游戏世界可以实时生成，不用再手动搭建了
游戏开发通常需要大量人力手工构建场景，成本高且难以修改。AlayaWorld 是一个开源框架，它让 AI 根据玩家操作实时生成游戏世界——你往前走，AI 就生成前方的画面；你施法，AI 就生成法术效果。它基于游戏录像和真实视频训练，能模拟物理和视觉规律，支持自由探索、战斗、召唤怪物等交互。虽然目前还无法直接用于商业游戏，但它展示了未来游戏可能不再需要预先建模，而是像聊天一样动态生成。
📄 原文摘要(英文)
Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and expensive to modify after deployment. Recent advances in video world models offer a fundamentally different paradigm. Rather than explicitly authoring every component of a virtual environment, these models autoregressively synthesize future observations conditioned on the current world state and user interactions, enabling playable worlds to be generated online. Trained on both gameplay recordings and real-world videos, they can capture diverse visual appearances and physical dynamics, opening new opportunities for interactive applications beyond gaming, including embodied intelligence. In this paper, we present AlayaWorld, a full-stack open-source framework for building interactive generative worlds. AlayaWorld enables open-ended real-time interaction, allowing users to freely navigate and perform diverse actions such as combat, spell casting, and monster summoning. The framework unifies the complete development-from data preparation model architecture, model training, inference acceleration, and deployment-within a modular and extensible architecture. Alongside the framework, we release reproducible pipelines, reference implementations, evaluation tools, and comprehensive documentation, establishing a practical foundation for future research and real-time applications of generative world models.