Core Viewpoint - The self-driving industry is experiencing a surge in recruitment for the 2026 graduate cohort, with numerous companies like Horizon Robotics, Didi, and Yuanrong Qixing opening positions, indicating a robust demand for roles related to perception, control, end-to-end systems, and large models [1][2]. Group 1: Recruitment Trends - Many companies are increasing positions related to embodied intelligence, reflecting a trend of integration between self-driving technology and embodied concepts [1]. - Positions available include hardware development engineers, perception post-processing engineers, middleware software engineers, planning control algorithm engineers, and more, with multiple openings across various cities [2]. - The recruitment process is expected to ramp up with technical and HR interviews scheduled for late July and early August [1]. Group 2: Community and Resources - The AutoRobo Knowledge Circle serves as a community for job seekers in the fields of self-driving, embodied intelligence, and robotics, with nearly 1,000 members from various companies [6]. - The community provides resources such as interview questions, industry reports, salary negotiation tips, and resume optimization services [6][7]. - Members can access a wealth of information including successful and unsuccessful interview experiences, which can help refine their job application strategies [18][19]. Group 3: Job Opportunities - The 2026 internship positions include roles such as C++ development intern and PyTorch framework development intern, indicating a focus on software development skills [8]. - The community shares job openings in algorithms, development, and product roles, ensuring members are informed about the latest opportunities [7]. Group 4: Industry Insights - The community also compiles industry reports to help members understand the current state and future prospects of the self-driving and embodied intelligence sectors [16]. - Topics covered in the reports include market opportunities, technological trends, and the development of humanoid robots [16].

Group 1 - The article announces the recruitment of 10 partners for the autonomous driving sector, focusing on course development, research guidance, and hardware development [2][5] - The main areas of expertise sought include large models, multimodal models, diffusion models, SLAM, 3D object detection, and closed-loop simulation [3] - Candidates from QS200 universities with a master's degree or higher are preferred, especially those with significant conference contributions [4] Group 2 - The benefits for partners include resource sharing for job seeking, PhD recommendations, and overseas study opportunities, along with substantial cash incentives [5] - There are opportunities for collaboration on entrepreneurial projects [5] - Interested parties are encouraged to contact via WeChat for further inquiries [6]

部分试点城市小有所成 2022年，中国工程院院士、清华大学车辆与运载学院教授李克强团队正式提出车路云一体化技术方案， 旨在通过车、路、云协同解决智能网联汽车规模化落地的瓶颈问题。 近日，特斯拉首辆也是全球首辆汽车，实现了从工厂产线直接自动驾驶到客户家里。与此同时，特斯拉 Robotaxi首批车辆也已经开始在美国运营。始终坚持走单车智能路线的特斯拉在高级别自动驾驶方面再 次取得了令人振奋的成绩。 反观另一条智能交通路线——车路云一体化，则好像处于发展相对缓慢的状态。作为自动驾驶行业的中 国方案，车路云一体化方案的理论体系已经相当完备，但在实际落地过程中却困难重重。无论是车端还 是路侧，建设车路云一体化的态度都不够积极。 问题出在哪儿？如何破冰？成为车路云一体化方案继续推进先要攻克的课题。 第二，管理体系不完备，亟待打通数据"烟囱"。目前，车辆数据、路侧数据、交通数据不互联互通，存 在重复建设、效率不高的问题。 车路云一体化方案得到了国家相关主管部门的认可。与新能源汽车发展初期的模式一样，中央政府也是 先对车路云一体化方案进行部分城市应用试点。 2024年1月，工业和信息化部、公安部、自然资源部、住房和城乡建设部 ...

商业化要素齐备，无人物流时代开启 ——无人物流车跟踪报告 2025年7月11日 分析师：倪昱婧，CFA（执业证书编号：S0930515090002） 分析师：邢萍（执业证书编号：S0930525050001） 核心观点 风险提示：无人物流车量产进展不及预期、物流需求减少、政策与市场风险。 请务必参阅正文之后的重要声明 1 无人物流车当前以中短途运输为主：当前无人物流车主要应用于中短距离的支线运输/末端配送，我 们判断，1）无人物流车可有效解决偏远地区/高峰时段用工短缺问题，配送效率高+应用范围广；2） 无人物流车的核心应用场景为城市配送（快递/外卖/零售/商超等），或有望重构城市配送产业生态。 商业化落地要素齐全，无人物流车有望率先放量：我们判断，无人物流车在政策/技术/成本三方面或 均已具备相对成熟条件，有望在L4级自动驾驶商业化场景中率先实现大规模放量：1）政策：一方面 无人物流车支持政策范围已涵盖二三线城市、且有明确的安全/责任规定，另一方面，2024年至今国 内各地加速发放无人物流车上路牌照；2）技术：与其他L4级自动驾驶场景相比，无人物流车主要针 对低速+固定路线场景，算法+算力要求均相应降低；3） ...

