Core Viewpoint - The Shanghai Financial Regulatory Bureau and the Shanghai Science and Technology Commission have issued guidelines to develop a high-quality technology insurance system that aligns with the construction of an international technology innovation center in Shanghai [1] Group 1: Framework and Objectives - The guidelines propose a comprehensive insurance development framework that covers the entire chain of technological innovation and the full lifecycle of technology enterprises [2] - The initiative aims to inject stability into key areas such as technological breakthroughs, industrial upgrades, and international expansion of enterprises [2] - The guidelines emphasize the importance of supporting major scientific research tasks and nurturing future industries through technology insurance [2] Group 2: Product and Capability Innovation - The introduction of "Shanghai Science Points" aims to explore precise pricing in insurance and promote the deep application of artificial intelligence in the insurance sector [2] - Large insurance institutions are encouraged to play a leading role in building specialized products, professional talent, and dedicated systems [2] - The guidelines advocate for the development of specialized regulatory methods that align with technology insurance [2] Group 3: Partnership and Long-term Vision - The guidelines focus on creating a "partnership" between the insurance industry and future industries, emphasizing a win-win process and the importance of long-term commitment to innovation [3] - Shanghai's technology insurance initiatives began in 2010, with the establishment of a tripartite risk-sharing model [3] - As of the first quarter of this year, Shanghai's technology insurance provided risk coverage of 2,572 billion yuan, marking a 16% year-on-year increase [3] Group 4: Ecosystem Development - The guidelines promote an "ecological, systematic, and international" approach to provide comprehensive risk protection and development engines for technological innovation [4] - The development emphasizes deep collaboration among government, insurance institutions, research institutes, and enterprises [4] - A technology insurance expert database and data-sharing mechanisms are proposed to enhance standardized evaluations [4] Group 5: Systematic and International Integration - The policy aims to cover the entire chain of technological innovation and the lifecycle of technology enterprises, focusing on key stages such as research and development, pilot testing, and industrialization [5] - The guidelines leverage Shanghai's international reinsurance center to provide cross-border risk defense capabilities for enterprises expanding globally [5] - The introduction of special risk transfer tools and the integration of insurance and loan services are aimed at creating a sustainable and manageable technology insurance ecosystem [5]

Core Viewpoint - The article discusses the 2025 Key Technology R&D Plan for "Brain-like Intelligence" projects in Shanghai, emphasizing the importance of innovation and collaboration in advancing brain-inspired technologies and applications. Group 1: Brain-like Intelligent Product Development - Direction 1 focuses on developing brain-like fusion visual sensors aimed at XR and intelligent terminal applications, targeting a resolution of at least VGA, an equivalent frame rate of no less than 1000 frames, and a perception power consumption of no more than 50mW [2][3] - Milestone 1 includes completing chip testing and application validation with at least two enterprise users [2] - Milestone 2 aims for mass production with a target of selling no less than 100,000 units [3] Group 2: Common Technology R&D Service Platform Construction - Direction 1 aims to establish a public service platform for brain-like intelligence applications, creating at least three industry data sets and providing open data services exceeding 5000 hours [13] - The platform will support the development and validation of new models and algorithms, with a service revenue target of no less than 1 million yuan [13] - The execution period for this initiative is from August 1, 2025, to July 31, 2027 [14] Group 3: Disruptive Technology Research - Direction 1 involves exploring new principles and methods for brain-inspired intelligence, focusing on algorithm and model development [18] - The execution period for this research is also from August 1, 2025, to July 31, 2027 [19] - Funding for this direction is capped at 100 million yuan for up to three projects, with a required co-funding ratio of at least 2:1 [19] Group 4: Application and Submission Requirements - Applicants must be registered entities in Shanghai with the capability to implement projects [27] - The application process is conducted online, with a submission window from June 20, 2025, to July 9, 2025 [35] - All applicants must adhere to research integrity and ethical guidelines [27][28]

Core Concept - The article discusses the rapid development and potential of brain-like intelligence (neuromorphic intelligence) in China, highlighting its distinction from artificial intelligence and brain simulation technologies [1][3]. Group 1: Development and Characteristics of Neuromorphic Intelligence - Neuromorphic intelligence is not a simple imitation of the brain but is designed to mimic the brain's structure and functioning, enabling intelligent systems to perceive, understand, learn, and make decisions [3][4]. - The field has gained momentum due to advancements in neuroscience and related technologies, with significant progress made in the last decade, positioning China as a global leader in this domain [3][4]. - Neuromorphic intelligence differs from artificial intelligence and brain simulation in definitions, technical principles, and application scenarios, indicating a unique development path [3][5]. Group 2: Applications and Future Prospects - Neuromorphic intelligence is in its early application stage, with potential uses in various fields, particularly in medicine and communication technology, supported by national policies promoting interdisciplinary research [5][6]. - Breakthroughs in brain-computer interface technology are expected to enhance memory and improve sleep quality, indicating transformative impacts on human health [5][6]. - The future may see widespread adoption of compact, energy-efficient neuromorphic computers in households and workplaces, fundamentally changing lifestyles and making intelligent services more accessible [5][6]. Group 3: Economic and Social Implications - The development of neuromorphic intelligence is anticipated to position China as a leader in intelligent design and manufacturing, benefiting various industries including IoT and telecommunications [6]. - China's large population and diverse application scenarios provide a robust foundation for the growth of neuromorphic intelligence, with significant demand in areas like pain management [6]. - The emphasis on independent intellectual property rights in neuromorphic intelligence development reflects a commitment to domestic innovation while remaining open to international collaboration [6].

Group 1 - The core viewpoint emphasizes the importance of developing the marine economy and building a strong marine province in Guangdong, which is seen as crucial for both the province and the nation [2][3] - Guangdong has established a Marine Strong Province Construction Work Committee, led by the provincial party secretary, to coordinate efforts across various departments to promote marine economic development [1][3] - In 2024, Guangdong's marine GDP reached 2.002 trillion yuan, maintaining its position as the largest marine economy in China for 30 consecutive years, contributing 27% to the region's nominal economic growth [2][3] Group 2 - The newly passed "Regulations on Promoting High-Quality Development of the Marine Economy" will take effect on July 1, 2023, marking a significant step in Guangdong's efforts to enhance its marine economy [3][4] - The marine economic structure in Guangdong shows a high proportion of the tertiary industry at 65.6%, which is 6 percentage points higher than the national average, indicating a need for better balance with primary and secondary industries [3] - The current transition in China's marine economy towards deep-sea resource development presents new opportunities for Guangdong, which is encouraged to leverage technology and innovation in marine sectors [3][4]

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]