文 | 听潮TI，作者 | 郭佳哿，编辑 | 张晓 智能驾驶已经走到新的现实拐点。 过去几年，它被定位为高端车型的核心卖点；但随着渗透率进入主流区间，行业焦点开始从PPT里的期 望值转向交付规模。能否真正让更多用户买得起、用得上，成为当下最直接的竞争锚点。 去年末，地平线举办了自己成立十年来的第一届技术生态大会，会上地平线创始人兼CEO余凯给出了新 目标：10万元的车将普遍实现城区NOA。 更早一些，去年年初Momenta创始人曹旭东也曾断言，2025年高阶智驾会规模起势，并在2026年触达10 万级市场。 对内，这是技术与成本的再压缩；对外，则意味着主动拥抱更大体量的普惠市场。 事实上，在能力下放这件事上，真正承担工程复杂度、成本压力和交付责任的，并非只有整车厂。 地平线与Momenta所代表的，是智能驾驶背后一条不被大众熟知但至关重要的供应链价值链：地平线依 托车规级芯片与工具链，试图通过软硬结合建立可复制的量产能力；Momenta以算法和数据驱动的渐进 式迭代路线，与车企深度绑定，推动高阶方案走向规模落地。 它们的角色，不只是技术提供方，更是推动智驾平权的核心力量。 如果说过去的行业竞争更像打着口号炫肌 ...

Core Viewpoint - The photovoltaic (PV) industry is undergoing a structural change in its cost dynamics, with silver paste replacing silicon material as the primary cost variable from 2024 to 2026, significantly impacting the competitive landscape and survival of companies in the sector [1][2]. Cost Structure Changes - In January 2024, silicon material's cost share decreased to approximately 10%-12%, while silver paste's share rose to 10.5%, marking a shift in cost dominance [2]. - By January 2025, silver paste's cost share surged to 14.2%, surpassing silicon material at 11.3%, indicating a reversal in cost structure [3]. - In January 2026, silver paste's share increased to 16%-17%, while silicon material's share fell to 9.9%, solidifying silver paste's dominance in cost structure [4][7]. Supply and Demand Dynamics - The global supply of silicon material is projected to exceed demand significantly in 2026, leading to a price drop to around 46,000-53,000 yuan per ton, which is below the cost line for many second and third-tier companies [8]. - The technological maturity in silicon material and wafer production has reached a plateau, limiting further cost reductions [9][10]. Silver's Unique Position - Silver's cost dynamics are driven by industrial demand rather than its traditional roles, with the industrial sector accounting for nearly 60% of silver demand in 2024 [15]. - The photovoltaic sector represents only 25%-30% of global industrial silver demand, indicating that it cannot dictate silver prices [18]. - The supply of silver is largely dependent on the production of other metals, making it less responsive to price changes [19]. Technological Innovations - The industry is witnessing a shift towards silver reduction technologies, with three main approaches emerging: gradual silver reduction, silver-coated copper paste, and copper plating [25][31][36]. - Silver-coated copper paste is expected to become the mainstream solution by 2026, offering significant cost advantages [31]. - Copper plating technology is anticipated to lead the industry by 2027, providing a complete alternative to silver and significantly reducing costs [36][47]. Future Outlook - The silver price is expected to remain high and volatile through 2026-2027, driven by supply-demand imbalances and industrial demand growth [50]. - Companies that can effectively implement silver reduction technologies will gain a competitive edge, as the ability to manage silver costs becomes a critical survival factor [52][53].

