Editor profile
Chief Editor, Global AI Strategy
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.
david.sterling@aiindustryreview.orgAI 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.