据介绍，本次活动由中央网信办网络安全协调局指导，国家计算机网络应急技术处理协调中心主办，网 络安全众测平台、国家网络安全人才与创新基地提供技术和环境支持，旨在推动AI大模型在发展中更 好统筹高质量发展和高水平安全。 （文章来源：人民日报） 本报昆明9月16日电 （记者张驰、金歆）16日，在昆明召开的第二十二届中国网络安全年会暨国家网络 安全宣传周网络安全协同防御分论坛上，国内首次针对AI大模型的实网众测检验结果揭晓。 本次活动共对国内15款大模型及应用产品进行了漏洞测试。测试产品中既有基础大模型产品，也有垂域 大模型产品，还有智能体、模型开发平台等相关应用产品，其中既包含单模态大模型，也涵盖多模态大 模型，具有较广泛的代表性。本次活动累计发现各类安全漏洞281个，其中大模型特有漏洞177个。 ...

Group 1 - The 2025 Indonesia Digital Transformation Expo (DTI-CX) recently concluded in Jakarta, marking a significant upgrade as the first overseas exhibition organized by China in the digital technology sector, attracting over 11,000 buyers and generating an intended transaction volume of nearly 10.4 million USD from Hangzhou enterprises [1] - DTI-CX has rapidly evolved from its 1.0 version in 2024 to become Indonesia's top digital technology event in terms of scale and professionalism, with international exhibitors accounting for 50% of the total, featuring leading tech companies from the US, Singapore, and Indonesia [1] - Hangzhou enterprises represented 36% of Chinese exhibitors, showcasing advanced technologies and innovative solutions, thereby enhancing Hangzhou's reputation as "China's Digital Economy Capital" [1] Group 2 - The expo successfully facilitated high-quality matchmaking events, inviting representatives from key Indonesian associations and organizing over 20 intended cooperation orders through targeted business negotiations [2] - Hangzhou's exhibition group actively engaged with Indonesia's Ministry of Communication and Digital Affairs and visited various innovation centers to deepen market understanding and explore potential collaboration opportunities [2] - A special promotion area for the "Fourth Global Digital Trade Expo" was set up, with Indonesian authorities expressing commitment to organize professional buyers for participation, highlighting the shared opportunities in the digital era [2]

2025中国国际大数据产业博览会（以下简称数博会）将于8月28日在贵州贵阳启幕。本届数博会以"数聚 产业动能 智启发展新篇"为主题，旨在推动数据资源的高效汇聚和开发利用，为产业转型升级和经济高 质量发展注入强劲动力。北京交通大学信息管理理论与技术国际研究中心教授张向宏作为数据领域的深 耕者和数博会的长期参与者，近日接受对话专访，围绕数字化转型成效、数据要素市场化破局、基础设 施挑战与机遇、数博会平台价值及未来发展等核心议题，分享了他的深刻洞察与前瞻建议。 第四梯队是中小企业、农业等领域，大多数还处于信息化初级阶段，信息系统还没有建设应用，数据资 源还未得到充分重视，数据还没有得到应用。 问：数据要素市场化是当前的热点，您认为不同行业在数据确权、定价、交易等环节存在哪些共性难 题？结合您的研究，有哪些针对性的解决思路？ 张向宏：数据是一种新型生产要素，具有与土地、劳动力、技术、资本等传统生产要素迵然不同的新特 点，如数据的多环节性和低成本易复制性特点，决定了数据要素很难确权或者确权成本很高；数据的阿 罗信息悖论效应特征，决定了数据很难实现场内规模交易；数据价值不确定性特征，决定了数据价值易 变、很难定价。 张向 ...

Core Viewpoint - The Guangdong provincial government is accelerating the development of a modern industrial system, focusing on the artificial intelligence and robotics sectors, with a special meeting held to discuss strategies for high-quality growth in these industries [2]. Group 1: Development Strategies - Four major strategies were proposed by Tang Hongwu, an academician of the Chinese Academy of Engineering and president of South China University of Technology, to promote high-quality development in Guangdong's AI and robotics industries: building high-energy platforms, optimizing financial support, accelerating key technology breakthroughs, and promoting application scenarios to create a collaborative industrial ecosystem [2][5]. Group 2: Educational and Research Contributions - South China University of Technology has established a comprehensive development system integrating education, technology, and talent in the AI and robotics fields, leading over 30 major projects in these areas since the 13th Five-Year Plan, achieving internationally leading results in brain-computer interfaces and digital twins [5][6]. Group 3: Key Recommendations - Tang Hongwu emphasized three key recommendations for the development of the AI and robotics industry in Guangdong: 1. Accelerate the creation of high-energy platforms by deploying new infrastructure such as big data processing platforms and supercomputing clusters, and striving for national-level research platforms [5]. 2. Focus on overcoming key technological bottlenecks by establishing special funds within provincial R&D plans to encourage collaboration between universities and enterprises on new technologies [5]. 3. Promote application scenarios by creating a demand-driven collaborative model between industry and academia, enhancing procurement incentives, and establishing a technical adaptation service system to lower barriers for enterprise applications [5].