While fiber optics long dominated data transfer between data centers ('scale out'), the next growth wave is 'scale up.' This involves replacing short copper Ethernet cables within individual server racks, a move necessitated by rising data speeds and the physical limitations of copper, promising unprecedented unit volumes.

The short range of copper cables is a key driver behind modern data center design. To maintain bandwidth, GPUs are packed into incredibly dense, megawatt racks. These racks are so heavy they require reinforced concrete floors to support their weight, highlighting a physical bottleneck that photonics technology aims to solve.

Massive, long-term investment in AI data centers assumes current power models will persist. Future AI efficiency breakthroughs could render many of these facilities obsolete or underutilized, similar to the overbuilt fiber optic networks of the dot-com era.

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 investment in data centers isn't just a bet on today's models. As AI becomes more efficient, smaller yet powerful models will be deployed on older hardware. This extends the serviceable life and economic return of current infrastructure, ensuring today's data centers will still generate value years from now.

The current AI infrastructure expansion differs critically from the dot-com bubble's fiber buildout. There are no 'dark GPUs'; every unit of computing power, even older generations, is immediately utilized, suggesting demand is keeping pace with supply.

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.

After addressing GPU and memory supply, NVIDIA is making deals with optical networking firms like Corning. As data center bandwidth needs escalate, high-speed optical components are the next critical performance bottleneck, and NVIDIA is moving to control this layer of the hardware stack.