David Craver argues the current AI spending boom isn't a bubble yet, precisely because widespread concern signals market rationality. He believes the real bubble will inflate later, once foundational AI companies like OpenAI are public and the technology is so widely adopted that euphoria replaces skepticism.
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While many fear an AI bubble, Ben Horowitz argues that current valuations are supported by fundamentals. Unlike past cycles, the customer adoption and revenue growth rates for AI companies are unparalleled. This historic demand justifies the rapid value creation, suggesting it's more than just speculative inflation.
The massive capital expenditure in AI is largely confined to the "superintelligence quest" camp, which bets on godlike AI transforming the economy. Companies focused on applying current AI to create immediate economic value are not necessarily in a bubble.
A true market bubble is a psychological phenomenon requiring near-universal belief that it isn't a bubble. The fact that so many people are actively questioning whether AI is in a bubble indicates the market has not reached the necessary state of widespread 'capitulation' from skeptics.
The current AI investment surge is a dangerous "resource grab" phase, not a typical bubble. Companies are desperately securing scarce resources—power, chips, and top scientists—driven by existential fear of being left behind. This isn't a normal CapEx cycle; the spending is almost guaranteed until a dead-end is proven.
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.
Unlike the dot-com bubble's revenue-less companies, the current AI wave involves companies that can deploy capital and immediately generate revenue. This indicates real value creation and suggests we are in an early, sustainable phase of the cycle, not a speculative peak.
Historical bubbles, like the dot-com era, occur only when everyone capitulates and believes prices can only go up. According to Ben Horowitz, the constant debate and anxiety about a potential AI bubble is paradoxically the strongest evidence that the market has not yet reached the required state of collective delusion.
The current AI infrastructure build-out avoids the dot-com bubble's waste. In 2000, 97% of telecom fiber was unused ('dark'). Today, all GPUs are actively utilized, and the largest investors (big tech) are seeing positive returns on their capital, indicating real demand and value creation.
The risk of an AI bubble bursting is a long-term, multi-year concern, not an imminent threat. The current phase is about massive infrastructure buildout by cash-rich giants, similar to the early 1990s fiber optic boom. The “moment of truth” regarding profitability and a potential bust is likely years away.
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.