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In-depth analysis of the entire process of enterprise AI application, from pilot projects to large-scale commercial deployment. This article provides rational, data-driven industry insights for decision-makers from three dimensions: enterprise AI strategy, AI infrastructure (computing power, data centers), and governance framework.
In-depth analysis of the business model, capital flows, and drivers of computing power deployment for GPU as a Service (GPUaaS) in the AI infrastructure field. Exploring the contract, capital, and computing ecosystem behind the prosperity of AI infrastructure.
Based on Mary Meeker's in-depth report, analyze the capital expenditure drivers, model scale competition, energy challenges, and the competitive landscape between open-source and closed-source in the AI industry to provide industry perspectives for business decision-makers.
In-depth analysis of the key transformation from pilot to scale for enterprise AI applications, exploring the profound impact on corporate strategy, talent, and infrastructure from productivity enhancement, business reshaping, and AI governance.
A policy brief from Harvard's Belfer Center shows that U.S. data center electricity consumption could rise to 325–580 terawatt-hours by 2028, accounting for 6.7%–12.0% of national electricity use. The debate over who pays for grid upgrades is reshaping the siting, financing, and regulatory logic of AI infrastructure.
Observer has released its 2025 AI Power Index, listing 100 leaders shaping the future of artificial intelligence. This article interprets the list from an industry perspective, analyzing the distribution of AI power, the interplay between capital and ideas, and how businesses and investors should understand this landscape.
In the first half of 2026, total US venture capital investment reached $412.7 billion, with AI companies receiving 86% of that funding. The market is undergoing a structural shift, but high concentration brings potential risks.