Azeem Azhar

But more interestingly, it has a ratio called PEG, which is price-earnings growth, of about 0.7.

And the rule of thumb is that under one, you've got a company that's undervalued.

Now, NVIDIA has a $500 billion portfolio.

order backlog.

So this whole thing is painting a picture of a little bit of confusion, maybe not a bubble, more of a utility that can't build power plants fast enough.

And so we see this extreme dispersion in the markets, that persistent bubble bust anxiety.

And I think what it comes down to is fundamentally

that the traditional capital markets are not well suited for dealing with this degree of change, uncertainty, and speed.

The return profile of AI as this general purpose technology, as an invention of a method of invention, as an exponential technology is really orthogonal to the returns profile that capital markets look for.

What they want is focused, understandable return on capital over a three to 10 year period.

And yet with general purpose technologies, as it will be with AI, those gains are diffuse.

They may be spread out across

the economy.

They may be spread out across industries.

They may accrue to the public rather than to things that private companies can benefit from.

And the pathways may be indirect.

And there may be great lags before profits emerge.

So existing capital market apparatus doesn't price this kind of system level change.

It prices firm level cash flows.

This specific GPU cluster produces this specific revenue stream over the following years.