Public and political fear of Japanese economic takeover reached its zenith in the early 1990s, with books like Michael Crichton's "Rising Sun." Ironically, this coincided with the bursting of Japan's asset bubble, highlighting a critical lag between economic reality and popular discourse.

Despite a massive tech stock run-up, key sentiment indicators and surveys of major asset allocators show caution, not the extreme bullishness seen in bubbles like the dot-com era. This suggests the market may not be at its absolute peak yet.

The dot-com era was not fueled by pure naivete. Many investors and professionals were fully aware that valuations were disconnected from reality. The prevailing strategy was to participate in the mania with the belief that they could sell to a "greater fool" before the inevitable bubble popped.

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.

Analysis shows that the themes venture capitalists and media hype in any given year are significantly delayed. Breakout companies like OpenAI were founded years before their sector became a dominant trend, suggesting that investing in the current "hot" theme is a strategy for being late.

While being a market Cassandra can build a reputation, being too early is costly. Charles Merrill of Merrill Lynch famously warned of a crash in 1928, but investors who heeded his advice missed a 90% market run-up before the October 1929 peak, illustrating the immense financial downside of exiting a bubble prematurely.

Contrary to intuition, widespread fear and discussion of a market bubble often precede a final, insane surge upward. The real crash tends to happen later, when the consensus shifts to believing in a 'new economic model.' This highlights a key psychological dynamic of market cycles where peak anxiety doesn't signal an immediate top.

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.

Marks emphasizes that he correctly identified the dot-com and subprime mortgage bubbles without being an expert in the underlying assets. His value came from observing the "folly" in investor behavior and the erosion of risk aversion, suggesting market psychology is more critical than domain knowledge for spotting bubbles.