The AI revolution promises to change everything, but what if it’s leading us straight into another financial collapse? Glenn Beck and economist Peter Atwater break down the eerie parallels between today’s AI boom and the 2008 housing crash, revealing how speculative hype, overvalued tech giants, and circular corporate investments are inflating a dangerous bubble. Could this “AI gold rush” be the next market disaster waiting to happen?
Transcript
Below is a rush transcript that may contain errors
GLENN: Is it not a bubble?
I don't know. Are we close to AGI or not close to AGI.
Again, I don't know.
Is it to change things? Yes. I saw a story in our show prep today. I'm not going to get a chance to get it. It's about other countries that are building these giant server farms. Their electricity and their water is being shut off because all of it being diverted to these big server farms. And if we're not careful, that's exactly what's going to happen to us.
Peter Atwater is a guy that Stu and I have been talking about for a while because he's comparing this AI bubble. He's like, "Look, I wanted to show you a chart. I'm not smart enough to figure out the chart. But let me show you a chart, and I want to show you a chart that I did in, like, 2007 or 2008 with the housing bubble! Wow, they kind of look exactly the same. And it's a little frightening."
Peter is with us now. Peter Atwater from the College of William & Mary. He's an adjunct lecturer there. He's the guy who coined the term K-shaped recovery.
Welcome to the program, how are you, sir?
PETER: I'm great, Glenn. Thanks very much for having me.
GLENN: You bet. Okay. So can you explain the housing -- or, not the housing bubble.
The AI bubble. Do you believe it is? And if so, why? And what does that mean?
PETER: I do believe it is.
And I study confidence and its impact on what we do.
And so what I see in the AI bubble is a lot of similarities to what we saw during the housing bubble. Where everybody wants to be involved.
There's a social frenzy to it. There's a want to, you know, make a lot of money, to see the opportunity in it.
There's a lot of speculation.
And what matters so much, to me as a researcher, is that this network that existed in the -- in the housing bubble. Where mortgages were sliced and diced.
And you had these conveyor belts that moved everything from, you know, mom and pop's house to folks all over the world.
GLENN: Right.
PETER: Now, it's within the AI system. Where you have enormous amounts of capital moving, but also equipment.
So it looks a lot like the Just In Time Network that we saw stumble during COVID.
GLENN: Okay. That doesn't make me happy. But there's a difference between the housing bubble, where it was all being inflated and resold and repackaged. And this, which does seem to be a game-changer on productivity. Where housing was not.
This seems to be like it could be a real game changer for economies. Agree or disagree?
PETER: Oh. There's no question, it will be a game changer. But we can think about it the same way we said dot-com was going to be a game changer. Like railroads. And all of these other things that we have in terms of speculative mania.
There's real productivity. Real improvement that comes from it. But what happens is that investors anticipate it happening far sooner, in far larger scale.
And much more profitably than it ever does.
GLENN: So what are you predicting? How is this going to -- how is this going to happen?
What's a bad case scenario, not necessarily worst?
I don't know if I can handle worst. Bad case scenario, and realistic scenarios.
PETER: Yeah. So to me, the realistic scenario is that valuations come down dramatically. At the same time, the build-out continues at a much lower pace.
And eventually, maybe a decade from now, it all settles out.
But in the meantime, there's a lot of financial pain that's going to go along with it. Particularly because today, more than 40 percent of an S&P 500 ties to AI.
GLENN: Like seven companies. Right?
PETER: Seven companies, and -- and the ones that are closest to them. So that, you know, retirees, pension plans, you know, folks that invest in index funds, have a super sized allocation to AI whether they realize it or not.
GLENN: Can you give me an example of this happening in history, that's not housing, but more industry?
PETER: Sure. You can go back to radio. In the -- in the 20s. I mean, RCA was a mammoth weight in the markets. Because people were incredibly excited about it.
You saw it even -- go back even further to canals. We -- we love new technology. Particularly where we can identify the efficiencies that we see coming from it.
STU: One of the things that's really interesting about the trends you've highlighted, Peter, is this sort of circuitous relationship with these companies. It's too complicated to go through all of it.
Just to give you one quick relationship here. And tell me if I'm understanding this right.
OpenAI, of course, buys a bunch of chips from NVIDIA. They're spending a ton of money with NVIDIA. NVIDIA is investing $100 million into OpenAI. OpenAI is -- has a 300 billion-dollar cloud deal with Oracle.
Oracle is spending tens of billions of dollars in chips with NVIDIA. And then NVIDIA is investing into OpenAI. There's a bunch of these arrows, that are pointing in this circular directions. And it seems like companies are flowing money back and forth to each other, and all these arrangements. And you wonder if there's any disruption here.
Are we looking at some sort of short-term collapse of all this stuff.
