Realistically, they're worse than a central bank, because they can't exactly expand supply monotonically like a normal central bank. Nor do they realistically control rates.
The material cement that allows chips to exist above it.
And the platform is made of time: ours.
The mint?
Everything influences each other with varying gravitational pull
At one point the mental model was more like a web, but spacetime with mass matches the model more closely
at any given time there is a finite amount of it most easily observed in currencies’ relative price to another currency, and its movement between owners causes distortions in asset prices
most people I’m around and most trading indicator developers I’ve seen don’t seem to conceptualize the flow of value around the economy. so it feels niche and maybe visualizing this mental model can help many people
[1] central banks can functionally delete money in their bond purchase and roll off programs
Both PS 5 and Xbox are based on AMD APUs and both serve the AAA market quite well. GTA 6, Assassin's Creed and CoD are probably good enough indicators that the performance is enough, even if there is always room for more (as PC ports show). The PC market will also probably be fine even if stagnation in perfomance gains has been creeping in for a few years now.
[0]: except Nintendo which relies on NVIDIA although their APU there focuses more on efficiency than top performance.
> I really don't think it's an if question but a when because it almost feels like an afterthought
I feel your reasoning is very weird. Are they losing money by selling consumer GPU? Just because the profit isn't that much compared to AI it doesn't mean that it's negative, and for-profit companies are not known for leaving money on the table. Apple doesn't reveal how much Apple TV+ makes for them either but I don't see it be gone anytime soon.
DLSS 5 is trying to relight and retexture the scene using AI. DLSS 4 is just trying to take a lower quality image and upscale it using AI
If you can fab 1000 chips, and can sell some for $500 and some for $80000 what are you going to do?
The game GPU is at once profitable, but causes them to give up far more profits than they're gaining from it.
They're maintaining the game market to have multiple markets and not go all in, but it's strategic hedging at this point. When NVidia makes a gaming GPU instead of a data center GPU they are leaving money on the table in the short term since they're constrained at the fab level.
Apple TV is at least a growth market for them, whereas gaming is sort of capped and clearly a tiny piece of nvidia’s revenue atm.
Nvidia still will ship gaming products. The upcoming RTX Spark laptop APUs are still gaming-capable - we also have Blackwell gaming GPUs and the Nvidia-powered Nintendo Switch 2.
People echoed this sentiment during the crypto mining crunch, and we still got gaming hardware designs after that blew over. One of CUDA's core value props is the consumer market, and Nvidia probably won't surrender it unless hardware becomes unreasonably scarce.
https://ourworldindata.org/data-insights/nvidias-revenue-fro...
The GPU crunch came because cards like the 3060 were extremely cheap and could outrun most sub-$1000 ASICs at the time. The dedicated crypto GPUs were too-little too-late; hundreds of thousands of ordinary CUDA-capable GPUs had already been repurposed for mining by the time they launched.
Edit: about half in fact! The rest is shared between the other traditional gaming types.
That'll buy you:
- a set of used golf clubs
- a couple years of fishing licenses, bait, tackle, used fishing rods and line
- a couple really entry level tennis rackets, balls, and court reservation fees
- maybe a used bicycle
- a decent pair of running shoes from last year
The ssd example was to illustrate how much more expensive pc components have gotten just a few years before you could buy it for 50$
The only developers chasing cutting-edge hardware features are the AAA studios and I honestly think a lot of them would just die before successfully relearning how to make games that play well instead of just look pretty.
And it’s maybe 5-10% of their revenue at lower profit margins.
Consumer cards just don’t matter very much to nVidia anymore.
In 2020 it was half of their revenue.
It's still profitable, it's their original raison d'etre, and there's no real reason for them to stop even if it its rounding error on their regular business.
Probably will never, ever see an Nvidia card with >32GB of VRAM though unless they start making dies that lack LLM performance like the gimped ethereum mining cards.
It continues modern trend of chow companies don't want consumers to truly own anything. Finance a car, pay a monthly subscription fee for heated seats, rent a phone, stream a movie, get rid of physical media, rent a GPU.
But if GeForce NOW doesn't take off, and they get convinced that the AI bubble will not pop, I could see them pulling a Micron and ending their consumer product lines.
It's kind of weird. nVidia kind of has the PC market cornered, but AMD has had the last couple of generations of Xbox and Playstation. Also, they power the Steam Deck/Machine, and Valve has been contributing a lot of AMD graphics features into the Linux drivers. There is a world where AMD (and maybe even Linux on AMD specifically) becomes the de facto standard for gaming.
I have been getting the vibes that Sony is positioning themselves to back out of videogames. I don't think we're going to see a PS6.
Inflation is.
But I think the undersold part would be inflation is likely far more correlated to rate and values the stock market going up, than the disclosed and reported inflation numbers given to you by the people directly responsible for monetary adjustments.
Sounds great until the wheels fall off because MBAs decided to save a few bucks on "unnecessary" bolts to hold them on
Intel is going nowhere but we all knew that anyways.
And again, you must not be paying attention, AMD is doing exactly what they said they would. No flagship for RDNA4 (just like RDNA2), RDNA5 flagship (10900 XT) coming right on schedule
Demand for Nvidia cards has outstripped supply even on the mid-high cards specifically because they do better with local models than AMD cards with the same VRAM do broadly.
AI has completely broken the PC gaming market (and PC/Laptop market more broadly but gaming is really hit hard because it's the exact components that matter for both that overlap).
Nvidia had the mind share among gamers but so did Intel once, inertia only lasts so long they've been thoroughly intent on burning that to the ground for a while, back to the post 1080's
If RDNA5 is good (and 4 was it closed the gap on RT) they'll been in a solid place to take the spot if Nvidia do cede the ground.
I have a 7900XTX the last flagship card AMD did (about equal to a 9070XT for raster but 24GB VRAM not 16GB) and it has been and is a stellar card for gaming (let down only if you care about RT and the games I play don't have it).
Flawless under Linux, weaker on the AI behind nvidia but it runs Qwen surprisingly well and I didn't and don't care too much about that except to poke it occasionally.
RIP. My first gaming ~GPU~ (we called them 3d accelerators back then) was a Diamond Monster II with a 3dfx Voodoo 2 chip.
Oh shit, I had file deleted that. I remember now. I think I used that with the first N64 emulator, I think Project something to play Turok the first person dinosaur hunter game. Life before the internet was better I think.
The prices of gpus are nuts right now due to demand, but theoretically speaking demand causes more supply to appear and thus decrease prices* and then gamers can reap the benefits of massive amounts of investment.
* or at least thats what people on this site keep telling me.
You could make the same argument for why is AMD still making processors for the consumer market or APU’s for the PlayStation/Xbox current gen and more importantly next gen.
In a gold rush as a shovel seller it’s dangerous to only be selling shovels when the gold rush can end/reduce at any point.
AMD has powered 2 generations each of Sony and Xbox consoles, Steam deck and shops a ton of GPUs especially if you count APUs. And then Intel literally ship more GPUs than Nvidia and AMD combined.
The gaming market doesn't need Nvidia. Especially as AAA is cratering.
It really shouldn't: the most money in games are those games that don't require high end GPUs.
Game consoles like PS5 have been AMD for a few generations. Steamdeck/Steam Machine are AMD.
