Core Viewpoint - The article discusses the recruitment process and job responsibilities for a perception algorithm engineer in the autonomous driving industry, emphasizing the importance of skills in computer vision, deep learning, and sensor fusion technologies [1][5][6]. Group 1: Job Responsibilities - The role involves processing large amounts of autonomous driving data, building automated ground truth labeling systems, and designing cutting-edge AI and vision technologies [6]. - Algorithms and code developed will be deployed in millions of mass-produced vehicles [6]. - Key tasks include detecting static scene elements, tracking dynamic targets, and developing calibration methods for various sensors [10]. Group 2: Job Qualifications - Candidates should have a master's degree or higher in relevant fields such as computer science, automation, or mathematics [7]. - Proficiency in programming languages like C++ or Python, along with solid knowledge of algorithms and data structures, is required [7]. - Familiarity with multi-view geometry, computer vision, deep learning, and sensor technology applications is essential [7]. Group 3: Preferred Qualifications - Experience in developing perception algorithms for autonomous driving systems or ADAS, such as lane detection and obstacle tracking, is a plus [9]. - Candidates with experience in sensor fusion involving visual, LiDAR, and millimeter-wave radar are preferred [9]. - Publications in top conferences or journals in the fields of computer vision, machine learning, or robotics are advantageous [9]. Group 4: Community and Resources - The article mentions a community platform for job seekers in autonomous driving and robotics, providing resources such as interview questions, industry reports, and salary negotiation tips [12][13]. - The community aims to assist members in preparing for job applications and understanding industry trends [12][21].

Core Viewpoint - The article announces the recruitment of researchers for embodied intelligent large models at Zhiyuan Research Institute, offering various employment formats including social recruitment, campus recruitment, and internships [1]. Group 1: Job Responsibilities - Responsible for research and development of embodied intelligent large models (VLA models or hierarchical architectures) [4]. - Design and optimize model architectures, handle data processing, training, and deployment on real machines [4]. - Conduct in-depth research on cutting-edge technologies in the field of embodied intelligence, track the latest developments in the large model industry, and explore the application of new technologies in this field [4]. Group 2: Job Requirements - Master's degree or above in relevant fields such as computer science, artificial intelligence, robotics, automation, or mathematics [4]. - Proficiency in Python with a solid foundation in deep learning, familiar with deep learning frameworks like TensorFlow and PyTorch [4]. - Research experience in the large model field with a deep understanding of mainstream visual and language large models, including experience in pre-training, fine-tuning, and deployment processes [4]. - Experience in robot control and familiarity with mainstream embodied model training and deployment is preferred [4]. - Excellent learning ability, English proficiency, hands-on skills, and good team communication and collaboration skills; publication of relevant papers in top conferences (RSS, ICRA, CVPR, CoRL, ICLR, NeurIPS, ACL, etc.) is preferred [4]. Group 3: Community and Resources - AutoRobo Knowledge Planet serves as a community for job seekers in autonomous driving, embodied intelligence, and robotics, currently with nearly 1,000 members from various companies [6]. - The community provides resources such as interview questions, industry reports, salary negotiation tips, and internal referrals [6][7]. - The platform also shares job openings in algorithms, development, and product roles, including campus recruitment, social recruitment, and internships [7]. Group 4: Industry Reports - The community compiles various industry reports to help members understand the current state, development trends, market opportunities, and the landscape of the embodied intelligence industry [15]. - Reports include topics such as the World Robotics Report, China's Embodied Intelligence Venture Capital Report, and the development of humanoid robots [16].

