Nvidia dismisses "circular financing", says every $1 it invests brings back $100
invezz.com
invezz.com
who is going to pay back the money nVidia invests in AI labs, AI datacenter companies if the models are being served dirt cheap.
the Chinese are not the only competitor - Amazon with their Trainium, Google with their TPUs etc.
Nvidia might have a moat on training but on serving it's gonna be a blood bath.
But for now they're capturing 80% of all the AI spend so they gonna keep making money.
The fallacy I see repeatedly is someone spots a legitimate issue that could hurt Nvidia and by the time they have stood up the challenge to pull that off, Nvidia has pivoted and addressed it. Or more recently, they just acquired it like Groq.
For your premise to hold, you're asserting Nvidia is blind to inference. And yet his public positioning suggests otherwise.
https://qz.com/nvidia-gtc-2026-jensen-huang-keynote-takeaway...
What makes you think they've hit some sort of metaphorical iceberg and all they'll do before they sink is rearrange deck chairs?
the bet is against the high margins in inference - when other capable players have entered the market as models become commoditized and the inference serving chips as well. Cerebrus ai etc are already showing custom silicon can make a dent while being served cheaper & faster.
That is, revenues may be unusually cyclically high.
It's going to be hard for frontier labs to keep spending at this rate without starting to make money. And even if they do, lower cost alternatives will likely impact at least to -some- extent how much of that revenue nv gets.
Compare and contrast with Tesla.
It still prices in revenue growth.
It is possible that nv maintains an absolutely dominant market position and total amount spent on GPUs continues to rise.
It's also possible that either of these things doesn't happen.
And this is why the stock remains high. This hasn't even started to make a dent in Nvidia's bottom line yet.
These comparisons to Enron are absurd when Nvidia is generating this much cash flow.
Let's see the other alternatives come online and start taking away sales.
What is this?
Demand functions (price as a function of quantity demanded) take all kinds of shapes. Veblen goods are the silly example of wrong-sloped demand [1]. The in-vogue example of sigmoid demand, however, is hot water–make hot water (or lighting, for that matter, as another comment today pointed out for LEDs) cheaper and there is a limit to the things we want hot water for. Halving the cost of hot water doesn't induce much new hot-water demand, it increases demand for other goods and services.
Not everything is an Enron
In particular, the "circular financing" agreements look very structurally similar to things like the Merrill Lynch barges. They're not exactly the same, but Nvidia's statements in the source article make me more rather than less concerned; does it just so happen to be the case that their investment targets all want to spend lots of money on Nvidia products, or does an Nvidia investment come with implicit and unaccounted guarantees that the target will spend lots of money on Nvidia products?
Kind of reminds me of the current lack of supply of GPUs and ram to consumers.
You could make an argument that maybe this is similar to oracle (I think?) in the com bubble financing networking gear to customers.
I still think that misses the mark since the customers using hardware are have demand for computer by their customers.
The WSJ recently reported that there’s around 3 trillion in off balance sheet liabilities floating around in AI. It’s very unclear where the $3 trillion to pay those bills will come from.
Nobody is saying it’s “illegal” but it was news in the WSJ as the companies using creative accounting aren’t exactly going out of their way to make sure everyone knows that this $3 trillion in liabilities exists.
I think there questions for the commitments your talking about but they are not due today and I suspect when spread out over the life of the commitment are dwarfed by cash flow.
NVDA hasn't sold any stock to the public since 1999. If they want to trade shovels for ownership stake in the mines - good for them.
They have issued billions corporate bonds, but buyers like Goldman Sachs and J.P. Morgan have armies of analysis and lawyers.
Nvidia's financing is disclosed. Enron lied about its schemes.
I've also seen zero evidence that Nvidia is extending this credit to related parties to put in sham orders–that was part of Enron's shtick, too.
There is nothing illicit or illegal in anyway about what NVidia is doing. It's reasonable business practice, and people on HN are simply ignorant to think otherwise.
NVidia is very aware of the risks it entails, but has the money to cover those risks.
