General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual environments to decision-making systems. Recently, the emergence of the Sora model has attained significant attention due to its remarkable simulation capabilities, which exhibits an incipient comprehension of physical laws. In this survey, we embark on a comprehensive exploration of the latest advancements in world models. Our analysis navigates through the forefront of generative methodologies in video generation, where world models stand as pivotal constructs facilitating the synthesis of highly realistic visual content. Additionally, we scrutinize the burgeoning field of autonomous-driving world models, meticulously delineating their indispensable role in reshaping transportation and urban mobility. Furthermore, we delve into the intricacies inherent in world models deployed within autonomous agents, shedding light on their profound significance in enabling intelligent interactions within dynamic environmental contexts. At last, we examine challenges and limitations of world models, and discuss their potential future directions. We hope this survey can serve as a foundational reference for the research community and inspire continued innovation. This survey will be regularly updated at: https://github.com/GigaAI-research/General-World-Models-Survey.

翻译：通用世界模型是实现通用人工智能（AGI）的关键路径，作为从虚拟环境到决策系统等多种应用的基础。近期，Sora模型的出现因其卓越的模拟能力而备受关注，展现出对物理规律的初步理解。在本综述中，我们全面探索了世界模型的最新进展。我们的分析贯穿视频生成领域的前沿生成方法，其中世界模型作为关键构建模块，促进了高度逼真视觉内容的合成。此外，我们审视了新兴的自动驾驶世界模型领域，细致描绘了其在重塑交通与城市出行中不可或缺的作用。进一步地，我们深入探讨部署于自主智能体中的世界模型所固有的复杂性，揭示了其在动态环境背景下实现智能交互的深远意义。最后，我们考察了世界模型面临的挑战与局限，并讨论了其潜在未来方向。我们希望本综述能够为研究社区提供基础参考，并激发持续创新。本综述将在以下链接定期更新：https://github.com/GigaAI-research/General-World-Models-Survey。