Jensen Huang

Now, apply the NVIDIA story to the world's GDP.

And so what's likely to happen is that that $50 trillion is augmented by, let's pick a number, $10 trillion.

That $10 trillion needs to run on a machine.

Now, the reason that AI is different than IT in the past

In a way, software was written a priori, and then it runs on a CPU.

A person would operate it.

In the future, of course, AI is generating tokens.

But a machine has to generate the tokens, and it's thinking.

So that software is running all the time, whereas in the past, the software was written once.

Now the software is, in fact, writing all the time.

It's thinking.

In order for the AI to think, it needs a factory.

And so let's say that that $10 trillion

of token generated, 50% gross margins, and $5 trillion of it needs a factory, needs an AI infrastructure.

So if you told me that on an annual basis, the CapEx of the world was about $5 trillion,

I would say the math seems to make sense.

And that's kind of the future, right?

Yeah.

Going from general purpose computing to accelerated computing, replacing all the hyperscales with AI, and then now augmenting human intelligence for the world's GDP.

Eddie last night, Eddie Wu at Alibaba said, between now and the end of the year, excuse me, now and the end of the decade, they're going to increase their data center power by 10x, right?