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ππ€ The AI Cold War Just Went Global
TL;DR The US is restricting access to its most powerful AI models in the name of national security. China has responded by releasing cheaper, open models that are rapidly closing the gap. The race is no longer just about building the best AI. It's about deciding who gets access to it. π
What Happened? Over the past two weeks, the AI landscape has shifted dramatically.
The US government forced Anthropic to suspend access to its most advanced models, Fable 5 and Mythos 5, before partially restoring access to trusted US organisations. OpenAI has reportedly also been asked to launch its next frontier model, GPT-5.6, in a controlled rollout with government oversight rather than a public release.
Meanwhile, Chinese AI companies didn't wait.
Z.ai launched GLM-5.2, an open-weight model that's approaching the performance of America's best systems in coding and cybersecurity while costing a fraction of the price. Other Chinese firms, including 360 Security, have launched competing security-focused models too.
The result?
The AI race has gone from building bigger models to controlling who can use them.
πΊπΈπ¨π³
The logic behind US restrictions is understandable.
If frontier AI could reshape cyber warfare, defence and national security, governments don't want their most powerful systems ending up in the wrong hands.
But software doesn't behave like missiles.
When you restrict access to a popular product, people don't simply stop using it.
They look for alternatives.
And increasingly, those alternatives are Chinese.
As one researcher put it: "Right now there are more restrictions on Anthropic than there are on Z.ai."
That's a remarkable place to find ourselves.
There's another twist.
Many of China's strongest models are open-weight, meaning organisations can download, modify and run them on their own infrastructure.
That makes them:
πΈ Cheaper
β‘ More flexible
π Less vulnerable to geopolitical restrictions
If American companies become harder to access because of export controls while Chinese models remain widely available, businesses may simply optimise for cost and certainty rather than nationality.
Ironically, attempts to preserve America's AI lead could accelerate adoption of Chinese alternatives.
π¬π§ Why Europe Should Care
Europe β including the UK β is largely watching this unfold from the sidelines.
We don't own the frontier models. We don't manufacture the frontier chips. And increasingly, we may not control access to either.
For governments and businesses building on foundation models, this raises a fundamental question:
What happens if the AI your company depends on becomes unavailable because of another country's foreign policy?
That's no longer hypothetical. It's already happened.
πΏ So What? For years, people compared AI to electricity.
That analogy no longer works.
A better comparison might be semiconductors.
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Strategic.
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Restricted.
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Geopolitical.
The companies building frontier AI are increasingly behaving less like software firms and more like defence contractors.
The biggest risk isn't that America loses the AI race.
It's that, by limiting access to its own technology while China rapidly closes the capability gap, it accidentally encourages the rest of the world to build on someone else's.
Because in technology, the platform that wins isn't always the most powerful.
It's often the one that's simply available. π€
π Read Moreπ€ Mashable: White House wants OpenAI to limit the launch of its next model
https://mashable.com/tech/white-house-openai-slow-down
π° The New York Times: Chinese AI models close the gap with Anthropic and OpenAI
https://www.nytimes.com/2026/06/25/technology/zai-china-artificial-intelligence-models.html
π The Wall Street Journal: China has matched Anthropic in cybersecurity, resetting the AI race
https://www.wsj.com/tech/ai/chinese-ai-anthropic-mythos-cybersecurity-574b02c2
π TechCrunch: Asian AI startups launch Mythos-like models as Anthropic's export ban drags on
https://techcrunch.com/2026/06/27/asian-ai-startups-launch-mythos-like-models-as-anthropics-export-ban-drags-on/
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