1. The equity investments Nvidia has made in its customers.
2. The guarantees/backstops it has extended to some of its customers.
3. Vendor financing.
The vendor financing is the least interesting of the bunch. Nvidia has already disclosed that when it provides vendor financing, the average customer pays in less than 60 days. These are not long-term financing arrangements and virtually every big company sells on these type of terms (net-30, net-60, etc.).
The equity investments and guarantees are where there is room for legitimate debate.
The guarantees dwarf the equity investments. If there is a shenanigan, it's going to be there.
A problem: the line between the guarantees and traditional vendor financing is blurry–one could argue use commitments are no different from repurchase commitments.
I agree that the guarantees are where the risk is.
First, under US GAAP accounting rules (ASC 606), these are absolutely not repurchase agreements. The customer takes title to the asset (the chips) and Nvidia does not have a contingent obligation to repurchase the asset. Providing a contingent guarantee to purchase services is not a repurchase under the accounting rules, but of course you can have legal accounting and still have a problem.
As I've made public market investments in and traded in this space, I've done some math on the guarantees and what came out was this: relative to Nvidia's current earnings, the guarantees amount to approximately a quarter of a year's revenue at the guarantee cap.
That's my own analysis and I'd encourage anyone who cares to run the numbers themselves. It's easy enough as Nvidia is publicly traded.
The thing that differentiates Nvidia from previous vendor financing examples like Lucent in the 1990s/early 2000s is that its margins are huge. So what I see, based on the current numbers, is that in the really ugly scenario, Nvidia has to live with depressed earnings, no stock buybacks and a weaker (but still comparatively strong) balance sheet for a number of years. This is a stock problem, not a solvency issue.
The wildcard is if Nvidia keeps extending big guarantees, or starts using debt to do so, to the point where the commitments are expanding faster than its cash flow. At that point, the risk obviously compounds accordingly.
Which is exactly the point of the person you're responding to. What part of “but completely legal” isn't clear enough?
(Also note that illegal != illicit.)
The OP clearly is implying that it should be illegal for some reason. This is wrong - not only is it nothing like Enron (!?) but it's a great way for both NVidia and the companies building on them to build what they want.
Google+ was the fastest-growing social network of all time not that long ago.
When you're one of a pair of VC darlings that have effectively-infinite money because of -in part- handwavy promises to cure cancer and eliminate 90% of payroll everywhere, or if you're an established company that has total control over very widely used consumer products, you can do all sorts of things to manufacture amazing growth numbers.
In the case of those VC darlings, we're seeing their shift towards providing their products that are most expensive to create exclusively to B2B customers and also the shift towards justifying the elimination of most of their R&D expenditure. Every company performs belt-tightening in advance of their IPO, [0] and those two are no exception.
[0] ...which is when their finances will be scrutinized by the public and regulators...
The world is fundamentally and momentously being rewired.
I wish we still lived in an age where things were sold to cover their costs.
My money's on their product having 10% of its current user base if they charged 50 cents per month.
How much would the average normie pay if Google suddenly charged? Sure the user-base would drop.
And what? Did Google suddenly become a bad business?
I find it funny how people have these strange and hypocritical viewpoints when it comes to OpenAI and Anthropic when the hyperscalars like Google, Amazon etc, followed these exact same kinds of playbooks for years and years.
Google Searches, once the infra setup was finished, were ridiculously cheap. Not the case for OpenAI & co.
Inflation adjusted, launching most of Google's core services (Search, Gmail, Maps, etc) cost less than launching ChatGPT 5. Running them at similar scales is also much cheaper per user.
There is a point at which it's just too much.
Oh, Google and Amazon never had these kinds of humongous losses and they reached profitability much sooner.
Yes, I'm against all predatory economic behavior. Selling user data, price dumping, platforms/walled gardens/monopolies/oligopolies/cartels/etc.
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It can be manufacturing demand that wouldn't otherwise exist. It can be facilitating demand to come online sooner and smoother. You can't tell which it is by only looking at the transaction; you need to know how many dollars are going into the ecosystem as a whole for purchases of goods and services. Until Anthropic's S-1 lands tomorrow-ish, we won't have that publicly.
I'd argue that in this case, if the flywheel never reaches critical velocity, they are manufacturing demand.
