Core Viewpoint - The article introduces a new course titled "World Models and Autonomous Driving Small Class," focusing on advanced algorithms in the field of autonomous driving, including general world models, video generation, and OCC generation [1][3]. Course Overview - The course is developed in collaboration with industry leaders and follows the success of a previous course on end-to-end and VLA autonomous driving [1]. - The course aims to enhance understanding and practical skills in world models, targeting individuals interested in the autonomous driving industry [11]. Course Structure - **Chapter 1: Introduction to World Models** - Discusses the relationship between world models and end-to-end autonomous driving, including historical development and current applications [6]. - Covers various types of world models, such as pure simulation, simulation + planning, and generation of sensor inputs and perception results [6]. - **Chapter 2: Background Knowledge of World Models** - Focuses on foundational knowledge, including scene representation, Transformer, and BEV perception [6][12]. - Highlights key technical terms frequently encountered in job interviews related to world models [7]. - **Chapter 3: General World Model Exploration** - Examines popular models like Marble from Li Fei-Fei's team, DeepMind's Genie 3, and Meta's JEPA, along with recent discussions on VLA + world model algorithms [7]. - **Chapter 4: Video Generation-Based World Models** - Concentrates on video generation algorithms, starting with Wayve's GAIA-1 & GAIA-2 and extending to recent works like UniScene and OpenDWM [8]. - **Chapter 5: OCC-Based World Models** - Focuses on OCC generation methods, discussing three major papers and a practical project that extends to vehicle trajectory planning [9]. - **Chapter 6: World Model Job Specialization** - Provides insights into the application of world models in the industry, addressing pain points and interview preparation for relevant positions [10]. Learning Outcomes - The course aims to equip participants with the skills to reach a level equivalent to one year of experience as a world model autonomous driving algorithm engineer [14]. - Participants will gain a comprehensive understanding of world model technologies, including video generation and OCC generation methods, and will be able to apply their knowledge in practical projects [14].