"回顾工业革命的历程，从机械化、电气化到自动化，每一次变革都极大地提升了生产力。"中国工业互 联网研究院院长鲁春丛表示，当前在经历以智能化为主要特征的第四次工业革命。如果说第三次工业革 命主要解决的是"机械化换人"和"自动化减人"的问题，那么第四次工业革命，就是要实现智能化无人或 人机协同。 2月24日下午，广东省高质量发展大会"智能制造与工业互联网"分会场在广州举行。 一是建设数智基础设施，破解联不稳、算不快的数字基建瓶颈问题，构建云边协同、控网算一体的新型 基础设施，为海量工业数据的实时处理和智能应用的规模化部署提供坚实支撑。 二是推进工业互联互通，解决采不上、看不懂的数据源头难题，要实现工业全要素的泛在互联，重点要 解决"人机物料法环测"等要素的有效采集问题。 三是建设工业高质量数据集，破解数据多但质量低、有数据但不会用的数据要素瓶颈。 鲁春丛在会上提出，制造业是实体经济的根基，2025年，我国工业增加值达到41.7万亿元，其中，制造 业增加值达到34.7万亿元，占GDP比重稳定在25%左右，总体规模连续16年保持全球第一，我国还拥有 全球最完整、门类最齐全的工业体系，这构成了人工智能技术最宝贵的"全场 ...

Core Insights - The industrial software industry is at a critical juncture, driven by the need for innovation and the urgency of development, particularly in the context of China's economic transformation and the push for self-sufficiency in core technologies [1][4][17] - The market for industrial software in China is projected to approach 300 billion by 2024, indicating robust growth despite challenges such as a hollowing out of core technologies and imbalanced industrial structures [1][17] - The evolution of industrial software is characterized by a shift from tools to systems, platforms, and eventually to a genetic level, focusing on data value and efficiency [2][48] Industry Dynamics - The industrial software market is large, with significant opportunities for companies to target head, mid, and long-tail customers, each with distinct needs and potential for revenue generation [2][50] - The core evolution path of industrial software is from tools to systems, then to platforms, and finally to genetic integration, emphasizing the importance of data flow and value efficiency [48][49] - The industry faces systemic challenges, including a lack of foundational technologies and difficulties in integrating into supply chains, which hinder the development of domestic industrial software [26][17] Product Development Trends - Current industrial software primarily focuses on product sales, but there is a shift towards selling "intelligence" as data assets are accumulated and utilized effectively [3][52] - The integration of AI and large models is expected to enhance the capabilities of industrial software, particularly in areas such as code generation and human-computer interaction [43][52] - Future products are anticipated to evolve into "digital engineers," capable of autonomous task execution and intelligent interaction, moving beyond traditional software tools [52] Market Characteristics - The industrial software market is characterized by a high degree of fragmentation, with varying levels of domestic replacement and integration needs across different customer segments [14][50] - The demand for industrial software is driven by practical applications in enterprises, government initiatives, and the integration of research institutions, each with unique procurement focuses [14][16] - The market is currently experiencing a transition from subsidy-driven growth to a more market-oriented approach, emphasizing the importance of innovation and self-sufficiency [19][12] Challenges and Opportunities - The industry is grappling with significant challenges, including a lack of core technologies in research and design software, which is critical for engineering optimization [23][17] - Companies are encouraged to leverage policy incentives and market opportunities to enhance their technological capabilities and address the "bottleneck" issues in core components [17][26] - The evolution of industrial software is expected to create new revenue streams through data value services, as companies adapt to the changing landscape of technology and market demands [30][52]

