorship bias.

I am pessimistic in US stocks because they are so concentrated on AI for returns and its definitely a bubble or approaches its territory, there is somewhat no denying about it from what I observe.

Your comment really is just off putting to me because I feel like its just a copium which is going to be inhaled by the new generation and then if we fail which lets be honest failure is a natural part of life, we are gonna blame ourselves and that's just really depressing.

I'd better be right than rich. Maybe my rich definition is something that I can get out of hard work while maybe being pessimist (just enough money to have freedom lol)

I don't want to make billions or hundreds of millions, i don't want to build a vc funded disaster for humanity in the name of shareholders whether its an Ad dystopia or an AI nightmare fuel, I'd rather make a imprint on humanity other than my bank account number but maybe that's me being "optimistic"

Sorry but your comment truly ragebaited me... I have very strong opinions in this regards.

> I am pessimistic in US stocks because they are so concentrated on AI

The russel 2000 index just made an all time high. The bull market is diverse and global. Indexes of many countries are also at all time highs.

I am pessimistic in US S&P 500 for the most part actually given how concentrated it is in AI (refer to that hank green video)

I also didn't know that the other world's stocks are doing fine actually. but maybe there is a difference in economy and stocks at this point...

I believe that we can all surely agree on the legendary john bogle's philosophy and in the current day and age realize that us s&p stocks are too centralized on ai and world stocks can be better...

Regarding russel 2000 index. I feel like a lot of money trickles down from the AI hype but its honestly great that russel is doing great.

The point I am trying to make is that atleast for US right now, its political system is so shaky that I can't trust its economical system and there is no denying that if the AI bubble bursts, then it would bleed the whole economy at this point including russel.

There was a great hank green video which I recommend about this concept https://www.youtube.com/watch?v=VZMFp-mEWoM

Also, A lot of countries are definitely in turmoil right now so I am actually surprised by your statements that world economy is doing quite high, maybe stock markets are just another asset class which have gotten so inflated that they are out of touch from the ground reality... (Something I heard in an atrioc video)

I am definitely a bit surprised to hear that the world stocks are doing fine from all the bloodbath of tarrifs and some political issues the world is facing right now...

Politics is a distraction and largely irrelevant to investing.

The stock market has so much money going into it that it is in a bull market. Because people have nowhere else to put their money into (real estate is dead atm).

You are letting your political biases poison your financial decisions.

It isn't even a political bias but rather we can't deny that the economy feels like kissing the ring whether its us buying intel stocks or sort of forcing nvidia to buy some intel stocks and etc.

And I feel like its in a bull market because of AI Hype which was the main comment of the original parent to which you responded I think...

If this AI hype fails to deliver. Literally the magnificient 7 will have a huge loss of money which would then make the stockholders feel less wealthy which will spend less and it would have a drastic impact in the WHOLE economy.

Yes its in a bull market but I feel like I don't want to find out if I am in the peak of a bull market for an AI craze y'know?

And I am not advocating against stocks omg, I am just saying that world stocks are better in current landscape and I doubt if its poisoning my financial decisions.

NO I Don't want all of my saved money to go into an index which is going to be heavily dictated by the future of AI which I and many presume to be a bubble. I would much rather invest in index funds that target the world, heck maybe even index funds that target every country ex usa

My point is that the bubble will burst and then atleast S&P / nasdaq will definitely bleed.

Either we can talk about if you think its a bubble or not, since I am not comfortable investing in a bubbly situation no matter how lucrative it becomes y'know?

What are your thoughts on it?

You can find excuses not to invest at any time. Easiest thing in the world has always been finding an excuse not to invest.

Mag7 are some of the most profitable and well run companies in history investing their insane profits.

No other country has public markets as developed, regulated and liquid as the US. Likely you are just investing into the unknown with a ton of risk factors you are not aware of. In places outside of the US politics actually is a significant factor in investing.

Okay so I appreciate your comment once again. I hope that this discussion can happen in good faith and lets really continue it as I think that I can learn something new.

I can be wrong, I usually am.

That being said, My question to you is:

Do you believe that it is an excuse if I don't invest in mag7 while they are most profitable and well run because I believe that their stock price is highly overflated and past performances aren't indicative of future performances unless we are talking over an aggregate time which the general markets do have.

Now the question is, Do you think its an excuse if I don't want to invest in mag7 because I am worried that its an AI bubble and that worry is backed up by the fact of this AI craze.

If AI doesn't deliver on its prices, can you wager that MAG7 would actually do good? Of course it wouldn't.

What do you mean to think that AI would deliver to its prices as it seems to be either only hyper applicable in tech and all other AI tech is seemingly run at a loss and I can see no way how they might force normal users when there is so much foss ai to actually pay for ai...

What is the monetization plan? Is it to churn the money that you get from stocks into AI to get a higher evaluation of stocks and do some passing around the circle from one company to other and repeat?

Well run is another questionable term given how Magnificient7 includes tesla but maybe we can talk about it later.

I believe that time in the markets beats timing in the markets, so your experiences shouldn't be with a market that feels bubbly y'know? Otherwise, you might just stop it alltogether and I feel like that things might fall down quicker than we think as AI is kinda scrambling through, A lot of people felt disappointed in gpt-5. Reality is settling in, but is reality settling in those magnificient 7 stocks?

I consider myself to be an average investor in the sense that being a superior investor is insanely insanely difficult and its much easier to think you are a superior investor because you might get lucky and then lose more money than you could've made over a long term of time and you try to recoup previous money and previous money.... I definitely don't want to experience it in first place to keep my experiences somewhat moderate y'know?

This is HN so I presume you don't get bored with this response as I love this talk & trying to understand your point in good faith!

> I believe that their stock price is highly overflated and past performances aren't indicative of future performances

You are confusing a popular, cover my ass legal statement with market truth. Past performances absolutely are indicative of future performance the vast majority of the time. They are of course not a guarantee. Inflated price is also not a particularly good indicator of future performance. A stock generally has a high valuation for a reason.

> What do you mean to think that AI would deliver to its prices as it seems to be either only hyper applicable in tech and all other AI tech is seemingly run at a loss and I can see no way how they might force normal users when there is so much foss ai to actually pay for ai...

