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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.

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The massive capital expenditure by hyperscalers on AI will likely create an oversupply of capacity. This will crash prices, creating a golden opportunity for a new generation of companies to build innovative applications on cheap AI, much like Amazon utilized the cheap bandwidth left after the dot-com bust.

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 proliferation of sensors, especially cameras, will generate massive amounts of video data. This data must be uploaded to cloud AI models for processing, making robust upstream bandwidth—not just downstream—the critical new infrastructure bottleneck and a significant opportunity for telecom companies.

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.

Unlike the dot-com bubble's finite need for fiber optic cables, the demand for AI is infinite because it's about solving an endless stream of problems. This suggests the current infrastructure spending cycle is fundamentally different and more sustainable than previous tech booms.

The massive capital expenditure in AI infrastructure is analogous to the fiber optic cable buildout during the dot-com bubble. While eventually beneficial to the economy, it may create about a decade of excess, dormant infrastructure before traffic and use cases catch up, posing a risk to equity valuations.

The AI infrastructure boom has moved beyond being funded by the free cash flow of tech giants. Now, cash-flow negative companies are taking on leverage to invest. This signals a more existential, high-stakes phase where perceived future returns justify massive upfront bets, increasing competitive intensity.

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.

The next wave of data growth will be driven by countless sensors (like cameras) sending video upstream for AI processing. This requires a fundamental shift to symmetrical networks, like fiber, that have robust upstream capacity.

The massive energy demand from AI data centers is driving a $75 billion buildout of extra-high-voltage (765kV) power lines, a class of infrastructure capable of moving six times more power than standard lines. The presence of wealthy AI companies as guaranteed buyers de-risks these huge projects for grid operators, creating a foundational upgrade for U.S. industrial capacity akin to the interstate highway system.