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Gavin Baker claims markets underestimate AI demand by focusing on public companies while missing the massive, untracked compute spending from private AI labs and open-source inference providers. Data points like rising GPU rental prices indicate that the underlying demand for AI infrastructure is much stronger than stock prices reflect.

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The demand for AI tokens is growing faster than the supply of GPU infrastructure. This profound imbalance creates a market where not just top-tier AI labs, but also second and third-tier players will likely sell out their capacity. Superior models will command better margins, but the overall resource constraint means even lesser models will find customers.

The current AI boom isn't a speculative demand bubble. Real companies are paying for and getting value from AI, creating a supply shortage, not an overhang. In the long term, the market's disruptive potential is actually undervalued.

Unlike the dot-com bubble's speculative fiber build-out which resulted in unused "dark fiber," today's AI infrastructure boom sees immediate utilization of every GPU. This signals that the massive investment is driven by tangible, present demand for AI computation, not future speculation.

The 2000 tech bubble was defined by massive overinvestment in unused telecom infrastructure ('dark fiber'). In contrast, today's spending on GPUs sees immediate, high utilization and positive ROI for the largest buyers, indicating a fundamentally healthier market driven by real demand.

Financial leaders like JPMorgan's Jamie Dimon and BlackRock's Larry Fink are signaling a major shift in market sentiment. They now believe the AI boom is real and that the primary constraint is a shortage of supply—compute and infrastructure—to meet overwhelming demand, directly countering earlier fears of a speculative bubble.

The transition to agentic AI creates an exponential, non-speculative demand for compute that far exceeds supply. This justifies massive CapEx investments by hyperscalers, indicating a rational response to real demand rather than a speculative bubble.

Unlike previous tech bubbles characterized by speculative oversupply, the current AI market is demand-driven. Every time a major player like OpenAI 3x-es its compute capacity, the new supply is immediately consumed. This sustained, unmet demand indicates real utility, not just speculative froth.

The key signal for an AI bubble isn't just stock market commentary. It's the transition of data center buildouts from being funded by free cash flow to being funded by debt, particularly from private credit firms. This massive, less-visible market is the real stress test for AI's financial stability.

The perceived constraint on AI compute isn't a true supply issue, but a consequence of VC-funded companies pricing their services below cost to fuel growth. This creates artificial demand that masks the true, profitable market size until unit economics are forced.

The narrative of "off the charts" AI demand is misleading. Major AI providers like OpenAI are "burning tens of billions of dollars," indicating they are not charging the true cost for their services. A realistic picture of demand will only emerge once they are forced to price for profitability, which could significantly cool the market.