“Market is going to crash.”

“Getting dot-com bubble vibes.”

“Stocks are way too expensive.”

Spend enough time around markets right now and you’ll hear some version of all three.

It’s easy to understand why. Stocks have had a huge run. Hundreds of billions of dollars are being poured into AI infrastructure with no guarantee the returns will justify the spending. Interest rates are high, oil prices have surged, and parts of the economy look increasingly uneven.

Then there’s the obvious comparison: the dot-com bubble.

The internet really did change the world. Yet investors who bought internet stocks near the peak still got crushed.

Could AI follow the same path? Could the technology be world-changing while the stocks still turn out to be terrible investments?

Absolutely.

But before declaring this Dot-Com Bubble 2.0, it’s worth looking at two things that made 2000 so extreme: valuations and euphoria.

On both measures, today looks different.

Stocks have gone up a lot, but valuations haven’t risen nearly as much as many assume.

The S&P 500 trades at roughly 19x forward earnings today versus about 25x in March 2000. The Nasdaq-100 trades around 21x forward earnings versus roughly 60x at the peak of the dot-com bubble.

That doesn’t make stocks cheap. But there is a meaningful difference between expensive and dot-com expensive.

There is also a major difference in what investors are actually paying for.

Many of the companies driving the dot-com boom had little or no profit. Investors were valuing businesses based on revenue growth, website traffic, users and the promise of future earnings.

Today, some of the biggest AI winners are already generating enormous profits.

NVIDIA, for example, is producing tens of billions of dollars in quarterly profit while continuing to grow rapidly. Yet despite the stock’s huge run, it trades at a forward earnings multiple that would have looked remarkably ordinary compared with many technology stocks in 2000.

Micron is another example. AI-driven demand for memory has sent its profits sharply higher, while the stock trades at a single-digit forward earnings multiple.

There is an important caveat with Micron: memory is highly cyclical, so a low forward P/E can reflect expectations that earnings are near a peak.

But the larger point remains.

The companies at the center of today’s AI boom are not simply selling investors a vision of profits that might appear someday. Many are already producing enormous earnings.

Great businesses can still become overpriced, and their stocks can still fall dramatically. But that is a very different setup from paying extreme valuations for businesses that barely make money at all.

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Bubbles aren't just about valuation. They're also about psychology.

At the height of the dot-com boom, investor optimism was extraordinary.

The AAII Sentiment Survey asks individual investors whether they expect stocks to rise, fall or remain roughly unchanged over the next six months.

Near the 2000 peak, bullish sentiment reached extreme levels. At one point, roughly three-quarters of respondents were bullish.

Today, the picture looks very different.

Only about a third of investors are bullish, while nearly half are bearish.

That is an unusual backdrop for a supposedly euphoric bubble.

To be fair, sentiment isn’t universally cautious.

The CBOE equity put/call ratio is relatively low, suggesting options traders are positioned more aggressively for upside. So there are clearly pockets of optimism and speculation.

But that is different from the broad euphoria that defined the late 1990s.

None of this means the market has to keep going up.

Interest rates are high. AI spending could eventually outrun the revenue it generates. Earnings estimates could prove too optimistic. NVIDIA could be an incredible company and still be a bad stock at the wrong price.

And the market doesn't need a dot-com bubble to fall 10%, 20% or more.

That’s the important distinction.

The question isn't “Can stocks go down?”

Of course they can.

The question is whether today’s market actually resembles the speculative excess of 2000 closely enough that we should expect the same outcome simply because stocks have risen a lot and investors are excited about a new technology.

In 2000, investors were paying extraordinary valuations for many companies that weren't making money, while investor optimism was near historic extremes.

Today, the S&P 500 and Nasdaq-100 trade at dramatically lower multiples, many of the biggest AI beneficiaries are highly profitable, and individual investors are still more bearish than bullish.

Maybe the market is expensive.

Maybe AI expectations are too high.

Maybe we're due for a correction.

But “this feels like 2000” isn't the same thing as actually being 2000.