海豚湾恋人
锚定“两地一中心”，2030年突破2万亿 杭州服务业扩能提质“路线图”出炉_我的网站
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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]
。 杭州服务业高质量发展特别报道解码“杭州服务”一座服务业标杆城市的成长逻辑
记者 陈中秋 摄服务业有多重要？在8月13日召开的全市服务业大会上，我们听到了这样一组数据，贡献了杭州全市六成的就业、七成的经济总量和税收、八成的固定资产投资、九成的市场主体。数据听起来没感觉，那就拆解来看——服务业分为生产性服务业和生活性服务业两大类。生产性服务业包括批发、运输、仓储和邮政、金融、商务等16个国民经济行业门类，348个行业小类；生活性服务业包括零售、住宿和餐饮、旅游、修理、教育、卫生、娱乐等13个专业门类，288个行业小类，个个都和产业发展、经济循环、民生就业、老百姓生活息息相关。会议明确杭州服务业发展的总目标：两地一中心。
B | 即打造先进生产性服务业集聚地、品质生活性服务业共享地，加快建设东部现代服务业中心。会议要求，聚焦“6+4”重点领域和省级56条细分赛道，围绕8条杭州特色赛道，加快推动“两地一中心”建设迈上新台阶、取得新突破。会上，《杭州市推进服务业扩能提质行动方案（征求意见稿）》（以下简称《方案》）正式亮相。目标到2030年，全市服务业增加值突破2万亿元，生产性服务业增加值占服务业比重60%以上。《方案》围绕生产性服务业发展的六大方向：科技服务、软件信息、现代物流、金融服务、商务服务、节能环保，聚焦生活性服务业发展的四大领域：居民服务便利化、养老托育服务高效适配、健康服务专业化、文旅商体融合，明确了具体工作任务。方向明确后，关键在落地。《方案》指出，要以加快服务业数智化升级、深化服务业标准化建设、推进服务业品牌化培育、推动服务业融合化发展、提升服务业国际化这五大主线为牵引，推动服务业发展跃升。东部现代服务业中心先进生产性服务业集聚地（六大方向）1.科技服务全社会研发投入强度达4.5%，每万人高价值发明专利拥有量达78件，全市检验检测收入达200亿元。2.软件信息软件营收达1.7万亿元，全市智能算力规模突破100EFLOPS，探索设立“AI产品体验券”，建设“AI场景交易所”。3.现代物流全市快递业务量达到54亿件，新建无人机公共起降场36处，新增低空物流航线200条。4.金融服务探索“科技企业培育板”，全市金融业增加值超3540亿元，保费收入达到2000亿元。5.商务服务深化钱江新城、运河、黄龙三大法务集聚区建设，提升法律、财税、人力资源、数字广告等专业服务水平。6.节能环保推进零碳园区、零碳工厂、绿色工厂建设，完成既有建筑节能降碳改造，积极争创全国“无废城市”。
C | 品质生活性服务业共享地（四大领域）1.居民服务便利化实现家政机构、社区网点和服务人员三类信用档案联网查询，推动涉宠服务规范化、多元化发展，支持钱江新城商圈争创国家级商圈。
D | 2.养老托育服务高效适配鼓励开展“AI+养老”，拓展适老化文旅、康养文旅、银发金融等消费场景，推进社区嵌入式托育和“医育结合”健康促进模式，支持幼儿园开设托班。3.健康服务专业化发展数智医保和互联网健康消费，推动中医药与养老、旅游等产业融合发展，培育健康消费新业态。4.文旅商体融合大力发展网络文学、网络影视剧、网络游戏，文化“新三样”规上企业营收超3000亿元，积极承办世界羽联世界巡回赛总决赛、2027亚足联U20亚洲杯，创新推出“杭州消费礼遇卡”。
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