Google, Microsoft and others run real world AI and I doubt it is at a loss. They make a ton on money on infrastructure. OpenAI operates at a loss, but it is a private company.

> I feel like that things might fall down quicker than we think as AI is kinda scrambling through, A lot of people felt disappointed in gpt-5. Reality is settling in, but is reality settling in those magnificient 7 stocks?

You consider yourself to be an average investor, yet you disagree with the market, thus you think you are smarter than the market. This is cognitive dissonance. The market is a public consensus of the future. Stocks that are more valued have a higher price, because people are willing to bet money they will do better in the future.

This is not toolip mania, or even the dotcom bubble. Bull markets are always caused by investment cycles. Before AI it was mobile and cloud. Those were not bubbles. Neither is AI, because the real world usage is undeniable. The user growth trajectory of ChatGPT was unprecedented. Google deepmind founders got a nobel prize for their work, for something that happened just a few year prior, but was so groundbreaking it deserved it.

Also I am not some investing guru, I just listen to some great investment podcasts. The Real Eisman Playbook (Steve Eisman is the person portrayed by Steve Carell in The Big Short) and Compound and friends.

Hm I appreciate it but a genuine question:

It seems that we aren't agreeing on if the market is in a somewhat bubble or not.

You say that real usage is undeniable. But to me its undeniable because its being spoon fed to you for free for SOTA models from all fronts including open source chinese models.

They are running at a loss because they are having these insane growth cycles but they have no moat to a somewhat degree.

Tell me how OPENAI or any AI company plans to be profitable and actually return great profits on what the investment is.

The thing is, that they have to constantly train and retrain the models to reach SOTA and people are realizing that they are being benchmaxxed.

Open source models are coming to a somewhat close degree and I doubt that it would be thaaat noticable for most consumers y'know?

There is no moat. Sure, maybe there is some moat in coding as I feel like that is the only thing that wasn't touched by Open source models.

Open source has sort of SOTA image models, SOTA-ish video models and what not & so anybody can try to compete with these on things like open router which is where half the api uses become because of how convoluted other apis are and how openrouter just sorta works...

I can provide you sources as well but there is a long consensus that AI doesn't really help in research thaat much.

The point is, that sure there is this great tech but its just unprofitable at the scale if you consider providing free access to the masses too.

Tell me how these companies are gonna make a consistent profit on AI without being crunched by each other's SOTA benchmaxxing and kill throat competition from China's open source models.

I genuinely wonder what "real world AI" to you is & how its turning up at a profit.

Like, okay, maybe I can agree that sure maybe inference could be made profitable if done to somewhat degree like how deepseek did but there is no way that it was worth the return in investment...

And do you know what happened? Nvidia selling the shovels, "infrastructure" got to be the most valuable company. If this isn't a bubble then why did Nvidia lose so many billions of $'s just because China released deepseek model.

Sure nvidia has regrown but are you really not going to take the past into account?

Regarding past performance quote, I think that I had also agreed in my original quote but I had mentioned past performance of something like 100 years. Computer stocks have been less time than that and this AI hype is quite new.

These companies like google etc. are integrating everything AI not because they want to but because their stock rises up when they mention AI for the most part.

I will repeat this again, my friend, but if you can tell me how the average investor is investing into a business which is going to make a profit...

How are they going to make a profit given the amount that they have invested in with degrees of no moat, it seems that entreprise is the most clear moat they have but https://www.forbes.com/sites/jaimecatmull/2025/08/22/mit-say...

Coding models might be the most profitable imo given that people want absolute best in it and they don't mind paying the price (claude code) but that is a niche of niche and that alone can't justify the amount of investment and stock prices made I suppose, not unless you believe in some sort of AGI.

How are these companies going to make a profit dude, the only way they have been for now is by their stock prices but I know that you know that it isn't sustainable, thus it becomes a sort of bubble situation.

I am an average investor, yet I am cautious of the times here, because I believe that AI just kinda came out of no where and became a mainstream word and VC's were funding things like devin which was literal BS LMAO but the amount of fear mongering there was, was crazy. So like, there was a fomo of more VC's which invested in more AI's which then made people jump into the trend to then have a scene where anything labelled with AI gets stock price to

Am I false in the above statement?

How is this not a bubble? The tech is cool but people aren't paying in stock markets to support a tech or smth, they want returns now... And once those returns stop coming in the sense that people realize this... Oops, looks like nobody want those Ai stocks anymore.

I have read the intelligent investor to a somewhat degree to then pick up on John bogle's index fund related book to realize that benjamin graham, the creator of intelligent investor would've also preferred index funds and thus my whole sentiment shifted towards realizing diversification and to maybe preventing bubbles I suppose.

Honestly, so funny because your statements could be shown in history as what people believed before the bubble burst and it would still be accurate and mine tbh can also be taken in that intepretation from the other way...

I hope you are still interested as I still love this discussion!

You are conflating OpenAI, xAI, Anthropic with the entire field of AI. They are spending billions of private money with the goal of actual general AI. Maybe they will reach it, maybe they wont. They are doing a moonshot and pushing the field forward and they have the money to do it.

But that is an entirely different game compared to what AI is being used for now. Two random examples I came across:

https://x.com/LinusEkenstam/status/1965014479760204118

https://abelpolice.com/

https://longevity.technology/news/new-ai-tool-demonstrates-p...

This is AI as it is capable now, solving real life problems and making industries more efficient. This is happening throughout practically every field of human endeavor, which is why ChatGPT is used so much. Medicine, biomedicine, law, translations, coding, investing, learning and so on.

nVidia is the most valuable company in the world right now, because they are powering practically all of it.

Worrying about profits right now is an entirely wrong thing to concentrate on. Analogous to the previous investment cycle: Youtube is one of the most valuable pieces of the tech industry. It was a money loser for a damn long time and would have gone broke if google had not bought them, not to mention being sued out of existence (a real threat in the early days). When it was made in 2006 it was a bet everyone thought was insane, because of the infrastructure costs and legal risks. Right now it is very profitable, because they had time to optimize and develop their business model.

