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Nvidia is the central bank of AI

economist.com

221–230 of 366 posts

Re: Nvidia is the central bank of AI

#221

I wonder when they will give up on the gaming market because that could take down several publishers and developers. I really don't think it's an if question but a when because it almost feels like an afterthought at this point (they removed the standalone gaming revenue report from the financial reports this summer). Also I don't think AMD and Intel is capable "to step in" to replace them.

AMD and Intel would be HAPPY to replace them, and plenty capable.

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.

Re: Nvidia is the central bank of AI

#223
post #113

Earlier quoted context omitted.

Yea, but they would have to become insolvent in a way that makes compute lose value. 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…

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

> investor money

But that’s the point. Investors believe investment in AI will pay off.

Re: Nvidia is the central bank of AI

#225
post #113

Earlier quoted context omitted.

“as long as it’s cash flow continues” is doing a lot of optimistic heavy lifting. The 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. Also Nvidia isn’t really creating money. The 500B number is third party capital that already exists (BX, Apollo, etc).

Yea, but they would have to become insolvent in a way that makes compute lose value. 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…

The problem is that if OpenAI doesn't want the compute nobody does. All of these companies' demand for compute are correlated. It isn't likely that OpenAI will want less compute in isolation. Furthermore, the circular financing structure means that if OpenAI buys less chips it means that Nvidia has less money to give to say Anthropic to buy more chips and suddenly the exponential growth that circular financing has allowed to grow runs in reverse.

Re: Nvidia is the central bank of AI

#226

Earlier quoted context omitted.

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

> investor money But that’s the point. Investors believe investment in AI will pay off.

Right, "believe".

Re: Nvidia is the central bank of AI

#228

Weird to think we are currently living in the ‘unlimited free Ubers because you recommended a friend or 2’ phase of this new technology. 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.

This is what I’m not getting - we’re spending more than the global gross sales of all software on the planet on AI, how much more software needs to be sold and for how much more to recoup?

The economics only make sense if they can replace a huge number of workers with AI.

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)

Re: Nvidia is the central bank of AI

#229

> worth around $5.4trn 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 othe…

> The good news: I have seen no evidence Nvidia has borrowed against its stock or otherwise linked its equity value to these commitments.

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!

Re: Nvidia is the central bank of AI

#230

Earlier quoted context omitted.

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. 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,…

> People are realizing that what they need isn't more general intelligence, it's more specialization. A small but well tuned coding model... 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 m…

> more diverse knowledge tend to cross-pollinate across domains

Yeah, the cross domain transfer learning from RL is overstated by a lot.

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