Nvidia is the central bank of AI

> when debt is wiped out through bankruptcy that inflation remains

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.

> “Federal reserve note”

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.

I'm not advocating for corporations to have equal power with governments, though. I think that's generally a terrible idea.

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.)

> if OpenAI can’t use the compute, someone else can

This is the big point IMO since I have never given $1 to OpenAI but I subscribe to Vidu and Typecast, and have given money to Kling, Hailou, and even Gemini in the form of Google Workspace.

So these other guys have products and use cases, which OpenAI has never been able to crack beyond ChatGPT. And ChatGPT was never worth paying for, IMO.

If OpenAI dies, it's not because there is no market for the technology (which is all NVIDIA cares about), it's more that OpenAI doesn't know how to run a relevant technology company.

They were given everything, not just NVIDIA's billions of dollars and credit backing but all the first-mover advantage, all the respect and credibility early on, so it's really sad to see them unable to develop interesting products and turn a profit in a space they helped pioneer, while so many others are making money with the tech all around them.

NVIDIA is fine. The technology will continue to improve and NVIDIA will stay at the center. OpenAI is fucked - knew it when they retired Sora to focus on text-to-text and coding (a largely solved problem).

If you reshuffle your argument, and apply the same facts you get to a similar conclusion but with a drastically different spin.

> 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".