转自：新华财经 其中，国家工业操作系统检验检测公共服务平台以工业操作系统标准测评认证体系建设为核心，以保障重点行业的关键基础设施安全为根本，打造覆盖芯片 级至行业级的全栈适配测试验证工具链，构建国家测试基准与标准体系；开放原子紫金专区运营总部由江苏软件产业人才发展基金会、苏州市工信局与吴中 区人民政府三方共建，将建立市场化运营团队，联动省内软件名园、重点企业、高校院所，围绕RISC-V（计算机开源指令集架构）、工业软件、AI模型等 关键领域，探索形成一批具有全国影响力的开源技术成果；工业操作系统（数字制造）综合创新平台由苏州汇川技术携手重点软件企业、制造业龙头与科研 院所共建，聚焦工艺设计、工厂规划、产线仿真、数字装备等关键领域强化协同创新，打造贯穿"设备—产线—工厂"的全生命周期工业软件体系和数字工厂 底座。 近年，吴中区聚力发展"机器人+人工智能"产业集群，推动软硬件协同发展，工控系统、人工智能垂域大模型、具身智能大小脑等核心领域发展迅速，落地 哈工大苏州研究院、赛迪苏州研究院、信通院江苏分院、浙大苏州智能制造研究院等大院大所，打造了江苏省智能机器人技术创新中心、苏州市具身智能机 器人综合创新中心、苏州工 ...

智通财经APP获悉，信达证券发布研报称，回顾计算机板块全年至今走势，受到924行情延续、 DeepSeek等现象级催化、基本面结构性改善等影响，总体呈现"年初蓄势、二月冲高、年中调整、九月 突破"四阶段。估值维度，计算机板块PS水平当前处于历史相对高位区间。受AI产业趋势影响，板块营 收规模的"扩容天花板"正持续上移，这种营收端的高成长性为PS估值提供了强支撑，体现市场对其在产 业变革中"营收增量空间"的乐观预期。展望未来，AI应用端相关企业受益于算力扩容提质、模型能力快 速进步等影响，有望享受突出的估值弹性。 信达证券主要观点如下： AI+Coding 智能驾驶 VLA架构作为语言模型赋能智驾的最新技术之一，将物理世界的视觉信息转化为语言可理解的逻辑， 进而指导车辆操作。元戎启行CEO周光阐释其技术逻辑：自动驾驶正从"弱专家系统"向"强专家系统"演 变，VLA架构顺应这一趋势，不仅适用于汽车，还可拓展至机器人等移动设备，目标是实现L5级全域 自动驾驶。与此同时，年初各大主机厂发起的智驾平权战略正在快速提升高速NOA和城市NOA的普及 与渗透，盖世汽车数据，2023年1-8月至2025年1-8月，高速NOA标 ...

Summary of Key Points from the Conference Call Industry Overview - The focus is on the **Industrial Technology and Mobility** sector, specifically the rise of **Physical AI** as a transformative technology in industrial markets [1][12][49]. Core Insights and Arguments - **Growth Potential**: There is a projected **double-digit percentage growth** in AI-enabled edge devices, including Autonomous Mobile Robots (AMR) and robotics, as well as in design/simulation software driven by generative design [2][28]. - **Capital Expenditure Growth**: The adoption of Physical AI is expected to contribute a **mid-single digit percentage** to annual customer capital expenditure growth as capital investments replace labor [2][36]. - **Data Requirements**: Industrial AI requires substantial amounts of data, categorized into real-world data from intelligent devices and simulated data for design stages [3][49]. - **Cloud vs. Edge AI**: Both cloud and edge AI are essential, with cloud offering scalability and cost advantages, while edge AI addresses latency and security concerns [4][49]. - **Robotics Adoption**: Task-specific automation and intelligent robotic arms are deemed optimal for over **90% of manufacturing tasks**, indicating significant potential for AI in traditional automation [5][49]. - **M&A Activity**: Recent mergers and acquisitions, such as Siemens/Altair, are integrating simulation capabilities with real-time data to enhance AI adoption in industrial settings [3][49]. Stock Implications - A basket of **28 global stocks** has been identified as beneficiaries of the Physical AI trend, with companies like Siemens, Rockwell Automation, and ABB highlighted for their exposure to industrial control and design/simulation software [6][22][19]. Additional Insights - **AI Adoption in Industry**: AI adoption in industrial applications is still in its infancy, with only **15%** of advanced industrial customers using AI in supply chain management and **13%** in manufacturing [48][49]. - **Future Projections**: The installed base of industrial robots is expected to grow significantly, with projections suggesting a **CAGR of over 20%** over the next decade, driven by AI's ability to displace manufacturing tasks [28][29]. - **Strategic Considerations**: Companies are encouraged to focus on pricing for value and adapting to new SaaS models that reflect AI-driven efficiencies [63][64]. Conclusion - The era of Physical AI presents substantial opportunities for growth and innovation in the industrial sector, with significant implications for capital expenditure, robotics adoption, and stock performance in related companies. The integration of AI into industrial processes is expected to enhance efficiency and productivity, marking a pivotal shift in how industries operate [1][49][63].