Exactly my point. I agree with your statement tbh Really great that we can reach to a conclusion but

Here's the thing though:

Youtube has a moat. It is a social media and the networking effect runs wild on it and tbh there were a lot of other things too like (vines?) which fall.

But, can you say the same for Ai given open models?

China couldn't create an alternative to social media (in some sense?) because it requires a network effect.

But it sure can use gpu's, maybe even build their in house gpus so that they can then train on the data just as how america did and effectively price dump with no restrictions :/

Honestly, I can agree if you believe that AI Has a moat similar to social media, then sure, but I just don't believe it has a moat.

Youtube turned profit because of moat, Is there any moat in LLM's?

And if we are talking general purpose robotics/ automation, then I agree that yes its good.

But for an average investor whose investing, they are investing thinking that its sort of inevitable actual general AI when that's not the case.

From what I know, the optimizations of LLM's don't really apply to robotics, so all this funding of billions going into LLM only to pivot into robotics is a bit :/ for the investors.

IMO When I mentioned S&P AI stocks, that's exactly things like Google,microsoft,amazon which are still similar to OpenAi and anthropic, don't you think?

S&P's growth is heavily based on the calculated return that Google,microsoft,amazon are gonna be the winners of the Ai "wars", that's what I meant!!

If google says a line similar to yours that LLM's aren't the future, then you can naturally expect how the market would react.

The funny thing is, is that between your comment, I got recommended a video about AI bubble... which is accused in comments to be created by AI

https://www.youtube.com/watch?v=37aUuoRyMhM

The tech is cool but 95% are focused on the wrong thing or smth and there is no advantage/moat and uh its still literally something like. bubble. Even in a bubble, google/amazon survived.

You can say that I should still invest because stock prices grew even after bubble bust, but they were in a deep awakening, and I feel like as an average investor I'd rather prefer some more stability knowing that there is still a condition of a bubble formation in S&P and US tech stocks atleast

These companies are using AI as a magic word. Vercel's keynote had AI esque words 42 times... LET ME REPEAT, 42 times. Vercel isn't even that AI based lol, its a react next app thingy for most people.

Still hoping you can comment! I was thinking of creating a hackernews post about involving other people in this discussion since at the day our discussion boils down to: is this a bubble?

I thought that it was common knowledge to everybody but maybe not, I can create a ASK HN: Do you think that S&P 500 / Magnificient 7 is an AI bubble right now? or smth!

Looking forward to your feedback and I had a blast in this conversation! Wish to discuss more lol!! Have a nice day, (waiting for your comment)

> From what I know, the optimizations of LLM's don't really apply to robotics, so all this funding of billions going into LLM only to pivot into robotics is a bit :/ for the investors.

AI wave is more than just LLMs. Movement autonomy for cars/robots, image/video generation, protein folding, etc. Those are not LLM based AI applications. They are all downstream from the transformer architecture. Autonomy AI development is the missing piece of robotics, which is why so many billions are being invested now.

The lack of moat regarding LLMs is a problem only to those playing in that field, but their actual goals are not just running LLMs, they are like I said aiming for actual general intelligence.

In the mean time, companies are training or optimizing their own models for their use cases, like the ones I listed in the previous reply. They do have a moat, because they require specialized knowledge to play in that field. Even the abel police guys, their competitors were just an interface to ChatGPT and it worked abysmally.

> IMO When I mentioned S&P AI stocks, that's exactly things like Google,microsoft,amazon which are still similar to OpenAi and anthropic, don't you think?

Absolutely not. OpenAI is a private company spending insane billions for a moonshot project. The public S&P500 companies are investing their insane profits and making a return on those investments. Their infrastructure and scale is a moat.

I had written a original draft of an reply but this conversation is getting really interesting and wanted to write it again lol.

I agree with all the aspects of protein folding / general purpose automation due to "AI" and not LLMs but that was happening before the "AI" hype thanks to OpenAI / chatgpt where so much money was flowing into it...

And I have no issues with them if their prices were baked into realism that they were baked into pre 2022's / whenever chatgpt got launched

My biggest issue which is the crust of this discussion might be that I believe that tech stock prices are roaring so high mostly because of the AI hype that they bring which raises their prices.

Oracle made larry Ellison the richest person for some time due to the stargate project / due to their deal with OpenAI / then larry invested into openai for some hundred billion $ which openai paid back to oracle and oracle's stock price increased more... rinse and repeat?

The thing is, why is oracle which I think is S&P company raising because of their deals in LLM's at an unastronomical rate/ unprecedented rates.

Google/meta/microsoft/amazon are also all integrating AI into their every project / mentiniong AI as much as possible which lets be honest again, is mostly LLM's for the most part.

Yes I know, google has some really interesting non LLM AI projects which I know and love but they were pre 2022 and google's price wasn't as much dictated by those projects as they are doing now y'know?

My conclusion is that A lot of people can't / couldn't invest into OpenAI / thus flowed their money into anything LLM / AI related in the markets... & the companies are loving this and mentioning AI as much as possible

Can we agree on this or not?

I can agree if you think that these companies are investing into infrastructure but that infrastucture is now mostly GPU's which are only really useful for LLM related tasks and becomes redundant for general purpose stuff like running servers for the most part.

Do we agree on this or not?

Also regarding infrastructure, The thing is, That most of them are just packing Nvidia Gpu's which is something that Nvidia also offers and others could do too but yeah, I can get that part but is it an "investment" is questionable...

Its an investment only if LLM's turn out to be profitable.

Firstly the cut throat competition means that literally everyone is competing in it so it cuts each other profits.

Secondly, there are some recent models which are kinda small and could run to a somewhat degree on modern hardware if need be which could satisfy some users needs without having to need that infrastucture

Then again, even if there are some people that might not have that and they search on things like chatgpt. They do it out of freebies that its not gonna cost them that much. And they can switch out if those AI providers do charge them first... with open source models while they themselves ride this end of AI hype.

If you believe that AGI is near, whatever that means, then literally everything I said gets out of the equation but I am assuming you aren't believing that.

