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Can US afford cost of clean-energy protectionism in race for AI capabilities?_我的网站

A |     (ECNS) -- Chinese humanoid robot maker Unitree Robotics has attracted strong market attention after its IPO subscription results showed the lowest winning rate in the history of Shanghai’s STAR Market.     Unitree priced its shares at 150.80 yuan ($22.2) each, requiring successful applicants to pay 75,400 yuan for one lot of 500 shares. The online winning rate was just 0.0181 percent, prompting comparisons to “winning a lottery.”        Unitree Robotics issued about 40.45 million shares, accounting for 10 percent of its post-IPO total shares, and is expected to raise about 6.1 billion yuan. Based on the issue price, the company’s market capitalization is estimated at about 61 billion yuan.    The IPO attracted a strong lineup of strategic investors, led by the National Council for Social Security Fund.    Major technology and industrial investors also participated, including DeepSeek, Kunlun Capital under China National Petroleum Corporation, China Southern Power Grid and China Telecom Capital.    DeepSeek received about 933,000 shares worth 141 million yuan, subject to a 36-month lock-up.    Meituan-affiliated investment entities are among the company’s largest external shareholders, while Tencent, Alibaba and Ant Group also hold stakes in the company. Leading venture capital firms Sequoia China and Matrix Partners China, along with state-backed investors such as the Beijing Robotics Industry Development Investment Fund and Shenzhen Capital Group, further broadened support.    Founder Wang Xingxing is also expected to benefit from the listing. Before the IPO, Wang held about 33.36% of the company’s shares directly and indirectly. Based on the issue price, his stake was valued at around 18.3 billion yuan, though his ownership ratio will be diluted after the listing.    The IPO also lifted related robotics stocks on Aug. 11 and 12.    (By Helen Mo, intern Liu Shuangjing)                    。    

    Illustration: Liu Xiangya/GT
Recent media reports have questioned whether a natural gas plant built to power an Amazon data center project in Texas could become the largest climate polluter in the US. The controversy, whatever the eventual outcome, offers a reality check for America's artificial intelligence (AI) drive. 
It exposes a growing contradiction: The US is racing to expand its AI capabilities, yet its protectionist trade policies are making it harder and more costly to access some of the clean-energy technologies needed to sustain that expansion. This raises a broader question: Can an energy-intensive AI race afford the costs of renewable energy protectionism?
The US is entering a new era of rising electricity demand. Data centers, the backbone of the AI economy, are emerging as one of the fastest-growing sources of power consumption. Much of that demand is still being met by fossil fuels: The International Energy Agency reports that natural gas supplies more than 40 percent of the electricity used by data centers in the US, making it their largest source of power. 
So, it's not surprising that the expansion of data centers has raised concerns over their environmental impact and the pressure they could place on local power systems and electricity bills. A Gallup survey conducted in March found that seven in 10 Americans opposed the construction of AI data centers in their local area, including 48 percent who strongly opposed such projects.
The findings point to a broader challenge for the US: The race to develop AI is increasingly becoming a race to meet growing energy needs. Addressing this challenge will require more than advances in computing technology; it will also depend on an energy system capable of delivering large amounts of reliable, affordable and cleaner power. That, in turn, will require faster development and broader deployment of clean-energy technologies, from solar power to energy storage.
Yet in the clean-energy sector, the US has increasingly relied on protectionist trade measures that limit access to cost-competitive products from global markets. The country has placed greater emphasis on expanding domestic manufacturing capacity, but rebuilding entire clean-energy supply chains at home is a costly and time-consuming process. Even if expanded domestic production is achieved, it is likely to come at a higher cost, making the deployment of renewable technologies more expensive and potentially slower.
The solar industry offers a clear illustration of this policy direction. The US has continued to expand trade barriers in the sector. Reuters reported that the US government announced on Thursday a series of price floors and a 15 percent tariff on products made from polysilicon, a raw material used in solar panels.
The challenge lies in the limited scale of the US polysilicon industry. Reuters reported that the country has two polysilicon factories. Against this backdrop, relying on domestic polysilicon production while restricting access to imports runs counter to the goal of expanding solar power in the US. The country risks creating barriers that ultimately constrain its own access to the global supply chains needed for growth.
The pressing issue for the US is the speed at which new power demand is emerging. The expansion of data centers is creating electricity needs that cannot wait for domestic clean-energy capacity to develop gradually. Global supply chains can provide the scale and speed required in the near term. By narrowing access to these sources, the US risks turning clean-energy policy into a drag on the infrastructure needed for its AI race.
The US has placed AI high on its economic and technological agenda. The outcome of this race will matter greatly, as financial markets are also watching whether America can turn its AI efforts into commercial success.
This leaves the US with a difficult choice: Can it afford the cost of clean-energy protectionism while racing to build AI infrastructure? The answer may be no. Trade barriers that limit access to competitive renewable technologies could ultimately become a constraint on the AI expansion that Washington is seeking to accelerate.
The author is a reporter with the Global Times. [email protected]

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