Core Viewpoint - The article emphasizes the need for deeper technical exploration and collaboration in the autonomous driving industry, highlighting recent technological advancements from companies like Tesla, Xiaopeng, and Li Auto [2]. Group 1: Industry Direction - The main focus areas for the autonomous driving sector include but are not limited to: autonomous driving product management, 4D annotation/data loop, world models, VLA, autonomous driving large models, reinforcement learning, and end-to-end systems [4]. Group 2: Recruitment and Collaboration - The company is seeking to expand its team with talented individuals, particularly for roles related to autonomous driving training partnerships targeting both enterprises and educational institutions, as well as content creation for students and job seekers [5]. - Interested parties are encouraged to reach out for discussions regarding compensation and collaboration methods [6].

Core Viewpoint - The article emphasizes the need for deeper technical exploration and collaboration in the autonomous driving industry, highlighting the importance of addressing the challenges and pain points within the sector [2]. Group 1: Industry Direction - The main focus areas for development include but are not limited to: autonomous driving product management, 4D annotation/data loop, world models, VLA, autonomous driving large models, reinforcement learning, and end-to-end systems [4]. Group 2: Job Description - The positions are primarily aimed at autonomous driving training collaborations, targeting both B-end (enterprises, universities, research institutes) and C-end (students, job seekers) audiences for training, course development, and original article creation [5]. Group 3: Collaboration Invitation - The industry is calling for more talented individuals to join and contribute to the advancement of autonomous driving technology [3]. Group 4: Contact Information - For further communication regarding compensation and collaboration methods, interested parties are encouraged to add the WeChat contact provided [6].

Group 1 - The article highlights the importance of continuous learning in the field of autonomous driving, emphasizing the need for professionals to stay updated with the latest technologies and trends [6] - It mentions a variety of advanced topics and learning routes available, including VLA, world models, closed-loop simulation, and diffusion models, indicating a comprehensive curriculum for learners [6] - The platform offers opportunities for direct interaction with industry leaders and academic experts, facilitating knowledge exchange and networking [6] Group 2 - The article outlines various promotional offers for new users, including discounts on courses and membership renewals, aimed at attracting more participants to the learning community [4][3] - It lists seven premium courses available, covering essential topics such as trajectory prediction, camera calibration, and 3D point cloud detection, catering to both beginners and advanced learners [6] - The content emphasizes the significance of face-to-face discussions with top authors and experts in the field, enhancing the learning experience through direct engagement [6]

Group 1 - The core viewpoint emphasizes the rapid evolution of the autonomous driving technology stack, highlighting the need for continuous learning to avoid obsolescence in the field [1] - The company has established three platforms focusing on autonomous driving, embodied intelligence, and large models, encouraging exploration and adaptation in a changing environment [2] - The company is actively promoting industry advancement and has launched significant promotional activities during the National Day and Mid-Autumn Festival, offering discounts on courses [2][4] Group 2 - The knowledge community for autonomous driving includes nearly 40 learning paths, covering cutting-edge technologies such as VLA, world models, and closed-loop simulation [8] - The community facilitates face-to-face interactions with industry leaders and offers seven premium courses aimed at beginners, fostering skill development [8]

Group 1 - The article promotes various discounts and offers for courses, including a 70% discount and a reduction of 80 or 99 yuan for specific courses [1][3][4] - A yearly subscription to the "Big Model Planet" is available for 99 yuan, which includes technology, industry insights, and job-seeking assistance [1] - The platform offers a 1v1 tutoring service with a maximum discount of 1000 yuan off a 5000 yuan fee, and a 1v6 paper tutoring service with a 1000 yuan reduction [1] Group 2 - The "Autonomous Driving Heart" section highlights cutting-edge self-driving technology, featuring nearly 40 learning routes including VLA, world models, and closed-loop simulation [6] - The community facilitates face-to-face interactions with industry leaders and academic experts, providing insights into the future direction of autonomous driving [6] - The article mentions seven premium courses aimed at beginners, focusing on essential skills and knowledge in the field [6]

