日前，美国与英国签署《科技繁荣协议》，以深化两国在前沿科技领域的战略合作。这一协议标志着美 英"特殊关系"在科技领域的升级，但此番升级究竟能为两国科技产业发展带来多大助力，仍有待观察。 根据协议内容，双方重点在人工智能（AI）、量子计算和民用核能等飞速发展的技术领域合作。比 如，双方称该协议将帮助美英两国在全球AI领域"占据主导地位"。英国政府在9月16日发布的一份新闻 公报中称，微软、谷歌、英伟达、OpenAI等美国顶尖科技公司承诺将斥资310亿英镑（约合420亿美 元），用于提升英国的AI基础设施和前沿技术，涵盖数据中心、计算机芯片以及AI算力等。 对于这样一份"重磅"协议，市场反映不一。一方面，有分析认为，协议构建了从设计到制造的替代供应 链，将减少美英两国对他国的技术依赖，增强两国技术实力。特别是对于英国来说，这份协议可能为民 意支持持续走低的现任政府带来急需的经济提振和政治资本。若协议承诺的巨额投资能够顺利落地，将 向民众展示政府吸引外资、发展高科技产业的能力，成为稳定执政、兑现"重建英国"承诺的有力支撑。 英国政府公报已表示，在相关投资带动下，英格兰东北部地区将成为新的人工智能增长区，有望创造超 ...

Core Insights - The evolution of logistics from ancient times to the present showcases a significant transformation in delivery efficiency and technology [1][2][3][4][5] Group 1: Historical Context - The traditional logistics system in ancient China was characterized by inefficiency, with long delivery times and high resource consumption, as illustrated by the example of sending lychees from Lingnan to Chang'an [1] - Historical records indicate that the official courier system required extensive time and resources, with the journey from Chang'an to Lingnan taking 22 days through 138 relay stations [2] Group 2: Technological Advancements - The introduction of automated sorting systems in logistics, starting with the "Double Eleven" event in 2009, significantly increased processing capabilities, allowing for a leap from 8,000 to 32,000 packages per day [3] - The current logistics landscape features advanced technologies such as AI and robotics, exemplified by the "Hive Intelligent Warehouse" in Shanghai, which processes packages at a speed of 0.8 seconds per item [4] Group 3: Economic Impact - The express delivery industry has become a crucial driver of economic growth, with a 10% increase in the sector correlating to a 1.2% rise in regional GDP [5] - The logistics sector's transformation reflects a broader shift from an agricultural civilization to a digital economy, with modern delivery systems enabling rapid distribution of goods across vast distances [5]

美股再创历史新高。 当地时间9月18日，美股三大指数齐创历史新高。截至收盘，道指上涨0.27%，报46142.42点，标普 500指数上涨0.48%，报6631.96点，纳指上涨0.94%，报22470.73点。 消息面上，当地时间18日，美国政府请求美最高法院允许总统特朗普解雇美联储理事莉萨·库克。 此外，当地时间18日，美国政府请求美最高法院允许总统特朗普解雇美联储理事莉萨·库克。 美国联邦住房金融署署长比尔·普尔特8月公开指认库克曾同时把两处房产申报为其"主要住宅"以获取更优 惠贷款利率，并向司法部提交相关刑事指控。特朗普8月25日以涉嫌住房抵押贷款欺诈为由解除库克职 务。库克否认有任何不当行为，并于8月28日提起诉讼。 华盛顿特区联邦地区法院法官9月9日裁定暂停解雇决定。特朗普政府11日向一家联邦巡回上诉法院提出 紧急申请，要求该法院在"15日下班前"推翻下级法院就库克一案所作裁决。美国联邦上诉法院15日裁 定，阻止特朗普在美联储议息会议召开前将理事莉萨·库克撤职。当地时间16日，美国白宫发言人表示， 特朗普政府将就法院阻止撤换美联储理事莉萨·库克的裁决提出上诉。 英特尔暴涨，中概股下跌 热门科技股中 ...

当雷锋同志的泛黄历史照片，通过AI技术修复，他的笑容更加亲切、温暖；当首都博物馆里沉睡已久 的金代铜坐龙与唐代蛇像，在北京电视台春晚舞台上苏醒，它们聊起"生肖换班"的话题；当讲着地道方 言的虚拟主播，提醒你明日添衣——这些北京广播电视台为观众呈现的AI时代新图景告诉我们，技术 不再是冰冷的代码，而是一把能解锁创意、触达人心的"魔法钥匙"。 从最初提升效率的工具，到深度融入业务的创新引擎，再到如今连接用户与内容的生态枢纽，北京广播 电视台的实践证明：AI最动人的力量，不在于取代人，而在于成就人。 在北京国际电影节宣传片《雨燕》中，AI通过拟人化建模，让一只雨燕从电影胶片的光影中振翅而 出，翩然飞翔在北京的古今地标，向世界传递着东方美学与电影艺术的交融。"AI智绘坊"团队凭借《最 美京秋》《京津冀花海》等一系列作品，将AI美学与地域文化深度融合，成了名副其实的城市形象"网 红制造机"。与此同时，一支由"时间小妮""成成""波波龙"组成的数字主播军团，已经实现7×24小时全 天候播报，大大降低了人力成本，也构建起全新的内容生产范式。 （作者为北京广播电视台技术管理部主任） 如果说这些是看得见的"面子"，那AI对全流 ...

