暑假就要结束了，开学季越来越多的同学联系峰哥和柱哥。有刚入行的研一小白，也有秋招激战正酣的研二/研 三的同学，也不乏打算转行自驾的小伙伴。很开心，通过自动驾驶之心和大家连接在一起，共同推进行业的发 展。 我们的愿景是让AI与自动驾驶走进每个有需要的同学。 『自动驾驶之心知识星球』目前集视频 + 图文 + 学习路线 + 问答 + 求职交流为一体，是一个综合类的自驾社 区，已经超过4000人了。 我们期望未来2年内做到近万人的规模。给大家打造一个交流+技术分享的聚集地，是 许多初学者和进阶的同学经常逛的地方。 社区内部还经常为大家解答各类实用问题：端到端如何入门？自动驾驶多模态大模型如何学习？自动驾驶VLA 的学习路线、数据闭环4D标注的工程实践。快速解答，方便大家应用到项目中。 更有料的是： 星球内部为大家梳理了近40+技术路线，无论你是咨询行业应用、还是要找最新的VLA benchmark、综述和学习入门路线，都能极大缩短检索时间。星球还为大家邀请了数十位自动驾驶领域嘉宾，都 是活跃在一线产业界和工业界的大佬（经常出现的顶会和各类访谈中哦）。欢迎随时提问，他们将会为大家答疑 解惑。 除了上面的问题，我们还为大 ...

研究生开学，很多同学都很迷茫。最近有个研一的新生找柱哥诉苦： 末9硕双非本。导师实验室传统上是做规控 的，这几年还在做基于机器学习的工业流程上的控制，除此之外小方向还有机器人的控制，多车辆车队控制。导 师现在让我们选择一个自己的发展方向，想咨询一下您觉得三年以后哪个方向能吃香一点。然后我们组规控可能 做的好一点，因为做了很多年了，但是看网上说规控不少失业的，岗位也越来越饱和...最近才看到我们自动驾驶 之心的技术社区，里面也有很多方向，想听听柱哥的建议... 这位同学刚入学就有了紧迫感，是好事。但也不用太担心，都说互联网下半场，现在也还朝气蓬勃，技术的发展 总是曲折的，所以自动驾驶行业能做的还有很多。你实验室有机器人、规控和车辆的底子，无论是具身智能还是 自动驾驶你都有的选。先从基础开始学起，大概半年的时间，在这期间也follow下星球内我们日常分享的技术前 沿，之后再去聚焦一些技术壁垒更高的方向，像VLA或者端到端后面转大模型或者具身也更容易。尽快把自己 的技术栈扩展和打牢才是重中之重。 如果你没有较强独立学习和搜索问题的能力，可以来我们的自驾社区，也 是目前国内最大最全的自驾学习平台【自动驾驶之心】知识星 ...

Core Viewpoint - The article highlights the evolution and growth of the company over the past year, emphasizing its transition from pure online education to a comprehensive service platform that includes hardware, offline training, and job placement services. The focus is on the advancements in the autonomous driving sector, particularly the impact of large models on new intelligent driving solutions [1]. Group 1: Business Development - The company has expanded its offerings to include hardware business, paper tutoring, and job placement services, marking a significant shift from its original online education model [1]. - The establishment of the "Autonomous Driving Heart Knowledge Planet" has been a major investment, creating a platform for industry, academia, and job-seeking interactions [1][3]. Group 2: Community Engagement - The company has successfully built a community that includes members from renowned universities and leading companies in the autonomous driving field, facilitating knowledge exchange and collaboration [14]. - Plans for future community engagement include hosting roundtable discussions with industry leaders and launching online sessions to address members' real-world challenges [1]. Group 3: Technical Resources - The company has compiled over 40 technical routes and invited numerous industry experts to provide insights and answer questions, significantly reducing the time needed for members to find relevant information [3]. - A comprehensive entry-level technical stack and roadmap have been developed for newcomers, while valuable industry frameworks and project plans are available for those already engaged in research [8][10]. Group 4: Job Opportunities - The community continuously shares job openings and career advice, aiming to create a complete ecosystem for autonomous driving [12]. - Members can freely ask questions regarding career choices and research directions, receiving guidance from experienced professionals [78].

Core Viewpoint - The article discusses the significant progress made in the field of autonomous driving and embodied intelligence over the past year, highlighting the establishment of various platforms and services aimed at enhancing education and employment opportunities in these sectors [2]. Group 1: Company Developments - The company has developed four key IPs: "Autonomous Driving Heart," "Embodied Intelligence Heart," "3D Vision Heart," and "Large Model Heart," expanding its reach through various platforms including knowledge sharing and community engagement [2]. - The transition from purely online education to a comprehensive service platform that includes hardware, offline training, and job placement services has been emphasized, showcasing a strategic shift in business operations [2]. - The establishment of a physical office in Hangzhou and the recruitment of talented individuals indicate the company's commitment to growth and industry engagement [2]. Group 2: Community and Educational Initiatives - The "Autonomous Driving Heart Knowledge Planet" has become the largest community for autonomous driving learning in China, with nearly 4,000 members and over 100 industry experts contributing to discussions and knowledge sharing [4]. - The community has compiled over 30 learning pathways covering various aspects of autonomous driving technology, including perception, mapping, and AI model deployment, aimed at facilitating both newcomers and experienced professionals [4]. - The platform encourages active participation and problem-solving among members, fostering a collaborative environment for learning and professional development [4]. Group 3: Technological Focus Areas - The article highlights four major technological directions within the community: Visual Large Language Models (VLM), World Models, Diffusion Models, and End-to-End Autonomous Driving, with resources and discussions centered around these topics [6][33]. - The community provides access to cutting-edge research, datasets, and application examples, ensuring members stay informed about the latest advancements in autonomous driving and related fields [6][33]. - The focus on embodied intelligence and large models reflects the industry's shift towards integrating advanced AI capabilities into autonomous systems, indicating a trend towards more sophisticated and capable driving solutions [2].