Core Viewpoint - Shenzhen has released the "Artificial Intelligence+" Advanced Manufacturing Action Plan (2026-2027), aiming to integrate AI technology deeply into the manufacturing process and enhance the semiconductor industry through AI applications [1][3]. Group 1: Key Support Platforms - The plan emphasizes the establishment of an Industrial Intelligence Innovation Center and aims to accelerate the construction of provincial and national manufacturing innovation centers [5]. - It supports the development of industrial software and knowledge alliances, focusing on standardizing industrial knowledge and creating leading autonomous industrial software products [5][6]. Group 2: Empowering Key Industry Clusters - AI will be applied to critical areas of the semiconductor industry, optimizing chip design and software coding efficiency, with a focus on developing high-performance SoC chips for various AI applications [8]. - The plan also highlights the importance of AI in robotics, promoting the development of multimodal interaction technologies and enhancing the capabilities of robots in industrial settings [8][9]. - In the low-altitude economy, the plan aims to establish a drone autonomy evolution system and enhance drone capabilities for various applications, improving resource scheduling and operational efficiency [9]. Group 3: AI in Electronics and Healthcare - The plan encourages collaboration among leading enterprises in the electronic information manufacturing sector to explore potential AI application scenarios and develop benchmark projects [9]. - In the pharmaceutical and medical device sectors, the plan promotes the integration of AI in drug development and medical technology, aiming to accelerate innovation and enhance the capabilities of medical devices [10].

事关"人工智能+"，深圳最新发文。 今日（2月12日），据深圳工信微信公众号消息，深圳市工业和信息化局近日印发《深圳市"人工智能+"先进制造业行动计划（2026—2027年）》（以下简称《行动 计划》），从打造重点支撑平台、赋能重点产业集群、强化工作保障三个方面提出了13条具体举措，抢抓智能化与工业化交汇融合的历史机遇，加快人工智能技术 与制造业全过程、全要素深度融合。 《行动计划》明确，推动人工智能技术应用于半导体产业链的关键环节，利用AI优化芯片设计、软件代码等领域和环节的效率。以AI芯片为突破口做强半导体产 业，面向AI手机、AI眼镜、智能机器人等各类AI终端需求，研发高性能、高能效专用SoC主控芯片，支持存算一体、存内计算等新型架构处理器。 深圳重磅发布 2月12日消息，深圳市工业和信息化局近日印发《深圳市"人工智能+"先进制造业行动计划（2026—2027年）》，其中提出，到2027年，在"人工智能+"先进制造业领 域，建成国家人工智能应用中试基地（消费领域移动终端方向），建设工业智能体创新中心，组建工业知识联盟，开放百个应用场景，打造百个垂直行业模型及工 业智能体，推广百个示范应用，形成"一基地、 ...

Core Insights - The industrial software industry is at a critical juncture, driven by the need for innovation and the urgency of development, particularly in the context of China's economic transformation and the push for self-sufficiency in core technologies [1][4][17] - The market for industrial software in China is projected to approach 300 billion yuan by 2024, indicating robust growth despite challenges such as a hollowing out of core technologies and imbalanced industrial structures [1][17] - The evolution of industrial software is characterized by a shift from tools to systems, platforms, and eventually to a genetic level, focusing on data value and efficiency [2][48] Industry Dynamics - The industrial software market is large, with significant opportunities for companies to target different customer segments: head clients with strong demand for domestic alternatives, mid-tier clients forming communities, and long-tail clients expanding revenue potential [2][50] - The development of industrial software is influenced by policy support, technological advancements, and market demand, with a notable shift towards integrating AI and data-driven solutions [9][12][14] Product Evolution - Current industrial software primarily involves purchasing products, but the future will see a transition towards selling "intelligence," exemplified by the emergence of industrial intelligent agents [3][52] - The focus on data accumulation and utilization will drive the transformation of industrial software into platforms that offer integrated solutions and services [48][52] Challenges and Opportunities - The industry faces significant challenges, particularly in the R&D design sector, where a lack of foundational technologies and real-world testing scenarios hampers progress [17][23][26] - Companies must navigate a complex landscape of technical, ecological, and commercial challenges, with a systemic approach required to overcome these hurdles [26][39] Market Characteristics - The industrial software market is characterized by a high degree of specialization, with significant barriers to entry and a focus on high-value data services [20][30] - The market is currently experiencing a shift towards platformization and the integration of AI, which is expected to enhance operational efficiency and drive innovation [48][52] Future Directions - The next phase of industrial software development will emphasize platformization and the internalization of industrial knowledge into code, leading to the creation of digital engineers capable of autonomous task execution [48][52] - Companies are encouraged to leverage policy advantages and technological breakthroughs to enhance their competitive positioning in the market [50][52]

