Artificial Intelligence (AI) computing requires substantial energy, increasing the urgency for sustainable, scalable, and modular energy solutions. Th

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2024-05-06 01:30:05

Artificial Intelligence (AI) computing requires substantial energy, increasing the urgency for sustainable, scalable, and modular energy solutions.

The spot price for Uranium doubled over the past year due to a supply-demand imbalance, as current uranium supplies struggle to meet the demand from nuclear reactors.

I argue that the current market presents a good entry point for diversifying into the uranium sector. Macroeconomic tailwinds could suggest a strong outperformance over the next decade at the cost of short-term volatility. I outline my thought process for choosing URA 0.00%↑ as a vehicle to do so.

A few weeks ago, I discussed data center capacity planning with a friend who works for a major tech company. While we initially focused on the scarcity of GPUs—a common topic nowadays—what surprised me was learning how significantly energy consumption factors into the planning process.

Apparently, most large data centers contain vast arrays of unused racks simply because there isn't enough energy available to power everything. My own experience in capacity planning has primarily involved estimating resources like usage, cost, bandwidth, storage, memory, and CPU. However, I've never had to consider the challenges of acquiring hardware, installation, heat dissipation, or energy consumption. It was fascinating to realize that energy is often the critical limiting factor.