Core Insights - Haier Kaos has strategically invested in Shanghai Carbon Source Energy, aiming to leverage both parties' resources to establish the Kaos Green Low-Carbon Research Institute, focusing on AI carbon technology and zero-carbon solutions [1][4] Group 1: Strategic Investment and Goals - The strategic investment allows Haier Kaos to enhance its technology, products, and services, driving a new ecosystem for digital transformation through "industrial digitalization + dual carbon technology" [1] - Shanghai Carbon Source Energy is recognized as a "specialized, refined, and innovative small giant" enterprise, focusing on zero-carbon solutions for major energy-consuming clients [2] Group 2: Research Institute and Technological Focus - The Kaos Green Low-Carbon Research Institute will combine Haier Kaos's industrial internet capabilities with Shanghai Carbon Source Energy's carbon management technologies, focusing on AI carbon technology applications [5][7] - The research institute aims to drive industry innovation and green development by integrating advanced technologies such as industrial models and IoT with green manufacturing scenarios [5][7] Group 3: Industry Collaboration and Future Directions - The collaboration will facilitate the establishment of a comprehensive energy ecosystem, promoting a business model where "energy is a service, data is an asset, and carbon is currency" [3] - Shanghai Carbon Source Energy will support the development of zero-carbon parks and provide full-chain services, contributing to national zero-carbon park construction [7][8]

转自：中国质量报 □ 本报记者 朱文达 文/摄 在人工智能浪潮席卷全球，各国抢占科技竞争制高点的今天，传统的质量管理体系正迎来历史性重构。我国积极部署"人工智能+"行动，鼓励企业将人工智 能融入战略规划、组织架构、业务流程等，助力传统产业改造升级。利用人工智能加快推动质量变革、效率变革、动力变革，提高全要素生产力，培育质量 竞争新优势已成为大势所趋。 在此背景下，海尔集团公司（以下简称"海尔"）将AI技术的创新应用提升至企业核心战略高度，全员、全面、全流程拥抱AI，以智能协同实现从"人 控"到"智控"的质量管理跃迁，联合用户共创重新定义质量标准，构建开放生态赋能产业链升级，开启了高质量发展新范式。 战略引领 全员、全面、全流程拥抱AI 面对人工智能浪潮，海尔将2025年定位为"AI应用元年"。海尔董事局主席、首席执行官周云杰强调，AI不仅是技术变革，更是思维方式的重构，企业必须从 战略、组织、流程等多个维度进行调整，全员、全面、全流程拥抱AI。 这一战略定位的核心是"创用户最佳体验"，并基于此构建了覆盖全员、全面、全流程的大质量体系。 在全员层面，海尔鼓励员工积极应用AI，推动员工从"技能持有者"跃迁为"生态 ...

Core Insights - The year 2023 marks a period of rapid development and popularization of general large models, while 2024 and beyond will see the application of various specialized large and small models in vertical fields, becoming a major trend in the integration of artificial intelligence across industries [1] - Industrial sectors, characterized by complex production processes and clear mechanisms, are identified as key areas for the commercialization of vertical large models [1] Group 1: Industrial Applications - Industrial large models are being applied in energy conservation, manufacturing, and management, with expectations for accelerated commercialization as data accumulation enhances model capabilities [1] - The introduction of large models can significantly improve production accuracy, with average accuracy rates increasing from 70% to 90% in complex manufacturing processes [2] - Large models facilitate the integration of various energy mediums and types of water used in production, allowing for comprehensive decision-making in energy conservation efforts [2] Group 2: Challenges and Solutions - Challenges include the limited understanding of production processes by personnel and the lack of integration between independent systems, which hampers effective energy efficiency control [3] - The introduction of large models enables comprehensive energy and carbon management, creating a unified service model that enhances operational efficiency [4] - Data issues remain a significant barrier, with many facilities lacking real-time data collection capabilities, which is essential for deploying large models effectively [6] Group 3: Implementation Strategies - The fastest implementation projects are often retrofitting older facilities, particularly in the energy sector, which yields immediate economic benefits and encourages further digitalization efforts [6] - Service providers are also engaging in new facility construction, establishing digital twin systems to facilitate comprehensive large model integration across the entire production chain [7] - The combination of immediate results and flexible implementation strategies is accelerating the commercialization of industrial large models, providing better adaptability and customized solutions for various application scenarios [7]