The article discusses the international competition in artificial intelligence (AI) between the US and China, with a focus on the military implications and potential risks. The key point is that despite not being a top concern for Americans, the AI race has significant consequences, including the possibility of cyberwarfare and loss of economic power. According to the article, the US currently holds an edge in AI capabilities, with better models, more compute power, and greater revenue than China. However, this advantage could be squandered by policies that drive Chinese AI talent away from the US.
Written by the local model on 2026-09-05,
using this article's own text rather than the other coverage of the
same event.
U.S.-China competition gets mentioned in certain circles, but it’s probably safe to say that it’s not Americans’ chief topic of concern.
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it → mention → concern
But it still matters!
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it → matter → ?
Cyberwarfare so far hasn’t been decisive in military conflicts, but AI’s incredible cybersecurity prowess could change that.
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prowess → change → that
If AI ends up strengthening defense more than offense — say, by finding all of the available exploits and patching them before an attacker can get to them — then cyberwarfare will become less important.
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cyberwarfare → end → them
But if those who possess the best AI models are able to successfully hack anyone using a less capable model to defend, it could lead to a decisive shift in the balance of power.
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it → possess → power
AI hacking doesn’t have mutually assured destruction, like nuclear warfare does.
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warfare → assure → destruction
Imagine if China were to gain a big lead in AI models that gave it the power to easily hack into American banks and brokerage accounts and erase people’s wealth.
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that → imagine → wealth
It would cause absolute chaos in American society, but how could the U.S. retaliate?
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U.S. → cause → society
Nor could the U.S. hack China in return, since China’s more capable AI would also be used to defend.
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AI → hack → return
If either country opens up a large, sustained lead in AI capabilities, it might upend the balance of power between the two.
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it → open → two
If the U.S. and China both continue pushing forward with AI research at maximum speed, it may quickly cause safety issues.
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it → continue → issues
The recent AI agent swarm attack on Hugging Face shows that AI has reached the level where it can pose a significant hazard to human companies and organizations — and perhaps soon to human society itself.
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it → show → society
Bioterror risk is certainly the most terrifying, but there are plenty of other ways that highly capable AI could cause chaos.
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AI → be → chaos
The U.S. and China have a shared incentive to implement strict safeguards against these catastrophic risks, and perhaps even to regulate the pace of AI development.
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U.S. → have → development
But given the Chinese Communist Party’s power-seeking nature, it seems much more likely that China would agree to cooperate on AI safety if U.S. capabilities were comfortably ahead.
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capabilities → give → safety
So even if the goal is cooperation, the U.S. should be thinking about how to keep its technological edge.
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U.S. → think → edge
Fortunately, the U.S. is still beating China in the AI race.
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U.S. → beat → race
Our companies have better models, more compute, and far more revenue.
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companies → have → models
But there are ways that the Trump administration, despite claiming to be the AI industry’s best friend, could squander America’s lead — especially by pushing Chinese AI talent out of the country.
U.S. models are still better than Chinese models
There have been several moments when it seemed as if China’s frontier models were catching up to America’s in capabilities.
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models → be → capabilities
The most dramatic was the “DeepSeek Moment” in early 2025, which put Chinese AI on the map.
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which → put → map
More recently, the release of Moonshot’s Kimi K3 this July and Z.ai’s GLM-5.3 a few weeks ago seemed to indicate that Chinese models were nipping at the Americans’ heels.1
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models → seem → Americans
Z.ai especially made waves when it beat Anthropic’s famous Mythos model on one measure of cyber-hacking capabilities:
Chinese AI startup Z.ai said on Friday its open-source GLM-5.3 model had neared Anthropic’s restricted Mythos 5 in identifying software vulnerabilities…Z.ai said GLM-5.3 scored 84.5% on CyberGym, a test of whether a model can review code, identify security flaws and confirm that they are real.
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they → make → flaws
That was slightly higher than the 83.8% it reported for Mythos 5.
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it → report → Mythos
The results have not been independently verified.
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results → verify → ?
Note that this is just one measure of cybersecurity prowess, and that Mythos was still comfortably ahead on other measures:
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Mythos → note → measures
GLM-5.3 lagged behind Mythos 5 in converting discovered flaws into working attacks — a standard part of defensive security research.
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GLM-5.3 → lag → research
Z.ai said its model scored 54.4% on the ExploitBench test of this capability, versus 78.0% for Mythos 5…
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model → say → Mythos
In a separate timed test, Z.ai said GLM-5.3 completed 105 attack-development tasks in two hours and 130 in six hours.
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Z.ai → time → hours
Mythos 5 completed 181 and 247 tasks, respectively.
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Mythos → complete → tasks
But still, if Chinese AI could get within striking distance of America’s best, it was a big deal.
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it → get → America
What this discourse rarely mentioned, though, is that Mythos is not America’s best.
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Mythos → mention → What
It was simply the best that’s been released.
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that → release → ?
Mythos Preview came out in April, four months before GLM-5.3.
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Preview → come → GLM-5.3
And the original Mythos actually finished training three months earlier, in January, and was released internally in February.2 Anthropic delayed its release due to cybersecurity concerns.
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Anthropic → finish → concerns
Z.ai, being a fast follower, probably had far fewer such concerns.
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Z.ai → have → concerns
In fact, Anthropic has stated that it has internal models that are better than Mythos.
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that → state → Mythos