Overview - The article discusses the learning curves associated with various 3D industrial software, highlighting user experiences and preferences based on a survey of 327 professionals in the mechanical, mold, and additive manufacturing sectors [3][4]. Ranking Summary - CAXA 3D is rated as the easiest to learn with a score of 2 for initial difficulty and 3 for mastery, praised for its user-friendly Chinese interface [3]. - SolidWorks follows with a score of 2.5 for initial difficulty and 4 for mastery, noted for its extensive tutorials [3]. - Fusion 360 has a score of 3 for initial difficulty and 3.5 for mastery, recognized for its cloud collaboration features [3]. - Siemens NX and CATIA both score 4 and 5 respectively for initial and mastery difficulty, with CATIA being particularly challenging for newcomers [3]. Learning Dimensions - Language accessibility is crucial, with CAXA 3D fully localized in Chinese, while CATIA's translations are often criticized for being poorly done [4]. - Command logic varies significantly, with CAXA 3D offering a straightforward interface compared to NX's complex multi-level menus [4]. - Resource availability is highlighted, with CAXA 3D having a wealth of Chinese tutorials and community support, while CATIA struggles with limited resources [6][8]. Community and Training - CAXA 3D boasts a vibrant community with numerous online groups and training centers across China, making it accessible for learners [7][8]. - In contrast, NX and CATIA have limited training resources concentrated in major cities, making it difficult for learners in smaller cities [7]. Industry Application - CAXA 3D is favored in manufacturing settings due to its integration with national standards and ease of use, while CATIA is preferred in automotive industries for its advanced modeling capabilities [9]. - Educational institutions are increasingly adopting CAXA 3D for teaching, with significant textbook sales indicating its popularity among students [10]. Cost Considerations - Time costs are significant, with CAXA 3D requiring an average of 40 hours to reach competency, compared to 110 hours for NX [11]. - CAXA offers a free educational version, while CATIA and NX have high costs associated with their licenses, making CAXA a more attractive option for small businesses [12]. Future Outlook - The integration of AI and cloud technologies is expected to further ease the learning curve for 3D software, with CAXA already implementing AI features [14]. - Educational strategies are recommended to combine CAXA for foundational skills and advanced software for specialized training [14]. Conclusion - CAXA 3D stands out in terms of user-friendliness, resource availability, and cost-effectiveness, making it a preferred choice for many in the industry [15].

The Stock Exchange of Hong Kong Limited and the Securities and Futures Commission take no responsibility for the contents of this Application Proof, make no representation as to its accuracy or completeness and expressly disclaim any liability whatsoever for any loss howsoever arising from or in reliance upon the whole or any part of the contents of this Application Proof. Application Proof of BEIJING DELTAPHONE TECHNOLOGY CO., LIMITED 北京德風新征程科技股份有限公司 (the "Company") (A joint stock company incorporated in t ...

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2025 Performance Highlights - Q4 underlying orders growth was 6%[7] - Full year underlying sales growth was 3%, impacted by softer book-to-ship in Europe and China[7] - Adjusted EPS for 2025 was $6.00, a 9% year-over-year increase[7] - Free cash flow reached $3.24 billion, up 12% year-over-year[7] - Annual Contract Value (ACV) was $1.56 billion, a 10% increase year-over-year[7] 2026 Guidance - Sales growth is projected at approximately 5.5%, with underlying growth of around 4%[7] - Adjusted segment EBITA margin is expected to be approximately 28%[7] - Adjusted EPS is guided to $6.35 – $6.55[7] - The company plans to return approximately $2.2 billion to shareholders through share repurchases of around $1 billion and a 5% dividend per share increase[7] Regional Outlook - Sustained momentum is expected in North America, India, and the Middle East, offset by continued softness in Europe and China[13] - China is expected to be approximately flat in terms of underlying sales growth[27] Financial Details - The company anticipates free cash flow between $3.5 billion and $3.6 billion[30] - Price is expected to contribute approximately 2.5 percentage points to sales growth[30] - The tax rate is projected to be around 21.5%[30]

