Contrary to the long-term belief that AI will be deflationary, the current surge in demand for computer equipment for data centers is stronger than supply, causing prices to spike and contributing significantly to producer price inflation (PPI).

Drone strikes on Amazon data centers during the Iran conflict suggest that critical AI and cloud infrastructure are now viewed as high-value military targets. This parallels how oil fields and refineries were targeted in previous eras of warfare.

Experts predicted air freight prices would plummet after the U.S. ended the duty-free 'de minimis' rule for China. Instead, prices remained high because a massive, simultaneous boom in shipping components for AI data centers absorbed all the excess capacity.

Daniel Gross's prescient question about copper being mispriced proved correct. The metal hit all-time highs due to AI's physical needs, with a single NVIDIA server rack containing two miles of copper wire. This highlights a critical, non-obvious bottleneck in the AI supply chain.

The intense signal jamming by Russia in Ukraine makes remotely piloted drones ineffective in the final phase of an attack. This has created a tactical necessity for drones that can autonomously complete their mission after losing their data link, accelerating the development of practical, on-board AI for target engagement.

Unlike the speculative "dark fiber" buildout of the dot-com bubble, today's AI infrastructure race is driven by real, immediate, and overwhelming demand. The problem isn't a lack of utilization for built capacity; it's a constant struggle to build supply fast enough to meet customer needs.

The massive, concurrent AI build-out by large tech firms creates such inelastic demand for components like copper, gas turbines, and memory that their prices are soaring. This tech-specific investment is fueling broader inflation in industrial and hardware markets, a significant ripple effect of the AI boom.

Unlike the speculative overcapacity of the dot-com bubble's 'dark fiber' (unused internet cables), the current AI buildout shows immediate utilization. New AI data centers reportedly run at 100% capacity upon coming online, suggesting that massive infrastructure spending is meeting real, not just anticipated, demand.

Previous fears of a glut in undersea cable capacity have been erased by the rise of AI. The massive data flows required for training and operating AI models are accelerating the need for new, higher-capacity cables, driving the next major investment cycle in the industry.