Maybe I'm in the middle of the road :)
Seems like economy, scale, velocity, and even "critical mass" are related in some way, but not the same at all.
I would say it's quite possible that economies of scale can go from positive to negative without much warning.
I think it's most sustainable financially when the underlying "economy" is what drives the resulting scale-up, which usually does occur in phases or stages where each successful milestone informs the next campaign more realistically than you can get any other way.
As market demand grows beyond baseline sustainability it becomes less costly to serve each additional customer this way.
The opposite effect could occur if meeting lofty scaling goals requires an ever increasing cost of customer acquisition beyond the point of unmet initial pending demand.
When the scaling process itself is what drives the activity without being limited by the actual buying power of the ultimate consumers at any one point, things can really get ahead of themselves. Accounting practices can be so diverse that the only way to be sure whether scaling ahead of the curve was actually "economical" is after liquidation ends up occurring.
Unfortunately, liquidation of one kind or another is more likely when the scale is based on hyperbolic dreams rather than more reasonably optimistic estimates. But who's to say which is which, and the continuum between them is blurry enough without any highly interested parties trying to muddy the waters even further. Who even knows if they've given it as much thought as it deserves, or if more clear-headed thinking could be the primary factor given what there is to work with :\
Hence the designation "Hyper-Scalers".
Do you mean economies of scale?
Eh, I think it's an open question whether OpenAI and Anthropic would be buying GPUs like they are with or without Nvidia's financing. Financing customers' purchases isn't proof per se of demand creation versus demand inducement. Anyone who claims they've seen a certain fact in these financings is deluded or lying.
You need to be more specific, because there are absolutely sections of the AI economy that are clearly and presently profitable.
> Ai farms and much of Ai software world are money sucking machines
If AI farms refers to datacenters, plenty of existing ones are currently profitable.
Whose assets? Where are you getting this from to be able to state it with this level of certainty?
But here a reference; https://www.tomshardware.com/pc-components/gpus/datacenter-g...
This is just extremely unbelievable to me. I am certainly not operating at a level the hyperscalers are and have much more limited direct experience. But I do actually put various GPUs inside datacenters (and much harsher locations) and have operated them at balls-to-the-wall 100% utilization for over a decade now.
You get the typical bathtub curve of failures. Unless the hyperscalers are operating these things even more overclocked and beyond thermal specification limits than early GPU crypto miners used to do, I simply cannot believe that the average hardware life is less than the useful life of the whole chip generation itself.
I have plenty of decade old GPUs that operate today just fine. Both consumer and datacenter form factors. The failures tend to be board-level like capacitors and such, so if you are operating at a massive scale partnering with someone who can fix those relatively cheaply is not all that difficult either.
It could be that these H200 and above class sort of stuff is engineered extremely fragile, but I seriously doubt it. The prevailing "common knowledge" pre-AI for GPUs were that they'd burn out in a year or two of heavy use, and that was simply untrue. I saved a ton of money buying batches of used units because everyone was terrified of this - and had no more early failures than I did buying brand new after basic refurb of re-pasting and putting a new fan on them.
I've been pitched data-center deals. They depreciate on an 18- to 24-month schedule, well under the Tom's Hardware terms. The ones who went online a year or two ago aren't losing their chips like ducklings through a storm gate; if anything, their resale value has remained remarkably stable because compute production is the bottleneck.
You've given a source (a great one, btw) for depreciation but not revenue. If you can name a company, I can look if I have a public source that confirms what I know. But broadly speaking, no, unit economics in the AI economy is weirdly sound, though I suspect it's because every non-AI CEO is blowing out their budgets on frivolous spending.
If you haven’t read “Smartest guys in the room” it’s important reading now as it’s scary similar to what’s going on now across AI. Nobody has alleged anything illegal but the net effect on building a house of cards in the AI bubble can be the same.
And that gap in where people are watching (AI company press releases or the creative accounting going on) explains why those watching this are saying “oh no, we’ve seen this movie before” when others are blinding all rah rah about the AI bubble going on forever.
Have you bothered to look at the finances of Nvidia's AI clients?
