新京报讯 据"北京人社"微信公众号消息，今年7月，北京市人社局首次推出人社政策咨询智能助手"京 晓保"，发挥人工智能在赋能传统岗位方面的作用，探索人机协同的新型管理模式。截至目前，"京晓 保"已累计接待访问9.3万余人、解答问题近21万个。 为解决群众急难愁盼问题，聚焦改善人民生活品质，市人社局创新政务服务新模式，在12333热线咨询 服务的基础上，采用"大语言模型+北京人社知识库"，整合了人社领域1200余篇政策文件、8800余条常 见问题，通过探索人机协同的智能化处理方式，实现新政策24小时内入库、热点问题48小时内迭代，确 保知识库与实际业务同步，最终打造了平均2秒钟响应的智能助手"京晓保"，优化了市民和企业的咨 询、办事体验，有效缓解了人工电话咨询压力，拓展了服务群众的范围。 目前，"京晓保"每日17时至次日9时的访问量比12333热线多22.3%，显著解决了群众打不通热线、咨询 等待时间长的问题，是对12333咨询热线的有益补充，有效提升了人社政务服务治理能力。 市民可以在市人社局官网、"北京人社"微信公众号、"北京民生一卡通"微信小程序等平台访问"京晓 保"，通过文字或语音实时交互的方式，围绕就业 ...

近日， 合合信息 正式向香港联合交易所提交主板上市申请，有望借助资本市场资源，强化在商业 大数据 与智能 决策领域的核心能力。与此同时，合合信息发布的智能审核白皮书，为企业审核自动化开启了全新篇章。 以财务场景为例，合合信息AI智能审核系统深度嵌入业务流程，支持与OA系统、费控系统、ERP系统等多系统对 接，实现财务审核全流程自动化。在与某知名物流企业的合作中，面对海量定制版式账单，该系统展现出强大的 泛化能力，有效解析多语种、多版式、多文件格式的文档，海外invoice和账单样本字段识别准确率高达98%以 上。 在产品侧，合合信息旗下产品TextIn DocFlow为企业用户提供了"开箱即用，一键集成"的便捷使用模式。作为标准 化产品，它能智能处理海内外各类文档，实现一站式智能采集、分类、提取、核验与处理。同时，产品具备强大 集成能力，支持通过邮件、API接口等多种渠道接收文档，并将提取的数据无缝传递至各种自动化系统和业务流 程中，极大节省了开发时间。 随着以大模型为代表的 人工智能 技术发展，AI能够自动化处理大量重复性审核工作，降低操作风险，提升工作 效率，"人机协同"工作模式成为现实。未来，合合信息将 ...

专题：财富领航征程丨金融新启航 作为金融市场的重要组成部分，理财行业在支持实体经济发展、满足居民财富管理需求、优化社会融资 结构等方面发挥重要作用。围绕做好金融五篇大文章，金融机构应如何扎实服务实体经济、助力经济高 质量发展？本期《财富领航征程》对话北京大学汇丰商学院助理教授赵泠箫。 当前，中国理财行业正处于资管新规深化转型的关键阶段，风险与收益再平衡成为核心课题。赵泠箫认 为，居民理财理念正从"保本保息"向"风险收益相匹配"转变，此过程对机构的资产配置能力、风险管理 体系，以及投资者的长期陪伴与教育机制提出了更高要求。 她认为，理财行业创新将在科技与制度双轮驱动下突破发展瓶颈。科技端，大模型与可解释AI的融合 将推动智能投顾从标准化工具升级为动态化"财富管家"，通过实时解析投资者需求与市场变化，实现全 生命周期精细管理；制度端，个人养老金账户的快速普及将显著优化资金期限结构，借鉴生命周期基金 和目标日期基金等国际成熟模式的本土化实践，结合投资者教育引导资金从短期避险转向"长期风险收 益平衡"，为科创板ETF、绿色债券等国家战略领域提供长期资本支持。 理财行业处于资管新规深化转型关键期，风险与收益再平衡成为核 ...

中国代表介绍了如何通过小破绽发现企业财务资料造假的案例，展示出审计人员既要有临门一脚的魄 力，更要有持之以恒的韧性。"中国审计人员的专业素养和职业精神令人敬佩。"来自乌兹别克斯坦的审 计人员艾哈迈德江感叹。 面对发展环境和经济活动的复杂多变，审计工作要主动适应新形势、应对新挑战、解决新问题；要敢于 查真相、说真话、报实情，保障国家安全和公共利益；要通过锤炼审计本领，承担起促进完善国家治理 时代重任的使命担当……在这次研修项目中，中国审计理念引发广泛共鸣。 开发多样化的人工智能审计工具，并注重对审计人员的职业技能和新技术培训；注重对被审计对象的审 前研究，强调审计人员的职业敏感性培养；将人工智能技术广泛应用于被审计单位的风险识别和预 警……本次研修项目中，外方审计人员分享了各自国家的审计工作亮点与创新实践，互学互促、合作共 赢氛围浓厚。 中国审计署国际合作司有关负责人表示，本次研修的深层价值，在于构建了一个平等互鉴的"亚洲审计 青年共同体"，有关国家通过交流互鉴，促成多元智慧的碰撞融合，凝聚更广泛的合作共识。 9月22日至26日，首届亚洲审计组织青年研修项目在南京、上海举办，来自42国最高审计机关的90余名 青 ...