Core Insights - The article highlights the significant opportunity for companies deeply integrated with industrial internet and artificial intelligence, particularly focusing on Kaos IoT Technology Co., Ltd., a subsidiary of Haier Group, which has submitted its listing application to the Hong Kong Stock Exchange [1][2]. Industry Overview - China's industrial digital transformation has entered a critical phase of large-scale application and value enhancement, with the market for industrial digital solutions projected to reach RMB 2 trillion in 2024, growing at a compound annual growth rate (CAGR) of 12.2% from 2020 to 2024 [2]. - By 2029, the market size is expected to expand to RMB 3.4 trillion, driven by urgent transformation needs on both supply and demand sides [2]. Company Positioning - Kaos holds the leading market share in platform-based industrial data intelligence solutions in China, with a 1.2% market share, and has been recognized as a top "dual-cross" platform for seven consecutive years [1][3]. - The company’s COSMOPlat platform is designed to integrate the entire manufacturing value chain, transitioning from providing automation for individual factories to offering an intelligent operating system for entire industrial ecosystems [3]. Financial Performance - The company's revenue increased from RMB 49.94 billion in 2023 to RMB 44.21 billion in the first nine months of 2025, reflecting a year-on-year growth of 21.6% [4]. - The revenue share from high-value "data intelligence solutions" rose from 18.3% in 2023 to 29.0% in the first nine months of 2025, with a year-on-year absolute growth of 59.6% [4]. Technological Advancements - Kaos has developed over 110 intelligent development tools and has applied for more than 200 patents, serving over 9,500 paying enterprises across various industries [3][4]. - The company has been recognized for its research capabilities, receiving multiple awards and certifications, including the highest level "five-star intelligent level" certification for its COSMOPlat platform [6]. Strategic Initiatives - The upcoming IPO aims to enhance the company's core AI capabilities, expand market penetration, and explore potential investments and acquisitions to solidify its technological leadership [9]. - The company envisions becoming a foundational provider and rule-definer in the industrial sector during the intelligent era, fostering a collaborative innovation ecosystem involving developers, partners, and customers [9].

中化新网讯日前，中国信息通信研究院(以下简称中国信通院)正式启动首批可信AI工业智能体评估工 作。 该评估依据中国信通院人工智能研究所依托中国人工智能产业发展联盟智能体创新与应用工作组，联合 上海移动、南方电网、广西电网、中国石化、中国石油等多家企业共同编制完成的《智能体技术要求与 评估方法行业应用工业》技术规范，立足工业行业对复杂性、可靠性的要求，结合智能体的能力特性， 从技术到应用展开全面评估，覆盖基础能力、业务场景、服务应用3大能力域，共计20余个能力项。 其中，基础能力部分主要评估工业智能体在感知、认知、决策、执行等方面的基本技术能力，包含工业 数据采集、工业数据加工、机理融合、生产规划、协同控制等能力项；业务场景主要评估工业智能体场 景应用的丰富程度，包含研发设计、工艺仿真等产品研发场景，生产优化、运行维护、质量控制等生产 管理场景，供应链管理、经营管理等运营管理场景；服务应用主要评估工业智能体服务应用的成熟度， 包含业务效果、智能交互、混合部署、系统兼容、安全保障、运维监控等能力项。(吴班) ...

价值锚点："今天排"智能体，解耦复杂排产 目前，圆木智能从"排产"这一具体场景切入，为应对"多品种小批量、订单变化频繁、工序复杂设备 多"等企业排产中面临的复杂挑战，推出了"今天排"智能体产品。"今天排"通过大模型理解生产约束， 融合优化算法实现动态排程，将排产时间从小时级缩短至分钟级，面对插单等异常情况，系统可快速生 成新方案。同时，"今天排"能适配多源数据输入，降低使用门槛，实现产品在排产场景中规模化落地。 目前，产品已在苏州、无锡等地机加工工厂投产使用，帮助客户实现全工序自动排程，排产时间缩短 90%，订单交付率提升15%以上，有效提升设备稼动率与交期确定性。 圆木智能核心成员均毕业于清华大学、北京大学等顶尖学府，兼具人工智能前沿研发、成功SaaS产品从 0到1商业化、以及超过二十年的工业数字化实战与销售经验。"算法+工业+产品"的复合背景，使团队 既能够洞察工业领域复杂性背后的核心痛点，又具备将新一代AI技术转化为稳定、易用产品的研发能 力。此外，圆木智能已与百度、智谱等大模型厂商达成深度合作，与清华、浙大、复旦等高校实验室建 立产学研合作关系，不断巩固技术优势，共同夯实工业智能的基座。 未来蓝图：从 ...

