AI Infrastructure

AI infrastructure covers the physical and software stack required to train, deploy, and operate modern models: accelerators, memory, networking, data centers, power, cooling, model-serving software, and cloud capacity. This hub treats AI infrastructure as a sector because demand shocks rarely stop at one company. A new model, procurement deal, export restriction, or power bottleneck can move chips, utilities, cloud platforms, and equipment suppliers at once.

The page emphasizes capacity and constraint. Positive signals include GPU orders, data-center leasing, cloud capex commitments, inference adoption, and supply-chain expansion. Negative signals include power scarcity, margin pressure, regulatory controls, customer digestion, or evidence that compute demand is overbuilt. The article list below keeps the page tied to the latest events shaping capacity, cost, and competitive positioning across the AI stack.