Now sure there are gonna be returns but they aren't gonna be nearly as expected. In fact I think that most S&P companies are gonna be in a loss with all of these training of models / building infrastructure. Also, training of models is a recurring cost for the most part if they have to stay SOTA iirc with higher developer's cost working in AI/ML (100 million$ income is provided by the people investing into S&P dude)

So with all of these things, I believe that there is a legitimate concern that the investment isn't worth the return.

Then why are companies investing?

Because of fomo. When the AI hype started thanks to chatgpt. every private equity rushed for similars and that kinda leaked into S&P companies which are doing the same thing with AI hype mentioning it so much.

Do you agree?

If you can agree with all 3 of these statements to a reasonable degree, then I believe that we can agree that we are in an agreement and that it isn't much of an investment as its a way to somehow increase their stock prices by essentially mentioning the word AI and that's all that matters to them in the end, but its all on a proposition that someone is gonna buy the stocks thinking that its gonna go up and so on and so on.. when fundamentally the business model is kinda messed up when you think about it y'know? This is a bubble to me in my definition of it when people are investing into things without caring about things for the most part / logically I suppose...

If we have any disagreements, do let me know so that I can maybe lighten up on some other points as I love talking lol. I am loving it although I feel like I write realllly long sentences but hey, I am writing this to really explore why I believe the things the way I do and if you can convince me then sure, I can be wrong, I usually am.

Have a nice day and looking forward to your next comment!

> My biggest issue which is the crust of this discussion might be that I believe that tech stock prices are roaring so high mostly because of the AI hype that they bring which raises their prices.

They are not that high at all, at least nowhere near bubble territory according at least to the financial analysts I follow. A better metric than simply p/e is looking at forward p/e because the current price reflects their forward guidance.

> My conclusion is that A lot of people can't / couldn't invest into OpenAI / thus flowed their money into anything LLM / AI related in the markets... & the companies are loving this and mentioning AI as much as possible

I guess, but that in itself does not mean it is a bubble.

> I can agree if you think that these companies are investing into infrastructure but that infrastucture is now mostly GPU's which are only really useful for LLM related tasks and becomes redundant for general purpose stuff like running servers for the most part.

Recommendation algorithms run on GPUs, which is a huge part of any social network (like meta and tiktok). Like I said there is more than LLMs and those need to run on GPUs as well. They also provide a service to rent out GPUs to other companies to run their own models and make a very good business of it.

> when fundamentally the business model is kinda messed up when you think about it y'know?

You are alone in that opinion. These are some of the most profitable companies in history, which is why they make such a huge part of the S&P. You are talking about a feedback loop of investing, which is normal in any investment bull cycle. It can turn into a bubble and we may be at the start of one, but being an AI skeptic investor just means not participating and having poor returns. The future is uncertain and it sounds to me like you are looking for reasons not to invest.

Recommendation algorithms run on GPU's but they were running on GPU's previous to the AI hype and they are still running while running AI inference/training so those datacentres for AI are still gonna be vacated if demand drops down and so it isn't definitely something of an investment

These companies have sort of saturated their markets and thus joined into LLM etc. to try to catch the new shiny thing.

>You are alone in that opinion. These are some of the most profitable companies in history, which is why they make such a huge part of the S&P. You are talking about a feedback loop of investing, which is normal in any investment bull cycle. It can turn into a bubble and we may be at the start of one, but being an AI skeptic investor just means not participating and having poor returns. The future is uncertain and it sounds to me like you are looking for reasons not to invest.

Please try to change the word Ai in this sentence to crypto to see how relevant it might be :>

Also, this line kinda means "It may be a bubble but it pays right now" in the sense that you are basing your returns STILL on the fact of some predicted PE.

I am just saying that people shouldn't consider S&P 500 "safe enough" then I suppose due to this AI hype if there is even a sheer possiblity of bubble formation.

Higher profits generally mean higher risks and there is no free lunch. So S&P 500's higher profits does have a higher risk and people should know that risk before investing and my risk appetite doesn't support it and I am wondering how yours could.

Superior returns aren't easy and if someone's saying them without giving you the underlying reason ie. realized productivity gains in an underlying trade (think a house builder built a house which was productive to the family and they are gonna pay for it) (compare it to how messy AI is, and how we haven't really still discussed on why there is so much hype in the market when the economy is doing kinda bad)

> it sounds to me like you are looking for reasons not to invest.

Yes, I naturally took the discussion from this side in investing in S&P markets and It's wild how you think so when I really agreed to you on a lot of things and your last line sort of sums it except when you look at the true gravitas of the situation, there is almost very little uncertainty about that (so no need for maybe)

Sam Altman, CEO of OpenAI, has expressed concerns that the AI market may be experiencing a bubble, similar to the dot-com bubble of the late 1990s

This is my opinion too.

I was thinking of someone who wants to have a long time in the market as I think I said but time in the market beats the timing in teh market and so these "maybe" lines do frighten me. Do I want to mess around and find out if things are in a bubble with my money!? On a company which is massively enshittening itself in the names of AI (youtube auto dub comes to mind)

This was a good faith discussion and I appreciate it but I don't agree on how it means not participating in bubble-ish maybe activities means you aren't getting returns, its like saying that I am not getting returns on crypto because I am not participating... because the whole thing is bubblish & those returns aren't magical...

S&P should be considered a safe enough investment not something that is on the whims of a maybe, I suppose?

I really like your last line I must admit, and it can take both an AI skeptic (AI skeptic in the sense that the tech is cool but its not gonna generate much profit given the investment) and pro AI person...

> You are alone in this opinion ..

I;d genuinely love to know if that's the case and I really wish to create an Ask HN, linking to this discussion as I don't think that my take is unreasonable?

Also pardon me if uh I became way too much harsh, I just felt as if some of my points were definitely being missed and that frustated me thinking that you were pin picking which might not be exactly correct tbh

Do you have any way that I can contact ya tbh as I really find our discussion a bit fascinating and something that I agree on which sort of makes me believe even more that it might be a bubble yet at the same time, maybe its not thaaat harsh at the same time y'know. Like its partially a bubble, definitely something to be cautious but still

Would love to get a way to contact ya, msg me on my mail please, I have also added my signal information just for this in my hn bio i guess.

reminds me of this image https://www.reddit.com/media?url=https%3A%2F%2Fi.redd.it%2F6...

