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一国家级平台新增33个重点项目 助推智能出行成果转化,一国家级平台新增33个重点项目 助推智能出行成果转化_我的网站

A |     　　广州8月21日电 (蔡敏婕 刘露璐)“乘‘智’而上，词元赋‘能’”全国高校区域技术转移转化中心(粤港澳大湾区)陆空一体化智能出行分中心项目平台入驻活动21日在广州番禺举行。    

    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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B | 继首批9个项目入驻运营后，再有33个重点项目正式进驻，标志着该国家级平台在高校科技成果转化领域跑出“加速度”。8月21日，全国高校区域技术转移转化中心(粤港澳大湾区)陆空一体化智能出行分中心项目平台入驻活动在广州番禺举行。

C | 广州市番禺区委宣传部 供图　　2025年4月，教育部批复同意建设全国高校区域技术转移转化中心(粤港澳大湾区)。作为国家布局的全国性区域中心，其将发挥粤港澳大湾区科技创新与产业集聚优势，打造立足湾区、辐射全国的高校科技成果转化高地。　　去年12月，生物医药、陆空一体化智能出行等多个区域技术转移转化分中心揭牌，标志着中心按多分中心架构运行。其中，智能出行分中心聚焦飞行器续航时间不足、网联智能化不够、飞行器安全性能不高等难点，围绕新型能源动力、智能网联、低空飞行器三大领域，面向全国高校、匹配产业需求，开展有组织科研、转化及人才培养等工作。　　在21日的活动现场，智能出行分中心交出半年“成绩单”：第二批33个项目进驻、8个平台签约，广州大学城词元·智能体联合创新工坊启动，珠江科技创新院揭牌，万博云创中心、新造智造新城、经开区智造中心3个OPC社区同步发布，11个科创生态伙伴链接合作。　　本次进驻的33个项目涵盖低空飞行器、新型能源动力、智能网联和人工智能等领域，系统展现了大湾区智能出行产业的创新成果与市场前景。　　一批高价值项目正加速落地：“AI驱动的智能网联动态能效提升算法IP及芯片”攻克AI射频增强处理器技术，为低空、商业航天、6G通信打通关键通信堵点；“国产自主可控无人机飞控研发与产业化”打造全栈国产化无人机飞控，以国产装备护航低空经济大规模商业化起飞。　　为支撑项目发展，智能出行分中心联合广州数字科技集团有限公司启动立体智慧交通运营中心、低空飞行器质量检验检测平台、车路云一体化出行服务平台3个新建平台，同步引入全空间无人体系装备中试平台等10个共享平台，为进驻项目提供技术攻关、测试验证、商业闭环等公共服务。

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