Information has never moved faster than it does today.

People can learn about anything they'd like... in seconds. With that speed and access, narratives grow at a blistering pace.

Once-uncommon beliefs can quickly become the consensus. And that's exactly what has happened with the "AI bubble" in recent weeks.

Sure, some folks on the fringe have been screaming about an AI bubble for years. But now, it has become the accepted view – and the newest market boogeyman.

Folks aren't asking if today's market is on shaky ground... Instead, they're asking: When will the house crumble?

That fear is worth questioning, though.

Scary headlines will always get clicks. But as I'll explain, today's situation is much different than the past... And just because everyone believes this is a bubble doesn't mean the market is spiraling toward a crash.

The Escalation of Bubble Fears

We can see the explosion in AI-bubble fears by looking at Google Trends data. This tool lets us compare interest in Google search terms over time.

As you can see, folks are searching for "AI bubble" more than ever. In fact, search interest recently hit an all-time high. Take a look...

AI has only been in the public consciousness since ChatGPT launched in late 2022. And until recent months, we saw almost no concern about an AI bubble. But that has changed.

Now, the "AI bubble" has gone from a fringe thought to top of mind for anyone watching the markets (and for plenty of other folks, too).

They're concerned because of the massive amount of dealmaking we've seen in recent months... specifically, deals with OpenAI.

The problem isn't the deals themselves. Folks are worried about the structure of these deals.

You may have read about "circular deals" as a way of describing what's going on. That can come in many forms. But the most obvious kind is when a supplier invests in its customer... then the customer turns around and uses that investment to buy from the supplier.

That's what happened on September 22, when OpenAI and Nvidia announced a major partnership...

The deal means OpenAI will use Nvidia products to build 10 gigawatts of computing power. That massive build-out will allow OpenAI to develop more advanced AI models for its customers.

This partnership happens in a unique way. Nvidia will invest $100 billion into OpenAI. That will come through as cash payments (roughly $10 billion at a time, as OpenAI hits certain thresholds). OpenAI will take Nvidia's cash... and use it to buy Nvidia chips.

So, the supplier (Nvidia) is making cash investments into a customer (OpenAI)... Then that customer is turning around and spending the cash with the supplier.

If you're cynical, you might say Nvidia is funding its own sales through a partnership with OpenAI.

In reality, this is a mutually beneficial relationship. OpenAI wants to build out its own data-center network. And it'll need all that computing power if its products scale like it expects. So it's a true buyer of Nvidia chips.

The relationship between these AI companies isn't built on creating fake demand – the demand is real. But it's true that it could end quickly (and lead to problems for both sides) if the AI boom turns into a bust.

This isn't the only circular-looking deal we've seen in recent months. And folks are right about one thing – historically, this hasn't been a good sign.

But we can see one more key difference between today's AI space and the past. It's all in the health of the spending...

A Dot-Com Repeat? Not Quite

Network-equipment giant Cisco Systems (CSCO) got itself into trouble through similar means during the dot-com boom. The problem was more direct. Cisco provided financing of its networking equipment to customers.

It sent goods... booked revenue... but never received any cash. In 2000, about 10% of the company's revenue came from vendor financing. And over the next few years, as the dot-com boom turned into a bust, many of those loans went bad.

Nortel Networks and Lucent Technologies – two other major networking-equipment companies of the day – followed similar schemes. And both ended up going bankrupt in the wake of the dot-com bust.

We have not-so-distant examples of suppliers financing their customers... and most of us remember how it all ended.

But the current AI setup isn't exactly the same. At least, not yet.

For one, the vast majority of these deals aren't based on financing – that is, they're not fueled by debt. Any investment in a business always has some risk. But companies like Nvidia aren't going to go broke because of these deals, even in a worst-case scenario.

What's more, the major hyperscalers (such as Amazon, Alphabet, Meta Platforms, and Microsoft) that are the biggest spenders in the AI build-out are cash-rich. They can afford all the spending they're doing... and a lot more. And they've done nothing to hint that spending will break down anytime soon.

That could change, of course. But for now, we shouldn't assume this is an unhealthy bubble. It's a spending boom. And until that changes, the market won't go bust.

Good investing,

Brett Eversole


Editor's note: We've all seen the fear-packed headlines... But Brett says a historic pattern taking shape today could soon send $7.4 trillion flooding into stocks. That's why he's stepping forward to reveal why we could see years of higher returns ahead. Plus, he'll share details about the stocks you should buy immediately – including his No. 1 stock to own right now.

Further Reading

Last month, we saw the end to the longest government shutdown in history. And that isn't just a good thing for our country... It also points to double-digit gains over the next year – which means this is a great time to be bullish.

"All-time highs are a great time to buy," Brett writes. Investors are always looking for reasons to sell – and nothing scares folks more than a major rally. But history shows that buying after highs isn't as risky as you might think.

Market Notes

HIGHS AND LOWS

NEW HIGHS OF NOTE LAST WEEK 

American Express (AXP)... financial giant
Citigroup (C)... financial giant
Morgan Stanley (MS)... financial giant
Goldman Sachs (GS)... financial giant
Barclays (BCS)... financial services
Bank of New York Mellon (BK)... financial services
Banco Santander (SAN)... Spanish bank
Broadcom (AVGO)... semiconductors
Tower Semiconductor (TSEM)... semiconductors
Unity Software (U)... gaming software
Cisco Systems (CSCO)... networking tech
Ciena (CIEN)... telecom equipment
Fox (FOX)... mass media
Warner Bros. Discovery (WBD)... entertainment
TJX Companies (TJX)... discount department store
Ross Stores (ROST)... discount retail
J.B. Hunt Transport Services (JBHT)... shipping
Southwest Airlines (LUV)... airline
Royal Gold (RGLD)... gold royalties

NEW LOWS OF NOTE LAST WEEK

Zai Lab (ZLAB)... biopharmaceuticals
Doximity (DOCS)... health care networking
The Trade Desk (TTD)... digital advertising

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About the Editor
Brett Eversole
Brett Eversole
Editor

Brett Eversole is the Editor of and Lead Analyst for True Wealth, True Wealth Systems, and DailyWealth. Brett is also a member of the Stansberry Portfolio Solutions Investment Committee. Brett boasts a strong background in applied mathematics and statistics, and has a degree in actuarial science.

He has put his analytical expertise to work in the markets for more than a decade. And, notably, Brett helped develop True Wealth Systems – one of Stansberry Research's most in-depth, data-driven products – alongside founding editor Dr. Steve Sjuggerud. This service uses powerful computer software, similar to the kind found at hedge funds and Wall Street banks, to pinpoint the sectors most likely to return 100% or more.

Brett takes a top-down investment approach. His first goal is spotting big macro trends in the market. These are the kinds of inescapable tailwinds with major profit potential for investors. From there, Brett looks for opportunities that are cheap and unloved by the market. Last, he always waits for the momentum to be in his favor before investing. This means Brett consistently takes a contrarian approach to investing. Combine that with data-driven analysis, and it leads to fantastic long-term performance.

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