None of them are making any money. They're borrowing money they don't have in oder to buy from Nvidia. And now some of this money is coming from Nvidia itself.
In a round about way, Nvidia is buying it's own product.
It's pretty clear that this sort of thing can't continue indefinitely --- just like any Ponzi scheme.
Who are you thinking of? Because yes, I have, and they're not in line with the YouTube influencer consensus.
All the "frontier" AI vendors are borrowing money to invest in AI (and buy from Nvidia). None of these Nvidia customers are actually making money from it.
Anthropic and OpenAI are two cash burning machines that Nvidia has invested billions into --- so they can continue buying from Nvidia.
Bottom line: A lot (if not most) of Nvidia's cash flow is borrowed money --- and some of it is borrowed from Nvidia itself.
Some of it isn't even "cash flow". It's contract futures being counted as cash flow --- a la Enron accounting.
What is your source for Anthropic being cash-flow negative?
On a GAAP basis (including stock compensation), Anthropic is likely still unprofitable.
At the same time they gushed about a small quarterly profit using "Enron" accounting, they borrowed $30 billion more.
And this is just the tip of the "Enron" game being played here.
By utilizing these structured finance vehicles, Anthropic has sequestered massive hardware deployments entirely off its corporate balance sheet.
https://finance.yahoo.com/technology/ai/articles/anthropic-s...
Anthropic just announced it's second "profitable" quarter using "adjusted operating income".
This reportedly means they achieved this remarkable goal by excluding some really big expenses like revenue sharing and the cost of model training.
https://www.msn.com/en-us/technology/artificial-intelligence...
The amount of money Nvidia has put into the ecosystem is much, much less than money coming into the ecosystem from actual customers who are willing to pay for the products!
The idea that somehow Nvidia is financing the entire AI industry is laughable. The numbers do not add up at all if you look at the numbers of people paying for Google cloud GPU compute, AWS GPUs, Azure GPUs, Nebius, Coreweave, etc, not even including companies like Fireworks, BaseTen, Together AI, etc .
The reality is this, enterprise companies are spending HUGE amounts of their money on AI products because they are gaining value from them. This money (which doesn't originate from Nvidia) is flowing into the ecosystem. The money being spent by enterprises combined is far, far more than Nvidia puts in.
Yes, it is --- and this is not something I said. This is an absurd extrapolation done by you.
But there is no denying that Nvidia is investing billions in it's own customers (aka "lending") and others up and down the AI infrastructure stack.
And all of it has one objective --- to create and enhance what is being marked as "sales" for Nvidia. In a round about way, Nvidia is buying at least some of it's own product.
https://www.cnbc.com/2026/05/09/nvidia-embraces-ai-investor-...
Which is a fundamental difference. When Apple extends me credit to buy an iPhone, that isn't circular financing in a problematic way. I was buying the phone anyway, the financing just made it easier.
Generally, the fact that most non-Boomer people simply don't have the means to even save up for basic consumer goods like cars, furniture or a phone but have to go into debt instead is scary. Our entire economy has become a house of cards.
Oh hell yeah. But a lot of folks are treating the existence of customer financing as damning per se. The scale is daunting. But the scale of the entire AI enterprise is massive.
Yeah because it's gotten completely predatory. That is what people are getting ever more pissed off about - advertising, social media and gamification (have you seen the ads for Tiktok, Whatnot, Wish and whatever else goes with "live shopping" recently?) leads people to go way deeper into credit than they can afford.
That makes sense. It's still an emotional misplacement. Your and my relation with our consumer lenders has nothing to do with Nvidia's relationship with OpenAI, Anthropic and SpaceXAIwhateverthefuck.
Yes, but your original comment said that Apple's financing "isn't circular financing in a problematic way". It might not be the classic way of "circular" financing but it is highly problematic.
And I'd even go as far as to saying that, yes it is a form of circular financing, because Apple hands you money to spend that money on a product they make at much less cost than it costs you on paper and, that's the more important thing, serves as an entrypoint into their highly effective walled garden called App Store.
Yes --- and the scale of the money being set on fire is epic. And if/when the burning comes to a screeching halt, the resulting crash wil be likewise.
