Derek Thompson

And they showed me really compelling data that shows that firms who self-describe as AI companies on Stripe are dominating revenue growth on the platform and surpassing the growth rate of any group in that platform's history.

So what's confusing to me, but also fascinating, is that it can simultaneously be true

that revenue growth for AI companies is astounding, and that the amount of spending on AI infrastructure is so much larger than the amount of revenue that we still might be looking at a bubble, like we're investing in a $1 trillion economic market as if it's a, say, $10 trillion economic market.

So that's where I think it's worth being very specific here.

And fortunately, your analysis is very specific.

You've said there is no one way to answer the question, is AI a bubble?

In fact, there are five ways.

There are five distinct tests.

And what I want to do in the rest of our time together is go through each of those tests.

So you define these tests as, and folks might not remember it as I say it now, but they'll remember it later.

economic strain, industry strain, revenue growth, valuation heat, and funding quality.

No need to remember those terms now.

We'll repeat them a lot through the show, but let's start with number one, economic strain.

This is basically asking the question,

Is investment in this sector large enough to bend the economy the same way that railroads bent the economy or the dot-com bubble bent the economy?

A third of recent GDP growth can be traced to data center construction right now.

That's enormous.

Why isn't that big enough to make us afraid of a bubble in AI?

There's two ways, I think, to tell the story that you just told.

One is that we used to not build things in the physical world, and now we're building things in the physical world.