Core Insights - The article emphasizes the transition of autonomous driving technology from Level 2/3 (assisted driving) to Level 4/5 (fully autonomous driving) by 2025, highlighting the competitive landscape in AI, particularly in autonomous driving, embodied intelligence, and large model agents [2][4]. Group 1: Autonomous Driving Community - The "Autonomous Driving Heart Knowledge Planet" is established as the largest community for autonomous driving technology in China, aiming to serve as a training ground for industry professionals [4][6]. - The community has nearly 4,000 members and over 100 industry experts, providing a platform for discussions, learning routes, and job referrals [4][6]. - The community focuses on various subfields of autonomous driving, including end-to-end driving, world models, and multi-sensor fusion, among others [4][6]. Group 2: Learning Modules and Resources - The knowledge community includes four main technical areas: visual large language models, world models, diffusion models, and end-to-end autonomous driving [6][7]. - It offers a comprehensive collection of resources, including cutting-edge articles, datasets, and application summaries relevant to the autonomous driving sector [6][7]. Group 3: Job Opportunities and Networking - The community has established direct referral channels with numerous autonomous driving companies, facilitating job placements for members [4][6]. - Active participation is encouraged, with a focus on fostering a collaborative environment for both newcomers and experienced professionals [4][6]. Group 4: Technical Insights - The article outlines various learning paths and technical insights into autonomous driving, emphasizing the importance of understanding perception, mapping, planning, and control in the development of autonomous systems [4][6][24]. - It highlights the significance of large language models and their integration into autonomous driving applications, enhancing decision-making and navigation capabilities [25][26].

Core Viewpoint - The smart driving industry is experiencing significant growth, with companies willing to invest heavily in research and talent acquisition, indicating a robust job market and opportunities for new entrants [2][3]. Group 1: Industry Trends - The smart driving sector continues to attract substantial funding for research and development, with companies offering competitive salaries to attract talent [2]. - There is a noticeable trend of shorter technology iteration cycles in the autonomous driving field, with a focus on advanced technologies such as visual large language models (VLA) and end-to-end systems [7][11]. Group 2: Community and Learning Resources - The "Autonomous Driving Heart Knowledge Planet" aims to create a comprehensive community for knowledge sharing, focusing on academic and engineering challenges in the autonomous driving industry [3][11]. - The community has established a structured learning path covering various aspects of autonomous driving technology, including perception, planning, and control [13][15]. Group 3: Educational Offerings - The community offers a range of educational resources, including video courses, hardware tutorials, and live sessions with industry experts, aimed at both newcomers and experienced professionals [3][15]. - There are dedicated modules for job preparation, including resume sharing and interview experiences, to help members navigate the job market effectively [5][12]. Group 4: Technical Focus Areas - Key technical areas of focus include visual language models, world models, and end-to-end autonomous driving systems, with ongoing discussions about their integration and application in real-world scenarios [11][36]. - The community emphasizes the importance of understanding the latest advancements in algorithms and models, such as diffusion models and generative techniques, for future developments in autonomous driving [16][36].

Core Insights - The autonomous driving industry is experiencing significant changes, with many professionals transitioning to related fields like embodied intelligence, while others remain committed to the sector due to strong funding and high salaries for new graduates [2][6] - The article emphasizes the importance of networking and community engagement for knowledge acquisition and job preparation in the autonomous driving field [3][4] Group 1: Industry Trends - The autonomous driving sector continues to attract substantial investment, with companies willing to offer competitive salaries to attract talent [2] - The technology iteration cycle in autonomous driving is becoming shorter, indicating rapid advancements and a focus on cutting-edge technologies such as visual large language models (VLM) and end-to-end systems [8][12] Group 2: Community and Learning Resources - The "Autonomous Driving Heart Knowledge Planet" is highlighted as a leading community for professionals and students in the autonomous driving field, offering resources such as video courses, technical discussions, and job opportunities [4][14] - The community provides a structured learning path covering various aspects of autonomous driving technology, including perception, planning, and machine learning [19][21] Group 3: Technical Focus Areas - Key technical areas identified for 2025 include VLM, end-to-end systems, and world models, which are crucial for the future evolution of autonomous driving technology [8][43] - The community emphasizes the integration of advanced algorithms and models, such as diffusion models and 3D generative simulations, to enhance autonomous driving capabilities [15][22]