AI Capital Cycle and Rotation explains how AI investment begins with capex buildout and later broadens through capital rotation across the stack.

A structural map showing how data centers integrate power, cooling, compute, and connectivity to enable large-scale AI systems.

A structural map of AI networking and interconnect infrastructure, covering switching, optical systems, interconnect technologies, and data center integration.

A structural map of the AI compute supply chain, showing how accelerators, advanced packaging, memory systems, and server infrastructure enable large-scale AI deployment.

The expansion of AI systems is ultimately constrained by electricity infrastructure. While most discussions focus on chips and models, the scaling of AI depends first on the ability to generate, transmit, and distribute power to data centers. Electricity → Power Infrastructure → Data Centers → Compute → AI Systems

AI and robotics expansion follows a physical constraint chain: electricity, compute, infrastructure, perception, actuation, and applications.

Broadcom’s $10B buyback signals a new phase in the AI capex cycle. While many tech giants redirect cash toward massive AI infrastructure spending, Broadcom is using strong AI-driven cash flow to retire shares, creating a liquidity defense under the EG LRM-14 macro framework.

The EGTB framework indicates that the Feb 12 bottom signal remains active, with no evidence of top formation. Current market conditions reflect re-calibration within an intact structural advance, characterized by rotational breadth dynamics, liquidity normalization under the EGLRM-14 framework, and a contained volatility structure with no Equity Regime Water-Drop reset signal triggered.

As AI investing shifts from narrative-driven trades to cash-flow repricing, a structural separation is underway. Nvidia’s resilience may signal where capital is truly aligning in the emerging AI capital cycle.