Core Insights - AVEVA, a global leader in industrial software, will showcase its AI-driven industrial intelligence platform, CONNECT, at the 2025 ADIPEC exhibition, aimed at helping energy companies achieve digitalization and sustainable operations [1] - The platform covers the entire lifecycle from design, construction, operation to maintenance through augmented reality and virtual reality demonstrations [1] - Jesus Hernandez, Senior Vice President of AVEVA, stated that the company's technology is facilitating the industry's transition to net-zero [1] - During the exhibition, AVEVA will present innovative results of digital twin and AI integration at booth 4410 in Hall 4 [1]

Core Insights - Siemens and Capgemini are expanding their strategic partnership to co-develop AI-native digital solutions for product engineering, manufacturing, and operations, focusing on 16 high-impact capability areas to enhance production efficiency, time-to-market, quality, and sustainability [1][2] Partnership Details - The collaboration aims to address long-standing challenges in integrating IT and operational systems by leveraging technologies such as industrial AI, digital twins, and next-generation automation [2] - The partnership will utilize orchestrated AI agents to enhance collaboration across engineering and manufacturing silos [2] Leadership Statements - Siemens' CEO Cedrik Neike emphasized the partnership's role in guiding customers through digital transformation with speed and precision, while Capgemini's CEO Aiman Ezzat highlighted the ambition to help clients achieve operational efficiency and tangible business impact [3] Client Case Studies - For Airbus, the partnership is focused on decarbonizing four industrial locations, targeting a 20% reduction in energy consumption and an 85% reduction in Scope 1 and 2 emissions by 2030, utilizing energy system twins for optimal decarbonization roadmaps [3][4] - In the case of Sanofi, the collaboration is standardizing production processes and accelerating the rollout of Manufacturing Execution Systems (MES), resulting in a 70% reduction in review time and an 80% decrease in deviations [4] - For GravitHy, the partnership aims to digitalize industrial processes, targeting a hydrogen production cost reduction of up to 10% [6] Industry Focus - The joint initiative will concentrate on key industries such as aerospace, automotive, and life sciences, as well as emerging markets like hydrogen and water/wastewater [7] - Capgemini plans to expand its pool of certified experts to enhance its Siemens technology capabilities [7] Company Background - Siemens generated revenue of €75.9 billion and net income of €9.0 billion in fiscal 2024, employing around 312,000 people globally [10] - Capgemini reported global revenues of €22.1 billion in 2024, with a workforce of 420,000 team members across more than 50 countries [11]

Summary of Key Points from the Conference Call Industry Overview - The conference call discusses the **15th Five-Year Plan (FYP)** in China, focusing on **technology and consumption goals** as part of a broader economic strategy aimed at achieving balanced growth [1][5]. Core Insights and Arguments - **Shift in Economic Strategy**: The FYP emphasizes a transition from a supply-centric approach to a more balanced growth model, highlighting the importance of household consumption [5][7]. - **Efficiency as a Goal**: Total Factor Productivity (TFP) gains are now a key performance metric, indicating a focus on efficiency rather than merely scaling production [7]. - **Increased Household Consumption**: The plan explicitly aims for a higher share of household consumption, marking a significant policy shift [7]. - **Wage Share and Social Welfare**: There is a noted increase in wage share and a commitment to optimizing social welfare systems to enhance consumption propensity [7]. - **Public Service Spending**: The plan includes provisions for modestly higher public service spending, which is expected to support consumption growth [7]. - **Consumption Subsidies**: The introduction of consumption subsidies, alongside the removal of regulatory bottlenecks (e.g., auto license plates), is aimed at stimulating demand [7]. - **AI and Technology Integration**: The strategy includes the development of AI as infrastructure, with plans for unified national computing power networks and broad integration of AI into the real economy [7]. - **Supply Chain Improvements**: The FYP addresses key supply chain bottlenecks in sectors such as semiconductors, industrial software, and advanced materials through coordinated campaigns [7]. - **Expansion of Strategic Sectors**: The definition of "strategic emerging sectors" has been broadened to include areas like quantum computing and 6G networks, indicating a forward-looking approach to technology development [7]. Additional Important Points - **Gradual Reflation**: The economic outlook suggests a gradual reflation process, with expectations of a negative GDP deflator and sub-4% nominal GDP growth in 2026, turning mildly positive from 2027 [5][7]. - **Policy Execution**: While the goals are ambitious, the execution of these policies is expected to be gradual, reflecting a cautious approach to economic reform [1][5]. This summary encapsulates the key themes and insights from the conference call, providing a comprehensive overview of the strategic direction outlined in China's 15th Five-Year Plan.