ElProlactin

Taxis, mom-and-pop retail, newspapers, manufacturing. Millions of people pushed out of real jobs and into gig work. Companies breaking the rules and pushing established businesses to the brink with a mindset of "it's better to ask for forgiveness than permission".

Sure, there were some within the "tech community" who didn't like the effects, but the overall vibe was this is progress. There was a lot of arrogance about companies needing to adapt and people needing to reskill. "Teach your kids to speak Python".

And why would you complain if you were making $200,000+/year writing JS at a company selling dog food as a subscription?

Now tech is coming for the tech people and somehow it's really the end of the world.

And then there's this: https://epoch.ai/data/gpu-clusters-documentation/coverage

> The coverage of Chinese companies is particularly poor. Our average coverage of 8 major companies is 15%.

The bigger issue is that if you're interested in frontier training, the national aggregate doesn't tell you much. The question is whether your top labs can get to the chip scale necessary to train a frontier model and China's labs have already demonstrated they can. See https://newsletter.semianalysis.com/p/deepseek-debates

But it's not even clear that training frontier models is where the real innovation occurs. When it comes to fine-tuning, deploying, and building AI-based products, inference is the name of the game and the chip quality is less important. Huawei's Ascend is already pretty competitive here and then you're also discounting China's open-weight access to good models, a huge base of engineering talent and a massive domestic market to iterate against.

And unless Anthropic, OpenAI et. al. are willing to invest billions of dollars training models that will only be used by a small number of clients (like the government), there's no way to fight distillation. Protecting any model from distillation means forgoing its full revenue potential, improvement via feedback and all the benefits AI is supposed to bring to the broad US economy. And if you restrict your most advanced models, you just push people to Chinese open-weight models, which is what we're already seeing.

Very few things in this world are all-or-nothing, and not every purchasing decision is based on price alone.

Do you always buy the cheapest meal? Car? When you renovate your house, do you always choose the cheapest contractor?

Tons of developers will lose their jobs, and many more will find it hard to maintain the salaries/rates the industry has been accustomed to. This is already happening. The days where an average graduate from a run-of-the-mill CompSci program or even a coding bootcamp could sleepwalk into a $150,000+/year entry-level job are largely gone. The days where you have job security simply because you're a competent developer with 10 years of experience are in the process of going away.

This does not mean that there is no subset of developers who cannot be successful in this market. There are people who are doing just fine because they know how to articulate their value and sell themselves to employers or clients.

Plenty of reasons, including:

1. They don't (yet) know how to use AI to accomplish what they need.

2. The ROI is still meaningfully positive and they don't want to have to do it themselves.

3. Having a third-party do the work provides protection for decision-makers. If the project fails, the third-party takes the blame and "nobody gets fired for buying IBM".

4. The vendor does bring valuable insight to the table and pairs it with the use of AI to deliver a result that wouldn't have been possible in-house.

This doesn't mean that everyone will be able to get work and maintain their rates in AI world but some people will.

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.

"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.

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.

Spending $500+ billion/year (and close to a trillion now) on defense for decades and in ~6 months it has depleted stocks of critical weapons trying unsuccessfully to defeat a third-rate military power of a country that has been under sanctions for almost 50 years. And it can't even replenish them without Chinese raw materials and components.

No it won't.

This is a call for a "safety cartel"[1] in which the dominant firms become more entrenched against competition by colluding to limit the progress would-be competitors can make in the market.

[1] https://x.com/alexwg/status/2098793433275985932

Like the US government wouldn't allow Iran to close the Strait of Hormuz? Or a bunch of sandal-wearing Islamists to take control over the Red Sea coastline?

The US government is not omnipotent. To the contrary, it's increasingly impotent.

China has somewhere around 200x more shipbuilding capacity than the US today. It has more shipbuilding capacity in one shipyard that the US has in all of its shipyards. China is already a force in AI and there is nothing the US government can do to stop it at this point.

The road to hell is paved with good intentions.

Dario Amodei is a 40-something dude who is obviously very, very intelligent. But intelligence is not wisdom and his "essay" here can easily be read as someone who opened a can of worms and doesn't know (or can't accept) that he won't be able to put the worms back in. But he's going to try because he believes he owes it to humanity to try.

It's hubris in its most basic form, even if the guy who has it looks nice and wears shawl-collar sweaters.

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.

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.

Not really.

When you look back, seeing how things turned out, history looks different than it almost certainly felt to most people at the time.

It took 250-300 years for the Roman Empire to collapse. You could make a pretty strong argument that the US has been in decline for decades, and that cracks in Pax Americana were already forming during the Vietnam War era.

You don't even need to try because it's not happening.

You mean the chain of command that has been purged of experienced professionals?

If pilots weren't being given enough rest time, as alleged, you don't believe that might affect decision-making in the cockpit?

> The Amazon Prime Air Boeing 767 cargo plane that crashed off a Miami runway on Sunday, killing five people, was operated by a North Carolina company that has been accused by past employees of violating safety regulations, legal documents reveal.

There's a lot in the article, but this allegation is worth highlighting:

> Seuring's attorney, Michael Anello, told the judge that another 21 Air pilot, Johnny Salmonson, "was being pressured to fly in periods of time that were too short to comply with the proper amounts of rest, and that implicated safety. The layovers were too short."

Here's the thing: they don't give a rat's you-know-what about what you prefer. And it's not just due to arrogance (maximizing profit) it's due to the harsh economic realities of running a service business in the US.

I'm an American who has lived in Asia for many, many years. It's very common in many Asian countries for restaurants and the like to be virtually overstaffed, and many businesses (especially cafes) are open ridiculously long hours. Mostly because labor is cheap and many of these businesses are family-owned, so family members (sometimes including children/teens) perform the labor. And also because the costs of starting a small business and keeping it running are much lower.

Whenever I visit the US, I have to prepare myself for woefully understaffed businesses...that charge 2-3x what a meal, coffee, etc. costs in much of Asia. And many are open for 5 hours a day because they can't stay open longer and make money.

Beggars can't be choosers. The economics of American life, and the expectations that have been bred, have led to a situation in which paying more for less is the norm and it's only going to get worse. Unless you're willing to pay $20 and wait 30 minutes for a cappuccino, expect fewer humans to be serving you.

> For instance, AI can’t bathe a patient.

Until there are robots. Or the AI gets creative in an attempt to find a solution to this "problem" and orders a fatal dose of morphine for the patient.

> And new tasks will appear

> Historically, new technologies have also created new tasks for workers. For a nurse, that might be checking how well an AI triages patients, or reviewing an AI-proposed care plan.

You can see where they're going with this.

> At the individual level, it means coders and call service center agents may have to switch to jobs like electrician and nurse, which are less exposed to AI.

It's weird they call nurses "less exposed to AI" when the earlier section discusses how AI could turn nurses into underlings for AI taskmasters.

> How might powerful AI change the economy?

Worth noting that this discussion is built around 2030, which is now less than 3.5 years away.

The hedges that make the Extreme scenario sound less bad fail to explain how anyone is going to pay electricians when the highest paid group (human knowledge workers) is being decimated. It sounds like the theory is that everyone is either going to become an electrician or a totally fair and efficient wealth redistribution scheme will magically appear.