Core Viewpoint - Intel is selling its stake in Mobileye for $900 million, which includes a direct buyback of $100 million, potentially leading to total proceeds of $1 billion. This move reflects Intel's strategic shift amidst challenges in the semiconductor and autonomous driving industries [1][2][3]. Group 1: Intel's Strategic Shift - Intel has faced significant challenges in recent years, particularly against competitors like AMD, Apple, and Nvidia, leading to a need for strategic adjustments under new CEO Chen Lifang [2]. - The sale of Mobileye shares is part of a broader strategy to optimize assets and focus on core business areas, particularly data center and AI chips, which are seen as future growth points [3][5]. Group 2: Mobileye's Market Position - Mobileye, acquired by Intel for $15.3 billion in 2017, has seen a decline in competitiveness as the market shifts towards fully autonomous driving solutions. The company has lowered its revenue expectations for 2024 to between $1.6 billion and $1.68 billion, down from previous estimates [3][5]. - Despite its challenges, Mobileye still has a cash flow, making it a target for asset optimization by Intel [3]. Group 3: Industry Dynamics - The sale of Mobileye shares highlights a shift in the automotive industry, where car manufacturers are increasingly seeking to regain control over technology and software, moving away from reliance on suppliers like Mobileye [8][10]. - The changing landscape indicates a move from a hardware-dominated model to one that emphasizes software and service revenues, with projections suggesting that by 2030, over 50% of automotive revenue will come from services and software [8][9]. Group 4: Future Implications - The transaction may signal the beginning of a broader industry reshuffle, as companies adapt to new market realities and seek to establish more flexible partnerships [11][12]. - The evolving dynamics suggest that smaller players may struggle to survive unless they can secure ongoing orders from car manufacturers or develop software monetization capabilities [12][13].

Equity Market - On July 10, the market experienced a slight increase with the Shanghai Composite Index returning above 3500 points, closing up 0.48% [2] - The total trading volume in the Shanghai and Shenzhen markets reached 1.49 trillion yuan, a decrease of 11 billion yuan compared to the previous trading day [2] - Over 2900 stocks rose in the market, with sectors like silicon energy, real estate, rare earth permanent magnets, and diversified finance leading the gains, while sectors such as PCB, consumer electronics, gaming, and military industry saw declines [2] Domestic Developments - As of the end of May, the balance of inclusive agricultural loans in Jiangsu province reached 1.26 trillion yuan, with loans in key grain sectors amounting to 454.3 billion yuan [6] - The major agricultural banks have issued over 55 billion yuan in loans related to the "Three Summer" period, and the coverage rate for comprehensive cost insurance for the three major grain crops exceeds 90% [6] - From January to June, the customs at Nanjing Lukou Airport processed 542 tax refund applications for departing travelers, with a total refund amount of 2.9236 million yuan, marking increases of 124.9% and 165.47% year-on-year, respectively [6] Pension and Social Security - The Ministry of Human Resources and Social Security and the Ministry of Finance announced an adjustment to the basic pension for retirees, effective January 1, 2025, with an overall adjustment level of 2% based on the average monthly pension of retirees by the end of 2024 [7] - The adjustment considers various factors including price changes and wage growth [7] Automotive Industry - From July 1 to 6, the retail sales of new energy passenger vehicles in China reached 135,000 units, a year-on-year increase of 21%, but a month-on-month decrease of 11% [7] - The retail penetration rate for the new energy market reached 56.7%, with cumulative retail sales for the year amounting to 6.583 million units, a year-on-year increase of 37% [7] Global Investment Trends - Japan's Government Pension Investment Fund (GPIF) increased its investment in U.S. Treasury bonds to the highest level in a decade, holding 51.8% of its foreign bonds in U.S. Treasuries as of March [8] - Tether Holdings SA confirmed it holds approximately 80 tons of gold, valued at around 8 billion USD, making it one of the largest holders of gold globally, comparable to UBS Group [8] - Nvidia is planning to significantly expand its operations in Israel to meet the growing demand for artificial intelligence data centers [8]

