Core Viewpoint - The article discusses the implementation of the "Artificial Intelligence + Manufacturing" initiative, aiming to enhance the integration of AI technologies in the manufacturing sector by 2027, establishing China as a global leader in AI technology and application [1][6]. Group 1: Overall Requirements - By 2027, China aims to achieve secure and reliable supply of key AI technologies, maintaining a leading position in industry scale and empowerment levels globally. The initiative includes the application of 3-5 general large models in manufacturing, the launch of 1,000 high-level industrial intelligent entities, and the creation of 100 high-quality industrial data sets [6][5]. Group 2: Innovation Foundation - The initiative emphasizes strengthening AI computing power supply, supporting the development of intelligent chips and high-level computing facilities, and promoting the establishment of a national integrated computing network [7]. - It also focuses on developing high-performance algorithm models tailored for the manufacturing sector, encouraging the creation of industry-specific models and enhancing data governance capabilities [8][7]. Group 3: Application Empowerment - The initiative promotes the deep integration of AI in key manufacturing sectors, facilitating the development of intelligent factories and enhancing capabilities in design, production, and management processes [9][10]. - It encourages the establishment of AI application platforms to match supply and demand accurately, and supports the digital transformation of small and medium-sized enterprises [11][12]. Group 4: Product Breakthrough - The initiative aims to accelerate the iteration of intelligent equipment and the upgrade of smart terminals, including industrial robots and AI-driven medical devices, to enhance decision-making and operational capabilities [13][14]. - It also focuses on fostering new business models around intelligent entities and promoting the integration of AI with traditional software products [15][16]. Group 5: Ecological Growth - The initiative emphasizes the importance of standardization in AI development, encouraging participation in international standardization efforts and promoting an open-source ecosystem for AI projects [17][18]. - It aims to strengthen talent cultivation in the AI sector, ensuring a skilled workforce that understands both AI and manufacturing applications [19][18]. Group 6: Safety Assurance - The initiative outlines measures to enhance safety and security in AI applications, including the development of safety governance mechanisms and risk monitoring systems [20][21]. Group 7: International Cooperation - The initiative encourages international collaboration in AI, supporting enterprises in customizing AI products for different markets and participating in global AI discussions [21][20]. Group 8: Support Measures - The initiative calls for a comprehensive policy support system to facilitate the development of AI in manufacturing, including funding and resource allocation to promote new technologies and applications [22][23].

人民财讯1月7日电，工业和信息化部等八部门印发《"人工智能+制造"专项行动实施意见》，其中提 出，到2027年，我国人工智能关键核心技术实现安全可靠供给，产业规模和赋能水平稳居世界前列。推 动3-5个通用大模型在制造业深度应用，形成特色化、全覆盖的行业大模型，打造100个工业领域高质量 数据集，推广500个典型应用场景。培育2—3家具有全球影响力的生态主导型企业和一批专精特新中小 企业，打造一批"懂智能、熟行业"的赋能应用服务商，选树1000家标杆企业。建成全球领先的开源开放 生态，安全治理能力全面提升，为人工智能发展贡献中国方案。 ...

12月30日早间，华为官方公众号发布了轮值董事长孟晚舟的新年致辞。致辞以极具诗意的笔触，温情的回顾了华为在2025年忙碌与奔赴的奋斗历程。在娓 娓道来的叙事中，穿插着关于华为战略布局、技术突破与生态构建的诸多关键信息。 1、2025年，华为助力运营商建设5G-A网络，为6000万用户提供极速网络联接体验。 4、2025年，鲲鹏已发展6800多家合作伙伴、380万开发者。昇腾已发展3000多家合作伙伴、400万开发者。 5、2026年华为将发挥的"大杂烩"优势，助力千行百业智能化转型。 6、持续构建开源开放的鲲鹏昇腾生态，推动集群与超节点技术普惠。 轮值董事长 孟晚舟 时光的潮水正漫过2025的岸线，回望这一年的忙碌与奔赴，那些深浅不一的足迹，正是我们奋力向前的最好见证： 在撒哈拉沙漠南缘，网优工程师穿梭在44℃高温、红土飞扬的街头，厘清网络症结； 在大西洋的七级风浪中，光网专家克服严重晕船，和客户一起定位故障、恢复通信； 在海拔4300米的雪域高原，服务团队缺氧不缺精神，冒着零下15℃的严寒调试光储系统，把绿色电源送入千家万户； 在凌晨4:30的客户机房，抓住业务流量最小的间隙，研发团队奋战30天的技术方案紧 ...

