企业成长的背后，是杭州深厚的产业底蕴与战略支持。这座城市为企业提供了产业链配套、技术人 才等先天优势，而在中策橡胶关键转型期，杭州国资的战略入股、产业政策的精准扶持，更为其突破发 展瓶颈注入强劲动力。未来，企业依托现有的品牌、技术、市场、人才等方面的优势，通过增加投资、 技术创新和资源整合，还会进一步扩大其在国内市场和国际市场的份额。 向"新"要发展 新质生产力激活发展动能 6月5日上午，杭企中策橡胶集团股份有限公司（下称"中策橡胶"）在上海证券交易所上市。本次上 市，中策橡胶的发行价为46.50元/股，发行数量为8744.8560万股，预计募资总额约40.66亿元。该股开 盘报57.00元，截至收盘报49.68元，总市值434.44亿元。 这是今年截至目前，A股市场最大规模的IPO项目。这场资本盛宴不仅是企业发展的重要里程碑， 也证明了传统制造业在创新驱动下的无限潜力，展现了杭州这座城市在产业转型中的战略定力与创新智 慧。 67年风雨历程 企业与城市共成长 中策橡胶的发展史，就是一部杭州工业的奋斗史。中策橡胶是国内最早从事轮胎制造的企业之一， 其前身为1958年创建的杭州海潮橡胶厂，经过67年的发展，企业已 ...

Investment Rating - The report indicates a strong investment outlook for the AI large model industry, particularly highlighting the rapid growth and commercialization of large model applications in China [6]. Core Insights - The report emphasizes that the dual drivers of policy and technology are accelerating the development of China's large model industry, with significant investments from state-owned enterprises and government sectors [7][9]. - The demand for integrated large model machines is surging due to challenges in application deployment, with the market expected to reach a scale of hundreds of billions [30][36]. - DeepSeek is highlighted as a leading open-source large model, achieving performance levels comparable to top models like OpenAI's o3 and Gemini 2.5 Pro, which has garnered significant attention in the market [11][12]. Summary by Sections 1. Policy and Technology Driving Large Model Industry - The report outlines a trend where AI policies are increasingly focused on industry applications, with multiple ministries issuing guidelines to empower AI large models across various sectors such as healthcare and education [10]. - A comprehensive review of policies from 2024 to 2025 shows a systematic push from national to local levels, with cities like Beijing and Shanghai implementing action plans for large model development [9][10]. 2. Challenges and Demand for Integrated Machines - The report identifies several challenges in deploying large models, including complex software stack deployment, high computational requirements, and data privacy concerns, which are driving the demand for integrated large model machines [30][31]. - The market for integrated large model machines is projected to grow significantly, with state-owned enterprises and government agencies being key customers due to their need for localized and private deployments [36][39]. 3. Case Studies and Market Examples - The report provides examples of successful deployments of DeepSeek in various sectors, including energy and finance, showcasing its effectiveness in enhancing operational efficiency [25][26]. - It highlights the rapid adoption of integrated large model machines by numerous enterprises, with a focus on their ability to simplify deployment and reduce operational costs [36][41]. 4. Future Trends and Innovations - The report anticipates that future developments in integrated large model machines will focus on lightweight deployment and high integration, with advancements in model compression and dynamic inference optimization [57][59]. - It also discusses the potential integration of emerging technologies such as quantum computing and brain-like intelligence to enhance the capabilities of large model machines [63][64].

Core Insights - The 2025 CCF Youth Elite Conference (YEF2025) is being held in Zhuhai, Guangdong, focusing on diverse development paths in artificial intelligence (AI) [1] - The conference features various sessions including keynote speeches, forums, and specialized discussions, emphasizing the need for foundational breakthroughs and original innovations in AI [1][2] Group 1: Conference Overview - The conference is attended by over 1,000 young experts and scholars from the computer field, discussing the future of AI [1] - The event includes 7 keynote reports, 5 thought showcase reports, 2 main forums, and 22 specialized forums [1] Group 2: Key Themes and Innovations - The conference theme "Intelligent New Paths" reflects the current state of AI, highlighting the transition from lagging behind to achieving parity in certain areas [2] - The need for leading innovations in AI is emphasized, particularly in light of the maturity of large language models [2] Group 3: Research and Development Focus - The Guangdong-Hong Kong-Macao Greater Bay Area is positioned as a high-level open frontier for technology development, with significant policies already implemented [2] - The Guangdong Provincial Institute of Intelligent Science and Technology is focusing on brain science and brain-like intelligence, establishing research centers in cognitive neural networks, brain-like computing systems, and intelligent biomedicine [2] Group 4: Class Brain Intelligence - Academician Zhang Xu discusses class brain intelligence as a crucial future industry direction, aiming to overcome traditional computing limitations by mimicking biological brain mechanisms [3] - Class brain intelligence emphasizes characteristics such as parallelism, integrated storage and computation, and plasticity, which are essential for processing unstructured data efficiently [3] Group 5: Technological Advancements - Professor Ye Le from Peking University introduced a three-dimensional storage-computation integrated AI chip to address challenges like the diminishing effectiveness of Moore's Law and increasing computational demands [6] - The long-term vision includes integrating this chip technology into robots, suggesting a future where the number of robots could exceed that of humans [6]