If this isn't a house of cards, AI companies' customers. The companies and individauls ponying up for a Claude subscription or compute through OpenRouter.
Customer financing isn't inherently fucked. It's just highly suspect at the scale Nvidia's doing it. There was another thread where I noted that Nvidia's investments are literally monetarily significant, to the point that I expect them to start being directly referenced in the Fed's beige book [1].
Any one actor has finite cash flow (plus their cash-on-hand buffer). Directing cashflow towards inference necessarily directs it away from something else. Either these companies are spending less on something else, or they are returning less profit.
You can't analyse expenditure assuming income is constant, because all expenditure decisions will be made with a view to how they affect income.
If your argument is that a bunch of consumer-facing companies are collectively suddenly making trillions more in revenue due to adopting AI... well, I have a pretty nice bridge for sale here
In general, political discussion suffers a lot from far too much of it being simply "I am obviously right, you are an idiot and/or malicious if you believe the other guy". This is not a dig at you personally, look at any political discussion and you will see that 99% of it is like that. Our public sphere would be in better condition if more people pushed back on it. So no, I don't think anyone should accept "proof by ridicule/slur".
As I understand it they are risking that even if the major AI labs fail all the compute capacity that's been built out will remain in demand at sufficiently high prices.
Companies who pay 99$ to make >99$ in return. I am not saying it works in all cases but that's the idea when a company spends money.
> Because it seems like so far everybody is losing money with no reversal of this trend in sight
I am not sure what you are seeing: Anthropic (as one of only two major companies that do just AI) is starting to return profits, while demand for AI is accelerating and, clearly, compute is maxed out. And I mean: On the entire planet. They are turning profits despite everything being in full buildout mode.
You, when their circular financing scheme fails and you're the one left holding the bag as your government says "they're too important to let them fail".
So for example if you invest $100 in a farm and get a return of 10%, where does that come from? The nutrients in the soil, the effort expended by the workers, and the power of the sun to turn seeds into food. All value comes either from finite resources in the ground (nuclear, oil, ...), from solar power, or from human effort (work, innovations, etc.)
So can you trace back Nvidia's incredible 10000% return on investment to any of these sources? Which ones?
"Economic value" is great stuff and kind of all-encompassing.
But a lot of it is mainly moving money around after wealth has already been created, sometimes generations earlier.
To this day the lion's share of "creating wealth" is traceable to natural resources.
Value also comes from technology which you seem to suspiciously remove
> or from human effort (work, innovations, etc.)
The only thing "suspicious" here is your lack of reading comprehension.
> It's not a zero-sum game.
Well, it is. Thermodynamics. Earth is pretty much a closed system, except for the sun.
So for example if you invest $100 in a farm and get a return of 10%, where does that come from? The nutrients in the soil, the effort expended by the workers, and the power of the sun to turn seeds into food. All value comes either from finite resources in the ground (nuclear, oil, ...), from solar power, or from human effort (work, innovations, etc.)
Surprised basic stuff is now being questioned.
> Total prosperity of world has increased inflation adjusted over 100 years. Why?
Clearly, because people have worked to bring value to the world. But, most people actually doing the work see very little of the profits.
I often see this argument, "you have access to food, housing, healthcare etc., so that means that the system is working great". But you're missing the fact that me, my parents, and their parents, and their peers, have all worked to create all of that stuff. While simultaneously working to create the private jets and luxury yachts for the 1%.
In a more fair system we'd have twice as much prosperity, or work half as hard.
We're already seeing signs of this strategy from Open AI and Anthropic warning about the dangers of AI and the need for safety regulations. None of that stuff matters if China is not also on board with it.
You could say that about any historically inflated valuation all the way back to the tulip mania. Either the expected profit materializes or it doesn't.
> We're already seeing signs of this strategy from Open AI and Anthropic warning about the dangers of AI and the need for safety regulations
I would read this as a desire to pause training to be able to present a profit in anticipation of the IPO. The major AI labs mad scramble to IPO is if anything a sign that they aren't at all confident in the valuation. If they were they would be no hurry to cash out.
And I'd argue the timer started in 2023.
Reminds me of this:
>I went through this Ford engine plant about three years ago, when they first opened it.