Core Viewpoint - Amazon is restructuring its AI strategy by creating a new "AGI organization" to integrate its language model team, chip development unit, and quantum computing team, as a response to its lagging position in the AI race compared to competitors like Google, Meta, and Nvidia [1][3]. Group 1: Amazon's AI Strategy and Challenges - Since 2025, Amazon's stock performance has been poor, with no significant annual gains, indicating that investors do not view Amazon as a key player in the AI sector [3]. - Despite having strong assets like AWS, self-developed chips, and a global e-commerce platform, Amazon's AI initiatives have been perceived as reactive rather than proactive, leading to a strategic need for urgent correction [3][4]. - Amazon's AI models, such as the Nova series, have not gained significant traction in the market, with OpenAI and Google dominating token usage [4]. Group 2: Competitive Landscape - Amazon's AWS, once a leader in cloud services, is facing increasing competition from Microsoft Azure and Google Cloud, which are integrating AI capabilities more effectively [7][10]. - Microsoft Azure's market share is growing, driven by strong demand for AI services, while AWS's positioning as a "model supermarket" dilutes its competitive edge [10][11]. Group 3: Internal Challenges and Organizational Structure - Amazon's AI team has been fragmented across various business lines, focusing on incremental improvements rather than developing a cohesive AGI strategy, leading to missed opportunities in the consumer AI space [15][16]. - The company's historical focus on customer-centric improvements has resulted in a reluctance to invest in long-term, high-risk AI innovations, causing it to fall behind competitors who are more agile in adapting to new trends [16][17].

一个简单的事实足以说明剧变的剧烈程度：2025年全年，比亚迪卖出了近226万辆纯电动车，而特斯拉 的交付量停留在164万辆。 这不是一次偶然的超车。特斯拉交付量连续两年下滑，同比减少8.6%；比亚迪却保持着近28%的高速增 长。更重要的是，比亚迪的超越发生在特斯拉曾经占据绝对优势的欧美市场。 文 | 财能圈 当特斯拉2025年四季度的交付量同比下滑16%时，全球电动车行业的一个时代正式落幕。曾经不可一世 的领跑者，被中国对手比亚迪从销量榜首的位置拉了下来。 从产品老化到政策红利消退，从品牌争议到战略转向，特斯拉正面临前所未有的复杂挑战。而比亚迪凭 借全产业链优势和精准的市场策略，正在改写全球电动车市场的游戏规则。 特斯拉踩下刹车， 神话光环褪色 特斯拉四季度的成绩单，让很多投资者感到寒意。41.8万辆的交付量，同比下滑16%，不仅远低于华尔 街的预期，也未能达到公司自己设定的目标。 全年164万辆的交付数据，意味着特斯拉连续第二年销量下滑。官方的解释集中在"全球工厂升级"和"资 源向高附加值业务倾斜"上。但市场看到的是更直接的现实：主力车型Model 3和Model Y已经老了，而 市场期待的新车型还没大规模 ...

Core Insights - The year 2025 is identified as the "Year of AI Applications," with significant investments and developments expected in the AI sector [2] - Major tech leaders and investors have reached a consensus that AI applications will see large-scale implementation in 2025, driven by decreasing costs of large model inference and increasing API call volumes [2][3] - A total of 930 AI application companies secured new financing amounting to 107.07 billion RMB in 2025, indicating a high level of investment activity [2][3] Investment Landscape - The top 10 application scenarios account for 73% of the total number of financing companies, indicating a high concentration of capital in these validated or promising areas [3] - Among the 930 companies, 194 focus on embodied intelligence, representing 20.9% of the total, as it aligns with capital's vision of "AI + physical world" [4] - The top three scenarios (embodied intelligence, autonomous driving, and general AI) account for over 51.6% of total financing, highlighting a trend of capital concentration [12][14] Financing Trends - The average financing amount for autonomous driving projects is 45.29 million RMB, significantly higher than other sectors, indicating a strong investment preference [18][19] - 36% of AI application companies are in early-stage financing, while 46% are in growth stages, suggesting that most companies are still proving their business models [20][21] - The majority of financing is directed towards B2B projects, with 62.17% of the top 10 scenarios being purely B2B, reflecting a shift in capital preferences [11] Geographic Distribution - Beijing leads with 226 AI application companies, accounting for 24.3% of the total, followed by Guangdong and Shanghai, indicating a concentration of talent and resources in these regions [23][24] - The geographic distribution of AI application companies reflects a competitive landscape driven by capital, talent, and supply chain dynamics [24] Industry Dynamics - The financing landscape reveals a merging of software and hardware boundaries, with top companies in embodied intelligence and autonomous driving demonstrating this trend [29] - The rapid growth in AI applications is accompanied by potential risks, as many companies may face challenges in achieving sustainable profitability [30] - The acquisition of Manus by Meta for $2 billion signals a global competition for AI talent and resources, reshaping the industry landscape [30]

