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.

Major tech companies are investing in their own customers, creating a self-reinforcing loop of capital that inflates demand and valuations. This dangerous practice mirrors the vendor financing tactics of the dot-com era (e.g., Nortel), which led to a systemic collapse when external capital eventually dried up.

The AI boom is fueled by 'club deals' where large companies invest in startups with the expectation that the funds will be spent on the investor's own products. This creates a circular, self-reinforcing valuation bubble that is highly vulnerable to collapse, as the failure of one company can trigger a cascading failure across the entire interconnected system.

The AI race has been a prisoner's dilemma where companies spend massively, fearing competitors will pull ahead. As the cost of next-gen systems like Blackwell and Rubin becomes astronomical, the sheer economics will force a shift. Decision-making will be dominated by ROI calculations rather than the existential dread of slowing down.

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.

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.

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.

Companies are spending unsustainable amounts on AI compute, not because the ROI is clear, but as a form of Pascal's Wager. The potential reward of leading in AGI is seen as infinite, while the cost of not participating is catastrophic, justifying massive, otherwise irrational expenditures.

Michael Burry, known for predicting the 2008 crash, argues the AI bubble isn't about the technology's potential but about the massive capital expenditure on infrastructure (chips, data centers) that he believes far outpaces actual end-user demand and economic utility.