近日，复旦大学会计硕士（MPAcc）专业学位项目联合复旦管院商业知识发展与传播中心、复旦MPAcc CFO50人+论坛，正式发布《2025中国财务人员AI应用现状蓝皮书》。 专家组预测，未来三到五年，AI与财务专业的融合将进一步深化。AI应用将从"自动化"走向"智能化"； 人机协同将成为财务组织的新范式：未来的财务团队将是人类专家与AI系统深度协作的共同体，人类 的判断力、伦理观，以及战略思维将和AI的计算力与洞察力实现互补。核心能力要求将发生根本性重 构：对财务人员而言，专业技能与数字素养必须双轨进化。除传统的财务知识外，数据解读、流程建 模、提示工程及AI工具治理能力，将成为财务人才的核心竞争力——企业教育和培训体系需积极响应 这一能力结构的转变。 课题组组长、复旦大学管理学院会计学系副系主任，教授，博士生导师张新指出："这份报告不仅记录 技术变迁，更揭示了组织与个体协同进化的密码。人工智能不会取代财务专业，但会重新定义它。那些 积极拥抱变化、主动驾驭技术，并持续进行能力增值的个人与组织，将在智能财务新纪元中赢得前所未 有的发展机遇。" 人工智能正重塑商业世界，而财务，作为企业的核心枢纽，正站在这场变革的 ...

Core Insights - The article discusses a pivotal moment in AI development, transitioning from "human-machine collaboration" to "human-machine delegation," indicating a shift in competitive dynamics towards who can more effectively delegate tasks to autonomous AI agents [1][6][10]. Group 1: AI's Impact on Work - AI is currently enhancing productivity as a "co-pilot" but has not yet fundamentally disrupted organizational structures [1]. - A recent survey at Anthropic revealed that engineers' workloads have increased two to three times, with their roles shifting from coding to managing AI agent systems [1][7]. Group 2: Programming and AI - The ability of AI to handle programming tasks signifies a broader capability to tackle semi-open systems, suggesting that programming may soon be rendered obsolete in practice [2][3]. - Programming is characterized as a digital-native activity involving logic, system thinking, resource allocation, and continuous refinement, which AI is beginning to master [8][9]. Group 3: New Organizational Models - The emergence of "unmanned companies" is anticipated, where human roles transition from executors to managers and orchestrators of AI systems [7][15]. - The new organizational model will focus on strategic oversight rather than direct execution, with humans acting as value injectors, system architects, and macro navigators [17]. Group 4: Contextual Overload and Efficiency - A new "law" of exponential context overload will emerge, making human intervention impractical in AI-driven decision-making processes [10][11]. - Organizations that attempt to maintain human oversight in execution loops will likely face efficiency challenges and may be eliminated from competition [12][13]. Group 5: Automation and Augmentation - The definitions of automation and augmentation highlight a shift towards more complex task delegation and collaborative interactions with AI, moving beyond simple tool usage [21][22]. - Recent data indicates that users are increasingly assigning higher-level tasks to AI models, marking a significant shift in how AI is perceived and utilized [23].

Core Insights - DingTalk showcased its AI products at the 2025 Yunqi Conference, introducing the next-generation office application DingTalk One, the first AI hardware DingTalk A1, and five other AI innovations [1] - DingTalk's CTO emphasized that the essence of AI transformation is the evolution of human-machine collaboration, where AI will act as an intelligent agent capable of cognitive and decision-making abilities [1] - The company aims to become a factory for industry models and enterprise intelligent agents, enabling businesses to build and apply their own exclusive large models efficiently and cost-effectively [1] Group 1 - DingTalk has established an AI productivity platform that assists enterprises in training exclusive models from data labeling to API deployment [1] - The company introduced a "pay-per-performance" model, allowing businesses to use AI first and pay based on results, making AI more accessible [1] - DingTalk has successfully trained the first vertical medical large model in China, achieving a "Chief Physician" professional level [2] Group 2 - Collaborations with partners like Gujia Home and Tongyi Laboratory have led to the development of industry-specific voice models that enhance AI sales assistance and service quality inspection [2] - The company is committed to creating an open, intelligent, and human-centered collaborative work platform, aiming to connect AI with the physical world across various industries [2]

