智源研究院王仲远：世界模型的关键是真正预测下一个状态

Core Insights - The term "World Model" has gained significant attention in the AI field, representing a shift from mere recognition and generation to understanding and predicting the dynamics of the world [2] - Companies are seeking new growth points as the benefits of large models diminish, with DeepMind, OpenAI, and others exploring interactive 3D worlds and robotics [2] - The release of the Emu3.5 multimodal world model by the Zhiyuan Research Institute marks a potential breakthrough in AI, emphasizing the importance of multimodal and world models for future growth [2][3] Group 1 - The Emu3.5 model is trained on over 10 trillion tokens of multimodal data, including 790 years of video data, and has a parameter scale of 34 billion [3] - The "Discrete Diffusion Adaptive (DiDA)" inference method enhances image generation speed by nearly 20 times while maintaining high-quality output [3] - Emu3.5 achieves breakthroughs in three dimensions: understanding higher-level human intentions, simulating dynamic worlds, and providing a cognitive basis for AI-human interaction [3] Group 2 - The core of the world model is not merely video generation but understanding causal and physical laws, essential for tasks like predicting the outcome of robotic actions [3][4] - Emu3.5 supports embodied intelligence and can generate multimodal training data, showcasing an innovative architecture from a Chinese research team [4] - The evolution from Emu3 to Emu3.5 enhances AI's physical intuition and cross-scenario planning capabilities, indicating a future where AI understands the world and acts within it [4]