为什么蔚来会押注世界模型？

Core Insights - The article discusses the recent promotion of NIO's NWM 2.0, highlighting its positive reception and the potential of world models in intelligent driving [1] - It emphasizes that the true limit of intelligent driving lies in world models, which utilize video as a core component to understand spatiotemporal and physical laws, enabling machines to comprehend environments like humans do [1] Group 1: World Model Concept - World models address spatiotemporal cognition, while language models focus on conceptual cognition, with the former being more effective in modeling the real world's four-dimensional space-time [1] - The article mentions that many AI giants are developing general world models, including projects like Li Feifei's Marble, Yann LeCun's V-JEPA 2, and DeepMind's Genie 3 [1] Group 2: Challenges in Understanding World Models - The definition of world models remains vague, leading to confusion among newcomers in the field, who often spend significant time navigating challenges without clear guidance [1] - The article notes that understanding world models and completing tasks like data generation and closed-loop simulation can be particularly difficult for beginners [1] Group 3: Course Overview - A course is being offered to help individuals understand the world model domain in autonomous driving, featuring insights from industry algorithm experts [2][6] - The course will cover various aspects of world models, including their historical development, application cases, and different schools of thought within the field [6][10] Group 4: Course Structure - The course consists of six chapters, starting with an introduction to world models and their connection to end-to-end autonomous driving [6] - Subsequent chapters will delve into background knowledge, discussions on general world models, video generation-based models, OCC generation models, and industry applications [6][8][9][10] Group 5: Expected Outcomes - The course aims to equip participants with the skills to reach a level comparable to a world model autonomous driving algorithm engineer within a year [14] - Participants will gain a deeper understanding of key technologies such as BEV perception, multimodal large models, and generative models, enabling them to apply their knowledge in practical projects [14]