南都讯 2025年，"十四五"规划圆满收官。这一年，外部环境复杂多变，全球贸易增长放缓。压力之 下，考验的是一座城市的定力，也检验着一套制度的成色。记者从深圳海关获悉，2025年深圳外贸顶压 前行、表现亮眼——全年进出口总额达4.55万亿元人民币，同比增长1.4%，规模再创历史新高，继续位 居内地城市首位，出口实现"33连冠"。 一个数字，意味着什么？看份额，更看担当。 从体量看，深圳进出口规模连续6年保持正增长，占全国进出口总额的10%；占广东全省比重达48%， 对全省增长贡献率达15.5%，在稳住外贸基本盘中发挥"压舱石"作用。 从结构看，深圳出口规模长期保持领先，全年出口2.74万亿元；进口更是值得关注，全年进口1.81万亿 元，增长8%，对全省进口增长贡献率达53.2%，这意味着深圳不仅"卖得出去"，更"接得住、用得好"， 以开放的需求端，推动全球资源要素高效流动。 有进出口实绩企业6.23万家，同比增加16% 外贸的活力，来自企业。 过去一年，深圳有进出口实绩企业6.23万家，同比增加16%，新增超8600家，主体规模持续扩容。背 后，是一套不断适配企业需求的监管与服务体系。 深圳市百穗黄金智造有限 ...

炒股就看金麒麟分析师研报，权威，专业，及时，全面，助您挖掘潜力主题机会！ （来源：科技行者） 这项由上海交通大学、上海人工智能实验室、南京邮电大学、复旦大学和博世公司联合开展的研究于 2025年11月发表在计算机视觉领域顶级会议上，论文编号为arXiv:2511.16175v1。研究团队的核心成员 包括杨毅、李学琦、陈一阳等多位来自不同机构的研究者，其中上海交大的邓志杰教授担任通讯作者。 有兴趣深入了解的读者可以通过该论文编号查询完整研究内容。 想象一下，如果你的机器人助手在帮你收拾房间时，能够像经验丰富的管家一样提前"看到"下一步会发 生什么——当它伸手去拿桌上的杯子时，它已经能预见到杯子被放到洗碗机里的画面。这种神奇的能力 不再是科幻电影中的情节，上海交大的研究团队刚刚让这个想法变成了现实。 目前的机器人就像刚学会走路的孩子，它们只能看到眼前的东西，然后做出相应的动作。但问题在于， 这种"走一步看一步"的方式让机器人的学习效率很低，就好比你试图通过只看一张张静态照片来学习如 何骑自行车一样困难。研究团队发现，如果让机器人能够预见未来的画面，就像给它装上了"预言眼 镜"，它的学习能力会大幅提升。 然而，让机 ...

Core Viewpoint - The article argues that China is not "in trouble" as some in the U.S. claim, and the U.S. should abandon the notion of "defeating China" [1] Group 1: Economic and Trade Relations - The article highlights the U.S.'s initial confidence in defeating China in trade, which has been proven to be misplaced as China has demonstrated its strength in this area [1] - Despite the GDP gap, China leads significantly in critical future-oriented sectors such as rare earth production, solar capacity, electric vehicles, and industrial robotics [2] - A recent report from the U.S.-China Economic and Security Review Commission states that China is at the forefront of quantum communication and making rapid advancements in quantum computing and sensing [2] Group 2: Technological Advancements - China is making significant strides in chip technology, with reports indicating efforts to master lithography technology [2] - The article emphasizes China's advancements in electric vehicles, clean energy, and robotics, which are crucial for future competitiveness [2] Group 3: Military Capabilities - While the U.S. maintains the strongest military globally, China is rapidly catching up, particularly in naval capabilities with its latest aircraft carriers [3] - The article acknowledges China's economic and demographic challenges but notes that the government's "14th Five-Year Plan" is addressing these issues [3] Group 4: Soft Power and Perception - China's soft power is gaining traction in the U.S., as evidenced by the popularity of platforms like TikTok and the positive experiences of American tourists in China [3] - The article suggests that Americans are beginning to reassess China's global standing, indicating a shift in perception [3] - The article has sparked positive reactions among American netizens, advocating for more cooperation with China, while also drawing attention from Japanese netizens who criticize their own right-wing views [3]

