ai-regulation
The Temporal Paradox of Computational Acceleration
Hardware dedicated to artificial intelligence is growing by a factor of ten every nine months, a rate of expansion that Elon Musk has described as ‘insane’ in the context of the rapid evolution of model capabilities. This exponential increase is not simply an incremental improvement, but a radical transformation of the physical infrastructure on which the future economic and military strength of the United States rests. Senator Bernie Sanders’ proposal to impose a temporary pause on artificial intelligence research to dedicate resources to alignment and safety completely ignores the materiality of this process: while legislators discuss regulatory constraints, Chinese chip factories and data centers continue to expand with a purely physical logic.
The tension between regulation and innovation is not only political, but structural. A unilateral regulatory block in the United States would act as an artificial brake on a system that is naturally accelerating. As Marcus Aurelius observed in his essay ‘The New Sanders-Casar Ban’, a permanent and unilateral pause on superhuman AI research is ‘a guarantee of leaving the United States behind’. The logic of security, if applied rigidly without considering the hardware dynamics, transforms prudence into strategic vulnerability.
The Physics of the Technological Divide
The acceleration of hardware does not happen in a vacuum, but requires massive industrial support that the USA is struggling to sustain compared to China. The Center for a New American Security (CNAS) recently suggested that the United States should prepare for extreme scenarios, including state-sponsored espionage and even military attacks against Chinese data centers, precisely to prevent Beijing from achieving Artificial General Intelligence (AGI). This rhetoric reveals an awareness that the gap is not just about software, but also about physical infrastructure: servers, connectivity, and energy.
China is investing aggressively in computational infrastructure, creating a scale advantage that no US regulatory pause could ever match. While American companies like Anthropic are focused on alignment research—a necessary but slow and qualitative process—China is building raw capacity. The difference between ‘alignment’ and ‘computing power’ is the difference between software and hardware: the former can be regulated, the latter cannot.
Public Narrative vs. Technical Reality
The public and part of the American political class perceive artificial intelligence as an existential risk to be contained, rather than a crucial infrastructure race to win. This perception clashes with market realities: Anthropic, for example, reached a valuation of $2 trillion after admitting to pirating over 7 million books to train its models. The company paid a settlement of $1.5 billion, a sum that music publishers consider ‘not sufficient to deter illegal conduct’. This data highlights how legal sanctions are insignificant compared to the value created by hardware acceleration.
“$1.5 billion is obviously not a large enough settlement to deter infringing conduct by a company that has parlayed such mass infringement into a staggering $2-trillion-dollar valuation” — Music Publishers (Sony, EMI, Warner Chappell)
The tension between the narrative of safety and the reality of profit is evident. Companies that control hardware and data gain enormous competitive advantages, while attempts at regulation lag behind the pace of innovation. Sanders’ proposed pause does not address the alignment problem, but creates a power vacuum that China will fill with its infrastructure.
Strategic Implications and Time Horizon
The euphoria assumed that AI could be regulated like a traditional technology; the data shows that it is an exponentially expanding physical infrastructure. The 10x factor every nine months leaves no room for prolonged regulatory pauses without serious strategic consequences. The United States must decide whether to continue trying to stifle innovation with laws or to invest in the hardware itself to maintain leadership.
For decision-makers, the data to monitor is the production capacity of chips and the expansion of Chinese data centers. If the USA continues to focus on regulatory pauses, it will lose the strategic window to dominate AI infrastructure. Security does not come from blocking research, but from the physical superiority of its own computing infrastructures.
Photo by Steve A Johnson on Unsplash
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