Core Viewpoint - The article discusses advancements in bionic robotics and intelligent control, emphasizing the need for innovation in robot design to achieve better energy efficiency and functionality, particularly in humanoid robots [2][20]. Group 1: Bionic Robotics and Intelligent Control - The "2025 Bionic Robot and Intelligent Control Forum" held in Hangzhou attracted nearly 400 participants and over 10,000 online viewers, highlighting the growing interest in bionic robotics [2]. - The forum featured a keynote report by Professor Qian Zhihui from Jilin University, focusing on the principles and technologies behind bionic tensile and compressive robots [2]. Group 2: Current Challenges in Humanoid Robotics - Humanoid robots are currently in a "showcase-first" stage, with significant gaps in practical application, including issues with safety, arm manipulation, and high energy consumption [4]. - The Cost of Transport (COT) metric indicates that humanoid robots have much higher energy consumption compared to humans, with values such as 5 for Boston Dynamics' Atlas and 1.6 for Honda's Asimo, while humans have a COT of only 0.05 [5]. Group 3: Analysis of Robotic Limitations - Three main issues are identified in humanoid robots: 1. Material composition leads to poor safety in human-robot physical contact due to rigid components [6]. 2. Joint structures are simplified and require complex control, increasing energy consumption [6]. 3. Power systems are inefficient due to multiple energy conversions, unlike the integrated system found in human muscles [6]. Group 4: Innovations in Bionic Robotics - The concept of "Layagrity" is introduced, which combines tensile and compressive elements to create a new design for advanced humanoid robots [7]. - The first generation of bionic tensile robots has been developed, achieving walking speeds of 2.0-4.5 km/h with a COT of 0.069-0.107, significantly lower than traditional humanoid robots [11]. Group 5: Advances in Dexterous Manipulation - The development of bionic hands faces challenges due to the trade-off between rigid and soft hands, necessitating innovative solutions [14]. - A new three-dimensional dynamic X-ray imaging system has enabled the study of human hand biomechanics, leading to improved designs for bionic hands that replicate human dexterity [14]. Group 6: Future Directions in Robotics - The research team aims to create a modular bionic system that incorporates human-like movement characteristics, focusing on dynamic stability and high precision in robotic arms and hands [20]. - The ultimate goal is to overcome existing limitations in humanoid robotics by integrating biological design principles to enhance movement intelligence and adaptability [20].

证券代码：002195 证券简称：岩山科技 上海岩山科技股份有限公司 投资者关系活动记录表 编号：2025-001 | 投资者关 | □ 特定对象调研 □ 分析师会议 | | --- | --- | | 系活动类 | □ 媒体采访 √ 业绩说明会 | | 别 | □ 新闻发布会 □ 路演活动 | | | □ 现场参观 | | | 其他 □ | | 活动参与 | 线上参加业绩说明会的投资者 | | 人员 | | | 时间 | 2025 年 5 月 15 日（周四）下午 15:00~16:30 | | 地点 | 公司通过上海证券交易所上证路演中心（网址：https://roadshow.sseinfo.com/） | | | 采用网络文字互动的方式参加 2025 年上海辖区上市公司年报集体业绩说明会 | | 形式 | 网络文字互动方式 | | 上市公司 | 董事长：叶可先生 | | 接待人员 | 副董事长、总经理：陈于冰先生 | | 姓名 | 董事、常务副总经理：陈代千先生 | | | 董事、副总经理：黄国敏先生 | | | 董事、董事会秘书：张未名先生 | | | 财务总监：喻佳萍女士 | | | 独立董事：蒋 ...

