Derek Thompson

NVIDIA is making high quality chips right now that in two, three years will not be the frontier.

And so these companies, if they want the best kind of pre-training, will have to buy a new set of chips.

I genuinely don't know how this is going to work.

If these companies have to spend...

collectively half a trillion dollars every three years on the best GPUs, how are they ever going to make back this money?

You mentioned revenues, and I think we should jump right there.

Your second gauge is what you call industry strain.

And that's basically an answer to the question, are industry revenues commensurate with capital expenditures, right?

Are these companies making back the money that they are spending on the infrastructure to build AI?

And this is where I'm particularly interested in your case, that this isn't bubblicious, right?

By your own calculation,

Data center capex is roughly $370, $400 billion.

AI revenue, as you've calculated, is closer to $60 billion.

That's a 6x gap.

That is an enormous gap.

How is that not worrisome?

And we're going to get to revenue growth in just a second because the question that's being screamed here is, okay, well, it doesn't matter if revenues are low right now.

If they're going to grow by 300% every year, eventually you're going to catch up.

But I do just want to make sure that we pin this one point because in your entire...

Higher analysis, it seems to me, this is the place where you think AI is most susceptible to, most vulnerable to accusations of being a bubble.