But really, Nvidia has no reason to leave gaming behind. They can just start dialing back their ambition on the gaming side and providing GPUs that aren't too useful for inference or training. All gaming needs is stability so that devs can aim for something. Games looked great 20 years ago and they'll look great 20 years from now, as long as developers know what they are building for.
like can we get some new more interesting entertainment? maybe that's just me but all games look and feel the same now or worse dumbed down sometimes where even puzzles in the game have like basic or grindy aspect to them ...
https://en.wikipedia.org/wiki/Islamic_banking_and_finance
Imagine a scenario where the AI bubble bursts and AI companies and neoclouds go bankrupt en masse, and then a huge rebound occurs when AI has a delayed takeoff. Nvidia ends up with a massive amount of compute on its hands from its backstop deals, and it also owns assets from failed companies when profits start to grow. New startups running using Hugging take the place of OpenAI and Anthropic when their compute assets are divided between survivors like Nvidia, Microsoft, Alphabet, Meta.
If/when there is an AI crash, any number of small startups can buy compute for the price of electricity without anyone wanting to buy them. That is when the real innovation happens. The top of the hype cycle is usually more about getting rich quick and buying and shutting down competition.
Nvidia booked $496 million in interest income in Q2 alone [1].
[1] https://www.sec.gov/Archives/edgar/data/1045810/000104581026... page 15
Context of the discussion is: Nvidia is central bank of AI.
Nvidia's guarantees and commitments are absolutely debt like and dwarf its equity investments.
Now you are saying investments are "debt like" but that's not common way to talk about generic liabilities.
And then when the kings ran out of money, they sacked the Knights and whoopsies, looks like the knights had no real money as they spent it as quickly as they could maintaining their financial network... Sound familiar?
Let’s look to the past:
https://www.history.com/articles/1929-stock-market-crash-war...
https://portfoliocharts.com/2021/12/16/three-secret-ingredie...
Gold, small cap value, long term treasuries all have done well historically.
Maybe THAT'S the real recession indicator.
The Internet didn't stop expanding in 2000-2001. Everything got drastically larger over the following two decades. The multiples on earnings did implode for ~15 years however. MSFT stock for one example went nowhere during that time and compressed down to a near single digit PE.
AI will be a minimum of 10x larger in most every regard 20 years out. That has nothing to do with shorter-term multiples given to these companies in relation to the hyper fast growth they have been riding early in the boom.
Note that the Fed has a $6.7tn balance sheet [1]. (This is a silly comparison. But still fun.)
The real comparison: Nvidia's $500+ billion of investments and commitments [2] is substantially more than any easing the Fed has done in the same time [3]. Monetarily, Nvidia is creating a lot of money in our economy.
The good news: I have seen no evidence Nvidia has borrowed against its stock or otherwise linked its equity value to these commitments. Its stock could crash without causing–as long as its cash flows continue–a credit crisis through its investments and commitments.
[1] https://www.federalreserve.gov/monetarypolicy/bst_recenttren...
[2] https://www.sec.gov/Archives/edgar/data/1045810/000104581026...
[3] https://www.federalreserve.gov/monetarypolicy/bst_recenttren...
Bank takes $90 of that deposit (assuming 10% fractional reserve rule, no idea what the actual number is), and loans it out to party B, who pays it into either the same or another bank. Same rules apply -- except now it's down to $81 being loaned out, and so on and so forth, until that 100$ generated $1000 in total bank deposits.
edit: of course, it's never actually directly like this, a lot of other factors are involved, maybe the money is spent, maybe no one wants to borrow it, etc etc -- so it's more complicated but that's I think what they mean
Even if this money eventually gets loaned out eventually by one of NVIDIA's customers putting it into a bank, it isn't NVIDIA inflating the money supply, it's the borrowers, no? Or is this an ineffective way to look at things?
Quite why this persists when the Bank of England debunked it in 2014 [0] is anybody’s guess.
Just another of those concepts that is neat, plausible and wrong.
[0]: https://www.bankofengland.co.uk/quarterly-bulletin/2014/q1/m...
Yes, there is. We just changed how we measure the fraction from a crude one like a reserve requirement (which takes zero account of asset quality or funding source) to finer and more-robust ones like capital and liquidity reqirements.
Banks still have to hold reserves. And those required reserves constrain their lending and thus the amount of money they can create. The limits just aren't the old-school reserve requirement.
Liability side controls don’t work.
Which country's capital and liquidity requirements are you thinking of?
Because Basel III dictates ratios. These are hard limits on lending.
There’s no hard limits. They are ratios which are preprepared because a bank knows how big its sales pipeline is and that takes time to complete.
Nothing is limited in quantity. Even the silly SLR they have in the US is a pricing limit, not a quantity - as we see every time somebody moans about how much the deficit has gone up.
Ratios are limits!
> Nothing is limited in quantity
Of course it is. At a certain point, compliance will say you literally cannot issue loans of certain types because of capital or liquidity ratios. If compliance fails to do that, regulators come in and yell at everyone.
The capital ratio is 20%. I sell $20 of capital in exchange for $20 of deposits which are deleted.
And then I do the same tomorrow.
All ratios met. No limit on loans.
Which is, you know, the entire risk that people are worried about.
Bankruptcy is deflationary. The same way credit creation makes money bankruptcy (and any other reduction of debt, including through repayment) destroys it. It's why financial crises were often followed by deflation in gold-based economies.
They shouldn't have been a TA. Modern money is destroyed in three ways: through taxation, defaults and the extinguishing of debts.
Now to expand GP's example (still simplified):
- A borrows $100k money to pay B toward building a house. B puts $100k in their bank.
- C borrows $90k from B's bank toward building a house to pay D. D puts $90k in their bank.
- etc
So, houses were created (or other services were provided), and that's the real multiplicative factor. If banks loan out 90% of the cash stored (i.e. keep 10% in reserve [1]), the multiplicative factor of value creation in the economy is 10x the original amount of cash deposited in the first bank.
Now, if all of us withdrew our savings at once or sold all our stocks at once, we would have an economic shock analogous to that which resulted the Great Depression. That's why for banks, we have FDIC insurance - to mitigate such a panic so that money can serve its value-multiplicative role when it's not being actively used for anything else by the person owning the money. That's also why a positive (but low) inflation was originally considered economically healthy - so that people put their money in banks/market rather than under their mattresses gradually losing value. When interest rates are low, that encourages people to put their money into riskier (non-FDIC-insured) investments with higher growth potential, like a balanced portfolio of stocks/bonds/etc to avoid losing value to inflation, resulting in more economic growth.
[1]: https://en.wikipedia.org/wiki/Fractional-reserve_banking
It's the other way around. When a bank loans someone $1,000, they create a $1,000 deposit (their liability) and a $1,000 asset (their loan). Loans create deposits.
The Treasury can mint coin. But that's basically negligible in modern economies.
Unfortunately this kind of thinking is why so many people seem to think the big AI labs are totally killing it the second they make a “profit” on inference. Yes if you ignore the balance sheet all looks fine. Unfortunately companies go bankrupt because of their balance sheets, not operating profits and losses. You can make money on the direct COGS on every transaction and still be bankrupt.
It’s been zero in the UK for hundreds of years.
The 2008 global financial crisis was a result of this, so not a made up worry.
The GFC would not have been prevented by a reserve requirement. The problem didn't originate in the banking system, and transmission to the banking and payment systems wasn't reliant on leverage per se.
Who said anything about that?
> The problem didn't originate in the banking system
I guess i consider mortgage lending part of the banking system, but no matter - my point is it was created by financial institutions lending in ways that created money, helped their bottom line in the short term, and were unaccountable. That’s why i’m worried about how much of the US economy is created by private companies creating money out of thin air by loaning in loops.
But everyone is now chasing the same opportunity (AI and its dependencies like hardware and power) that will drive prices higher in those sectors until supply responds (or demand disappears).
