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Overenthusiasm during tech bubbles leads to massive overinvestment in infrastructure, like the fiber optic cable laid during the dot-com boom. When the bubble bursts, this infrastructure is acquired for pennies on the dollar, enabling the next generation of companies (like YouTube) to thrive cheaply.
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.
The massive capital expenditure by hyperscalers on AI will likely create an oversupply of capacity. This will crash prices, creating a golden opportunity for a new generation of companies to build innovative applications on cheap AI, much like Amazon utilized the cheap bandwidth left after the dot-com bust.
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.
Transformative technologies require massive initial capital for infrastructure (CapEx). The timing mismatch between spending and revenue often bankrupts early investors, as seen with railroads and the dot-com boom. The most profitable strategy is often to invest after the initial bubble bursts and the infrastructure is already built.
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.
Major tech shifts like canals, railways, and fiber optics consistently wiped out their initial funders who financed essential but unprofitable infrastructure. A second wave of companies then acquired these assets for pennies on the dollar and built enormously valuable businesses on top.
While disastrous for many investors, historical bubbles like the dot-com boom and railway mania left behind massively overbuilt infrastructure (fiber optics, rail networks). This infrastructure became cheap and abundant post-crash, enabling subsequent waves of innovation that benefited society for decades.
Bubbles have a paradoxical benefit. While they cause immense financial pain for investors caught in the crash, the frenzied capital allocation during the boom often funds transformative infrastructure. The railroad and dot-com bubbles, for example, left behind the national rail network and the fiber-optic backbone of the modern internet.
Howard Marks distinguishes between two bubble types. "Mean reversion" bubbles (e.g., subprime mortgages) create no lasting value. In contrast, "inflection bubbles" (e.g., railroads, internet, AI) fund the necessary, often money-losing, infrastructure that accelerates technological progress for society, even as they destroy investor wealth.