How Tech Giants Manage Energy in the Age of AI

2025-11-27T17:33:08+08:00November 27th, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , , , , , |

Executive Summary The growth of AI was once imagined as limitless, but energy is becoming its most tangible boundary. As power shortages emerge as the new ceiling of computation, competition among tech giants is shifting from who owns the most GPUs to who can govern the rhythm of energy. This article examines how seven major technology companies are redefining their relationship with power: Microsoft institutionalizes energy, building a governable system through long-term contracts and nuclear

Rubin Is Not Just a GPU Upgrade: NVIDIA Is Rewriting the Value Chain

2026-02-02T12:21:08+08:00October 16th, 2025|Categories: Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , , , , |

Executive Summary NVIDIA’s Rubin platform may look like a routine GPU upgrade, but its impact extends far beyond chip performance. By redesigning the internal architecture of AI servers, with a larger motherboard, liquid cooling as a core feature, and a modular dual-layer PCBA, Rubin fundamentally reshapes the value distribution within the supply chain. PCB and materials suppliers gain new momentum from increased complexity and higher technical requirements. Liquid cooling vendors and metal processing partners become

Reshaping the AI Chess Game: Why NVIDIA Is Betting on Intel and Teaming Up with OpenAI

2025-09-23T16:03:19+08:00September 23rd, 2025|Categories: Featured Notes, Global Business Dynamics, Strategic Tech and Market Signals|Tags: , , , , , , , , , , , , , , , , , , , , |

Executive Summary NVIDIA recently announced two major moves: investing in Intel to co-develop custom x86 CPUs with NVLink, and partnering with OpenAI to build AI infrastructure at the scale of a million GPUs. These actions may seem independent, but they reveal the same trend: the bottleneck in AI is shifting from the number of GPUs to the efficiency of CPU–GPU integration. In this transition, NVIDIA is reinforcing cross-platform standards through NVLink, Intel is focusing on

AI Deployment Bottleneck: Observing the Limits of AI Adoption and Market Narratives

2025-08-27T11:22:03+08:00June 3rd, 2025|Categories: Strategic Tech and Market Signals|Tags: , , , , , , , , , , , |

Executive Summary: From NVIDIA to the Rack When we talk about artificial intelligence (AI), the spotlight usually stays on models, compute power, and chips. But the most critical phase, which is deployment, is often left out of the conversation. Getting from NVIDIA’s chips to a fully operational rack in a data center takes far more than engineering. It requires navigating manufacturing logistics, capital pressure, thermal limits, geopolitical shifts, and a changing platform landscape. This article

Go to Top