No. Most money in modern economies is created by private parties [1].
[1] https://www.bankofengland.co.uk/-/media/boe/files/quarterly-...
They are regulated as bank under fed.
Currently. But nothing requires is. Banks can uniquely create M1. Nvidia is creating M4, which turns into M2 through the money markets, which turns into M1 at banks. It's more convoluted and limited than the Fed creating monetary base to increase M1. But the net effect is similar–more M1.
Nvidia is vendor financing its output.
An ai company order $100m of GPUs. Nvidia delivers and holds onto that debt as an asset - like a bank loan.
The production company uses AI to create better plant and purchases $100m of AI tokens to do so. The ai company hold that debt like a bank loan
Nvidia requests $100m of production based on its $100m of orders. The production company holds that debt like a bank loan.
You now have a monetary loop. Take a single $10 bank deposit and Nvidia pays the production company, who pays the ai company who pays Nvidia. Run that round the circle a few million times and everybody has been paid.
Rinse and repeat.
No. For the same reason that oxygen being transported into and out of the body doesn't mean there was no oxygen.
First, under US GAAP rules (ASC 606), you cannot recognize revenue from a vendor-financed sale unless it meets certain criteria, the biggest one of which is: it has to be probable that the buyer will actually pay you. If a default is likely, revenue recognition is deferred until cash changes hands.
Nvidia's massive revenue is therefore not from a bunch of dubious vendor-financed sales to counterparties who don't have the money to pay and need a fraudulent scheme to make the arrangement work. Furthermore, Nvidia, by its own disclosure, indicates that when it extends financing to customers, they pay, on average, within 2 months (53 days to be exact). So these are not years-long extensions of credit.
This doesn't apply to Nvidia extending trade credit and this description of bank money creation isn't even the accepted version today anyway.
Regarding velocity: a receivable on Nvidia's books isn't in M1 or M2 and nobody accepts it as payment. The AI company will still settle its bills with vendors and pay its employees in bank deposits. The "$10 running round the circle a million times" story is just netting. Clearinghouses have done this for centuries with literally 0 effect on the money supply.
If the OP's production company can't actually deliver $100 million of goods, someone has to write it down and no amount of velocity makes the company solvent. Net-60 payment terms are ordinary trade credit that any major B2B supplier extends. It's no different for Boeing, Caterpillar or [name a major manufacturer). If you're going to call this "money creation," you're saying that every net-30 or net-60 invoice is "money creation" too, which is ridiculous because it's patently false.
None of this is to say that there aren't legitimate circularity concerns about Nvidia, particularly around its equity stakes coming back as GPU orders. There are. But even those are about revenue quality and counterparty concentration, not monetary aggregates. Trying to make this a monetary argument when it's not actually weakens the circularity argument.
Of course it does. It's M4. Which turns into M3 through the money markets. Which creates M1 through banks.
Nvidia extending commitments creates M1 via a similar mechanism to the Fed buying Treasuries, thereby increasing deposits at the Federal Reserve (MB) which in turn prompts banks to increase M1.
> and this description of bank money creation isn't even the accepted version today anyway
What description? Most money in modern economics is created by banks. But nothing requires that to be the main mode. We're nowhere close to it, but a high-tariff economy would be expected to rely more on producers than consumers and thus their credit versus consumer deposits.
> If the OP's production company can't actually deliver $100 million of goods, someone has to write it down and no amount of velocity makes the company solvent
The $500 billion isn't net-sixty trade credit, it's long-term commitments for capital expenditure by third parties.
> Trying to make this a monetary argument when it's not actually weakens the circularity argument
No? They're separate issues.
Credit creates money. That's real and separate from to whom one is extending credit, in Nvidia's case, to its customers so they can buy more from Nvidia.
M3 hasn't been published in the US since 2006 and M4 has never been published publicly in the US. Aggregates don't turn into one another like they're moving on a conveyer belt. They're just classification buckets. If you have a dollar in a checking account, it's in M1, M2, M3 and M4 at the same time.
A purchase commitment or a capacity guarantee on Nvidia's balance sheet is just a contract. It isn't in any aggregate, it isn't traded in a money market and nobody accepts it as payment.
> ...via a similar mechanism to the Fed buying Treasuries, thereby increasing deposits at the Federal Reserve (MB) which in turn prompts banks to increase M1
Sorry but this is just wrong. Only the Fed creates reserves. Nvidia signing a contract doesn't do anything at the Fed.
Banks create deposits when they lend and they're constrained by capital and loan demand, not a reserve ratio. Since 2008, reserves have gone up 10x and M1 hasn't. See "Money creation in the modern economy". The multiplier theory as an explanation of how money gets created has been dead for years.
> The $500 billion isn't net-sixty trade credit
I wasn't even talking about this. My comment addressed the OP's argument that Nvidia is holding customer debt as a bank-like asset. That debt is receivables and it's 53 days on average, not years. The $500 billion in the article is mostly bank and private credit cash being loaned to Nvidia's customers and Nvidia providing backstops and guarantees. So if money is being created here, it's the lenders who are creating it, not Nvidia. In this case, Nvidia isn't a bank, it's a credit enhancer.
The legitimate concern is that Nvidia's guarantees are encouraging lenders to lend money to neoclouds on better terms than they otherwise would get (or should get if you want to make that argument). But that's not money creation and trying to pretend that it is only distracts from the real issues.
Conveyor belt is wrong. The term you're looking for is transmission channels. MB is turned into M1 through lending. M3 is turned into M1 through collateralisation and demand stimulation, among other effects.
> If you have a dollar in a checking account, it's in M1, M2, M3 and M4 at the same time.
Yes.
> A purchase commitment or a capacity guarantee on Nvidia's balance sheet is just a contract. It isn't in any aggregate
Of course it is. Why do you think the SPVs want the commitment? They turn around and issue commercial paper and get bank loans and get bonds underwritten against those commitments. All of which turns into checking account deposits. Those SPVs also get a credit rating which lets them sign construction contracts which builders turn around and turn into deposits.
> Banks create deposits when they lend and they're constrained by capital and loan demand, not a reserve ratio
Banks are constrained by capital and liquidity requirements, on one hand, and loan demand, on the other hand.
> if money is being created here, it's the lenders who are creating it, not Nvidia. In this case, Nvidia isn't a bank, it's a credit enhancer
Yes. When the Fed buys Treasuries and increases a bank's reserves at the Fed, it's not actually doing anything in the real economy. The banks then have to turn around and increase lending. If, as you noted, loan demand is stagnant, they have to cut prices, i.e. rates.
The Economist is comparing Nvidia "enhancing" credit conditions in a manner analogous to the way the Fed does. By creating a base that stimulates lending.
> that's not money creation and trying to pretend that it is only distracts from the real issues
It's absolutely money creation in the way a central banker or anyone in the money markets would talk about it.
"Transmission channels" are how policy (rates, credit, etc.) affects the economy, not how aggregates convert into each other.
MB doesn't get "turned into" M1 by lending. Banks don't lend reserves to non-banks. The reserves stay inside the banking system. Lending creates M1 and reserves are provided to match.
I see the point you're trying to make about M3. Instruments like commercial paper can serve as collateral for bank loans that create deposits, but that still isn't conversion. It's new deposit creation with a broad money instrument as collateral.
> Of course it is. Why do you think the SPVs want the commitment? They turn around and issue commercial paper and get bank loans and get bonds underwritten against those commitments. All of which turns into checking account deposits. Those SPVs also get a credit rating which lets them sign construction contracts which builders turn around and turn into deposits.