最近邀请了几个星球 嘉宾录制了一些求职类的视频课程，希望能帮助到正在秋招/社招的小伙伴。 主要关于小 厂、大厂面试，秋招的校招如何准备、公司选择等主要问题，以及大模型、自动标注、端到端一些岗位的介绍和 分析。 每年都有同学吐槽说秋招算法岗大爆炸，都来咨询我们如何准备。所以今年我们打算做一些实打实的教学视频， 从行业、岗位和工作内容的角度为大家剖析，应该怎么选，什么样子的最适合自己。 更多内容欢迎加入我们的求职星球了解，一个转为自动驾驶、机器人和大模型求职打造的社区。 AutoRobo知识星球 这是一个给自动驾驶、具身智能、机器人方向同学求职交流的地方，目前近1000名成员了，成员范围包含已经 工作的社招同学，如智元机器人、宇树科技、地瓜机器人、地平线、理想汽车、华为、小米汽车、momenta、元 戎启行等公司。同时也包含2024年秋招、2025年秋招的小伙伴，方向涉及自动驾驶与具身智能绝大领域。 星球内部有哪些内容？这一点结合我们已有的优势，给大家汇总了面试题目、面经、行业研报、谈薪技巧、还有 各类内推公司、简历优化建议服务。 招聘信息 星球内部日常为大家分享已有的算法、开发、产品等岗位，基本都是公司第一时间 ...

汽车纵横全媒体 中国科学技术协会主席万钢出席了本次会议；东风汽车集团有限公司原董事长、行业技术专家竺廷风为本次会议作引导发言；OICA（国际汽车制造商协 会） Technical Director Olivier FONTAINE，上海汽车集团股份有限公司副总裁、总工程师祖似杰，宝马中国研发中心高级副总裁Dr.Robert Kahlenberg，吉 利汽车集团高级副总裁王瑞平，奇瑞汽车股份有限公司副总工程师、开阳实验室CTO宋廷伦，中国汽车工业协会副总工程师王耀，中国第一汽车股份有限 公司研发总院副院长赵慧超，中国信息通信研究院总工程师敖立，北京汽车研究总院有限公司党委书记、院长王磊，广汽集团执委会委员吴坚，华为智能 驾驶解决方案产品线总裁李文广，博世电驱动系统事业部中国区总裁许长春，东软睿驰汽车技术（上海）有限公司总裁兼CTO杜强，地平线副总裁、战略 部&智驾产品规划与市场部负责人吕鹏，芯擎科技创始人、董事兼CEO汪凯分别在会上发表演讲；中国汽车工业协会常务副会长兼秘书长付炳锋出席并主 持了本次会议全程。 当下，中国汽车产业正面临智能化与碳中和双重变革。与会嘉宾以"松桦恋"共生哲学破题，并提出技术应当化繁为 ...

Core Viewpoint - The article emphasizes the importance of creating an engaging learning environment in the field of autonomous driving and AI, aiming to bridge the gap between industry and academia while providing valuable resources for students and professionals [1]. Group 1: Community and Resources - The community has established a closed loop across various fields including industry, academia, job seeking, and Q&A exchanges, focusing on what type of community is needed [1][2]. - The platform offers cutting-edge academic content, industry roundtables, open-source code solutions, and timely job information, streamlining the search for resources [2][3]. - A comprehensive technical roadmap with over 40 technical routes has been organized, catering to various interests from consulting applications to the latest VLA benchmarks [2][14]. Group 2: Educational Content - The community provides a series of original live courses and video tutorials covering topics such as automatic labeling, data processing, and simulation engineering [4][10]. - Various learning paths are available for beginners, as well as advanced resources for those already engaged in research, ensuring a supportive environment for all levels [8][10]. - The community has compiled a wealth of open-source projects and datasets related to autonomous driving, facilitating quick access to essential materials [25][27]. Group 3: Job Opportunities and Networking - The platform has established a job referral mechanism with multiple autonomous driving companies, allowing members to submit their resumes directly to desired employers [4][11]. - Continuous job sharing and position updates are provided, contributing to a complete ecosystem for autonomous driving professionals [11][14]. - Members can freely ask questions regarding career choices and research directions, receiving guidance from industry experts [75]. Group 4: Technical Focus Areas - The community covers a wide range of technical focus areas including perception, simulation, planning, and control, with detailed learning routes for each [15][29]. - Specific topics such as 3D target detection, BEV perception, and online high-precision mapping are thoroughly organized, reflecting current industry trends and research hotspots [42][48]. - The platform also addresses emerging technologies like visual language models (VLM) and diffusion models, providing insights into their applications in autonomous driving [35][40].

