4000人的自动驾驶社区，开学季招生了！！！

Core Viewpoint - The article emphasizes the establishment of a comprehensive community focused on autonomous driving technology, aiming to provide valuable resources and networking opportunities for both beginners and advanced learners in the field [1][3][12]. Group 1: Community Structure and Offerings - The community has been focusing on nearly 40 cutting-edge technology directions in autonomous driving, including multimodal large models, VLM, VLA, closed-loop simulation, world models, and sensor fusion [1][3]. - The community consists of members from leading autonomous driving companies, top academic laboratories, and traditional robotics firms, creating a complementary dynamic between industry and academia [1][12]. - The community has over 4,000 members and aims to grow to nearly 10,000 within two years, serving as a hub for technical sharing and communication [3][12]. Group 2: Learning and Development Resources - The community provides a variety of resources, including video content, articles, learning paths, and Q&A sessions, to assist members in their learning journey [3][12]. - It has organized nearly 40 technical routes for members, covering various aspects of autonomous driving, from entry-level to advanced topics [3][12]. - Members can access practical solutions to common questions, such as how to start with end-to-end autonomous driving and the learning paths for multimodal large models [3][12]. Group 3: Networking and Career Opportunities - The community facilitates job referrals and connections with various autonomous driving companies, enhancing members' employment opportunities [8][12]. - Regular discussions with industry leaders and experts are held to explore trends, technological directions, and challenges in mass production [4][12]. - Members are encouraged to engage with each other to discuss academic and engineering-related questions, fostering a collaborative environment [12][54]. Group 4: Technical Focus Areas - The community has compiled extensive resources on various technical areas, including 3DGS, NeRF, world models, and VLA, providing insights into the latest research and applications [12][27][31]. - Specific learning paths are available for different aspects of autonomous driving, such as perception, simulation, and planning control [12][13]. - The community also offers a detailed overview of open-source projects and datasets relevant to autonomous driving, aiding members in practical applications [24][25].