NICK SCHIFRIN: This year, perhaps# the most significant business and## economic story has been the development and# spending around artificial intelligence.

A.I.

spending is driving one of the tech# industry's most explosive periods and playing## a big role in overall U.S.

economic growth.# A few companies are churning immense profits,## most of all Nvidia, which posted# record gains of $32 billion,## a 65 increase in one year.

But there are very# real questions about whether this is a bubble.

Geoff Bennett dived into that in a# conversation he recorded recently.

GEOFF BENNETT: Experts say this boom exceeds# almost anything else you can imagine, spending## that goes beyond what was spent on the Manhattan# Project and the Apollo missions to space.

But a number of experts are concerned that# the trillions of dollars spent and intense## competition is creating an A.I.

bubble that won't# sustain the kind of earnings growth to match all## of that investment.

And if the bubble bursts,# it could affect more than just Silicon Valley.

For more, we're joined now by Cade Metz,## technology reporter for The New York# Times who covers the world of A.I.

Thanks for being with us.

CADE METZ, Technology Reporter, The# New York Times: Glad to be.. GEOFF BENNETT: So let's start with the# basics.

.. of A.I.

investment?

Why does it seem like# all these companies are piling in at once?

CADE METZ: Well since the arrival of the# chatbot ChatGPT about three years ago,## we have seen this technology# steadily progress and slowly## work its way into people's lives,# into the lives of office workers.

In many ways, it's a transformative technology.# It's helping people search the Internet in new## ways.

And, inside offices, it's# helping to transcribe meetings,## helping doctors and other professionals# do their jobs maybe a little bit faster.

But Silicon Valley sees much bigger things ahead.# They see this technology continuing to improve,## becoming more and more powerful over the# next few years.

So they're investing those## hundreds of billions of dollars into the# data centers that not only allow them to## improve this technology, but serve it up# to a much larger portion of the population.

GEOFF BENNETT: And, overall, you have# got trillions of dollars flowing into## A.I.

Is this growth sustainable or# are we in a bubble territory here?

CADE METZ: That's the question that everybody's# trying to answer and no one can quite answer.

This is enormous spending, to say the# least.

And it's a bet on the future.## These data centers are not only expensive.

They# take years to build.

So all these companies not## wanting to miss out on this big boom# are having to make a bet two, three,## four years into the future that they will be# able to pull in the revenues to pay for this.

Maybe they can.

Maybe they can't.

No one can# quite agree.

It's really a timing issue.

The## revenues are already coming in for a# lot of these companies.

It's a question## of how quickly it will come in and how many# companies can pull in those revenues.

There## are so many companies in this race.

A lot of# people believe not all of them can win out.

GEOFF BENNETT: Is that why it's so hard for# these companies to establish A.I.

dominance?

CADE METZ: In part.

You have got many big players.

The Googles#.. world are doing this.

And then you have# got more nimble start-ups like OpenAI## and Anthropic.

Meta recently doubled# down on this, the company that owns## Facebook and Instagram.

They have built# a new A.I.

lab.

Elon Musk is in the mix.

People in the Valley talk about# FOMO here, the fear of missing out.## No one wants to miss out on this technology.

So# the race has expanded even over the past year.

GEOFF BENNETT: Let's return to the# data centers, which you mentioned,## because the spending there has# just been enormous.

What risks## does that pose to the markets, to energy# systems, and to the broader economy?

CADE METZ: To the broader economy,# the concern here is that so much## debt is being taken on to build# these data centers.

For years,## the big players I mentioned, the Googles# and the Amazons and the Microsofts,## built these giant data centers largely with# cash on hand or essentially with cash on hand.

Those are companies that pull in billions of# dollars in revenues a year.

They can afford to## build these facilities.

But you have got# so much demand for this extra computing## power that so many other companies are# now in the mix and building these data## centers for various reasons, either# for themselves or for their partners.

And those companies are taking on# far more debt than we have seen in## the past.

And that's where the risk comes in.# Eventually, that debt has to be repaid.

And## if the revenues aren't coming in from these# companies by that time, you have a problem.

GEOFF BENNETT: So it's this idea# of a circular loop.

You have the## tech giants investing in the A.I.

firms,# which then use that money to invest in## those same tech companies' infrastructure.# Is that why folks are raising a red flag?

CADE METZ: Well, that's part of what's going# on.

All these companies are partnering up,## hoping to kind of bootstrap the# whole industry and move it forward.## And so you do have deals like that, where, for# instance, one company will take investment from## one of the big giants and then immediately# spend that money with the same company.

They see that as partnership.

Others see that## as a sign that the market may# not be as healthy as it seems.

GEOFF BENNETT: What about on the substance,# the concerns about how A.I.

is being deployed,## often poorly with little regulation, a# flood of low-quality, misleading content## on the Internet?

How are the companies# responding to those concerns and worries?

CADE METZ: Well, in some cases,# they're working to address that## disinformation issue you talk about.# These systems do make mistakes.

They## do cause problems.

We have got# three years documenting all that.

And there are constantly efforts to# improve that problem.

But you have## to realize this technology fundamentally# makes mistakes.

This is a technology that## is built by analyzing vast amounts of# data culled from across the Internet.## It looks for patterns in that data.# And that's how it learns its skills.

But that also means that, as it learns, it's going# to make mistakes.

It's going to learn from bad## data, but it's also going to make mistakes# just because these are probability engines,## right?

They're doing something based on what# they have seen in the data.

And that means,## fundamentally, a percentage of the time they're## going to make mistakes.

People have to# realize that that's always in the mix.

And that can also -- in addition to causing all# sorts of problems in -- just in the information## as it's distributed across the Internet, it# can cause problems in other ways these systems## behave.

The hope is that these systems will do# more and more important tasks as the years come.

But if those mistakes are in the loop, it# becomes harder to complete those tasks.

GEOFF BENNETT: Problems, to be sure.

What about the promise, the promise# of A.I.?

W.. in your reporting that you find most exciting?

CADE METZ: The most exciting part# of this, I think, is in health care.

What we have seen is, the technology that# drives something like the chatbot ChatGPT,## which many people are now familiar with,# that same technology can be used to aid## drug discovery.

Essentially, it can# help design medicines and vaccines## that can help deal with illness and# disease.

That's the most powerful## aspect of the technology, in some ways the most# promising, and in other ways the most important.

GEOFF BENNETT: Cade Metz of The New York Times,# thanks again for your time.

We appreciate it.

CADE METZ: Thank you.