彼时正值人工智能算力需求爆发前夜，Ross带领团队另辟蹊径，选择专注于"语言处理单元（LPU）"的 研发。 这种专为AI推理任务设计的芯片架构，从诞生之初就剑指英伟达GPU在实时数据处理领域的统治地 位。 与传统GPU依赖高带宽内存（HBM）等昂贵组件不同，Groq的LPU芯片通过独特的软件定义硬件架 构，在能效比与成本控制上实现突破。 其核心技术在于动态调度算法和大规模并行计算单元，能够高效处理自然语言模型（如ChatGPT）、图 像识别等场景的实时推理需求。 公司最新数据显示，LPU在特定场景下的推理成本仅为英伟达GPU的十分之一，能效比提升高达 300%。 近日，美国AI芯片初创公司Groq宣布启动新一轮融资谈判，计划募集6亿美元资金，估值接近60亿美 元。若交易达成，这距离其2024年8月完成的28亿美元估值融资仅过去不到一年时间，创下了硅谷AI芯 片赛道有史以来最快的估值增长纪录。 这家总部位于加州圣克拉拉的科技新贵，由谷歌Tensor处理单元核心团队成员Jonathan Ross于2016年创 立。 这种技术路径的选择在资本市场上获得热烈反响。自成立以来，Groq累计融资规模已达16亿美元，投 资 ...

Core Viewpoint - The article discusses the rapid evolution of the Yangtze River Delta's electric vehicle (EV) industry, transitioning from electrification to intelligent driving, driven by leading companies like Tesla, Li Auto, and BYD [1] Group 1: Industry Overview - The Yangtze River Delta region accounts for 40% of China's EV production and over 25% of global production, forming a significant industrial cluster with a "4-hour industrial circle" [1] - Li Auto's supply chain is heavily concentrated in this region, with 30% of its supply chain in Changzhou, 50% in Jiangsu, and 80% in the Yangtze River Delta [1] Group 2: Intelligent Driving Technology - By 2025, "smart driving equity" is expected to be a key industry term, with intelligent driving technology penetrating the mainstream market priced between 100,000 to 200,000 yuan [2] - China's L2-level assisted driving penetration rate has surpassed 50%, the highest globally, with expectations for advanced driving solutions to grow significantly by 2030 [2][3] Group 3: Technological Advancements - Horizon Robotics holds a 33.97% market share in L2 assisted driving solutions for domestic passenger vehicles, indicating that one in three smart cars is equipped with their technology [3] - The company emphasizes the importance of balancing cost and performance in chip development, aiming for significant improvements in computational efficiency rather than just raw power [4] Group 4: Localized Supply Chain Strategy - Li Auto is accelerating its localized supply chain strategy, with its Changzhou manufacturing base serving as a hub for key components like silicon carbide power modules and electric drive systems [7][8] - The company has achieved significant advancements in battery technology, with the latest models featuring rapid charging capabilities that have improved over a short period [8][9] Group 5: Collaborative Innovation - The relationship between Li Auto and its suppliers is characterized by co-creation and mutual empowerment, with regular collaborative meetings to enhance project and technology development [11][12] - Strategic partnerships have led to significant improvements in manufacturing processes and quality control, exemplified by the low defect rates achieved by battery supplier Xinwanda [12]