Group 1 - The article introduces a significant learning package for the new academic season, including a 299 yuan discount card that offers a 30% discount on all platform courses for one year [3][5]. - Various course benefits are highlighted, such as a 1000 yuan purchase giving access to two selected courses, and discounts on specific classes and hardware [3][6]. - The focus is on cutting-edge autonomous driving technologies for 2025, particularly end-to-end (E2E) and VLA (Vision-Language Alignment) autonomous driving systems [5][6]. Group 2 - End-to-end autonomous driving is emphasized as a core algorithm for mass production, with a notable mention of the competition sparked by the UniAD paper winning the CVPR Best Paper award [6][7]. - The article discusses the rapid evolution of technology in the field, indicating that previous learning materials may no longer be suitable for current industry standards [7]. - The challenges faced by beginners in understanding fragmented knowledge and the lack of high-quality documentation in end-to-end autonomous driving research are addressed [7][8]. Group 3 - The article outlines specific courses aimed at addressing the complexities of autonomous driving, including a small class on 4D annotation algorithms, which are crucial for training data generation [11][12]. - The importance of automated 4D annotation in enhancing the efficiency of data loops and improving the generalization and safety of autonomous driving systems is highlighted [11]. - The introduction of a multi-modal large model and practical courses in autonomous driving is noted, reflecting the growing demand for skilled professionals in this area [15][16]. Group 4 - The article features expert instructors for the courses, including Jason, a leading algorithm expert in the industry, and Mark, a specialist in 4D annotation algorithms [8][12]. - The curriculum is designed to provide a comprehensive learning experience, addressing real-world challenges and preparing students for job opportunities in the autonomous driving sector [23][29]. - The article emphasizes the importance of community engagement and support through dedicated VIP groups for course participants, facilitating discussions and problem-solving [29].

Group 1 - The article introduces a significant learning package for the new academic season, including a 299 yuan discount card that offers a 30% discount on all platform courses for one year [3][5]. - Various course benefits are highlighted, such as a 1000 yuan purchase giving access to two selected courses, and discounts on specific classes and hardware [3][6]. - The focus is on cutting-edge autonomous driving technologies for 2025, particularly end-to-end (E2E) and VLA (Vision-Language Alignment) autonomous driving systems [5][6]. Group 2 - End-to-end autonomous driving is emphasized as a core algorithm for mass production, with a notable mention of the competition sparked by the UniAD paper winning the CVPR Best Paper award [6][7]. - The article discusses the challenges faced by beginners in mastering multi-modal large models and the fragmented nature of knowledge in the field, which can lead to discouragement [7][8]. - A course on automated 4D annotation algorithms is introduced, addressing the increasing complexity of training data requirements for autonomous driving systems [11][12]. Group 3 - The article outlines a course on multi-modal large models and practical applications in autonomous driving, reflecting the rapid growth and demand for expertise in this area [15][16]. - It mentions the increasing job opportunities in the field, with companies actively seeking talent and offering competitive salaries [15][16]. - The course aims to provide a systematic learning platform, covering topics from general multi-modal large models to fine-tuning for end-to-end autonomous driving applications [16][18]. Group 4 - The article emphasizes the importance of community and communication in the learning process, with dedicated VIP groups for course participants to discuss challenges and share insights [29]. - It highlights the need for practical guidance in transitioning from theory to practice, particularly in the context of real-world applications and job readiness [29][31]. - The article also mentions the availability of specialized small group courses to address specific industry needs and enhance practical skills [23][24].