Same thing with the 1.3 billion EUR investment of ASML into Mistral. ASML -> Mistral -> NVIDIA -> TSMC -> ASML -> ...

It would be amusing if it also wasn't so accurate.

I didn’t see the step where Larry has to sell any stock, and hence puts downward price pressure on Oracle share prices.

What is the source of the cash in steps 3, 4, and 7?

He doesn't have to sell. He can finance the deal with debt backed by his newly risen stock as collateral. Then the debt is used to further inflate the price of the stock.

The flywheel metaphor is pretty apt.

It is us, index fund owners :clown:

Disclaimer: I also have a small amount of money in vanguard IRA

According to the image of the steps, Oracle’s share price is going up, presumably more than it would have without engaging in these steps. How can that cost index fund owners? They would be benefiting from the share price increase.

Ultimately, debt will fuel this. Oracle can't pay with cashflow.

Credit.

At least the deal is denominated in watts rather than currency which may hyperinflate soon.

This is more like reinvesting into the business as it's growing. It's a positive sum loop.

Nvidia makes money by selling to OpenAI. OpenAI makes money by selling a service to users that uses Nvidia. So Nvidia invests in the build out and expansion of the infrastructure that will use Nvidia.

This is a classic positive sum loop.

It's not that different than a company reinvesting revenue in growing the company.

But is OpenAI recouping this? I remember seeing reports a year ago that it was in the realm of $700M/mo in inference costs for them - are they earning that now?

Of course the strategy of taking a loss and reinvesting - but I don't see how OpenAI is making enough money to pay for all this, now or in the future.

It hasn't monetized any of its services. There are currently no ads. And it's not selling user data, well not yet.

That's literally hundreds of billions worth of revenue.

Just look at the options OpenAI has to generate revenue beyond subscriptions.

How would you "see" that, given that OpenAI isn't public?

I do not think the leveraging is going to end there. I suspect this will be used to justify/secure power generation investments, possibly even nuclear. Likely via one or more of the OpenAI/Altman adjacent power startups.

On the bright side, if lots of power capacity is added and most of the GPUs end up idle, then there might be cheap power available for other uses.

Power generation is not a monolithic enterprise. If more supply is built than needed, certain suppliers will go bankrupt.

They may, but that doesn’t mean that the capacity disappears. It may require some assumptions about USG willingness to backstop an acquisition but it’s not a significant leap to think that the generation capacity remains in (more capable?) hands.

Speaking of capacity, what happened to all the "dark fiber" that was supposedly built for Internet 2 or whatever? The fiber doesn't go away just because a bubble burst, right?

Railways are similar, many were built by investors who lost all their investment but the railway is still there.

What are the chances suppliers will go bankrupt but the plants get sold and still produce power?

Not if Ellison trickles it out for maximum profit.

And computing in general gets cheaper.

heating our homes next winter with clusters of h100s

Altman is all in on converting the solar system into a Dyson sphere to power OpenAI.

And it is hilarious [0]

[0] dyson spheres are a joke / Angela Collier https://youtu.be/fLzEX1TPBFM

Isn't that already happening via Oklo? Up 500%+ YTD.

Is this more of an accounting thing?

Is there some (tax?) efficiency where OpenAI could take money from another source, then pay it to Nvidia, and receive GPUs. But instead taking investment from Nvidia acts as a discount in some way.

(In addition to Nvidia being realistically the efficient/sole supplier of an input OpenAI currently needs. So this gives

  1. Nvidia an incentive to prioritize OpenAI and induces a win/win pricing component on Nvidia's GPU profit margin so OpenAI can bet on more GPUs now

  2. OpenAI some hedge on GPU pricing's effect on their valuations as the cost/margin fluctuates with new entrants

)?

It sounds like Nvidia has so much cash already that they would prefer to own x% of OpenAI instead.

It's not round tripping. Economically Nvidia is investing property is OpenAI. It's not investing nothing, far from it.

It's interesting how deals like this are politically relevant. Nvidia refused to do deals like this (investing in companies buying large amounts of NVIDIA GPUs) after they got the hammer from Biden's SEC for self dealing due to their investment in Coreweave.

But now that there is a new SEC, they are doing a bunch of these deals. There is this one, which is huge. They also invested in Lambda, who is deploying Gigawatt scale datacenters of NVIDIA GPUs. And they are doing smaller deals too.

"...man this is gonna crash hard when reality sets in."

Given the amount of money invested and the expectations, the crash will be of cataclysmic proportions

I'm not saying you're wrong, but with Nvidia pulling back from DGX Cloud, it makes sense that they'd continue to invest in their strategic partners (whether it's software companies like OpenAI or infrastructure vendors like Coreweave).

Really curious how xAI is working out financially. Grok blows me away for coding.

It's interesting how profitable Tesla is despite the huge investments in their AI training infrastructure. They seem to be one of the best positioned companies that can maintain enough profitability to be able to afford their AI infrastructure without issue.

Google?

Gemini isn’t the best though, I’ve found it not nearly as good as grok

The're just buying and investing from each other?

It forces us to confront a question.

How much investment and prioritization in scaling laws is justified?

Regardless of the scaling hypothesis, they need the compute to serve the models at scale.

My thought is think of all the really cheap compute that will be available to researchers. Sure, it will crash but at the end of the day there will be a huge glut of gpus that datacenters will be trying to rent out near cost.

I (as a uninformed rando) think that there are a lot of research ideas that have not been fully explored because doing a small training run takes 100k. If that drops to 1000, then there is a lot more opportunities to try new techniques.

With this level of power usage it might be the opposite. Once they can't subsidize the cost it might increase.

I do think about this where they are creating a printing / cash burning cycle where both OpenAI keeps on doing raises and Nvidia can get more sales...

Well I hope it crashes so we can get back to normalized GPU prices.

Perhaps I should short openAI… would you try it?