The commitment isn't in any aggregate. It's collateral or credit support for instruments that are (the SPV's commercial paper and the resulting bank deposits).
That's what I mean by Nvidia being a credit enhancer. You've now agreed the money is created by the lenders and Nvidia is the enhancer. That's what I said two comments ago, so what's left is semantics.
> Yes. When the Fed buys Treasuries and increases a bank's reserves at the Fed, it's not actually doing anything in the real economy. The banks then have to turn around and increase lending. If, as you noted, loan demand is stagnant, they have to cut prices, i.e. rates.
> The Economist is comparing Nvidia "enhancing" credit conditions in a manner analogous to the way the Fed does. By creating a base that stimulates lending.
The Fed changes the risk-free rate for the whole economy. Nvidia is compressing the credit spread for a specific set of borrowers by absorbing their tail risk.
That makes Nvidia less like a central bank than a guarantor. The better analogues are Fannie and Freddie, or a monoline insurer. A guarantor's business looks free until the tail risks it took on turn out to be correlated which is what happened to the monolines in 2007.
That's precisely the scenario the Economist piece is actually worried about (the guarantees coming due at the same time Nvidia's own sales weaken).
> It's absolutely money creation in the way a central banker or anyone in the money markets would talk about it.
Central bankers would describe this as easing financial conditions or enabling credit creation, not money creation.
You can sell that debt on to somebody else in exchange for goods and services.
That’s all money is - a circulating debt.
If I give you GPUs worth $1bn, but take 100m payments for 11 years, then during that time you can use your other mony to buy other things that arent GPUs
If we stop after the 11 years and dont make new loans, the supply has shrunk back
If you go to a bank and get a loan, that is literally money that did not exist before you got a loan. People think that you are borrowing money that somebody else put in the bank, but that's not true. Banks can lend out a lot more money than people put into them.
Uh, that’s a pretty load-bearing as long as its cash flows continue. The two things are surely correlated.
Now, whether many things NVDA has invested in with expectation of repayment or earnings would be able to repay or appreciate in a market environment where Nvidia’s stock was crashing? That’s another question entirely.
I'm worried I'm going to start picking up claudisms, and then accused of being AI.
It's an important difference. In the GFC, the value of AAA-rated tranches fell. With the benefit of hindsight, we know they continued paying. They were directly leveraged, however, so mark-to-market losses caused firms to fail.
Nvidia stock crashing shouldn't have a similar effect to these commitments. If someone else has massively levered their Nvidia position, they'll obviously blow up. But Nvidia could survive a good deal of equity-market tumult in a way a bank could not.
Ppl have made the prediction of it being a bubble or unsustainable since 2022. At this point, it's hard to say these people have credibility anymore. Ai is big enough, much like Google in 2005 or Facebook/Social Network in 2010 or apps in 2015, that it's an institution unto itself. It's not going to just crash as so many are expecting and have been wrong the past 4 years about.
Also Nvidia isn’t really creating money. The 500B number is third party capital that already exists (BX, Apollo, etc).
It's not. It's stating a condition. For traditional banks, a stock crash can independently trigger a failure.
> whole premise of the circular financing worry is that Nvidia sits in the middle of all the guarantees made to companies like OpenAI. If any of those companies become insolvent, Nvidia is on the hook for it
Sorry, I meant revenues. If Nvidia's revenues stay stable, these commitments aren't a problem. Even if the stock price crashes.
> Nvidia isn’t really creating money
It absolutely is. Similar to the way banks create money [1]. The commitments support credit that wouldn't exist without it.
[1] https://www.bankofengland.co.uk/-/media/boe/files/quarterly-...
Making a loan/offering credit isn't automatically money creation - the amount of money in the system before and after the loan might be the same. Haven't been following Nvidia all that closely, but it seems a little bit unlikely that they're a commercial bank. Financial chicanery they may be doing but offering deposit accounts would be new territory. The loan has to be made in a very particular way for it to be money creation (notably, in a way that creates new money), and it should be illegal for most people to do that otherwise we'd all be printing our own money instead of the printing being directed to wealthy asset owners first and foremost.
The Fed can limitlessly increase monetary base (MB) to increase M1. Non-bank lenders create M4 which turns into M2 through the money markets which turns into M1 through the banks. More convoluted and more limited, by design. But the net effect is the same–more M1.
More broadly: when you open a bar tab, you're literally creating money, even if it never hits M1.
Credit is always money creation. When it's done at scale it's almost always creating M1.
Or I suppose I should spend more time with an open bar tab come tax time.
The monetary aggregates are things that are theoretically equivalent to creating money, but I'm going to challenge whether it is proper to compare M4 activity to the fed balance sheet. One of those entities is involved in actual money creation. One of them is hyper-privileged money creation that is more impactful and less comparable to other forms.
Yes.
Nvidia issues a commitment to a firm that lets an SPV raise money. Some of that is just M1 being transferred from one account to another. A lot, however, will be created through loans (new M1), commercial paper (new M3) and the like. Some of that will be pledged as collateral. On the other side of the equation, when the SPV signs e.g. a construction contract, you'll have builders taking out bank loans and issuing commercial paper, et cetera.
You can pay your taxes out of a checking account using money a bank created out of thin air that morning that the Fed won't even learn about until the evening.
> monetary aggregates are things that are theoretically equivalent to creating money, but I'm going to challenge whether it is proper to compare M4 activity to the fed balance sheet
You're absolutely correct in M4 being unequal to the monetary base and deposits at the Federal Reserve. But the moment you say the Fed balance sheet, you're conflating two things. The Fed has lent, in the past, against non-Treasury collateral (most famoulsy, mortgage bonds).
And if we're talking about money in relation to the real economy, you can't spend reserves at the Fed. There is debate on what the most "real" money is, but pretty much everyone agrees that a deposit in a checking account is more relevant to the economy than unspendable reserves at the Fed.
How? And what is your theory why people pay taxes from their labour earnings instead of just creating new money to pay Just-In-Time?
> A lot, however, will be created through loans (new M1)
Isn't M1 is currency and overnight deposits? I'm pretty sure you're just making things up here; it sounds highly illegal for Nvidia to create new M1. Unless they've taken out a banking license when I wasn't looking.
> You can pay your taxes out of a checking account using money a bank created out of thin air that morning that the Fed won't even learn about until the evening.
Ditto prior. Nvidia isn't allowed to do that.
...from a checking account. Banks thoughtlessly lend against investment-grade commercial paper. The kind the SPVs Nvidia is commiting to are borrowing with. Nvidia's promises are creating debt that money markets and banks transmit into M1.
Note that the Fed doesn't directly create M1. It moderates it through the interbank lending market to manipulate the monetary base, M0 plus deposits at the Fed. That, in turn, influences banks' lending patterns which is what manipulates M1 and MZM. Underwriting M4 to drive up collateral that in turn increases M1 is the same mechanism, different channel.
> what is your theory why people pay taxes from their labour earnings instead of just creating new money to pay Just-In-Time?
I'm not Nvidia. I did just sign a purchase order with a builder for my deck that their local bank called me to confirm before issuing a loan that will appear as new money in their checking account. My signature, in that case, enabled the bank to create a tiny amount of money. It's not monetarily significant, however, because my deck isn't that fancy.
At the end of the day, all credit is money. If you can create credit, you can create money. Most of us can't, at least not in significant quantities.
> Isn't M1 is currency and overnight deposits?
M0 + demand deposits at commercial banks, yes.