Group 1 - The article discusses the importance of the autumn recruitment season, highlighting a student's experience of receiving an offer from a tier 1 company but feeling unfulfilled due to a desire to transition to a more advanced algorithm position [1] - The article encourages perseverance and self-challenge, emphasizing that pushing oneself can reveal personal limits and potential [2] Group 2 - A significant learning package is introduced, including a 499 yuan discount card for a year of courses at a 30% discount, various course benefits, and hardware discounts [4][6] - The focus is on cutting-edge autonomous driving technologies for 2025, particularly end-to-end (E2E) and VLA autonomous driving systems, which are becoming central to the industry [7][8] Group 3 - The article outlines the development of end-to-end autonomous driving algorithms, emphasizing the need for knowledge in multimodal large models, BEV perception, reinforcement learning, and more [8] - It highlights the challenges faced by beginners in synthesizing knowledge from fragmented research papers and the lack of practical guidance in transitioning from theory to practice [8] Group 4 - The introduction of a 4D annotation algorithm course aims to address the increasing complexity of training data requirements for autonomous driving, emphasizing the importance of automated 4D annotation [11][12] - The course is designed to help newcomers navigate the challenges of entering the field and to optimize their learning paths [12] Group 5 - The article discusses the emergence of multimodal large models in autonomous driving, noting the rapid growth of job opportunities in this area and the need for systematic learning platforms [14] - It emphasizes the importance of practical experience and project involvement for job seekers in the autonomous driving sector [21] Group 6 - The article mentions various specialized courses available, including those focused on perception, model deployment, planning control, and simulation in autonomous driving [16][18][20] - It highlights the importance of community engagement and support through VIP groups for course participants, facilitating discussions and problem-solving [26]

Core Viewpoint - The article reflects on the evolution of autonomous driving over the past decade, highlighting significant technological advancements and the ongoing need for innovation and talent in the industry [2][3][4]. Group 1: Evolution of Autonomous Driving - Autonomous driving has progressed from basic image classification to advanced perception systems, including 3D detection and end-to-end models [3]. - The industry has witnessed both failures and successes, with companies like Tesla, Huawei, and NIO establishing strong technological foundations [3]. - The journey of autonomous driving is characterized by continuous efforts rather than sudden breakthroughs, emphasizing the importance of sustained innovation [3]. Group 2: Importance of Talent and Innovation - The future of autonomous driving relies on a steady influx of talent dedicated to enhancing safety and performance [4]. - Innovation is identified as the core of sustainable business growth, with a focus on practical applications and real-world problem-solving [6]. - The article encourages a mindset of continuous learning and adaptation to keep pace with rapid technological changes [6]. Group 3: Educational Initiatives and Resources - The company has developed a series of educational resources, including video tutorials and courses covering nearly 40 subfields of autonomous driving [8][9]. - Collaborations with industry leaders and academic institutions are emphasized to bridge the gap between theory and practice [8]. - The article outlines various courses aimed at equipping learners with the necessary skills for careers in leading autonomous driving companies [9][10]. Group 4: Future Directions in Technology - Key technological directions for 2025 include end-to-end autonomous driving and the integration of large models [12][20]. - The article discusses the significance of multi-modal large models in enhancing the capabilities of autonomous systems [20]. - The need for advanced data annotation techniques, such as automated 4D labeling, is highlighted as crucial for improving training data quality [16].

Group 1 - The article discusses the recruitment of 10 outstanding partners for the "Autonomous Driving Heart" team, focusing on the development of autonomous driving-related courses, thesis guidance, and hardware development [2][3] - The main areas of expertise sought include large models/multi-modal large models, diffusion models, VLA, end-to-end systems, embodied interaction, joint prediction, SLAM, 3D object detection, world models, closed-loop simulation 3DGS, and large model deployment and quantized perception reasoning [3] - Candidates are preferred to have a master's degree or higher from universities ranked within the QS200, with priority given to those who have significant contributions in top conferences [4] Group 2 - The company offers various benefits including resource sharing for job seeking, doctoral studies, and studying abroad recommendations, along with substantial cash incentives and opportunities for entrepreneurial project collaboration [5][6] - Interested parties are encouraged to contact the company via WeChat for consultation regarding institutional or corporate collaboration in autonomous driving [7]