I also ask this as a rationalist technique, the moment you ask “what outcome would you actually put money on” people suddenly get far more realistic about how confident they actually feel. You get a whole lot less “oh they’re DEFINITELY gonna fail/succeed!” type hyperbole when money is on the line.

I think you have just described the global economy.

I also recall reading that OpenAI is developing its own chips. What happened to that?

I don't think the NVIDIA deal is an exclusive one... They can still use TPUs and GPUs and other cloud providers if they like. They may still be planning to.

Does this mean they pay for it through consumer GPU sales?

Last quarter, NVIDIA reported data-center revenue of $30.8 billion and gaming revenue of only $3.3 billion.

https://nvidianews.nvidia.com/news/nvidia-announces-financia...

This also explains why NVIDIA will not sell high VRAM consumer GPUs: it would cannibalize on their exorbitant data-center profits.

If they won't, somebody else will. And frankly that alone can pop their bubble.

No, those are a drop in the bucket.

> throwing more cards on a house of cards.

Nice metaphor! Huge bubbles usually get a historical name like "Tulip Craze" or "Dot Com Crash" and when this bubble bursts "House of Cards" is a good candidate.

Oh, I see now: house of cards (usual meaning) + throwing more cards on (like throwing money on the fire, and also how you destabilize house of card) + GPU cards in this case (even though they're not necessarily cards). I like it.

I just hope it works out just like the dot com crash in the long run - which is that the internet kept going and bringing real value it just needed a big market reset when it popped.

Same as they are doing with CoreWeave. In a sane world the SEC would do something but we are past that. What about Boeing opening an airline company and selling airplanes to itself?

Almost every model trained by the majors has paid for itself with inference fees.

I’m not saying there isn’t a bubble, but I am saying if the researchers and strategists absolutely closest to the “metal” of realtime frontier models are correct that AGI is in reach, then this isn’t a bubble, it’s a highly rational race. One that large players seem to be winning right now.

> Almost every model trained by the majors has paid for itself with inference fees.

Even if we assume this is true, the downstream customers paying for that inference also need it to pay for itself on average in order for the upstream model training to be sustainable, otherwise the demand for inference will dry up when the music stops. There won't always be a parade of over-funded AI startups burning $10 worth of tokens to bring in $1 of revenue.

My employer spends $100k/month or more on OpenAI fees. Money well spent, in both product features and developer process. This is just one fairly small random startup. Thousands of companies are spending this money and making more money because of it.

Curious what makes you think the money is well spent.

I can maybe digest the fact that it helped prototype and ship a bit more code in a shorter time frame... but does that warrant in enough new customers or a higher value product that would justify $100k a month?!

Some of that $100k/month might be powering the features, rather than supporting development.

yeah it's probably 80% going to product features (processing/classifying data, and agentic workflow features), and 20% to dev tools

Probably 80% of that money goes towards product features that are crucial to retention and acquisition of customers, and the business is profitable. Could those features exist without AI integrations? Some yes, but the data would be limited/inferior, other features would not be possible at all.

The 20% spent on dev tooling seems well-spent. About 10 devs on the team, and all at least 2x (hard to measure exactly, but 2x seems conservative) more productive with these tools.

Tokens that can be purchased for $10 may or may provide the purchaser with almost any dollar denominated result, from negative-billions* to postive-billions**.

Right now, I assume more the former than the latter. But if you're an optimistic investor, I can see why one might think a few hundred billion dollars more might get us an AI that's close enough to the latter to be worth it.

Me, I'm mostly hoping that the bubble pops soon in a way I can catch up with what the existing models can already provide real help with (which is well short of an entire project, but still cool and significant).

* e.g. the tokens are bad financial advice that might as well be a repeat of SBF

** how many tokens would get you the next Minecraft?

Isn't most of OpenAI revenue from end users and not revenue from token sales? For Anthropic, it is the opposite where almost all of their revenue comes from API usage. So even if AGI/ASI don't pan out, OpenAI will have a great consumer-focused inference business where they build useful applications (and new devices) using existing state-of-the-art LLMs and stop investing heavily in the next gen model training? I think potentially just replacing Google Search and smartphones with a new AI device would be massive consumer businesses that OpenAI could potentially go after without any major advancements in AI research.

I’m the other way — the cost of launching a creative / interesting software company / project just got cut to 1% or so. (I said launching. Maintaining … obviously not quite as good on the numbers).

I propose software creation, and therefore demand for software creation are subject to Jevon’s Paradox.

Ever since NLP and CSR, the two unassailable fortresses of every AI winter, fell to LLMs? I had no doubt that AGI is within reach.

It's less "will it happen" now, and more "whether it hits in a few decades or in a few years".

The thing is that AI researchers that are not focused on only LLM do not seem to think it is in reach.

Demis Hassabis seems to think this and not only does he not focus only on LLMs, he got a nobel prize for a non-LLM system ;)

As far as I know, that Nobel prize was for being the project manager...

If you talk to any of his early investors, they considered him absolutely crucial to the project.

They say the same about Sam Altman....

Which of these model-making companies have posted a profit? I'm not familiar with any.

They account internally for each model separately; Dario said they even think of each model as a separate company on Dwarkesh some time ago.

Inference services are wildly profitable. Currently companies believe it’s economically sensible to plow that money into R&D / Investment in new models through training.

For reference, oAI’s monthly revs are reportedly between $1b and $2b right now. Monthly. I think if you do a little napkin math you’ll see that they could be cashflow positive any time they wanted to.

Again with the "this is very profitable if you don't account for the cost of creating it?"

Then my selling 2 dollars for 1 dollar is a wildly profitable business as well! Can't sell them fast enough!

Why does it seem like so many people have ceased to think critically?

OpenAI claims that each GPT generation has sold enough inference at high enough margin to recoup the cost of training it.

The company overall is still not profitable because these proceeds are being used to fund training the next GPT generation.

You have LLM derangement syndrome, and don’t understand.

Say the first model cost $2 to make. On metered sales, they’ve made $10 on it.

They then decide to make a $20 model, raising more money. It turns out, that model made $100.

They then decide to make a $1,000 model. That model made $5,000.

There are two possible paths for their shiny new $10,000 model: either it will be a better market fit than the 1k model, or it will not.