Core Insights - The article discusses the evolution of China's low-altitude economy, highlighting a shift from traditional real estate to a new digital asset paradigm involving airspace below 1000 meters, which is expected to become a high-frequency trading asset by 2025 [1][2] Group 1: Low-altitude Economy Development - The low-altitude economy has transitioned from policy relaxation to industrial infrastructure development, marking a significant turning point in 2025 where applications are moving from single-point tests to large-scale clusters [2] - The explosion of the low-altitude economy relies on system-level scheduling capabilities rather than individual operators [3] Group 2: Core Drivers of Low-altitude Market - The core driver of the trillion-level low-altitude market is not merely the extension of the aviation manufacturing industry but rather an AI-driven "air operating system" that manages airspace operations [4] - Key technologies supporting this system include digital twins for airspace management, edge intelligence for autonomous decision-making, and swarm intelligence algorithms for coordinated operations [5] Group 3: Market Dynamics and Future Trends - As the industry matures, strict commercial rules will re-emerge in the low-altitude sector, leading to diminishing profits in hardware manufacturing, similar to the early smartphone market [6] - The future competitive landscape is likely to exhibit a "dumbbell structure," with one end focusing on core algorithms and platforms, while the other end specializes in vertical applications, leaving traditional aircraft manufacturers in a precarious position [7] Group 4: Strategic Focus for Businesses - Companies are advised to shift focus from hardware manufacturing to leveraging AI across traditional industries, including the low-altitude economy [8] - Understanding the data and algorithmic frameworks that underpin operations is more critical than merely achieving higher flight altitudes [9][10] Group 5: Infrastructure and Service Opportunities - The low-altitude economy requires invisible infrastructure, emphasizing the need for computational and communication capabilities, including low-altitude sensing networks and high-precision mapping services [12] - High-frequency vertical service providers that offer comprehensive solutions in high-risk and efficiency-demanding sectors will command premium pricing [12] - The post-operation market surrounding drones is expected to explode, with services like maintenance, AI pilot training, and automated positioning becoming vital segments [12]

Core Viewpoint - The collaboration between China National Petroleum Corporation (CNPC) and State Grid Corporation of China represents a strategic shift in the energy sector, moving from traditional oil and gas reliance to a comprehensive energy ecosystem that integrates electricity, hydrogen, carbon, and financial tools [1][7]. Group 1: Transaction Insights - CNPC transferred 3% of its stake in China Oil Capital to State Grid's subsidiary, establishing a deeper partnership that transforms their relationship from mere cooperation to a shared interest [1][2]. - China Oil Capital's acquisition of 100% of Yingda Futures for 1.129 billion yuan is crucial for CNPC's entry into the electricity market, allowing it to manage price volatility independently and enhance operational security [2][3]. Group 2: Strategic Implications for CNPC - The transaction serves as a "safety cushion" for CNPC's aggressive transformation strategy, enabling better risk management through financial instruments like futures and options [3][4]. - By securing a stake in State Grid, CNPC gains access to the core electricity ecosystem, facilitating smoother integration in distributed solar, energy storage, and charging networks [3][4]. Group 3: Broader Energy Ecosystem Strategy - The collaboration is part of CNPC's larger strategy to establish a dual-driven approach, combining physical energy production (oil, gas, electricity, hydrogen) with financial capital management to optimize resource allocation and risk control [5][6]. - This shift indicates a transition from point-to-point competition to ecosystem-based competition, where the focus is on building resilient and dynamic industry networks [7]. Group 4: Future Outlook - The partnership signals a new era in the energy sector, where capital and financial tools play a crucial role in addressing common challenges such as investment risks and market pricing [7]. - The essence of this collaboration lies in leveraging financial flexibility to navigate the complexities of industrial transformation, with the potential for significant competitive advantages in the evolving energy landscape [7].