> sounds highly illegal for Nvidia to create new M1
Nvidia causes the creation of new M1 through banks. Nvidia's commitments directly create money of a quantifiable amount that wouldn't have existed if Huang hadn't flicked his pen.
> unless they've taken out a banking license
Fun fact, you don't need a banking license to issue traveler's checks. And traveler's checks are counted in M1 in the U.S.
> pretty sure you're just making things up here
If that's your reaction to encountering new information, godspeed.
We've got Schrodinger's money here! One minute I can go down to the bar and create as much money as I like with the bartender. Then the next we suddenly discover that yes we need a bank and yes there all of a sudden a checking account is involved and no a bar tab isn't a legally recognised form of money.
> I'm not Nvidia. I did just sign a purchase order with a builder...
Again though, we discover that in fact the person in control of the part where the actual money was created was a bank. You can't just head off with your builder and create money - otherwise you'd be stupid to stop until you unseat whoever was the richest fellow in the world this morning.
> Nvidia causes the creation of new M1 through banks.
And the banks make another appearance!
---
I put it to you that Nvidia can't, in fact, create new money. You'd never get that line of argument past a tax collector.
> Fun fact, you don't need a banking license to issue traveler's checks. And traveler's checks are counted in M1 in the U.S.
And I'll add in postcript that I know nothing about travellers checks in the US, but I'm quietly confident it'd turn out to be illegal to go around creating vast amounts of new money there too, on the basis that people tend to work for a living.
No, its not! Its a swap on the active/left side of the balance sheet: If my mum borrows me 1 USD for icecream, she did not create money, instead she swapped her positions in her assets/left side of her balance sheet.
But aren‘t they currently sitting on like a margin of over 80%? So I assume their revenue will fall, because people are not going to like that in the long-term.
If NVDA gives a loan, its a swap on the active/left part of their balance sheet - thus, this does not have an effect on overall(!) money suppley. The balance stays the same, also the total amount of money in the whole system at that current point in time.
If a bank gives a loan, then it is extending/enlengthing its balance sheet. (the money created,though,needs to be available on the central bank account to float to other banks when paying for something,therefore we have liquity rules in reg reporting in a bank etc.,meaning someone else needs to have increase thecentral banking liquidity at another part in the system, see things like: https://en.wikipedia.org/wiki/Maturity_transformation ) ---
As working in the field, I know the BOE paper very well ;-)
The reason Nvidia is comfortable making these deals is because if OpenAI can’t use the compute, someone else can.
Granted OpenAI going insolvent likely means a drop in the value of compute…
They would have to go insolvent in a way that hits Nvidia revenue. Those are related by distinct factors, a difference that may matter in a crisis.
I see two factors converging to cause a collapse of this house of cards:
1. People are realizing that what they need isn't more general intelligence, it's more specialization. A small but well tuned coding model, a small but well tuned customer service model, a small but well tuned document explorer.
2. Specialized hardware - TPUs and NPUs - especially coming out of china. The latest GLM model was trained and runs on Huawei hardware. Nvidia is only worth so much because they are the biggest and best provider of the kind of compute needed to run llms, but the export bans mean china has a lot of incentive to topple that monopoly.
The amount of compute we need to do the things llms do is falling rapidly, the number of people who can provide that compute is rising.
> it's more specialization
China, constrained by hardware, and talent (not to slight the Chinese, but they are limited to domestic resources - and much of the US effort is very international). They did, what the Chinese do, and optimized the process of production, and drastically lowered the cost of development of their models. Cheeper to build, cheaper to run is just good economics.
Meanwhile in the us, we have open AI doing "experiments" - it looks like the costs around the hugging face hack are going to be about the same as China would spend on building out one of their smaller efforts (several million dollars). (Depending on whos numbers you trust, the fact that I can even make this claim should make you raise an eyebrow).
Go back to the 80s' and "expert systems" - most people will tell you that for their time, they were amazing, and useful. People would have loved to have more of them but they were so cost prohibitive that we all but abandoned them for serious use. The US frontier labs seem to have forgotten this lesson and their calls to "slow down" look like an excuse to "cut the waste so we can move to making money".
> Compute has already lost value for me. Six months ago I thought you needed a 1T+ model to be useful coding. Now I am able to get by just fine with a 27b model.
and I was explaining why the complexity question is important in that context. Specifically, because it's part of why people judge the 27b model to be adequate compared to the 1T+ one.
Yes, lots of people are slopping out low-quality things with powerful models because they don't know how software quality works and expect magic. I think we are talking at cross purposes but have no real disagreement.
It’s not quite as simple as that. Several studies have shown the opposite: models trained on more diverse knowledge tend to cross-pollinate across domains. So a more generalized model can actually perform better than a specialized one.
That’s why you’re not seeing tons of tiny models (one for Python, one for Pascal, one for Rust, etc).
But it doesn't match my experience. Qwen3.8 27b is clearly smarter at coding than MANY bigger models. gpt-oss-120b for example, is almost 4x the size, and performs way worse at coding tasks.
It's clear to me that you can build small models that work well at specific tasks.
Python vs Rust is probably too fine grained a way to build a model. Coding in general seems like a better target.
There will always be a place for large generalist models, no doubt. But I think that place is much smaller than the big ai companies are counting on.
I make heavy use of smaller local models on a daily basis (Qwen3-VL for auto-captioning images, Gemma3:27b for some translation work, etc.). Gemma3:27b is a good example of a very capable general purpose multimodal model and has handled almost everything I've thrown at it from sentiment analysis to documentation writing.
I suppose I was drawing a distinction between specialized and general intelligence versus small and large. I don’t think those are necessarily mutually exclusive.
And Qwen3.8-27b is still better at coding than opus 4.1.
Yes, if you list off models 27b is better than it’s all older models. But that’s my point - newer models are better than older models at the same AND much smaller size. That’s because model size matters less than they say. Training data and model architecture matter more.
It practically became a joke about how a huge amount of the training data for GPT-4 was bottom of the barrel reddit vomit and obvious bot spam. Leading to many bizarre edge cases.
Shows qwen3.8-27b along side seven larger models of ~similar vintage. Only one scores above 27b.
Many of those are closed models so idk their exact parameter count / active param count, but it hardly matters - i’m sure all of them are far above 100b params
My point is not that bigger is pointless. It’s just clearly not the only road to take to make a model better, which is obvious just from seeing how models of the same size have gotten better over the past few years
First off, I'd include Qwen flash-next and GLM 5.3 to show some of the other strong open weight models, and they predictably dominate it, but they're much larger. But, it shows up right next to DSv4 Flash 0731 on the overall index, and that's much larger. It's a great model! But then scroll down and hit Time Per Task, and you'll see that DSv4 Flash takes 3.6 seconds per task to Qwen's 21.1. That's what I meant when I said this:
>speed due to excessive thinking maybe to make up for the smaller amount of world knowledge baked in (qwen 27b's main issue iirc), etc - they're tuned for different things.
It can make up for its shortcomings by iterating a lot longer, and using way more thinking tokens. And that's a great trade if you don't have the vram to run the bigger models, but speed is pretty important for getting things done... And that's why DSv4Flash is great, too, despite being much larger, and scoring similarly on the intelligence index.
Absolutely - no argument from me here. Bigger is very clearly a lever you can pull to get more out of a model.
> But then scroll down and hit Time Per Task, and you'll see that DSv4 Flash takes 3.6 seconds per task to Qwen's 21.1
Fair point, qwen definitely is slower - it’s a dense model, 27b params, vs a sparse 13b active params model - but the data doesn’t quite agree with what you’re saying about reasoning. I.e.:
> It can make up for its shortcomings by iterating a lot longer, and using way more thinking tokens
If you look at the total tokens generated, deepseek thought for 45k tokens and qwen thought for 48k. Barely a difference. The wall clock difference is all down to the speed of token generation, not the amount of reasoning done. At least when we are comparing deepseek and qwen 27b. The comparison swings more towards your position when it comes to the other models on the chart that reason for much fewer tokens.
