The memo argues that the "hysteria of the bubble" compresses the timeline for building out new technologies from decades into just a few years. Patient, value-focused investing would never fund the massive, parallel, and often wasteful experimentation required to jump-start a new technological paradigm at such a rapid pace.
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The memo details how investors rationalize enormous funding rounds for pre-product startups. By focusing on a colossal potential outcome (e.g., a $1 trillion valuation) and assuming even a minuscule probability (e.g., 0.1%), the calculated expected value can justify the investment, compelling participation despite the overwhelming odds of failure.
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.
The current AI boom isn't just another tech bubble; it's a "bubble with bigger variance." The potential for massive upswings is matched by the risk of equally significant downswings. Investors and founders must have an unusually high tolerance for risk and volatility to succeed.
During technological bubbles or periods of intense change, it's possible to accomplish seven to ten years of work in one. This 'dog years' effect offers a unique opportunity for compressed learning and value creation, even if the specific venture fails. The key is embracing the frenetic pace.
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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.
Innovation doesn't happen without risk-taking. What we call speculation is the essential fuel that allows groundbreaking ideas, like those of Elon Musk, to get funded and developed. While dangerous, attempting to eliminate speculative bubbles entirely would also stifle world-changing progress.
Speculation is not an evil byproduct of innovation but its necessary component. Groundbreaking ventures like SpaceX are impossible without investors willing to bet on seemingly crazy ideas. The goal for policymakers shouldn't be to eliminate speculation, but to manage its excesses without killing the innovation it fuels.
Current AI spending appears bubble-like, but it's not propping up unprofitable operations. Inference is already profitable. The immense cash burn is a deliberate, forward-looking investment in developing future, more powerful models, not a sign of a failing business model. This re-frames the financial risk.
The dot-com bubble didn't create wealth in 1999; it destroyed it. Generational wealth came from buying and holding survivors like Amazon *after* its stock had fallen 95%. The winning strategy isn't timing the crash, but surviving it and holding quality assets through the long recovery.
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.