Starting 2026, most people are aware that a handful of Chinese companies are making strong, open AI models that are applying increasing pressure on the American AI economy.
While many Chinese labs are making models, the adoption metrics are dominated by Qwen (with a little help from DeepSeek). Adoption of the new entrants in the open model scene in 2025, from Z.ai, MiniMax, Kimi Moonshot, and others is actually quite limited. This sets up the position where dethroning Qwen in adoption in 2026 looks impossible overall, but there are areas for opportunity. In fact, the strength of GPT-OSS shows that the U.S. could very well have the smartest open models again in 2026, even if they’re used far less across the ecosystem. — Read More
Daily Archives: January 9, 2026
Chinese AI models have lagged the US frontier by 7 months on average since 2023
Since 2023, every model at the frontier of AI capabilities, as measured by the Epoch Capabilities Index, has been developed in the United States. Over that same period, Chinese models have trailed US capabilities by an average of seven months, with a minimum gap of four months and a maximum gap of 14. — Read More
The ROI Problem in Attack Surface Management
Attack Surface Management (ASM) tools promise reduced risk. What they usually deliver is more information.
Security teams deploy ASM, asset inventories grow, alerts start flowing, and dashboards fill up. There is visible activity and measurable output. But when leadership asks a simple question, “Is this reducing incidents?” the answer is often unclear.
This gap between effort and outcome is the core ROI problem in attack surface management, especially when ROI is measured primarily through asset counts instead of risk reduction. — Read More
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