So perhaps a hypothetical Qwen-27b-a13b could never rival deepseek’s larger model and the tradeoff is one of speed vs overall size - i.e. a small model needs more active params to compete than a big one does.
One data point that seems relevant to me is that the previous gen qwen Qwen3.6-27b was not so different in performance from its sibling model Qwen3.6-35b-a3b. We never got a qwen3.8-35b-a3b, but if we had, would the gap have stayed the same or gotten bigger? I.e. would the quality gains by improving training coming up against a hard limitation with 35b, or not.
>One data point that seems relevant to me is that the previous gen qwen Qwen3.6-27b was not so different in performance from its sibling model Qwen3.6-35b-a3b. We never got a qwen3.8-35b-a3b, but if we had, would the gap have stayed the same or gotten bigger? I.e. would the quality gains by improving training coming up against a hard limitation with 35b, or not.
Yeah good question, kind of shocking that a 3b active model would perform as well as a 27b dense.
In 2026, the default outlook should be suspicion for any big private organisations with profit motive.
You don’t need to think about climate change studies. Instead you can read the allegedly tainted studies we’re actually talking about and profess to all of us what is wrong with them. You can’t point to exactly where they’ve fudged them.
And let’s be real. If this were some conspiracy that OpenAI, Google, and Anthropic were tacitly or overtly conspiring on, I’m pretty sure Elon or Zucc would ruin it to get ahead
Yeah, the cross domain transfer learning from RL is overstated by a lot.
Just like how I could borrow $100 from you, and you could borrow $100 from me, and we'd be $200 in debt in total, I could buy 10% of shares in your company for $1m and you could buy 10% shares in mine, we'd have 2 companies worth $20m together in total.
And even if compute demand were perfectly elastic it’s only a good thing insofar as it drives demand for new Nvidia hardware. If tokens can be served from Apple hardware or Google hardware or Huawei hardware that doesn’t help Nvidia.
I mean… some homes definitely do. You must have seen those houses that are all lit up front the outside by lawn mounted spotlights.
Across that period, first world countries massively increased their demand for light.
Further efficiency increases only matter to individual choices if they take a use case from {economically impossible} to {economically possible}.
I'd offer that by the 1920s, most goings-on in first world urban environments were no longer price constrained in terms of their light usage.
[0] See table 1.4, p21 https://www.nber.org/system/files/chapters/c6064/c6064.pdf
If that dies because a lot of people’s needs turn out to be met by a system at home they can run a 30b-150b model on, a lot more of that money goes to apple or intel or amd.
1. Yes, smaller models will become more popular, especially as the tokenmaxxing trend dies down and people start stretching their budgets farther. That is a downward pressure on demand.
But along the same dimension, consider that currently only about 40 - 60% of the world uses AI for only about 5 - 15% of their work hours. That means there is still 2x growth from users and 7x - 20x growth from the rest of the work hours left to capture! That is 14x - 40x more demand. Then consider that agentic tasks require multiples more tokens, and that is the kind of usage that is most likely to be deployed, and also the kind of usage that is the least used right now. That's another huge multiple to be tacked on.
And the entire AI industry has been lamenting the extreme compute crunch they're facing (and also why Claude has 9's comparable to GitHub; whereas OpenAI has been chugging along because Altman was OK being called a "podcasting bro" while desperately scrounging for compute years in advance.)
Nvidia's meteoric rise is entirely due to this kind of exploding demand with extremely limited supply.
2. Competing hardware is definitely a threat, but it has its own hurdles. Because the real bottleneck is not Nvidia, it's TSMC.
Pretty much all demand for all chips in all devices in all the world flow to, like, 3 companies in the world that actually fabricate them, and TSMC is the biggest. And the supply is extremely tight, as the exploding costs of electronics clearly shows.
So now TSMC will of course try to keep all its customers happy, but it will inevitably be forced to choose which ones it will keep happiest. And those will be the customers who can pay it the most. And that would be the one with all the money from its de facto status as a monopoly (and possibly even a monopsony)...
Which would be Nvidia ;-)
So yes, compute per task is falling rapidly... but it's barely a dent in the humongous total addressable demand, and the amount of hardware to support that compute is still very constrained, and most of that supply will likely flow through Nvidia.
Ah yes, i am constantly lamenting that my barista isn’t using ai enough ;)
Hopefully you’ve adjusted your ceiling numbers to account for the large amount of people who can’t afford to pay for llms, and will never be able to pay, and aren’t worth it to advertise to since they can afford very little
It's not the baristas or other workers who are spending that money.
(You can explore adoption rates in various industries, including "accommodation and food services", here: https://www.genaiadoptiontracker.com/#explore-data)
If AI makes knowledge workers 1% more efficient on average that is $500 - 700 billion annually. Actual productivity numbers from studies from all the way back in 2024 put the productivity boost above 30%, so add the appropriate grains of salt and adjust numbers accordingly.
That is what the ceiling numbers should be based on. Your baristas will also be using AI eventually, paid for by their employers of course, but that would just be a cherry on top of the real TAM.
All the "frontier" AI companies *are* currently insolvent. They have never been anything other than cash burning machines.
The only way they keep the lights on and the doors open is by borrowing money --- and epic amounts of it. If those operating the cash spigot decide to turn it off, all AI companies will likely be similarly affected --- and so will Nvidia.
OpenAI expects to burn through more cash between 2024 and 2029 than Uber, Tesla, Amazon and Spotify did - combined - before those companies started making money
https://www.morningstar.com/news/marketwatch/20251205243/thi...
Fairly sure data center construction costs are also going up (they require so many resources that everything is constrained at the moment, especially electricity production).
So I don't understand in what world these frontier AI companies can somehow become profitable. The basic tech they're using is basically the same. Yes, around the edges there are a lot of things that can be done, and were done, like caching, batching, mixture of experts, etc, but basically everyone has done all of that by now, and they're still losing money.
So:
Total costs going up a lot - revenues per unit not increasing proportionally, if anything, Chinese models are forcing those down.
How does that math work out to profits? I don't see it.
Or about as bad, after trillions of dollars in investments over multiple years, let's say the entire frontier AI sector has a total profit of $20bn by 2030. In what world does that make sense? Assuming they can scale that total profit to $100bn in 2035 without investing another cent from 2027 to 2035 (utterly ridiculous), the return on investment would happen in roughly 20 years.
China is the one that is really in the driver's seat here. They have the opportunity and the ability to nullify/wipe out our huge investment in AI.
Failure to take into consideration those kind of correlations ("If my biggest client isn't able to buy it, I would be able to find someone else who will") is one of the principle causes why many risk models turned out to be garbage during the Great Financial Crisis.
But I also doubt Nvidia is on the hook if OpenAI just no longer wants the compute. I bet they are only on the hook if OpenAI cannot pay for it (is insolvent in some way).
I also have to bring up that OpenAI has already spat out an inference chip that beats Nvidia on flops per watt. So they could potentially not need the compute while other ai companies do.
The problem with that is that OpenAI can only afford to pay for the compute because they are burning investor money (and so are most of OpenAI's biggest clients). They are losing billions. If they stop burning money, nobody else will be there to pay for that compute at OpenAI's cost.
