David Sterling analyzes the strategic evolution of the global AI ecosystem and corporate commercialization. He provides high-level insights into how artificial intelligence reshapes international competitive landscapes.
The generative AI market size is expected to grow from USD 161.0 billion in 2026 to USD 1,260.15 billion in 2034, at a compound annual growth rate of 29.30%. North America leads with a 48.70% share, while Asia Pacific becomes the fastest-growing region. This article, based on a Fortune Business Insights report, provides insights into enterprise AI adoption trends, industry landscape, and investment directions.
The rise of AI is triggering a global data center construction boom, bringing tremendous opportunities to the construction, energy, and infrastructure industries, while also presenting challenges such as power consumption, cooling, and sustainability.
In-depth analysis of key scenarios for enterprise adoption of Agentic AI, including software development, RPA enhancement, customer support automation, and customer interaction management, while exploring its market impact and future trends.
Perplexity CEO proposes a new metric called "token value per watt," and with the rise of open-source models, enterprises are shifting toward controllable local deployment—reshaping the AI competitive landscape.
Observer releases the 2025 AI Power Index ranking. This article analyzes the capital and ideological competition behind the ranking from an industry perspective, revealing the concentration of power and geopolitical competition in the AI industry.
This article, based on the latest ICLG report, analyzes key developments in China's 2025 AI regulation from principles to implementation, including content labeling, protection of minors, security incident response, and tech ethics, and explores market impacts and corporate response strategies.
According to the latest market report, the global AI platform market is expected to reach $2.39 trillion by 2035, with a CAGR of 39.5%. This article analyzes market drivers, regional landscape, and corporate response strategies from an industry perspective.
Based on the latest MarketsandMarkets report, the global AI market size is expected to grow from $601.93 billion in 2026 to $3,638.08 billion in 2033, with a CAGR of 29.3%. Generative AI and Agentic AI are driving enterprises from pilot projects to production deployment, with the hardware and platform layers becoming the focus of competition.
A Columbia University report proposes an AI power gap index, which comprehensively measures the shaping power of tech giants, governments, open-source communities, and other entities on the AI ecosystem, revealing a trend of industrial power concentration.
AI infrastructure is expanding rapidly, but security measures have not kept pace. The Lava Labs report points out ten major security risks facing AI data centers, and traditional data center designs are unable to address these new threats.
Deloitte's "State of AI in the Enterprise" report shows that 74% of financial institutions plan to deploy autonomous AI agents, but only 21% have a mature risk management framework. The article provides an in-depth analysis of the bottlenecks, competitive landscape, and enterprise implications for the large-scale implementation of AI in the financial industry.
June 2026 marks the shift of AI governance from theory to operationalization, with three major control planes—model access, infrastructure capacity, and cybersecurity—becoming the new battleground for AI competition. This article provides an in-depth analysis of key events and their impact on the industry.
Zhipu's latest open-source model, GLM 5.2, trails Anthropic Opus 4.8 by only one percentage point in key benchmarks, while costing just one-fifth as much. The U.S. government's restrictions on the release of OpenAI and Anthropic models make open-source a safer choice.
As enterprise AI moves from experimentation to production, GPUs are not the only bottleneck. Data delivery efficiency is becoming a key factor in determining the return on AI investment, and enterprises need to re-evaluate the infrastructure between storage and computing.
The open-source large model GLM-5.2, launched by z.AI, has sparked heated discussion in Silicon Valley's tech community with its million-token context window and powerful code capabilities. This article analyzes the model's technical highlights, market impact, and changes in the China-US AI competition landscape.
Anthropic suddenly shut down the Fable and Mythos models due to government directives, exposing the supply risks of relying on closed AI. Microsoft CEO Nadella warned that companies should control their own IP, and the stock prices of Chinese open-source model companies surged accordingly. This article analyzes the profound impact of the event on the AI industry landscape, corporate strategy, and investment logic.
Research shows that current pathology foundation models lack robustness to non-biological features (such as differences in laboratory procedures), which may affect the safety of clinical diagnosis. The PathoROB benchmark provides a new standard for model evaluation.
Analyze the application challenges of AI governance in autonomous networks, discuss the EU AI Act, real-time monitoring, L5 autonomy, Asia's leading position, and trust issues, providing industry-level insights for enterprise decision-makers.
From Anthropic and OpenAI to Meta and Apple, global AI giants are diverging along three paths: frontier models, middle-layer infrastructure, and on-device AI. This article analyzes, from the perspectives of the industrial chain, commercialization, capital expenditure, and enterprise adoption, how these three “just right” AI strategies are shaping the competitive landscape.