中新经纬 30日上午，华为公众号发布华为副董事长、轮值董事长、CFO孟晚舟的新年致辞。全文如下： 追风赶月莫停留，平芜尽处是春山 ——2026年新年致辞 轮值董事长 孟晚舟 时光的潮水正漫过2025的岸线，回望这一年的忙碌与奔赴，那些深浅不一的足迹，正是我们奋力向前的 最好见证： 在撒哈拉沙漠南缘，网优工程师穿梭在44℃高温、红土飞扬的街头，厘清网络症结； 在大西洋的七级风浪中，光网专家克服严重晕船，和客户一起定位故障、恢复通信； 在海拔4300米的雪域高原，服务团队缺氧不缺精神，冒着零下15℃的严寒调试光储系统，把绿色电源送 入千家万户； 在凌晨4：30的客户机房，抓住业务流量最小的间隙，研发团队奋战30天的技术方案紧急切换上线； 鸿蒙生态工程师与伙伴一起披星戴月，从第一单外卖、第一条笔记、第一次出行开始，持续提升用户体 验； 手语工程师克服专业术语挑战，解决听障用户的售后难题，为他们架起无声的桥梁； 制造工匠深入钻研打螺钉，从小鸡喂食器得到启发，解决了手机微短螺钉供钉器随动打钉技术难题，大 幅提升打钉效率； 支付会计严格遵照公司流程，查授权验文档，以始终如一的匠心，守万亿支付零损失； 鲲鹏已发展6800多 ...

Core Insights - The article emphasizes that AGI is not the endpoint but the starting point towards ASI, with Alibaba Group's CEO categorizing the evolution into three stages: intelligent emergence, autonomous action, and self-iteration, currently in the autonomous action phase [2][3] Group 1: AI Development Stages - The current phase of AI is characterized by a shift from perception and generation to decision-making and action, driven by intelligent agent technology [3] - The transition to autonomous action is seen as a critical bridge towards self-iteration, enabling AI to create real-world value [3][19] Group 2: Technological Breakthroughs - Continuous breakthroughs in technology are essential for releasing AI's value, focusing on building foundational capabilities such as computing power, basic models, and technical ecosystems [4] - The integration of cloud computing and AI is creating a full-stack technology ecosystem, addressing resource and cost bottlenecks for scalable AI deployment [5][6] Group 3: Model Innovations - Large models are evolving from single-modal to multi-modal capabilities, enhancing AI's application scope across various fields such as education and healthcare [9][10] - Innovations like reinforcement learning from human feedback (RLHF) are improving models' abilities to solve complex tasks autonomously [10] Group 4: Application and Ecosystem Development - The rise of intelligent agents is reshaping software ecosystems, enabling dynamic decision-making and task execution [11][16] - Open-source initiatives are crucial for democratizing AI technology, with Alibaba contributing over 300 open-source models to lower development costs [13][14] Group 5: Industry Transformation - AI is driving systemic innovation across industries, enhancing operational efficiency and consumer experiences [20] - The global collaboration in AI innovation is reshaping industry structures and optimizing resource allocation, facilitated by AI cloud platforms [21] Group 6: Responsible AI Development - The article highlights the importance of a governance framework to ensure AI's sustainable development, addressing challenges like data privacy and algorithmic bias [25][26] - A collaborative approach involving industry, academia, government, and the public is essential for achieving responsible AI development [27]