Today's massive AI company valuations are based on market sentiment ("vibes") and debt-fueled speculation, not fundamentals, just like the 1999 internet bubble. The market will likely crash when confidence breaks, long before AI's full potential is realized, wiping out many companies but creating immense wealth for those holding the survivors.

A true bubble, like the dot-com crash, involves stock prices falling over 50% and staying depressed for years, with capital infusion dropping similarly. Short-term market corrections don't meet this historical definition. The current AI boom, despite frothiness, doesn't exhibit these signs yet.

The AI era is not an unprecedented bubble but the next phase in a recurring pattern where each new computing cycle (mainframe, PC, internet) is roughly 10 times larger than the last. This historical context suggests the current massive investment is proportional and we are still in the early innings.

Widespread public debate about whether a market is in a bubble is evidence that it is not. A true financial bubble requires capitulation, where nearly everyone believes the high valuations are justified and the skepticism disappears. As long as there are many vocal doubters, the market has not reached the euphoric peak that precedes a crash.

Vincap International's CIO argues the AI market isn't a classic bubble. Unlike previous tech cycles, the installation phase (building infrastructure) is happening concurrently with the deployment phase (mass user adoption). This unique paradigm shift is driving real revenue and growth that supports high valuations.

This AI cycle is distinct from the dot-com bubble because its leaders generate massive free cash flow, buy back stock, and pay dividends. This financial strength contrasts sharply with the pre-revenue, unprofitable companies that fueled the 1999 market, suggesting a more stable, if exuberant, foundation.

Historical technology cycles suggest that the AI sector will almost certainly face a 'trough of disillusionment.' This occurs when massive capital expenditure fails to produce satisfactory short-term returns or adoption rates, leading to a market correction. The expert would be 'shocked' if this cycle avoided it.

The risk of an AI bubble bursting is a long-term, multi-year concern, not an imminent threat. The current phase is about massive infrastructure buildout by cash-rich giants, similar to the early 1990s fiber optic boom. The “moment of truth” regarding profitability and a potential bust is likely years away.

A macro strategist recalls dot-com era pitches justifying valuations with absurd scenarios like pets needing cell phones or a company's tech being understood by only three people. This level of extreme mania highlights a key difference from today's market, suggesting current hype levels are not unprecedented.