The growth of AI is constrained not by chip design but by inputs like energy and High Bandwidth Memory (HBM). This shifts power to component suppliers and energy providers, allowing them to gain leverage, demand equity, and influence the entire AI ecosystem, much like a central bank controls money.

Hyperscalers are selling their own securities (stocks, bonds) to fund a massive CapEx cycle in physical infrastructure. The most direct trade is to mirror their actions: sell their securities and buy what they are buying—the raw materials and commodities needed for data centers, where the real bottlenecks now lie.

The current AI moment is unique because demand outstrips supply so dramatically that even previous-generation chips and models remain valuable. They are perfectly suited for running smaller models for simpler, high-volume applications like voice transcription, creating a broad-based boom across the entire hardware and model stack.

AI's ability to generate software at near-zero marginal cost is erasing the scarcity premium that propelled software stocks for over a decade. This realization is causing a massive capital rotation out of software ETFs and into tangible, scarce assets like metals and commodities.

Tech companies are acquiring essential AI hardware through complex deals involving stock warrants. The deal announcement inflates the chipmaker's stock, giving the warrants immediate value. This value is then used as capital to complete the original purchase, creating money "out of nothing."

The current AI investment surge is a dangerous "resource grab" phase, not a typical bubble. Companies are desperately securing scarce resources—power, chips, and top scientists—driven by existential fear of being left behind. This isn't a normal CapEx cycle; the spending is almost guaranteed until a dead-end is proven.

In a technology boom like the AI trade, capital first flows to core enablers (e.g., NVIDIA). The cycle then extends to first-derivative plays (e.g., data center power) and then to riskier nth-derivative ideas (e.g., quantum computing), which act as leveraged bets and are the first to crash.

The AI boom has created a series of supply chain bottlenecks. First, it was GPUs (Nvidia), then energy (GE Vernova), and now fiber optic cables (Corning). Companies that solve these critical shortages command immense pricing power, leading to soaring stock prices. The key is to find the next essential, scarce component.

A circular economy is forming in AI, where capital flows between major players. NVIDIA invests $100B in OpenAI, which uses the funds to buy compute from Oracle, who in turn buys GPUs from NVIDIA. This self-reinforcing loop concentrates capital and drives up valuations across the ecosystem.