If it is a better market fit than the 1k model, then it seems very likely that at some point it will make more than $10,000 (2x the prior model’s utility).

If it does not provide better value, then you can scrub that model, and keep selling the $1k model. Eventually it will likely provide the additional $5k of investor capital back through profits.

What we have seen is this above scenario, with a couple twists: first, the training (capital investment) decisions overlay the useful life of the prior model, so you have to tease out the profitability when you think strategy. Second, it turns out there’s quite a lot of money to be made distilling models the market likes into models that give like 90% better profit.

So, these businesses paying billions of dollars to train frontier models are absolutely rational actors. They are aggressive actors, engaged in an arms race, and not all of them will survive. But right now, with current inference demand, if all the global training capital dried up, (and therefore we are stuck with current models for some time), they would become highly, highly profitable companies during the period where fast followers tried to come in and compete on price.

Is the profitable model that makes 5x its cost in revenue here in the room with us right now?

The idea that it’s a bubble on the frontier model side is insane. AI assisted coding alone makes it the most valuable thing we’ve ever created.

Get your head out of the proverbial, a bullshitting machine that lets some developers do things faster if they modify how they develop isn't even close to the most valuable thing we've ever created.

It easily is, nothing else is even remotely close. Software is the most valuable industry on earth and we are well on our way to fully commoditizing it.

I think you’re wrong. Consider the following. It’s 1995. You and your next door neighbour Jeff Bezos have both just raised $10mm from competing VCs to build amazon.com.

You can choose to have a Claude API portal to the future where you pay 2025 prices for token inference, or you can skip it, and use 1995 devs to build your competitor.

Which do you do?

Totally agreed.

Does anyone in the finance business know how legal this all it? I am hearing terms like "round tripping" being thrown around. A practice where a company sells and buys back its own product to artificially inflate revenue.

I'm asking because its not just OpenAI that they are apparently doing this with, instead its with multiple other major GPU providers, like Coreweave.

And its just being done all out in the open? How?

IANAL but you can do pretty much anything as long as it's disclosed. The only problem with round-tripping is doing it secretly.

As an investor you may decide that round-tripping is dumb but in that case your recourse is to sell the stock.

First of all, it's not 'textbook round tripping' at all. The parent commenter is dead wrong but HNers upvote when they see "AI is a bubble."

Textbook round tripping is like: OpenAI buys GPUs from Nvidia. And the only reason it buys these GPUs is to resell it back to Nvidia, or just do nothing. It doesn't make it round tripping just because OpenAI is taking investment and buying stuff from Nvidia at the same time.

Unless you really believe OpenAI has no intention to use these GPUs for other purposes (like training GPT-6. I know, a crazy idea: OpenAI will train and release a model), it's not round tripping.

Its not just about OpenAI, though. Even though they have the biggest/flashiest deal. The other more obvious example is coreweave.

> OpenAI buys GPUs from Nvidia. And the only reason it buys these GPUs is to resell it back to Nvidia

Funny you should say this. Nvidia having those GPUs be rented back to them is also something thats happening.

https://www.kerrisdalecap.com/wp-content/uploads/2025/09/Ker...

"As detailed by The Information, in early 2023 Nvidia invested $100 million in equity and signed a $1.3 billion rental agreement through 2027, under which it rents back GPUs from CoreWeave to support internal R&D and its DGX cloud offering."

"CoreWeave is not the only neocloud to benefit from Nvidia’s strategic support. Nvidia has actively supported an ecosystem of emerging AI infrastructure providers – including Lambda, Nebius, and Applied Digital –"

They are quite literally buying GPUs only to rent them right back to Nvidia.

And these are just the public deals. Is Nvidia systematically selling GPUs and having them be rented back to, by every major GPU cloud providers?

https://www.investing.com/analysis/coreweave-nvidia-partners...

"This deep alliance culminates in the new $6.3 billion agreement. The deal’s most critical component is a strategic commitment from NVIDIA to purchase any of CoreWeave’s unsold cloud computing capacity through April 2032"

How I see it - the people with the money make the rules, why would they make rules against themselves?

Yes, but my point is that this almost feels like an Enron case. Things were fine, until they weren't. And then in retrospect the fraud is obvious.

I'm just surprised that nobody is yelling to the rooftops about practices that are just so out in the open right now.

Sure, but its going to be a great plot for the movie that comes out in five years.

What is this a bubble on? What does said bubble collapsing look like?

Nvidia is giving OpenAi money (through investment) to buy Nvidia chips. The bubble is that Nvidia got that money from its crazy high stock price, the extra investment raises OpenAi’s evaluation and the increased sells raises Nvidia’s evaluation. If the valuations see a correction then spending like this will decrease, further decreasing valuations.

Bubble collapsing looks like enshittification of OpenAI tools as they try to raise revenues. It’ll ripple all throughout tech as everyone is tied into LLMs, and capital will be harder to come by.

> The bubble is that Nvidia got that money from its crazy high stock price,

This is totally False, NVDA has not done any stock offerings. The money is coming from the ungodly amount of GPUs they are selling. In fact they are doing the opposite, they are buying back their stock because they have more money that they know what to do with.

A company buys back its stock if it thinks the stock is underpriced. Otherwise when “you have more money than you know what to with” you give it to your shareholders via a dividend. A concept mostly forgotten by tech companies.

A company buys back stock because distributing dividends incurs a 30% withholding tax.

Sorry guys but this is why I dont want to see many finance related posts here, because very few know what they are talking about.

Buybacks are the preferred method of RETURNING CASH to shareholders, because dividends historically have been sticky. Buybacks are flexible.

Buybacks are also done to optimise the debt ratio, to minimise the firms cost of capital and thereby maximizing firm value.

Ermm this is nothing but a wealth transfer from the shareholders who sell at too low a price, to those who dont.

NVDA outstanding shares are down ~1.2% year over year; the company has been buying back its own shares with —>> profits <<— to the tune of tens of billions.

Meanwhile NVDA stock is mildly up on this news, so the current owners of NVDA seem to like this investment. Or at least not hate it.

Agreed that we’ll see ad-enabled ChatGPT in about five minutes. What’s not clear is how easily we’ll be able to identify the ads.