Group 1 - The core theme of the event is how to leverage technology to enhance cultural originality, as discussed at the 2025 Beijing Cultural Forum [1] - Over 150 guests from 18 countries and regions participated in discussions on new trends and phenomena in artistic development, focusing on the concept of "cultural originality" and pathways for its enhancement through technology [1] - High-ranking officials emphasized the importance of maintaining emotional vitality and spiritual autonomy in an increasingly automated society, suggesting that technology should be transformed into human knowledge and experience [1] Group 2 - The "Comprehensive Chinese Painting Series" is a significant national cultural project aimed at systematically collecting, organizing, publishing, and researching ancient Chinese paintings using advanced technology, creating an unprecedented "cultural treasure trove" [2] - AI's role in cultural forums was highlighted, with discussions on human-machine collaboration as a pathway to originality, emphasizing the potential of AI in creative processes [2] - The establishment of a new cultural highland in Beijing, driven by artificial intelligence, is seen as a key development in the global innovation landscape, positioning the city as a center for AI technology and cultural integration [3] Group 3 - The integration of science and technology is viewed as a powerful engine for cultural innovation, reshaping the landscape of artistic creation and fostering a fertile ground for literary and artistic endeavors [3] - There is an expectation for technology to facilitate cultural exchanges and storytelling, promoting mutual understanding between Chinese and global civilizations [3]

在电商竞争日益激烈的环境下，不少企业面临一个共同困境：店铺咨询量高，但最终成交率却偏低。数据显示，若客户咨询后24小时内未下单，90%的客户 将会流失。这背后往往存在一个关键原因——售前客服缺乏有效的促单技巧。 高询单低转化问题的根源 客户主动咨询时，往往已具备购买意向，是促成交易的宝贵机会。然而，许多客服人员未能把握住此类机会，主要原因包括： 智能客服Agent的解决方案 针对上述问题，智能客服Agent提供了一套完整解决方案，可有效提升售前转化率： 响应迟缓，消耗客户耐心：研究表明，客服响应时间超过30秒，客户流失率增加40%；若超过1分钟，65%的客户会直接关闭对话框。很多客服因同时 处理多个对话导致回复延迟，或使用生硬、模板化的应答，缺乏亲和力。 缺乏主动挖掘需求的能力：客户有时并不清楚自身需求，客服未能通过有效提问进行引导，挖掘潜在需求。往往仅机械回答客户问题，未能深入理解 其真实意图。 产品知识不专业，难以建立信任：面对客户疑问，客服回答不够准确专业，常使用"可能是""不太清楚"等模糊表述，无法使客户放心。 缺乏促单技巧，错失成交时机：即便客户已表露购买意向，客服也未能及时识别购买信号并促成交易， ...

Core Viewpoint - Geoffrey Hinton, a Turing Award and Nobel Prize winner, has shifted his perspective on AI, now viewing it as a symbiotic relationship rather than a threat, particularly in the medical imaging field [1] Group 1: AI in Medical Imaging - AI is transforming disease screening, diagnosis, risk assessment, and clinical decision-making in the medical imaging market in China [1] - The company United Imaging established a subsidiary, United Imaging Intelligence, in 2017, focusing on AI medical solutions, and has launched over 100 AI applications, with numerous certifications from NMPA, FDA, and CE [1] - AI-assisted diagnosis is now a common tool for radiologists, significantly reducing the rate of missed diagnoses [3] Group 2: Key Personnel and Contributions - Gao Yaozong, the Chief Scientist at United Imaging Intelligence, has a background in computer vision and AI, previously working at Apple before returning to China to focus on medical AI [2][18] - Gao emphasizes the greater value of AI in healthcare compared to entertainment, highlighting the urgent need for AI solutions in China's medical landscape [2] Group 3: AI Development and Applications - The company has developed a lung nodule diagnostic grading system, C-Lung-RADS, based on extensive data from Chinese populations, enhancing early lung cancer screening accuracy [4] - United Imaging has created a mobile health management unit that provides lung cancer screenings to underserved areas, successfully identifying early-stage lung cancer cases [4] - The company has also launched an intelligent electronic medical record system that significantly reduces the time doctors spend on documentation [4][17] Group 4: Future Directions and Challenges - The ideal future technology path combines the strengths of general large models and specialized small models to enhance disease recognition and ensure precision in critical tasks [4][15] - The company faces challenges in developing truly universal, cross-modal medical imaging models and effectively integrating multi-modal information [12][13] - Regulatory challenges exist as AI medical products are classified as high-risk and require stringent approval processes [13][14] Group 5: Collaboration and Data Utilization - The company collaborates with hospitals to gather data while ensuring patient privacy and data security, employing a "data does not leave the hospital" approach [9] - Partnerships with leading hospitals are prioritized to ensure high-quality data for model training, with plans for multi-center validation for broader application [10] Group 6: Market Reach and Deployment - United Imaging's AI applications have been deployed in over 4,000 hospitals globally, integrating AI into imaging devices and providing independent AI platforms for various medical scenarios [11]