Core Insights - The article highlights the rapid advancements in technology expected by 2026, including emotional AI, wearable health devices, renewable energy innovations, and more, which are set to transform daily life and work environments. Group 1: Emotional AI - The next generation of emotional AI assistants is surpassing traditional ones like Siri and Alexa by understanding human emotions through tone, expression, and wording, providing personalized relaxation recommendations and enhancing customer care [2] - Emotional AI is becoming a partner in daily life, playing a significant role in mental health support and personal growth [2] Group 2: Wearable Devices - By 2026, wearable devices are expected to evolve into "life guardians," with smart skin patches monitoring hydration, stress hormones, and nutrition levels, while AI watches can predict heart disease risks days in advance [3] - These innovations are shifting healthcare from reactive treatment to proactive prevention [3] Group 3: Renewable Energy - New night-time solar panels will capture infrared radiation, allowing for continuous power supply even in darkness, while advancements in lithium-sulfur and solid-state battery technologies will enhance energy storage for electric vehicles [4] - 2026 may mark a historical turning point for the decline of fossil fuels as the dominant energy source [5] Group 4: Brain-Computer Interfaces - Brain-computer interface technology is moving from medical applications to everyday use, enabling paralyzed patients to control devices with their thoughts and enhancing work efficiency through instant data retrieval [6] - By 2026, these interfaces will be integrated into daily life, impacting prosthetics, rehabilitation, and augmented reality experiences [6] Group 5: Space Economy - The space economy is set to flourish, with suborbital flight prices dropping below $100,000 and companies developing zero-gravity hotels, indicating a new era of space exploration and commercialization [7] Group 6: AI in Education - AI-driven personalized education is emerging, adapting courses to individual learning styles and helping adults with career transitions, fundamentally reshaping educational approaches [9] Group 7: Quantum Computing - Quantum computing is expected to solve complex problems beyond the capabilities of classical computers, significantly reducing drug development timelines and optimizing supply chains [10] Group 8: Smart Cities - Cities will become smarter by 2026, with AI traffic systems alleviating congestion, IoT-enabled waste management, and predictive security systems enhancing urban living [11] Group 9: Robotics - Robotics will become ubiquitous in households and various work environments, with cooking robots, construction robots, and personal care robots transforming daily tasks [12][13] Group 10: Bioprinting - The bioprinting field is anticipated to achieve significant advancements, enabling the creation of disease models, personalized medicine, and potentially addressing organ donation shortages [14]

Financial Performance - In the third quarter of 2025, the total revenue was RMB 407 million, a slight decrease of 0.2% compared to RMB 408 million in the same period of 2024 [1] - The net loss for the third quarter of 2025 was RMB 100 million, an increase of 20.2% from a net loss of RMB 83.2 million in the same period of 2024 [1] Strategic Direction - 2025 is a critical year for RoboSense as it expands from lidar technology to a robotics technology platform [1] - The company has a clear path: the automotive business provides scale advantages and a technological foundation, while the robotics business contributes high growth [1] - The Robotaxi business opens up long-term growth potential, with a focus on chips, algorithms, and digital architecture to become a "global leading robotics technology platform company" [1]

Core Viewpoint - The recovery momentum of Chinese tech stocks is still in its early stages as China emerges as an AI superpower, attracting Western capital back to the market [1] Group 1: Investor Sentiment - Investors are eager to position themselves as their portfolios lack exposure to the Chinese AI trend [2] - Global investors have begun reallocating funds to some of China's largest and most liquid stocks, benefiting from recent policy stimulus and technological breakthroughs [3] Group 2: Market Comparisons - The recovery of Chinese tech stocks is at an earlier stage compared to the Nasdaq's growth, with lower price-to-earnings ratios compared to similar growth and profitability peers in the U.S. [4] Group 3: Foreign Investment Interest - U.S. investment firms managing global funds are increasingly interested in Chinese stocks, with investors from the Middle East, Southeast Asia, and Europe focusing on gaining exposure to China [5] - Middle Eastern investors seek stable long-term capital in China's digital economy, while European investors are drawn to the Chinese market due to a lack of local AI firms [6] Group 4: IPO Activity - The number of Chinese companies applying for IPOs in Hong Kong has reached a high level, covering various sectors including internet, software, AI, robotics, and tech supply chains [6] - Hong Kong IPO fundraising reached HKD 216 billion (approximately USD 27.8 billion) in the first ten months of this year, more than three times the amount from the same period last year [7] Group 5: Positive Outlook from Foreign Investment Banks - Despite a global tech stock pullback, several foreign investment banks are bullish on the Chinese stock market, citing advancements in the tech sector as a key reason [8] - Morgan Stanley predicts further gains in the Chinese stock market by 2026, with target prices for MSCI China Index, Hang Seng Index, and CSI 300 Index set at 90 points, 27,500 points, and 4,840 points respectively [9] - UBS anticipates another prosperous year for the Chinese stock market, driven by favorable factors including innovation, with a target for the MSCI China Index at 100 points, indicating a 14% upside from current levels [10]