PETER: The -- the dog eating its tail phenomenon is extraordinary here. And what's so unusual about this one is, in prior bubbles, the -- the conveyor belts were among smaller participants.
But in this one, we had the largest technology companies in the world, to spinning money around, among themselves.
It looked like one of those Esther drawings, where the waterfall just keeps moving in perpetuity. And the challenge, particularly given that OpenAI is at the center of it, is that this is a company that is barely profitable. That is committing to hundreds of billions of dollars in commitments.
STU: Hmm.
GLENN: So what does it look like if it starts to fall apart? And what are the signs we should be watching for?
PETER: So what we know right now, is that everybody wants to be affiliated with AI in some way.
And so you end up with these late arrivals to the party.
And typically when a bubble bursts, the last guy to the party, is the first to leave. When you think of this in the context of a mortgage bubble.
Where it was the subprime lenders who showed up right at the tail end.
And then collapsed first. So I'm -- I'm watching to see these companies that are barely AI-related, that have tried to position themselves as being AI industry leaders. Who are likely to fail in the not too distant future.
They just need rarefied air to exist.
GLENN: Like what companies?
PETER: I don't have specific names to throw out there.
GLENN: Sure. Okay.
PETER: But they're typically smaller highly leveraged offerings. To very, very compelling, but untested technologies.
GLENN: Now, this would be -- I mean, if it collapses, I mean, that would be horrific for our economy.
But also, what -- what happens with the race with China? I mean, China is deeper into this than we are, at like crazy.
How -- how does this affect China, what happens to the race, how does -- I mean, how does this not move forward?
PETER: So I am by no means a China expert, but I would expect that if our confidence in AI begins to fall, confidence in AI more broadly will come under question.
STU: Hmm.
PETER: So they then face questions in terms of policy maker credibility. In terms of, why did you commit so much to this?
No difference than a CEO faces that test, when a bubble bursts.
GLENN: So what does success look like to you?
Because I'm not sure -- I had a really fascinating conversation a couple of weeks ago.
And he's going to come on the show in a couple of weeks with Max Tegmark, who is a brilliant AI ethicist. And we were talking about AI, AGI. And he believes that that may not be happening. And he makes a great case on this.
But is that the goal, or, I mean. Because what -- what is the goal that we're not going to hit, that would fall short?
That would cause this kind of stuff?
PETER: So I think you -- we tend to fall short in terms of immediate usage. So volume short.
But also profitability.
You know, if you go back through dot-com bubble. They all imagined this huge, you know, pot of gold at the end of the rainbow. And you're seeing the same wild fascination with the potential profitability for AI.
And, again, that may come, but it's unlikely too come at the speed and magnitude that people now expect. I mean, we're -- we're fans of science.
GLENN: Boy, I mean, in a way, that would be really, really good.
Because that -- what I worry about is AI advancing as quickly as everybody says it is. And then what happens to all the jobs so quickly. I mean, you just can't absorb that kind of an impact. If it happens that fast. So I don't know which is better.
PETER: So typically, we'll see a backlash against new technology. I mean, if you go back to the 1920 bubble burst. And you saw this backlash to, you know, innovate technologies like the vacuum. And the ironing board. And all these things that people said, took jobs away. Well, we'll have that same thing in all likelihood. And this time, too, to a point you made earlier, likely compounded by a greater awareness of the environmental consequences of this, and also, the cost that it creates in the average consumer, in terms of the utility bills.
GLENN: Hmm.
Can you explain one more thing? Because you're the guy who invented the K-shaped recovery. And as Stu and I talked about the K-shaped recovery -- can you explain that? K-shaped recovery.
PETER: Sure. So when COVID hit, I immediately saw that if you were a white-collar worker who could work from home, your confidence improved immediately. Whereas, if you were a, you know, somebody who worked if a warehouse. Or stocked shelves in the supermarket. Or hospital worker.
Your confidence didn't start to improve for a long time.
And from that, what I have seen is that the economy that results from these two different tracks of confidence, are vastly different.
And today, those are the top, whether it's because of the markets, or because of corporate earnings, growth. Those at the top feel invulnerable.
And they're spending like it. They're investing like it. They're living like it. They're living like there's no tomorrow.
Well, on the other hand, those at the bottom today, aren't sure how they will make it through the take. They're delinquent on their car loans. They're now worried about health care costs. And so to me, this K that -- this divide has created two classes of Americans.
You have the increasingly desperate, and those who feel invulnerable.
GLENN: That does not sound stable long-term.
PETER: It doesn't feel stable to me too.
And I worry that those who are in a position to do something about it, we're spending so much of our time in this country, fighting between the left and the right, and we're not seeing that our biggest divide is up and down.
That those at the bottom, there's a bipartisan hopelessness that exists.
GLENN: Hmm.
PETER: That I feel like Washington is not paying enough attention to.