Core Insights - The development of brain-like intelligence (BI) is seen as a next-generation artificial intelligence (AI) that relies on exploring the computational capabilities of the human brain [2][3] - The industry is progressing through an interconnected research and development system that includes brain-machine interfaces, algorithms, intelligent chips, and general brain-like computers [2][4] - China is positioned at the forefront of the BI industry due to its rich application scenarios and a well-established industrial chain, which offers a first-mover advantage [5] Industry Development - The Guangdong Provincial Institute of Intelligent Science and Technology has successfully built the world's first brain-like computing system with a scale of 10 billion neurons, equivalent to about one-ninth of the human brain [3] - The innovation chain of BI encompasses biological research on brain perception and cognition, and it is essential for the industry to advance through collaboration between the innovation chain and the industrial chain [4][6] - The potential applications of BI in healthcare include decoding Chinese sentences and tones through brain-machine interfaces, as well as personalized sleep regulation through real-time brainwave analysis [5] Challenges and Opportunities - The BI industry faces challenges in computing power, investment, and talent cultivation, which need to be addressed for further development [7] - There is a need for software development that can convert brain data into mathematical models and run them on chips to produce functional outputs [7] - The industry requires strategic investments and enhanced talent training, particularly in management roles, to support its growth and innovation [7]

Core Viewpoint - The economic performance of Yuhang District in Hangzhou, Zhejiang Province, is highlighted, showcasing a GDP of 99.147 billion yuan with a year-on-year growth of 7.5%, surpassing national, provincial, and municipal averages, indicating its role as a "barometer" for regional economic trends [2] Group 1: Innovation - Yuhang's industrial economy showed resilience with a 5.9% growth in industrial added value, driven by high-end equipment manufacturing (11.5% growth) and high-tech industries (6.1% growth) [3] - The district had four enterprises listed in the 2024 national average efficiency ranking, the highest among all districts in China [3] - The service sector also performed well, with a 7.7% increase in added value, and the digital economy's core industries maintained their leading position in Zhejiang [3] Group 2: Policy Support - Yuhang's retail sales grew by 8.1%, with fixed asset investment increasing by 3.5% and total imports and exports rising by 38%, driven by effective policy measures [5] - The district implemented various policies to stimulate consumption, including subsidies for replacing old consumer goods and promoting activities for automotive and agricultural products [5] - The proactive approach in policy-making has led to a significant increase in retail sales and investment, contributing to economic recovery [5] Group 3: Business Environment - Yuhang saw the establishment of 15,200 new market entities, a 25.7% increase, and five new listed companies, indicating a vibrant business environment [6] - The district has developed a "one-stop service" model to support businesses, including over 300 service stations to assist enterprises [6] - Initiatives like the "Yushang Outbound" resource package provide extensive support for companies, enhancing their competitiveness in a complex external trade environment [6][7] Group 4: Future Outlook - Yuhang aims for a GDP of 335.567 billion yuan with a growth target of 6.0% for 2024, positioning itself as a model for county-level economic advancement in Zhejiang [8] - The district's ability to maintain high-quality economic growth amidst external challenges will be closely monitored [8]

中科院院士蒲慕明表示，我们要借鉴大脑的结构和计算特点，让人工智能突破算力、数据和参数规模的限制，实现更高级别的通用人工智能。 自上世纪80年代类脑计算的概念被首次提出起，有关类脑人工网络、类脑机器学习、类脑芯片等领域的技术研究不断涌现。而随着算力、芯片、算法三要素 的不断突破，以及多学科交叉融合的逐步深入，类脑智能发展正迎来新的发展契机。 4月18下午，在2025全国类脑智能产业创新发展推进会上，类脑智能产业创新发展联盟发起成立，类脑智能未来产业基金矩阵在会上首次亮相。 类脑智能未来产业基金矩阵由上海未来产业基金、博康共赢基金、道禾基金、杨浦科创集团等10家投资机构联合发起，将聚焦类脑智能产业新赛道，支持类 脑产业前沿技术研究、落地与应用，完善类脑产业布局，推动区域类脑产业发展。 于2017年就在全国率先开展类脑智能布局的上海，通过深化基础原创理论研究、加快关键核心技术攻关、承接国家重大战略任务等举措，在类脑计算芯片、 类脑视觉系统研发等领域取得了重要成果。 当前，规模定律（Scaling Law）已将达到算力和数据的瓶颈，人工智能的性能提升将会放缓。新算法与人工网络模型的进一步优化，借鉴低功耗但复杂而 精巧 ...

Core Insights - The development of robotics technology in China has made significant progress, reducing the gap with international advanced levels [1] - Over the past three years, China's industrial robot loading capacity has reached over 50% of the global total [1] - The establishment of humanoid robot factories serves as a core technological foundation, integrating intelligent algorithms to compensate for hardware system deficiencies [1] Industry Developments - The core technological foundation combines brain-like intelligence, neuroscience, and artificial intelligence technologies, creating a significant competitive barrier [1] - The general factory can quickly produce low-cost and relatively high-performance robotic systems to support the industrial and agricultural sectors in China [1]