即使在科学上取得奠基性成就后，考里科对科学本身的态度依然纯粹得近乎异类。"推动知识进步的始 终是科学，"她说。她批评一些同行将职业晋升置于科学发现之上，并告诫学生："他们不是在为上级工 作，而是在为推动科学进步而工作。" 如今，mRNA技术已从无人问津的角落跃升为生物医学的革命性平台，应用于从疫苗到癌症治疗、蛋白 质替代疗法的广阔领域。回顾这段旅程，考里科对成功的定义，与外界追逐的认可截然不同。她和Edu 指南分享道，"成功其实是，我还是60年前或50年前的那个自己，诚实、自然，仅此而已。" 文 | Edu指南 当整个世界将目光聚焦于mRNA疫苗，并将其誉为抗击新冠疫情的救星时，那位在幕后为其奠定科学基 石的女性，早已在一条人迹罕至、备受质疑的道路上孤独行走了四十年。 卡塔林·考里科（Katalin Karikó），这位2023年诺贝尔生理学或医学奖得主，她的故事并非一个典型 的、直线上升的天才叙事。它始于匈牙利一个没有自来水和稳定电力的小村庄。但"真正塑造我的，是 那种与自然紧密相连的简单家庭生活，"考里科在Edu指南访问中回顾道。观察小鸡破壳而出的童年好 奇心，成了她科学直觉的最初萌芽。 她的科研生涯，是 ...

图片来源：天桥脑科学研究院官方 在医学分支中，精神健康或许是最迫切，也最难被规模化革新的领域之一。这类疾病高度依赖对话进行 诊断、评估与干预，使其成为最具大语言模型（LLM）应用潜力的医学领域之一。 近日，在上海市精神卫生中心指导下，由天桥脑科学研究院（Tianqiao & Chrissy Chen Institute）联合盛 大集团、清华校友总会AI大数据专委会、上海交通大学计算机学院共同主办的2025合成数据大赛·灵溪 AI for Mental Health主题赛落幕。 尽管合成数据无法完全替代真实世界的复杂性与偶然性，但它为AI在精神健康领域的快速迭代与初步 验证，铺设了一条符合伦理且可行的技术路径。本次大赛，正是对这条路径的一次集中压力测试。 伴随赛事的成功举办，研究院同步对外展示其在AI for Mental Health领域从基础设施到生态建设的系统 性成果，标志着精神健康AI的发展迈向新阶段。 数据困境与合成破局： AI for Mental Health进入应用加速期 精神障碍的全球负担正在持续上升。世界卫生组织数据显示，全球超过10亿人正受到心理或精神障碍困 扰；在中国，精神科专业人力供给 ...

Core Viewpoint - The announcement by Redis to change its licensing from a permissive BSD license to commercial restrictions (SSPLv1 and RSALv2) marks a significant shift towards commercialization, impacting cloud service providers and the open-source community [1][2]. Group 1: Impact on the Community - The tightening of Redis's licensing has prompted cloud service providers to collaborate rapidly, leading to the creation of a new project named "Valkey" within just six days [2]. - Valkey aims to maintain compatibility with existing Redis protocols and data formats, ensuring minimal migration costs for users [3]. - The project is hosted under the Linux Foundation, which prevents any single commercial entity from unilaterally changing the rules, providing a sense of security for enterprise users [3]. Group 2: Role of Chinese Engineers - Chinese engineers have transitioned from being mere contributors to leading the development of core solutions, such as the "Slot Atomic Migration" feature, which addresses long-standing issues with Redis [4][5]. - The collaboration between Tencent Cloud and Google resulted in refining this solution, showcasing a shift in the role of Chinese technology teams from beneficiaries to leaders in the open-source community [5]. Group 3: Challenges and Considerations - The decision to support Valkey involved significant internal deliberation within Tencent Cloud, weighing the options of continuing with Redis or joining a new community [6]. - Concerns about market acceptance of the new Valkey brand and the sustainability of the project were prevalent among the Tencent Cloud team [6]. Group 4: Open Source Resilience - The closure of Redis has deeply affected community trust, and while Redis has made attempts to reintroduce open-source elements, the damage to trust is significant [7]. - Valkey's emergence serves as a reminder that there are no permanent safe havens in the open-source world, and the ongoing struggle for community voice and technical investment is just beginning [7][8]. Group 5: Future of Technology Collaboration - The evolution of Valkey reflects a broader trend where companies are encouraged to share core technologies to enhance global competitiveness [8]. - The rise of Valkey illustrates a shift towards a collaborative model of technology development, where public infrastructure is supported by multiple competitors rather than being owned by a single entity [9].