History shows a pattern: the 2022 "Crypto Bowl" preceded a crash, and the 2000 "Internet Bowl" preceded the dot-com bust. A flood of ads from one sector, like AI this year, suggests companies are urgently trying to monetize massive investments, indicating a potential bubble.
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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 spending spree by tech giants is historically reminiscent of the railroad and fiber-optic bubbles. These eras saw massive, redundant capital investment based on technological promise, which ultimately led to a crash when it became clear customers weren't willing to pay for the resulting products.
The proliferation of billboards for highly specialized, unintelligible B2B companies along Silicon Valley's Highway 101 signals market froth. When advertising shifts from consumer brands to obscure B2B2B services, it suggests excess capital is flowing deep into the tech stack, a classic sign of a potential bubble.
Overvaluing assets in a new tech wave is common and leads to corrections, as seen with mobile and cloud. This differs from a systemic collapse, which requires fundamental weaknesses like the massive debt and fraud that fueled the dot-com crash. Today's AI buildout is funded by cash-rich companies.
Veteran investor Jim Schaefer notes a recurring pattern before recessions: a massive, euphoric movement of capital into a specific area (e.g., telecom in 2001, mortgages in 2008). This over-investment inevitably creates systemic problems. Investors should be wary of any asset class currently experiencing such a large-scale influx.
Current AI investment patterns mirror the "round-tripping" seen in the late '90s tech bubble. For example, NVIDIA invests billions in a startup like OpenAI, which then uses that capital to purchase NVIDIA chips. This creates an illusion of demand and inflated valuations, masking the lack of real, external customer revenue.
The current AI-driven CapEx cycle is analogous to historical bubbles like the 19th-century railroad buildout and the dot-com boom. These periods of intense capital investment have historically led to major economic downturns and secular bear markets, suggesting a grim multi-year outlook beyond the current cycle.
The current massive capital expenditure on AI infrastructure, like data centers, mirrors the railroad boom. These are poor long-term investments with low returns. When investors realize this, it will trigger a market crash on the scale of 1929, after which the real value-creating companies will emerge.
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.
Large-cap tech's massive spending and debt accumulation to win the AI race is analogous to past commodity supercycles, like gold mining in the early 2010s. This type of over-investment in infrastructure often leads to poor returns and can trigger a prolonged bear market for the sector.