中铁第四勘察设计院桥梁院副总工王鹏宇介绍，针对道岔区连续梁改造的特殊结构和受力特点，项目团 队建立了高精度有限元分析模型，实现全过程模拟仿真。绍兴城际铁路上的这次"移旧换新"，也是国内 首例道岔连续梁换梁工程，填补了道岔区改造领域的空白。 （文章来源：科技日报） 记者从中国铁建股份有限公司获悉，10日凌晨，在浙江绍兴城际铁路柯桥站施工现场，总重4000余吨的 钢箱梁应用人工智能（AI）实现毫米级精准落位，标志着国内首次在运营铁路桥梁上尝试应用AI技术 换梁取得阶段性成果，为我国既有铁路改造升级提供了新方案。 中铁二十四局柯桥站项目经理潜英飞介绍，项目引入AI系统，依托数字孪生技术构建三维模型，通过 40个高精度传感点实时采集梁体姿态数据，实现毫米级精度准确感知。该AI系统由感知、仿真、控制 三大模块组成。感知模块相当于眼睛，集成光栅、拉线传感器、应变片及北斗定位等先进技术，实时监 测梁体沉降、应力与位移；仿真模块用于推演，通过数字孪生平台可视化模拟施工全过程；控制模块依 托智能算法预测梁体运动趋势，自动纠偏并同步操控36个顶升千斤顶和10个水平顶推千斤顶，开创了铁 路多跨桥梁快速更换施工先例。 ...

科学家不久前进行了一项实验，以研究AI对人类专业技能的影响，这项研究发表在权威医学杂志《柳 叶刀》上。 研究人员设计了一个多阶段的实验，以追踪AI辅助对医生诊断技能的动态影响。在初始阶段，研究人 员记录了医生在没有AI技术下的判断准确率。随后，这些医生开始使用一套AI系统，该系统能够在实 时影像中高亮标记可疑的疾病组织。正如预期，在AI的辅助下，医生的检测率获得了显著提升。 当研究人员撤除AI辅助系统后，要求医生重新进行独立诊断时，一个令人不安的现象出现了：这些医 生的平均检测率不仅回落，而且比他们最初未使用AI时的基线水平下降了约20%。 这个实验给我们带来很多有意思的启示。 首先，我们应该看到，AI给人类整体带来了福利。正如该实验中使用AI可以使检测率获得提升。 但我们也应该看到问题的所在，人类在这一过程中，会变得越来越依赖AI。 例如该实验的结果表明，当AI系统主动发出潜在的威胁时，医生自身的警觉性、注意力和视觉搜索模 式都在不知不觉中发生变化，他们从一个积极的"猎手"，转变为一个相对被动的"审核者"。 如今，和AI结合的远远不只是医疗体系，从驾驶汽车，到艺术创作、产品设计，几乎覆盖各行各业。 就拿写作 ...

记者从中国铁建股份有限公司获悉，9月10日凌晨，在浙江绍兴城际铁路柯桥站施工现场，总重4000余吨的钢箱梁应用人工智能（AI）实现毫米级精准落 位，标志着国内首次在运营铁路桥梁上尝试应用AI技术换梁取得阶段性成果，为我国既有铁路改造升级提供了新方案。 绍兴城际铁路是利用既有萧甬铁路改造而成的跨市区域城际铁路，其中柯桥站是该线新建车站，也是国内首个在运营铁路上增设的高架城际车站。因该站由 2股道增加为4股道，需将"咽喉区"混凝土梁更换为钢箱梁。同时，该工程位于铁路干线，技术难度大、安全风险高、施工环境复杂，传统工艺难以满足要 求。 中铁二十四局柯桥站项目经理潜英飞介绍，项目引入AI系统，依托数字孪生技术构建三维模型，通过40个高精度传感点实时采集梁体姿态数据，实现毫米 级精度准确感知。该AI系统由感知、仿真、控制三大模块组成。感知模块相当于眼睛，集成光栅、拉线传感器、应变片及北斗定位等先进技术，实时监测 梁体沉降、应力与位移；仿真模块用于推演，通过数字孪生平台可视化模拟施工全过程；控制模块依托智能算法预测梁体运动趋势，自动纠偏并同步操控36 个顶升千斤顶和10个水平顶推千斤顶，开创了铁路多跨桥梁快速更换施工先例 ...

