Speculative manias, like the AI boom, function like collective hallucinations. The overwhelming belief in future demand becomes self-fulfilling, attracting capital that builds tangible infrastructure (e.g., data centers, fiber optic cables) long before cash flows appear, often leaving lasting value even after the bubble bursts.

Bubbles provide the capital for foundational technological shifts. Inflated valuations allow companies like OpenAI to raise and spend astronomical sums on R&D for things like model training, creating advances that wouldn't happen otherwise. The key for investors is to survive the crash and back the durable winners that emerge.

History shows that transformative technologies like railroads and the internet often create market bubbles. Investors can lose tremendous amounts of capital on overpriced assets, even while the technology itself fundamentally rewires the economy and creates massive societal value. The two outcomes are not mutually exclusive.

History shows pioneers who fund massive infrastructure shifts, like railroads or the early internet, frequently lose their investment. The real profits are captured later by companies that build services on top of the now-established, de-risked platform.

Venture capitalist Seth Levine argues that bubbles are an inevitable, and even productive, part of the innovation cycle. While many investments will fail, the frenzy ensures massive capital flows into transformational technologies like AI, allowing the market to eventually find the winning companies and ideas.

While many early investors in tech booms (e.g., telecom, AI) lose money, these 'bubbles' are not a societal waste. They fund the rapid construction of foundational infrastructure, like fiber optic networks or data centers, creating immense long-term value and options for future innovation that society ultimately benefits from.

The massive capital expenditure in AI infrastructure is analogous to the fiber optic cable buildout during the dot-com bubble. While eventually beneficial to the economy, it may create about a decade of excess, dormant infrastructure before traffic and use cases catch up, posing a risk to equity valuations.

The epicenter of a tech boom is rarely the new technology itself. Instead, capital floods into adjacent, understandable sectors. The dot-com bubble wasn't about software but a massive telecom infrastructure bubble, fueled by debt financing for tangible assets like fiber and buildings.

The current AI boom may not be a "quantity" bubble, as the need for data centers is real. However, it's likely a "price" bubble with unrealistic valuations. Similar to the dot-com bust, early investors may unwittingly subsidize the long-term technology shift, facing poor returns despite the infrastructure's ultimate utility and value.