Valuations won’t see a correction for the core players, I have no idea why people think that. Both of these companies are already money factories.

Then consider we are about to lower interest rates and kick off the growth cycle again. The only way these valuations are going is way up for the foreseeable future

> Bubble collapsing looks like enshittification of OpenAI tools as they try to raise revenues

Why does monetizing OpenAI tools lead to bubble collapse? People are clearly willing to pay for LLMs

You read this backwards. If the bubble collapses we will see OpenAI raise capital by increasing revenue instead of investment.

AI and tech companies

Collapse might look a little like the dot com bubble (stock crashes, bankruptcies, layoffs, etc)

And it's worth reiterating that a bubble does not mean the technology is worthless. The dot com bubble collapsed despite the internet being a revolutionary technology that has shaped every decade since. Similarly LLMs are a great and revolutionary technology, but expectations, perception and valuations have grown much faster than what the technology can justify

These hype cycles aren't even bad per se. There is lots of capital to test out lots of useful ideas. But only a fraction of those will turn out to be both useful and currently viable, and the readjustment will be painful

Plus unused dark fiber = unused AI data centers and power generation capacity.

I think ultimately the conclusion that we're in a bubble is bad analysis. It jumps over a chasm and assumes that analogy to past historical situations allows us to draw conclusions.

This isn't a bubble. This is the collapse of 300 years of modern capitalism into corporate techno feudalism.

This won't crash and lead to a recession or depression. We are at the end game. Look around you. Capital is going scorched earth on labor. They are winning. Cost of living in metropolitan areas is exploding, and most of us will end up begging for scraps in peripheral areas.

This is the result of everything the elites have been working towards for the past few decades. Climate catastrophe is the cherry on the cake: they will shock therapy us into the last few bits. There will be corporate citizenship that enables one to live as a demi-god at the behest of the owners, and survival in the wastelands for the rest of us.

High end server gpus and AI roi expectations.

I think everyone is underestimating the advancements in wafer tech and server compute over the last decade. Easy to miss when it’s out of sight out of mind but this isn’t going anywhere but up.

The current SOTA is going to pale in comparison to what we have 10 years from now.

> I think everyone is underestimating the advancements in wafer tech and server compute over the last decade.

What advancements?

We have done a fabulous job at lowering power consumption while exponentially increasing density of cores and to a lesser extent transistors.

Delivering power to data centers was becoming a problem 20 ish years ago. Today Power density and heat generation are off the charts. Most data center owners are lowering per rack system density to deal with the "problem".

There are literal projects pushing not only water cooling but refrigerant in the rack systems, in an attempt to get cooling to keep up with everything else.

The dot com boom and then Web 2.0 were fueled by Mores law, by Clock doubling and then the initial wave of core density. We have run out of all of those tricks. The new steps that were putting out have increased core densities but not lowered costs (because yields have been abysmal). Look at Nvidia's latests cores, They simply are not that much better in terms of real performance when compared to previous generations. If the 60 series shows the same slack gains then hardware isnt going to come along to bail out AI --- that continues to demand MORE compute cycles (tokens on thinking anyone) rather than less with each generation.

I agree that it is a bubble.

But the "round tripping" kind of makes sense. OpenAI is not listed, but if it was, some of the AI investment money would flow to it. So now, if you are an AI believer, NVidia is allocating some of that money for you.

The real question is not whether this is a bubble since as you mentioned even if AI settles into a somewhat useful semi-mainstream tech, there is no way any of the likely outcomes can justify this level of investment.

The real question is what are we gonna do with all this cheap GPU compute when the bubble pops! Will high def game streaming finally have its time to shine? Will VFX outsource all of its render to the cloud? Will it meet the VR/AR hardware improvements in time to finally push the tech mainstream? Will it all just get re-routed back to crypto? Will someone come up with a more useful application of GPU compute?

Ai is already in semi-useful mainstream tech. There's a massive misunderstanding on this site (and other neo luddite sites) that somehow there is no "long tail" of business applications being transformed into ai applications.

any examples?

Current systems are already tremendously useful in the medical field. And I'm not talking about your doctor asking ChatGPT random shit, I'm saying radiology results processing, patient monitoring, monitoring of medication studies... The list goes on. Not to mention many of the research advances done using automated systems already, for example for weather forecasting.

I'm getting real "put everything on the blockchain" vibes from answers like this. I remember when folks were telling me that hospitals were going to put patient records on the blockchain. As for radiology, it doesn't seem this use of AI is as much of a "slam dunk" as it first appeared[1][2]. We'll see, I guess.

Right now I kind of land on the side of "Where is all the shovelware?". If AI is such a huge productivity boost for developers, where is all the software those developers are supposedly writing[3]? But this is just a microcosm of a bigger question. Almost all the economic growth since the AI boom started has been in AI companies. If AI is revolutionizing multiple fields, why aren't relevant companies those fields also growing at above-expected rates? Where's all this productivity that AI is supposedly unlocking?

[1] https://hms.harvard.edu/news/does-ai-help-or-hurt-human-radi...

[2] https://www.ajronline.org/doi/10.2214/AJR.24.31493

[3] https://mikelovesrobots.substack.com/p/wheres-the-shovelware...

Ok, but i am asking for uses for LLMs specifically.

Of course i agree ML has already helped in many other areas and has a bright future. But the thing everyone is talking about here are LLM's

"The bubble will pop any minute now, any second, just you wait" is cope.

Even if AI somehow bucks the trend and stops advancing in leaps? It's still on track to be the most impactful technology since smartphones, if not since the Internet itself. And the likes of Nvidia? They're the Cisco of AI infrastructure.

The dot com bubble popped. It doesn't mean that the internet wasn't successful, just that people got way too excited about extrapolating growth rates.

AI is here to stay, but the question is whether the players can accurately forecast the growth rate, or get too far ahead of it and get financially burnt.

The importance of the Internet didn't prevent the .com bubble from bursting.

Amells like yahoo driven 2000 bubble. Definitely short every ancillsry business involved

You know you can sell inferencing at near 100% margins, right? More, even.