Core Insights - The article discusses the unprecedented identity crisis faced by middle managers due to the increasing penetration of AI technology in business operations. AI is not only changing management tools but also reshaping management processes and fundamental logic [1][2]. Group 1: Transformation of Middle Management Roles - AI has taken over 42% of the routine tasks of middle managers, including data collection, process monitoring, and regular approvals, leading to a significant shift in their roles [1]. - A study from Harvard Business School indicates that "dual-track decision-makers," who can integrate AI insights with human judgment, achieve 23% higher team performance [2]. - Middle managers are experiencing "skill anxiety," with 51% feeling unprepared for the AI era, and teams led by managers who cannot adapt to AI collaboration perform 23 percentage points lower [2][3]. Group 2: Challenges in Collaboration and Power Dynamics - Research from Stanford University shows that over half of managers feel "disempowered" when AI systems directly provide work suggestions and performance feedback, indicating a struggle to transition from "command givers" to "collaborative guides" [3]. - The compression of interaction time due to AI technology has weakened emotional connections among team members, necessitating middle managers to act as "relationship integrators" to bridge the gap between algorithms and teams [3][4]. - Structural resistance within organizations, where managers lack the "technical-business translation ability," hinders successful project outcomes, with a 37% higher success rate for those who possess this skill [3][4]. Group 3: Becoming Enhanced Managers in the AI Era - The article emphasizes that the future value of middle managers lies not in performing old tasks but in realizing "augmentation" by leveraging high-level cognitive and social situational awareness that AI cannot replace [6][7]. - Middle managers must transition from being data consumers to data-driven decision-makers, capable of interpreting AI-generated insights within the context of organizational goals [7]. - In team building, middle managers should focus on fostering growth in areas where AI cannot excel, such as complex problem-solving and strategic thinking, thus taking on a coaching role [8]. Group 4: Integration of Technology and Business - The redefinition of organizational boundaries by AI requires middle managers to become "integration enhancers," bridging the gap between technology and business needs [8][9]. - The article concludes that technology alone will not lead to organizational evolution; it is the transformation of people that will complete the leap in management systems [9][10].

Group 1 - The global AI competition is shifting from a "sprint" of technological breakthroughs to a "marathon" of ecosystem building, with key variables being computing power costs, data quality, and scene implementation capabilities [1] - China aims to leverage its advantages in "green electricity + domestic chips," "data flow," and "scene sinking" to create a unique development path that combines technological breakthroughs with social benefits [1][2] - The high energy costs and chip supply limitations are major constraints on the global AI industry, and China's solution lies in integrating its renewable energy advantages with independent innovation to build a low-cost, high-security computing power supply system [1][2] Group 2 - The "Westward Migration" strategy of data centers is reshaping the cost structure of computing power, with regions like Qinghai and Inner Mongolia offering significantly lower electricity prices, thus reducing the costs of large model training [1] - The innovative "modular" chip cluster solution developed by Chinese companies allows for the combination of domestic 14nm chips to achieve performance equivalent to 3nm chips, drastically reducing training costs from tens of millions to millions [2] - The challenge of "data islands" and security concerns hinders the transformation of vast data into innovative momentum, but China's large-scale data base can provide continuous "live water" for AI development if data circulation barriers are broken [2][3] Group 3 - Innovations in data circulation are emerging across the country, with examples like Shenzhen's data element market and Hangzhou's "city brain" demonstrating the potential for increased efficiency when data is treated as a public resource [3] - The ultimate value of AI lies in solving real-world problems, and China's unique advantage is its comprehensive application scenarios from urban to rural areas, enabling AI to evolve from a "toy" to a "tool" [3][4] - Scene sinking is transforming traditional production methods, with AI applications in community markets and agriculture enhancing productivity and making technology accessible to ordinary people [4] Group 4 - The successful implementation of these three strategies relies on precise policy guidance, balancing innovation with resource management to prevent waste while allowing for experimentation [4]

Core Viewpoint - The company is focusing on innovative technologies and industry applications, particularly through the deployment of AI systems to enhance operational efficiency and drive sustainable development [1] Group 1: AI System Deployment - The company has privately deployed DeepSeek to build an efficient AI system for offline inference and service calls [1] - The AI system aims to facilitate diverse applications such as document data processing, text organization, and logical reasoning [1] Group 2: Business Innovation and Development - The company is exploring the integration of AI in operational management to promote continuous innovation and improve business efficiency [1] - The company is adopting an open approach to multi-level cooperation, selecting suitable development paths to leverage business capabilities and resource advantages for mutual benefit [1]