北京时间7月17日晚，抵达名古屋尚不足半天的男足集训队和中国女足先后展开赛前训练，以便更快寻找比赛状态——两支国字号球队东亚杯首战都在7月20日，中国女足20日14时30分对阵中国台北女足，国足选拔队20日晚18时对阵韩国队，尽管中国足协未给球队提出名次指标，只是要求“展现风貌，锻炼队伍”，但近期奔赴世界各地参加洲际赛事的多支中国体育代表队表现优异，国字号足球队除了迎难而上并无其他选择。面对日、韩两强，年初亚洲杯勇夺冠军的中国女足整体实力并不占优，半决赛点球淘汰日本队、决赛逆转绝杀韩国队除战术得当，全队上下一心毫无保留死拼对手，亦是取胜关键因素。此番3支女足亚洲强队再次在东亚杯上循环作战，中国女足已被对手当作“复仇”对象。         An illustration of the “5A Framework” for enterprise intelligent transformation unveiled at the 2026 Digital Intelligent Economy Forum in Langfang, North China’s Hebei Province, on August 12, 2026. Photo: people.cn         
The 2026 Digital Intelligent Economy Forum was held in Langfang, North China’s Hebei Province, on Wednesday. At the forum, organizer People's Daily Cultural Technology Corporation unveiled a “5A Framework” for enterprise intelligent transformation, aimed at helping businesses comprehensively innovate their business models, organizational structures and service systems in the artificial intelligence (AI) era.
A To A: Exploring new models for agent collaboration
AI is pushing the internet into a new stage characterized by the widespread participation of AI agents. In the future, China could develop an ecosystem comprising tens of billions of agent applications, while the global “digital population” could reach hundreds of billions. Following To B (business-oriented) and To C (consumer-oriented) models, enterprises and institutions should actively explore the emerging To A (agent-oriented) model. To enable better interaction and coordination among agents, unified data, technology, interface and service standards need to be established, while new business systems and service models should be cultivated.
AI-friendly: Building machine-readable data infrastructure
Today’s internet user interfaces are primarily designed for human browsing. The first step, therefore, should be to build an “AI-friendly” data system that is better suited to being read, understood and accessed by AI. By structuring content resources and turning them into organized knowledge, while strengthening ontology systems and knowledge graphs, such a system can improve AI’s ability to understand and apply information. On this basis, integrated hardware and software infrastructure combining computing architecture with data systems can be developed for AI applications.
AI-native teams: Reshaping organizations and workflows
AI is profoundly reshaping organizational structures and ways of working. AI-native teams should redefine job responsibilities, organizational structures and business processes around the A-To-A model and AI-friendly services, enabling “everyone to have multiple AI agents.” Professional capabilities and business experience can be encapsulated into “digital employees,” promoting autonomous learning by agents, multi-agent collaboration and the evolution of collective intelligence, thereby multiplying per-capita productivity.
AI for good: Putting values first, serving social development
AI also requires values-based guidance. Guided by the principle of “being people-centered and using AI for good,” efforts should follow the approach of “governing AI with AI and guiding intelligence with wisdom,” ensuring that AI always serves social development, the public interest and people’s needs. The “Mainstream Values Corpus,” whose development was launched by the People’s Daily in May 2023, has already begun to take shape and has been validated through numerous large-model applications.
Inclusive AI: Protecting cultural diversity, advancing global sustainable development
AI should not become merely “a game for rich countries and rich people,” but should benefit all countries. Efforts should be made to actively participate in global initiatives for inclusive AI, bridge the digital and intelligent divide, and enable more organizations and individuals to share the benefits of development on an equal footing, so that AI can truly become a powerful positive force for improving the well-being of all humanity and advancing human civilization.
This was translated and compiled by the Global Times, based on an article originally published on people.cn on August 12, 2026.

。2月亚洲杯结束，韩国女足4月和6月完成两场高质量热身赛，先是主场3∶0完胜越南女足，随后远赴多伦多，客场0∶0逼平东京奥运女足冠军加拿大队，韩国女足主教练科林·贝尔几乎集中了池笑然及旅欧球员赵昭贤和李永周在内的所有主力球员——对于韩国女足而言，战胜中国女足、压迫日本女足的战略目标始终没有改变。日本女足近期状态更强于韩国女足。

B | 6月旅欧两场热身赛，分别以5∶0和5∶1横扫塞尔维亚女足和芬兰女足，球队重新建立了亚洲称王的信心，尤其值得注意的，是日本女足欧洲热身23人名单中只有8人超过25岁，这意味着日本女足的新老交替基本接近完成且仍然保持相当竞技水准，此外今年8月哥斯达黎加女足U20世青赛和今年10月印度女足U17世少赛，日本女足都有资格参加——中国女足面临的关卡绝不止成年队一关。中国女足能做的，是用好全部有生力量，以亚洲杯夺冠阵容为框架，辅以海外效力关键球员，通过东亚杯检验短板，从而在接下来为期1个月的美国拉练中进行针对性补强。“我们是在为明年女足世界杯赛来考察队员、演练阵容，目前球队里面有老中青三代球员，大家在海口和青岛两期集训里面都表现出不错的状态。虽然东亚杯对手实力较强，但我们还是希望给年轻球员出场机会，让她们适应高强度的比赛。至于比赛本身，我们要找好定位，放平心态，把训练的东西和自己对足球的理解表现出来就好。”中国女足主教练水庆霞说，“赢了亚洲杯以后大家对女足的期望值很高，但球队难免出现问题，我们练兵的目的就是发现问题，解决问题。” 和具备一定实力的女足相比，国足选拔队此次东亚杯之旅“压力更大”：国足选拔队以U23球员为主，超龄球员只有蒋光太和谭龙两人，虽然日韩球队未招海外球员，但两队旨在为世界杯赛热身启用成年队，其本土精英实战能力皆在国足选拔队之上。抛开胜负不谈，倘若主教练扬科维奇执教的国足选拔队可以在两场硬仗中打出令球迷满意的内容，对于这支肩负亚运任务的球队而言便可算作胜利。“我们每期集训都不会召入很多球员，现在球队已经形成一个整体，球员之间都很熟悉，也了解我们的战术体系。面对强敌，我们也有想要达到的目标。”扬科维奇在球队出征前说，“我们3年没有打过国际比赛，目前这个阶段，日韩球员的个人能力要强于我们，我们的重点是让球员更积极、更有侵略性。我不是要把球队训练成一支田径队，但我们必须在体能训练方面有更好的表现。” 正印前锋张玉宁因伤缺战是球队在攻击线上的重大损失，面对日、韩亚洲顶级防线，扬科维奇要求年轻球员“要有一颗大心脏”，“我和队员说不要去考虑强弱的分别，这样容易分心，场上的球员不能算计着去踢球，他们要全力以赴。

C | ” “我希望中国球迷看到一支努力拼搏、战斗到底、不停奔跑的国家队”，扬科维奇说。

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