> There are acres and acres of machines, and here and there you will find a worker standing at a master switchboard, just watching, green and yellow lights blinking off and on, which tell the worker what is happening in the machine.
>One of the management people, with a slightly gleeful tone in his voice said to me, “How are you going to collect union dues from all these machines?”
>And I replied, “You know, that is not what’s bothering me. I’m troubled by the problem of how to sell automobiles to these machines
- Walter Reuther, Nov. 1956 https://quoteinvestigator.com/2011/11/16/robots-buy-cars
Trust me, there are many other people like me in the world and the enterprises are spending even more.
There is more money flowing into the overall AI ecosystem (by far) than the money Nvidia puts in.
The idea that Nvidia is artificially creating the whole demand is laughable and doesn't add up.
Power tools for knowledge workers, which is what we are getting, isn't enough to save it.
> Trust me, there are many other people like me in the world and the enterprises are spending even more.
Awesome, let's do some math here.
I'll do both $1k/month and $3k/month, please follow along. To make the math even simpler to follow, I'll actually reduce your amounts. ~$800/month will get us about $10k/year and ~1600/month will mean about $20k/year, makes for easier divisions.
Current total investment into AI is at least: https://isaiprofitable.com/ -> $1.8tn.
So $1 800 000 000 000.
From what we know about current AI tech, about ever increasing hardware prices, about ever increasing electricity prices, about the ever increasing DC construction prices, AI companies need to invest a fair chunk of money each year to keep the whole thing going, let's be SUPER conservative and put that amount at $200bn per year.
So:
1 800 000 000 000 + 200 000 000 000 = $2tn next year.
Then at least another 200 000 000 000 per year = $0.2tn/year.
So $2tn next year divided by $10k/year means that means that they will need 200 million yearly subscriptions to recover the money already invested. At $20 k/year would mean 100 million yearly subscriptions. Spread over 5 years that would mean 40 million yearly subscriptions and 20 million yearly subscriptions.
Then for each year, just to cover the costs, at $10k/year 20 million yearly subscriptions would be needed, and at $20k/year 10 million yearly subscriptions are needed.
So that's 60 million yearly subscriptions and 30 million yearly subscriptions.
I used Claude to extract some numbers. The total global addressable workforce that makes more than $80k per year (where an employer would dare spend $10k/$20k per year on AI) is about 100 million people. The total private population that has $10k/20k per year in disposable income is about 500 million people (excluding China, since they will for sure not use Western AIs en masse).
So that's about 600 million users (just stacking private users + how much companies would pay for their workers).
So just to break even each year, 10% of those would need to pay those crazy high subscriptions, and 5% the extra crazy high subscriptions.
For private users if they get 1% of that rate, it means that a lot of private individuals have fallen on their collective heads.
For enterprises, nobody's going to increase their salary expenses from $80k to $90k-$100k for benefits that we can't even quantity, let alone guarantee an upside of 10-25%. That kind of budget will be allocated for people making $150k or above, which makes the total global addressable workforce something like 50 million, most likely less.
I want to have what you're smoking.
Yes, demand is there. Demand to prop up how much we're investing. NO WAY. At actual prices and actual LLM productivity gains, we should probably be investing 20% of what we're investing.
A lot of people will be wiped because of Nvidia and friends. Even worse, a lot of regular people will suffer because we've distorted our societies so much due to this hype train.
If AI makes these workers even 1% more productive, that is $500 - 700 billion value annually. At an ongoing annual $0.5T return, a $2T investment (also over the next few years, note) doesn't seem too bad!
Then consider that actual studies from all the way back in 2024, i.e. the era of spicy autocomplete, before agents landed on the scene, put the productivity boosts much higher, like 30% or more. (Interestingly, this is corroborated by survey based data from the St. Lous Fed: https://www.genaiadoptiontracker.com/) Even assuming a conservative average boost of 10%, that is $5 - 7T value annually.
Add how many ever grains of salt you want to those numbers, the investment is nowhere near as out of whack to the potential revenues as people fear. This is why everybody from Big Tech to VCs to entire nation states are desperately scrambling to get in on the action.
