新华财经巴西贝伦11月19日电（记者陈昊佺吴昊）《联合国气候变化框架公约》（以下简称《公约》） 第三十次缔约方大会（COP30）正在巴西贝伦举行。按照会议议程，大会将在21日闭幕，但目前分歧犹 存。多方呼吁大会尽快凝聚共识，以共同应对气候变化。 《公约》秘书处执行秘书西蒙·斯蒂尔当天表示，COP30已取得一系列务实的气候行动成果，国家气候 计划也正展现出覆盖全经济范围、全社会的整体性策略，这在数年前难以想象。 斯蒂尔说，但这绝非自我陶醉之时，而是砥砺前行之刻。他呼吁各方快速、公平、规模化地达成成果， 弥合承诺与落实之间的差距。"每延误一刻，代价都将极其高昂。" （文章来源：新华社） 19日，巴西总统卢拉在COP30上介绍谈判进展时表示，大会成果必须建立在"共识与广泛对话"基础上， 而不是通过强加立场获得。 卢拉指出，各国必须认识到，应对气候变化关乎保护人类共同的唯一家园——地球。发达国家必须加大 对发展中国家在应对气候变化方面的支持力度，包括资金援助、技术转移与知识分享等。 据巴西媒体报道，尽管大会临近闭幕，但与会各方在气候融资、气候变化适应方案、减排目标以及数据 标准等多个关键议题上仍存在明显分歧。 ...

Core Insights - The Civil Aviation Data Set for Flight Operations has been selected as a national pilot project, marking a significant advancement in the development and utilization of aviation operational data resources in China [1][2] Group 1: Data Quality and Security - The data set focuses on key performance indicators such as flight punctuality and passenger boarding rates, establishing a high-quality aviation data network covering 333 domestic units [2] - The average data effectiveness has improved from 71.97% to 99.14% through the creation of an industry-first knowledge graph with business situational awareness and reasoning capabilities [2] - The system has operated for over 600 days with zero data leaks, managing more than 55 billion data entries securely [2] Group 2: Operational Efficiency - The data management system integrates real-time operational data from flights, airports, and airlines, breaking down previous data silos and enabling all units to make decisions based on the same accurate and real-time data [2] - Pilot programs at several airports, including Guangzhou Baiyun, Chengdu Shuangliu, and Xi'an Xianyang, have shown a 2% increase in average flight release normal rates and a 3% increase in boarding rates, enhancing passenger experience [2] Group 3: Industry Standards and Collaboration - The organization is actively promoting data standards and mechanisms to drive industry innovation, establishing a feedback loop for standard verification [3] - It has signed service agreements with 166 units and is exploring market-based operational mechanisms and revenue distribution based on contribution [3] Group 4: Future Developments - The data set will support 66 domestic airlines, 261 transport airports, and 26 airport groups, providing over 17,000 flight operation data entries daily, covering over 99.9% of domestic flights [5] - Future plans include integrating ground transportation data to create a comprehensive transport network centered around hub airports, enhancing seamless travel experiences for passengers [5]

Core Insights - Many small and medium-sized enterprises (SMEs) face challenges in realizing the return on investment (ROI) from their digital transformation efforts, despite having implemented various systems and automation equipment [3] - Approximately 90% of manufacturing enterprise data remains "asleep," particularly in SMEs, due to a lack of unified data and business process standards, leading to data silos and inefficient business collaboration [3][4] - The digitalization of supply chains is evolving from merely moving procurement processes online to achieving end-to-end collaboration and optimization through data integration [3] Group 1: Challenges in Digital Transformation - Enterprises often have multiple systems (e.g., SAP, PLM, MES) but struggle with data integration, resulting in data silos that hinder effective decision-making [4] - The absence of standardized business and data processes is a fundamental issue, as many companies jump into system implementation without proper design [4] - The "sleeping data" problem is exacerbated by the lack of a centralized data management system and effective edge data processing capabilities [5] Group 2: Solutions and Innovations - Companies are leveraging AI technologies to break down data barriers and enhance data sharing and value realization [4][5] - AI is being applied to improve supply chain transparency, responsiveness, and risk management, with successful case studies demonstrating proactive measures against price increases and stock shortages [6] - The development of platforms like "Procurement Butler" aims to streamline non-standard procurement processes, making them as simple and controllable as online shopping [6] Group 3: Future of AI in Manufacturing - 2025 is anticipated to be a pivotal year for AI applications, particularly in generative AI and large model technologies, although the manufacturing sector's approach differs from that of the internet industry [7] - The focus in manufacturing AI is on "small data" and "scenario closure," rather than the pursuit of large models, emphasizing practical applications over theoretical advancements [7] - Ultimately, the effectiveness of systems and AI in manufacturing will be measured by improvements in supply chain stability, speed, and intelligence [7]