7月10日，马斯克召开旗下AI模型Grok 4的发布会，此外还称，Grok很快就会登陆特斯拉汽车，同时特 斯拉正在扩大奥斯汀地区的Robotaxi服务范围；正等待监管部门批准在湾区推出Robotaxi服务，可能在 一两个月内推出。媒体获悉特斯拉还计划将Robotaxi服务扩展到亚利桑那州。 招商证券认为Robotaxi的商业模式从本质上有别于特斯拉传统汽车销售+FSD软件订阅的业务模式，从 单车盈利能力上来看Robotaxi > FSD软件订阅>传统汽车销售。结合公司最新给出的Robotaxi运营成本预 期，预计Robotaxi业务有望为公司带来173亿美元利润（假设远期Robotaxi车队数量达到20万辆）。 而2025年有望成为Robotaxi量产元年，全球Robotaxi产业有望迎来多重催化：1）Robotaxi商业化运营推 广加速，头部企业营收快速增长；2）量产车型有望陆续下线并投入使用，单车盈利能力快速提升；3） 全球Robotaxi运营范围持续扩大。 北汽蓝谷：与小马智聚焦极狐αT5 车型平台，将小马智行第七代 L4 级自动驾驶系统进行全栈技术集 成，联合开展全无人驾驶 Robotaxi 车型的正 ...

Core Viewpoint - Tesla is accelerating its Robotaxi business expansion amid increasing competition in the autonomous driving sector, with a recent application for testing and operation in Arizona, including both safety driver and no safety driver modes [1] Group 1: Tesla's Robotaxi Expansion - Tesla has officially applied to test and operate its Robotaxi service in Arizona, aiming to enter the Phoenix metropolitan area [1] - The review results for Tesla's application are expected by the end of July, which could mark a significant step towards commercializing Robotaxi services in multiple U.S. cities [1] - This move is seen as an attempt to catch up with Waymo, which has been a leader in the Robotaxi market since launching its fully driverless service in Phoenix in 2020 [1] Group 2: Technology and Testing - Unlike most autonomous driving companies that rely on expensive LiDAR and high-precision maps, Tesla focuses on a camera-based visual recognition system, which Elon Musk believes is more commercially viable for large-scale deployment [2] - Tesla is also conducting preliminary Robotaxi tests in Austin, Texas, using Model Y SUVs equipped with the latest autonomous driving system, although these vehicles are still in a "semi-automated" phase with a safety supervisor present [2] - Recent incidents, including a minor collision involving a Robotaxi, have raised public safety concerns and led to investigations by the National Highway Traffic Safety Administration (NHTSA) [3] Group 3: Regulatory Challenges - Despite challenges, Musk remains committed to expanding the Robotaxi service, with potential plans to extend it to the San Francisco Bay Area within one to two months [3] - California regulatory agencies have shown caution, having previously sued Tesla for alleged misleading statements regarding its autonomous driving features [3] - Tesla's upcoming earnings call on July 23 is expected to focus on the progress, operational feedback, and future plans for the Robotaxi service, drawing significant attention from investors and analysts [3]

Group 1: Autonomous Driving Developments - The Beijing high-level autonomous driving demonstration zone has accumulated nearly 40 million kilometers of autonomous driving testing mileage, showcasing the rapid development of the autonomous driving industry in Beijing Yizhuang [2][5] - The core of the "vehicle-road-cloud integration" model is collaboration, which involves smart road infrastructure, connected vehicles, and a powerful cloud platform to enhance system safety and operational safety [3][5] - The integration of vehicle-road-cloud systems allows for improved safety in complex traffic environments, addressing challenges such as blind spots caused by larger vehicles [3][5] Group 2: Talent Demand in Autonomous Driving - The autonomous driving industry is expected to create a significant demand for high-end talent, with new job roles emerging in areas such as remote safety personnel and data management [6][8] - The industry faces challenges in handling extreme weather conditions, necessitating advanced sensor technology and multi-sensor fusion to ensure operational safety [6][7] - As the technology evolves, the need for specialized training and knowledge in the field will increase, leading to the creation of new job opportunities rather than merely replacing traditional roles [8] Group 3: Maritime Navigation Innovations - The introduction of smart pilot systems and navigation simulators is enhancing the efficiency and safety of pilot operations in maritime navigation [10][11] - The smart pilot system integrates real-time tidal information and advanced radar technology to improve decision-making accuracy for pilots [11][12] - Training simulators provide a realistic environment for pilots to practice navigating under various weather conditions, contributing to skill development and operational preparedness [12][13] Group 4: High-Speed Maglev Train Development - The successful rollout of a 600 km/h high-speed maglev train system in Qingdao marks a significant advancement in China's transportation capabilities, filling the speed gap between aviation and high-speed rail [15] - This maglev system is positioned to facilitate rapid commuting within urban clusters and enhance long-distance transportation networks, supporting the vision of a "strong transportation nation" [15]

Group 1 - Grizzly Research, a short-selling firm, has announced a short position against Pony.ai (PONY.O) [1] - Following the announcement, Pony.ai's stock price declined by nearly 2% [1]