My point is that their math is wrong.
1. There's no way China will let any of the Western frontier labs in, so that's probably 1/3 out of those $50-70tn that they'll never touch.
2. It turns out that LLMs are more of a commodity than expected because the basic tech is basically "Attention is all you need" plus a few things everyone has access to (mixture of experts, caching, batching, etc). So yes, it's a "winner take most" market, but there will likely be a healthy base of cheap models so the "collection" (price gouging) part of the cycle (or enshittification) will be hard to execute.
3. Either hardware remains expensive, in which case every N years entire DCs have to be rebuilt and then Capex needs to flood in - think highway systems being rebuilt, but instead of every 20-30 years for highways, here we'd be talking every 5-7 years.
4. Or hardware becomes cheap in which case cheap LLM hosters are competitive and problem #2 is even worse. Or the nightmare scenario for all of these investment scenarios, local LLMs become viable for most people.
I agree LLMs are already a commodity market, definitely at the non-frontier model level, but I don't think it affects monetization prospects much. After all, server compute is a commodity and yet cloud businesses have been exploding even before AI.
And compute is exactly why it won't be a "winner takes most" market. It is clear now that compute capacity is and will likely remain the biggest moat. Looking at Claude Code is instructive; arguably it was the better product, but it kept going down so much that Codex and other competitors have gained on it. Similarly, China could have the best models, but its access to hardware is deliberately limited by geopolitics, so it's likely their threat will be manageable for a while yet.
A key part of the success of AI companies will be in securing hardware and operating that infra cost-effectively via economies of scale. Hardware will remain expensive for a long time yet because all the hyper-scalers and neo-clouds are severely crunched, and all the fabs (mostly TSMC) are already at capacity even as demand keeps exploding.
And for better or worse, most of that supply will still flow through Nvidia, despite attempts from competitors like TPUs and NPUs, for the simple reason that Nvidia has the monopoly profits to outbid everyone else on the real chokepoint, which is fab capacity.
No, it's very unlikely at this point every $1 Nvidia invests brings back $100. Stating something like that is almost a red flag that things are overheating.
That's great leverage.
As long as it really is true and continues to hold true for all the big players involved then things should be OK.
Though it does imply that there's got to be a long-term source of returns which is 100x richer than Nvidia is now, and that source is willing & able to give up 100x what Nvidia can afford to spend now, or where else is the return actually going to come from?
OTOH if the leverage turns out to be unsustainable, or never was quite as extreme as estimated, then adjustments will have to occur, whether that amounts to carefully planned compensation for any shortcomings, or more abrupt developments which relieve undue pressure.
seems no one is reading the article..
So, in one aspect, like the Matrix, they're not lying: they litterally see that on the paper they're reading from.
But like in the matrix, they just need to be unplugged from the bullshit machine to recognize that this money doesn't exist in the real world.
Scientists, particularly the ones who get ragged on, you know, social scientists, are now well aware that no matter how well any given social goal works in the lab; no matter how much pscyhology they evaluate, depend on, etc, what matters is real world implementation.
Thier sheets of cash raining in from some future valuation simply do not exist in a vacuum, but they want to pretend it does.
So we're litterally watching capitalists look at their piece of meat inside the matrix, and telling us: they do not care that it doesn't actually exists, because on the Capitalism ledger, it feels like real meat.
But still, it seems that billionaires are lying left and right. It isn't just Elon.
We are not at the top of this trend yet so I do not see this as over investment.
I remember the criticism Microsoft got for investing in Facebook/Meta that gave them a whooping $15B valuation and getting 1.7% in 2007. Not all deals will turn out that prescient but a few will and make up for any duds. This is a real market.
No, it's a high risk gamble.
If the market grows enough they will win the bet, but if the market doesn't or we get a recession that dries up capital they will be holding the bag.
So for this to become true there are some number of jobs that that pay $N salary are replaced completely by LLMs that do the job for $N-0.01?
Is that what you mean by "market grows enough"
Even in a recession I think the shift towards AI would just accelerate since it is usually cheaper than humans.
The real risk I feel if what if AI is too successful and there is a lack of human demand because of dropping wages/employment?