Sure, somebody will probably be able to use these GPUs, they just won't be able to pay nearly as much for them as OpenAI does.
In reality, it's just nowhere near worth as much as OpenAI pays for it. Inflating the cost of compute is part of the problem caused by the circular financing, and if (or maybe when) OpenAI goes, the price of compute will go with them.
But that’s the point. Investors believe investment in AI will pay off.
So when people say "somebody else will buy that compute", they are correct, but they are ignoring that it will still cause a massive decrease in revenue generated by that compute.
If you're asking me what my point about "believing" is, it's this. OpenAI is losing billions every quarter. It's only staying afloat because it can still find investors who believe in its ability to eventually become incredibly profitable. But there are signs that this is starting to change (e.g. it's unlikely that Softbank will be able to find much more money to give to OpenAI). If OpenAI can't keep raising more money and can't IPO at the level they need (as seems to be the case, given that they keep pushing any IPO date forward), OpenAI will eventually run out of money.
I'm not sure how investors believing in things changes any of this, so now it's your turn to explain what the point is you're actually trying to make.
How? The hardware is in OpenAI's datacenters. Does Nvidia have a couple hundred semi trucks, contractors, and IT technicians, to repo the hardware and resell it to someone else before it's lost most of its value? These chips will be replaced approx every 3-4 years. So if OpenAI tanks, after Nvidia pays for and waits for the process to collect the hardware, they then have to sell it for pennies on the dollar. They lose almost all the investment.
Also consider that SpaceXAI already had datacenters full of gear that they basically weren't using because nobody wanted their product, so they now rent it to Anthropic. The demand for hardware isn't really there at the scale of OpenAI.
Via logistics contracts, yes.
Gaming is lucrative but not THAT lucrative…
They have no idea how much compute will be needed. They are estimating and trying to push it but they do not know the future.
Load bearing, heavy lifting... Your comment wasn't LLM-written, either. I think we're starting to see LLMisms infect human writing. I might try to start speaking like this and see if anyone notices. It could be a good gag.
That’s what loans are.
If NVDA gives a loan, its a swap on the active/left part of their balance sheet - thus, this does not have an effect on overall(!) money suppley. The balance stays the same, also the total amount of money in the whole system at that current point in time.
If a bank gives a loan, then it is extending/enlengthing its balance sheet. (the money created,though,needs to be available on the central bank account to float to other banks when paying for something,therefore we have liquity rules in reg reporting in a bank etc.,meaning someone else needs to have increase thecentral banking liquidity at another part in the system, see things like: https://en.wikipedia.org/wiki/Maturity_transformation )
No, it's not. M2 includes things like traveler's cheques and money-market funds.
The Fed doesn't backstop physical currency. That is issued by the Treasury (specifically, the Mint). The FDIC backstops bank deposits; the U.S. guarantees is obligations.
The Fed doesn't properly "backstop" anything. It's the lender of last resort–if you have a Treasury or other good collateral, it will loan you money against it. It's a financial regulator. And it regulates interest rates (i.e. the price of money) to influence inflation and employment.
The only backstops the Fed truly makes are to banks, by guaranteeing to always stand ready to lend against Treasuries and other good collateral.
You are taking this too literally anyway. I know they don’t backstop jack squat but in practice there is a fed put.
Have a conversation with me, don’t be a pedant.
If you are saying they will lend last resort against treasuries you should know there are $40 trillion of those outstanding…
How about what’s the amount from banks that the fed would willing lend as a last resort?
That isn't a backstop, it's a direct obligation. It's also, like, not a real one? You can't redeem notes for specie. The term originates from when you could redeem dollars for metal. The Fed did play a role in backstopping that guarantee.
> know they don’t backstop jack squat but in practice there is a fed put
Sure. That isn't the same as a backstop. Backstops are hard–the Fed can't turn away an eligible borrower at the discount window. The Fed put is soft–the Fed will let market participants fail to send a message.
Going back to the top, it is incorrect to say the Fed backstops M2. This wouldn't be a footnote in a central-banking discussion, it would be something that would get called out as a screwup.
> How about what’s the amount from banks that the fed would willing lend as a last resort?
Infinity. The Fed mainly accepts Treasuries as collateral, but it can and has expanded the definition of good collateral in crises. There is no legal or frankly practical limit on how much money the Fed can create. Its only constraint is ultimately political. (Which is in turn mostly a function of inflation and employment and I guess now social media vibes.)
If you're looping this back to Nvidia, yes, I never claimed Nvidia has more lending capacity than the Fed. What I said was it's interesting that in practice, Nvidia appears to have created more money (if we're being pedantic, M3 which turns into M1) than the Fed has in that time. The Fed wasn't particularly trying to ease financial conditions in that time, so this is more of a curiosity tied to the title than a statement of capability.
The Fed can never default on any dollar-denominated debt. There is no similar currency that Nvidia can create ad infinitum.
That said, the number I think you're looking for in respect of the Fed is $30 to 40 trillion. It's about U.S. GDP. And it's also about U.S. bank and money-market assets plus the Fed's balance sheet. If every American bank failed, this could be the amount of money the Fed would have to create.
That said, Treasury running out and e.g. defending the euro-yen could easily increase that cross section in practice.
It can create obligations to provide future GPUs in return for present money.
Yes at some point people might start to question, but what are the true hard limits there, especially once SPVs and such start to get involved to shuffle things off the books?
None. But IOUs don't have the power of demand to pay taxes.
The Fed borrows massively through repos when it wants to tighten conditions.
Fair enough. Money-market assets are the real exception.
Nvidia doesn't need it. It funds other companies. They do this thing that Nvidia doesn't do. It shows up on their balance sheets and Nvidia just gets to claim the valuation of the investment on its balance sheet.
It can't go tits up!
What is the barrier to entry?
versus
Fed open market operations that occur in full instantly and are the primary mechanism for increasing the money supply
k.
nvidia's money either comes from equity, or from debt. This means this money is "created" not from nothing, but from future commitments (ala, debt repayments, or promise of profits), which is not the same as what comes out of the Fed.
The Fed printing has no backing behind it - it is definitely inflationary if they do it. Investment from nvidia (or any other company) "creating money" may be productive enough to completely offset their inflationary effects - after all, the company investing demands returns from their investments, and so will only invest in things they expect to return much higher than the cost of interest (or cost of capital).
Therefore, you cannot compare Fed printing money to company investing money.
Most money is created by banks, not by the Fed. When banks create deposits they're booking it against a loan. Similarly, the Fed creates money by buying assets, principally Treasuries. There is an offsetting account. The only party that can truly just "mint" currency is the US Mint.
> you cannot compare Fed printing money to company investing money
Yes, you can. Nvidia creates M4 which drives M2 and thus M1. Banks create M1. The Fed creates monetary base. These are different components of the same money supply [1].
[1] https://en.wikipedia.org/wiki/Money_supply#United_States
NVDA itself(!) does not increase M4 - if they give a loan, its an assets swap on their balance sheet with no influence on money in total available (since the money on their account is gone!)
The FED and banks can increase total money only.
Oh hell no. NVIDIA is present in a ton of 401k and similar retirement/savings/gambling vehicles. It holds 12% of NASDAQ tracking funds and 8% of S&P 500 trackers. NVIDIA goes down, a lot of people will panic sell and crash the economy.