Core Insights - The article discusses the development of RoboTron-Mani, a universal robotic operation strategy that overcomes the limitations of existing models by integrating 3D perception and multi-modal fusion, enabling cross-platform and cross-scenario operations [1][3][21]. Group 1: Challenges in Robotic Operations - Current robotic operation solutions face a "dual bottleneck": either lacking 3D perception capabilities or suffering from data set issues that hinder cross-platform training [2][3]. - Traditional multi-modal models focus on 2D image understanding, which limits their ability to interact accurately with the physical world [2][3]. - Single data set training leads to weak generalization, requiring retraining for different robots or scenarios, which increases data collection costs [2][3]. Group 2: RoboTron-Mani and RoboData - RoboTron-Mani is designed to address the challenges of 3D perception and data modality issues, achieving full-link optimization from data to model [3][21]. - The architecture of RoboTron-Mani includes a visual encoder, 3D perception adapter, feature fusion decoder, and multi-modal decoder, allowing it to process various input types and produce multi-modal outputs [5][7][9][10]. - RoboData integrates nine mainstream public datasets, containing 70,000 task sequences and 7 million samples, addressing key pain points of traditional datasets by completing missing modalities and aligning spatial and action representations [11][12][15][16]. Group 3: Experimental Results and Performance - RoboTron-Mani has demonstrated superior performance across multiple datasets, achieving a success rate of 91.7% on the LIBERO dataset, surpassing the best expert model [18][21]. - The model shows an average improvement of 14.8%-19.6% in success rates compared to the general model RoboFlamingo across four simulated datasets [18][21]. - Ablation studies confirm the necessity of key components, with the absence of the 3D perception adapter significantly reducing success rates [19][22]. Group 4: Future Directions - Future enhancements may include the integration of additional modalities such as touch and force feedback to improve adaptability in complex scenarios [23]. - There is potential for optimizing model efficiency, as the current 4 billion parameter model requires 50 hours of training [23]. - Expanding real-world data integration will help reduce the domain transfer gap from simulation to real-world applications [23].

点击下方 卡片 ，关注" 具身智能 之心 "公众号 作者丨 Jiahong Chen等 编辑丨具身智能之心 本文只做学术分享，如有侵权，联系删文 >> 点击进入→ 具身智能之心 技术交流群 更多干货，欢迎加入国内首个具身智能全栈学习社区 ： 具身智能之心知识星球 (戳我) ， 这里包含所有你想要的。 在机器人操控领域，" 通用化 " 与 " 轻量化 " 的矛盾长期制约着技术落地——现有视觉-语言-动作（VLA）模型虽能实现复杂任务推理，但因参数量庞大、计算需求 高，难以部署在移动机器人、嵌入式系统（如 Jetson Orin Nano）等资源受限设备上。 而由英属哥伦比亚大学、阿尔伯塔大学与小米汽车团队联合提出的 NanoVLA ，用 " 视觉-语言解耦融合+长短动作分块+动态路由 " 的创新架构，彻底打破这一困 境：既保留通用 VLA 模型的任务精度与泛化能力，又将推理速度提升 52 倍、参数量压缩 98%，首次实现 "在边缘设备上高效运行通用机器人策略" 的目标。 为什么要重构 VLA 模型的边缘部署逻辑？ 当前主流 VLA 模型陷入 "性能与效率不可兼得" 的困境：为实现跨任务泛化，模型通常依赖数十亿参 ...

Core Viewpoint - The article discusses the contradictions in the Trump administration's manufacturing repatriation policies, highlighting how tariffs and immigration policies are counterproductive to the goal of bringing manufacturing jobs back to the U.S. [1][2][4] Group 1: Policy Contradictions - Tariffs have increased the costs of raw materials and imported equipment for U.S. manufacturers, making it harder for them to expand [1][7] - New immigration policies may reduce the supply of skilled labor, exacerbating the shortage of workers in the manufacturing sector [1][10] - The administration's budget cuts threaten the subsidies necessary for companies to repatriate jobs, leading to an unstable subsidy environment [1][14] Group 2: Business Reactions - Business leaders express frustration over the lack of clarity in the "America First" policies, making it difficult for them to plan investments [1][7] - Companies like Ford have reported significant cost pressures due to tariffs, which hinder their ability to invest more in the U.S. [7][8] - The uncertainty surrounding tariffs and their potential continuation after the Trump administration creates a paralysis effect, preventing companies from approving repatriation projects [6][7] Group 3: Labor Market Challenges - There are currently over 400,000 manufacturing job vacancies in the U.S., particularly in high-tech fields like semiconductors and robotics [9] - New immigration policies, including increased fees for H-1B visas, may further complicate the ability of companies to hire skilled foreign workers [10][13] - Industry groups warn that the changes in immigration policy could undermine the talent pipeline necessary for rebuilding the manufacturing sector [12][13] Group 4: Funding and Investment Issues - The Trump administration has touted trillions in investment commitments from companies, but internal budget cuts have created uncertainty regarding subsidies that could stimulate further investment [5][14] - The White House has ordered a review of federal funding and loans, injecting additional uncertainty into the investment landscape [14] - The lack of a coherent strategy for funding and tariffs leaves companies confused about how to proceed with their manufacturing plans [14]

Core Viewpoint - Dongtu Technology (300353) does not directly produce humanoid robots but focuses on providing foundational technology support in the field of embodied robots [1] Group 1: Company Overview - The company's Hongdao operating system is involved in national major projects and possesses fully autonomous and controllable attributes [1] - Dongtu Technology's AUTBUS bus network is the only domestic bus technology that has received international standards certification [1] Group 2: Technological Capabilities - The combination of the Hongdao operating system and AUTBUS bus network can create a robotic electronic architecture with time-deterministic networks and deterministic computing capabilities [1] - This architecture supports the high safety, high performance, and high-quality development of embodied robots, providing autonomous and controllable foundational technology assurance [1]