极度隐私

一个月两次出手！京东再度驰援广西 无需汇报直接开仓救灾_我的网站

A |     8月25日消息，受第19号台风“紫檀”影响，广西崇左宁明县遭遇暴雨洪涝，防汛应急响应提升至一级。    

    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]

。    京东再次启动应急救援，这是一个多月之内京东第二次驰援广西灾区，沿用内部“无需汇报”救灾规则，就近调配物资紧急送往防汛一线。     按照京东早年定下的内部规则，国内出现灾害险情，就近仓储负责人不用层层上报审批，可以直接调拨仓库物资捐赠救灾，后续再补流程。

B |     这套机制省去大量审批环节，能够抢出宝贵救援时间，7月广西洪涝的时候这套机制就已经投入实战。         本次京东从南宁亚洲一号物流园调运物资，紧急筹措矿泉水、方便面、面包、八宝粥这类刚需生活物资。京东健康同步出动，调配1.9万件应急医疗物资送往受灾地区，覆盖急救、消杀相关品类，满足灾区防疫和伤员处置的需求。    京东物流无人机团队也已经待命，如果后续道路损毁车辆无法通行，无人机可以承担物资投送、灾情勘察、隐患排查、洪水范围监测等任务，解决偏远点位物资送不进去的难题。    在7月广西上一轮洪涝灾害中，京东就连夜送出近2万份生活物资，凌晨就运抵横州灾区。    除吃喝物资之外，还送去2.1万件消杀急救物资，专门准备2000份蛇伤解毒药剂，同时捐赠近3000个应急照明设备，快递小哥冒雨参与卸货搬运。    救灾讲究争分夺秒，层层审批很容易耽误时机。京东这套就近开仓、先行动后汇报的模式，把仓库变成救灾前置补给点。     面对接连发生的汛情，企业供应链物流能力，在灾情当中可以转化成实实在在的救援力量。京东两次驰援广西，也让这套“无需汇报”的救灾机制再次走到大众视野。              

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