(Then I wonder if sentient robot demand will make up for it? Although I realize that veers into science fiction futures.)
What else should they be buying? US bonds, housing?
And then the following trend will be humanoids and similar and they are barely getting started.
as long as things go up people conveniently ignore the lessons from the past.
we are long overdue for a correction and given the fear mongering oligopoly shenanigans we must be very close.
Its a mighty fine deal for Nvidia
From the article:
> I put in one, and a hundred comes back.”
> The figure was rhetorical, not a disclosed 100-times investment return.
There's a lot more words in there, but it doesn't seem to say anything else.
But the wealth, or value if you will, remains unaffected.
Money isn't wealth. It's just a representation. It used to be wealth back in the days before paper money, when a coin actually had the value it said it had.
What I came up with was Nvidia is maybe slightly overpriced currently, but a bad stock to buy or hold onto because the risk of it shrinking is significantly higher than the risk of it ever doubling again (and it trades at a tech/growth multiple). The case is far worse for Anthropic/OpenAI who, at current pricing, capture such a tiny slice of the pie it's hard to see how they will stay in business long term.
Nvidia is investing in their customers by buying their stock. Nvidia is directly buying compute from their customers. Nvidia is making "if you can't find a customer, we'll take all of your capacity" deals. Nvidia is making a ton of fake huge-number deals which are supposed to be realized over time but most likely never will.
They are doing everything they can to make that customer look like a healthy and valuable business which everyone should invest in and loan money to - which in turn flows directly back to Nvidia to buy GPUs and boost their revenue. They are essentially creating sockpuppets to keep external money flowing in so they can keep the money printer running.
And what about the purported "AI frontier slowdown" - if frontier labs stop pushing better and better models, the main way to grow the pie is more users and that will eventually stop, too. Then providers would probably stop buying new hardware hand-over-fist and move to a slower depreciation-based replacement.
But its quite obvious that while there are some similarities its simply not the same. Most analysis, so it seems, are quite surface.
Are there any deeper finical analysis on the investments of Nvidia and how they are financed?
given the stakes, we'd better hope it starts showing up soon.
Is it really that? AI is still heavily subsidized.
Apollo (credit) notes that AI isn't showing up in the bottom line of any companies besides the ones making it right now.
This isn't concerning for such a new technology, but if the trend continues it would be fatal.
Imagine how many businesses benefitted from the railroads at first - almost none because no one had freight to ship. Same kind of thing - the connective tissue is taking time.
But the catastrophic adoption of the technology could be what leads to its downfall.
My name is Charles Ponzi and I approve of this message.
When I zoom out to 5 years, it does not look like "keeps falling".
Yes, it seems very possible to me that Nvidia makes a lot of money. They are literally the largest company in the world.
Who pays? Only all the companies, desperately raising as much capital as possible, issuing new stock to do it, going for unprecedented investment rounds, burning cash reserves to fund the largest data centre rollout in history.
Who builds the things that go into said datacenters? The thing that has also raised in price dramatically in recent years?
From sub million to hundreds of millions I could theoretically see. Even tens of millions to billions. And even then I would be extremely skeptical.
But with Nvidia we are talking somewhere in the scale at tens or hundreds of billions. And that is actually very large sums of money. Even if it often does not look like it.
They are also talking out of their asses, as they are massively overselling their capacity, and everyone is on a 5 to 10 year backlog.
--- Bernie Madoff
If they put all of their money in the chip business they'd have major problem once someone else makes good enough chips in volume. And Chinese are obviously going to do that very soon.
But if NVidia owns comapnies who buy chips it's winning no matter who they buy the chips from.
With what NVidia is doing, it's making the ride better for themselves and provide a soft cushion for when it ends.
The only way for NVidia to lose is for AI to fail utterly. Which is pretty impossible.
Isn't this a contradiction?
It’s not circular because we put a little bit of money in, and a lot of money comes back
Mega eyeroll
God heavens. It's worse than 2000/2001!
Gotta start selling my portfolio
Your salaries if AI works (and takes your jobs), and your taxes if it doesn’t (bubble bursts, your taxes bail them out Becasue it’s too big to fail).