Wrong:
a) a company cannot create money in todays modern 2-level fiat systems, this can be done only by central banks
b) what NVDA does is "generating requests for more money in the system", throughthe demand side (either taking loans themself or having lots of customers who are willing to take a bank loans to invest, or other participants who wants to buy whatever stuff on a loan)
c) any money that is created on the "local bank system level" needs to be there on the existing central bank account when the money is leaving the local system, ie. transferred to another bank (like "paying NVDA bill for delivery of some chips")
The ideas we deal with when we discuss society and organization aren't exclusive to government, they relate to human nature in general. I wonder if in the future we will have more discussion of power and how to organize it in corporations, similar to what we discuss today about government.
The structure of the Fed is setup the way it is to limit the sort of self-serving, myopic political micromanaging that could be damaging to the economy at large. And, unlike a beneficiary of rapid growth like Nvidia, has (historically) tried to identify potential indicators warning of unsustainable bubbles that could lead to financial contagion and tries to mitigate that risk using the limited monetary tools available and their public soapbox.
A similar decision making structure would potentially be very undesirable to Nvidia shareholders as caution over long time horizons would likely produce what they would consider an excessively conservative, defensive strategy to avoid putting too much air into the bubble too quickly (at the expense of their valuation).
I'm not saying that corporations should have exactly the same rules and structure as government does, but perhaps many of the ideas used to design governments can be borrowed.
Just such a curious scenario to let your mind wander about, how society would look like in these scenarios!
/s
I'm honestly so sick of the suspense of disbelief on this site, how is this more "interesting" to you, than the absolute sheer terror you should feel about going back to feudalism and serfdom? A typical western national state ensures that you have basic rights as a human being and aren't exploited to the death by non-government entities.
Looking at any organization with power and people involved, perhaps we can use the same ideas that traditionally apply to government in more places. That's all I'm saying.
This is not some mindless intellectual exercise to distract from how things are. In fact, as a proposal for how to reform corporate power, it's the opposite.
(Also, even though I think corporate power should be limited to a very specific arm of society, and that we shouldn't encourage more corporate power, you are greatly exaggerating. Feudalism and the abolition of human rights are not right around the corner.)
In a country without religion, banner or ideology to unite the people in current-and-coming turbulent times, the bet is made on "unite under money, or have no money left"
the way to fight it is to be principled even in front of cheaper options - and to support others like you
https://www.youtube.com/watch?v=A64rR5Dp07s
"You have meddled with the primal forces of nature, Mr. Beale. And I won't have it!
Is that clear?! You think you've merely stopped a business deal. That is not the case. The Arabs have taken billions of dollars out of this country, and now they must put it back! It is ebb and flow, tidal gravity! It is ecological balance!
Am I getting through to you, Mr. Beale?
You get up on your little twenty-one inch screen and howl about America and democracy. There is no America. There is no democracy. There is only IBM and ITT and AT&T and DuPont, Dow, Union Carbide, and Exxon. Those are the nations of the world today.
What do you think the Russians talk about in their councils of state -- Karl Marx? They get out their linear programming charts, statistical decision theories, minimax solutions, and compute the price-cost probabilities of their transactions and investments, just like we do."
Sadly it seems like some haven’t watched the end of the last movie on this subject.
Companies just don't want to pay Jensen's tax. Hyperscalers might still pay Jensen's tax for LLM training but for inference. you don't have to. they are also betting on their own chip for training to replace Nvidia.
this is Nvidia panicking and doing vendor fiance to Neoclouds and buying Hugging Face. even none hyperscalers like Meta is betting on its own chip for AI inference.
If these cards burn out in less than the ~5 years of depreciation that accounting puts them at, well then there will be problems.
https://www.cnbc.com/video/2026/08/24/making-old-gpus-new-ag...
Imagine if running fable costs you what it actually costs to run fable. A lot of vibe coders (and just proper software engineers) are gonna be very sad if that comes to pass.
But that reminds me of the story of the union rep telling Ford: “good luck getting your machines to buy your cars”
(Fyi Ford took note and started paying his workers enough that they’d buy his cars)
Also the economy can grow and still leave everyone completely screwed except rich owner classes.
If Nvidia is the bank, they should be starting to sweat a bit. It's not often companies ask for a voluntary slowdown.
Not just building but actively testing
If you have a genuinely-held belief that AI systems will end life on earth and you willfully continuing working on them anyway, then, like... you probably shouldn't be allowed to walk free in civil society anymore, right?
The first messenger from Anthropic is out with this exact message. Stop us (them) or everyone will be killed by 2030
Predicting a usefulness plateau is absolutely wild given how fast AI agents have been improving at writing code this year. I have doubts about AGI but I think you’re making assumptions and translating it wrong. These two companies have always been asking for a slowdown from their inception, that’s not a new thing. It’s part marketing hype, but they both do want regulation to step in and slow down the competition, not because they see a usefulness plateau, but the opposite - the usefulness is growing so fast that they want to remain in control, and they are scared that working hard and competing will not be enough. Anthropic has also said out loud they think their competition (not just OpenAI) is not being responsible and they want the regulation so they can be the responsible shepherd, as AI gets more and more useful.
Have the models improved since Opus 4.x? I find the newer models are not better in my day job, maybe in one shotting mvp's and other tasks.
Not trying to argue your point, just intrested in the coding aspect, if the models were improving as fast as benchmarks I would expect capability improvements to be obvious, but talking to people and reading forums, it seems everyone has a different opinion.
Also yes, Fable is massively better than Opus. It requires significantly less instruction and specs and produces more directly mergeable code.
The improvement is obvious as soon as my Fable allotment runs out and I try to do something with Opus. Have you given the same (larger) task to Opus and Fable?
Personally I still use mainly Opus and find it handles most tasks quite well (without burning all my corporate quota).
https://x.com/theo/status/2097192907023458473
(^ this "swearing at a model" thing has happened to me multiple times on Astra already)
If you have to "debate" the quality of a new Big Number model (and double and triple check your eyes and model setting switches when it pukes up complete garbage), that is NOT a good sign.
This is a ridiculous claim that is disproven by simply using it for more than 5 minutes.
The "how much time does it save a dev" tests seem a stronger way to measure success, but not seen one of those run for a while.
Not bothered with Astra myself, but the demos I've seen people build don't seem any more impressive on the important stuff. Defaulting to three.js for games just feels smoke-and-mirrors to make them look better, as those games are still as unplayable for the same reasons they were in 2D.
I’ve never thought LLMs were on the AGI path, but I have to admit it’s surprising how far it’s come with no end in sight yet. There is something important to be said about how ‘intelligence’ is embedded in language, and it suggests that intelligence isn’t exactly what we thought it was. The language component of intelligence also goes a long way to explaining technology’s progress in human civilization; how language and the printing press and mail and radio/tv and the internet have each ushered in accelerations in the pace of progress. Biologically and evolutionarily speaking, it’s unlikely that humans have become any smarter in the last two thousand years, but technology (among other things) has exploded.
So whatever they're selling: LLM will do the jobs of every white collar worker isn't in the foreseeable future.
Not necessarily. Could be it's close and they are concerned about issues with it?
Even being cynical, maybe Dario thinks OpenAI's Astra is pretty much AGI and wants to slow things so Anthropic can catch up?
By AGI here I'm thinking when you can say to the model, go build a better model, and lay off the engineers.
What planet are you living on? How is this opposite-of-true nonsense being upvoted on HN?
The rate of advancement of models is exponential.
But is the improvement truly exponential??
Are the improvements we have seen from September 2025 to September 2026 really as significant as the improvements from September 2024 to September 2025?
I’m genuinely asking. I can’t answer myself because I haven’t been pushing the latest models to the limit with every new release.
Luckily, AGI is pretty boring. It's a tool that does it's job. It seems like very wishful thinking to expect the same of ASI.