Core Viewpoint - The industrial software industry is at a critical juncture, necessitating urgent development driven by innovation and supported by favorable policies. It serves as a core production material and key productivity for new industrialization, emphasizing the importance of self-control and supply chain security [1][4]. Industry Dynamics - The evolution path of industrial software is transitioning from tools to systems, then to platforms, and finally to genetic models, focusing on data value in the latter stages [2]. - The market is large, with a projected size nearing 300 billion yuan in 2024, but challenges such as core technology gaps and imbalanced industrial structure are prominent [1][17]. Product Development - Currently, industrial software is primarily sold as products, but it is expected to shift towards selling "intelligence" as data assets are effectively accumulated and utilized, leading to the emergence of industrial intelligent agents [3]. Development Background - Industrial software is crucial for innovation and transformation in the economy, with the shift of control from hardware to software becoming increasingly evident. The encapsulation of industrial knowledge in software is essential for optimizing production processes [4][7]. Driving Factors - Policy support and technological advancements, particularly in AI and large models, are accelerating the development and application of industrial software. Cities are introducing subsidy policies to stimulate innovation in this sector [12][14]. - Demand from enterprises emphasizes practical market needs while also considering domestic alternatives, with government and research institutions focusing on top-level planning and integration [14]. Market Characteristics - The industrial software market is characterized by a significant gap in core technologies, particularly in R&D design software, which is the most affected area by the "bottleneck" phenomenon. The imbalance in the industrial structure shows a stronger presence of management software compared to engineering software [17][19]. Industry Value Flow - The industrial software value distribution follows a "smile curve" model, where the closer to core technology, the higher the barriers and profits. The rise of data value services is expected to create new growth opportunities [30]. Profit Models - Current profit models for industrial software include software licensing, maintenance, and customized development, with ongoing exploration of platform and ecosystem revenue sharing [33]. Future Directions - The industrial software industry is expected to evolve towards platformization and genetic modeling, focusing on enhancing data flow efficiency and value. The future will see products transforming from mere tools to intelligent agents capable of autonomous task execution [48][52].

Core Insights - The industrial software industry is at a critical juncture, driven by the need for innovation and the urgency of development, especially in the context of China's economic transformation and the push for self-sufficiency in core technologies [1][3][17] - The market for industrial software in China is projected to approach 300 billion yuan by 2024, indicating robust growth despite challenges such as a lack of core technologies and imbalanced industrial structure [1][17] - The evolution of industrial software is characterized by a shift from tools to systems, platforms, and eventually to a genetic level, focusing on data value and efficiency [2][48] Industry Dynamics - Industrial software serves as a critical enabler for innovation and transformation in the industrial sector, acting as the "brain" and digital foundation of new industrialization [3][9] - The market is large, with significant opportunities for domestic companies to replace foreign products, particularly in the context of national policies promoting self-reliance [2][50] - The development of industrial software is slow and requires patience, but it also presents opportunities amid ongoing changes and restructuring [1][17] Market Characteristics - The industrial software market is characterized by a significant gap in core technologies, particularly in research and design software, which is crucial for engineering optimization [17][23] - The market structure shows a strong presence of management software while engineering software remains weak, indicating a need for improvement in the latter [17][19] - The demand for industrial software is driven by practical needs from enterprises, government initiatives, and the integration of research and education [14][50] Technological Drivers - The advancement of large models and AI technologies is accelerating the development and application of industrial software, supported by government subsidies aimed at fostering innovation [12][14] - The integration of AI and big models is transforming the capabilities of industrial software, enhancing areas such as code generation and human-computer interaction [43][45] Future Directions - The industrial software industry is expected to transition towards a model that emphasizes selling "intelligence" rather than just software, with products evolving into "digital engineers" capable of autonomous task execution [52][48] - The focus will shift towards platformization and the internalization of industrial knowledge into parameters and codes, enhancing the efficiency of data flow and value extraction [48][52] - Companies are encouraged to leverage head clients and policy support to drive technological breakthroughs while also exploring opportunities in mid-tier and long-tail markets [50][52]