Investment Rating - The report initiates coverage with a "Buy" rating for the company [4][9]. Core Views - The company is transitioning into a smart infrastructure asset service provider, leveraging its strong asset operation and financing capabilities while actively investing in the robotics industry to create a complete ecosystem [1][15][16]. Summary by Sections Company Overview - The company, formerly known as "首长国际," began its strategic transformation in 2016 and has established a solid moat in asset operation and financing, now focusing on building a robotics ecosystem [1][15]. - It has a diversified shareholder structure, backed by top global strategic investors including Shougang Group and Orix Group [22][23]. Performance Analysis - The asset operation business has shown stable growth, with revenue reaching HKD 920 million in 2024, a year-on-year increase of 39.8% [2][30]. - The financing business has experienced historical volatility but is expected to stabilize due to changes in accounting standards [2][35]. - The company has committed to a dividend payout ratio of no less than 80% before 2027, with cumulative dividends exceeding HKD 5.2 billion over 18 years [2][46]. - The company has over HKD 5 billion in available cash, with positive operating cash flow [2][49]. Robotics Business - The company has established a 10 billion RMB robotics investment fund in partnership with Beijing Guoguan, investing in various high-quality robotics companies [3][55]. - It leverages its extensive operational scenarios, including numerous parking lots and industrial parks, to shorten commercialization cycles and enhance product iteration [3][55]. Profit Forecast and Investment Recommendations - The company is positioned as a leader in parking lot operations, with a robust cash flow foundation supporting its robotics business expansion [4][24]. - Revenue projections for 2025-2027 are estimated at HKD 15.2 billion, 17.1 billion, and 18.9 billion, respectively, with corresponding net profits of HKD 5.8 billion, 7.1 billion, and 8.2 billion [4][24].

Group 1: Industry Overview - The Yangtze River Delta region has formed a "4-hour industrial circle" for the new energy vehicle (NEV) industry, accounting for 40% of China's NEV production and over 25% globally [1] - Leading companies like Tesla, Li Auto, and BYD are driving the transition from electrification to intelligentization in the NEV sector [1] Group 2: Intelligent Driving Technology - By 2025, "smart driving equity" is expected to become a key industry term, with intelligent driving technology penetrating the mainstream market priced between 100,000 to 200,000 yuan [2] - China's L2-level driving assistance penetration rate has exceeded 50%, the highest globally, with significant growth projected in the advanced driving assistance market [2][3] Group 3: Technological Advancements - Horizon Robotics has achieved a market share of 33.97% in L2 driving assistance solutions, indicating that one in three smart vehicles is equipped with their technology [2] - The company emphasizes the importance of balancing cost and computational performance, focusing on enhancing chip efficiency rather than merely increasing computational power [3] Group 4: Supply Chain and Localization - Li Auto is accelerating its supply chain localization strategy, with significant components like silicon carbide power modules and electric drive systems being produced in close proximity to its manufacturing base in Changzhou [7] - The collaboration between Li Auto and its suppliers, such as CATL and Horizon Robotics, is characterized by a tight integration that enhances development speed and quality [7][10] Group 5: Product Development and Innovation - Li Auto's new energy vehicles, such as the Li ONE and the recently launched Li i8, showcase advancements in battery technology, achieving rapid charging capabilities [8][9] - The company has established a collaborative model with suppliers, focusing on co-creation and mutual empowerment to enhance product quality and innovation [10][11]

Core Viewpoint - BYD is significantly focusing on the development of intelligent driving technologies and has established a competitive internal culture to drive innovation and efficiency in its new technology research institute [2][4]. Group 1: Establishment and Purpose of the New Technology Research Institute - The New Technology Research Institute was established in 2017 to focus on systematic research and development, addressing previous limitations in team integration and focus [3]. - The institute promotes competition not only internally but also against industry leaders like Tesla and Toyota, aiming to enhance product performance and user experience [4]. Group 2: Internal Competition and Development Strategy - Internal competition is encouraged to ensure that projects meet high standards; if a team cannot achieve desired outcomes, another team is selected to continue the project [5]. - The integration of cockpit and intelligent driving teams is a response to the trend of combined functionalities, with a focus on hardware evolution and collaborative projects [5]. Group 3: Technological Focus and Future Plans - BYD is prioritizing data and algorithms over self-developed computing chips, collaborating with companies like NVIDIA and Horizon to optimize computing power [5]. - The company maintains a dual-mode technology and intelligent development structure within the New Technology Research Institute, ensuring a cohesive approach to innovation [6].