Core Viewpoint - The article discusses the launch of World Labs' latest spatial intelligence model, Marble, which allows users to generate persistent and navigable 3D worlds from images or text prompts, marking a significant advancement in spatial intelligence technology [1][2]. Summary by Sections Marble's Features and Comparison - Marble shows significant improvements over similar products in geometric consistency, style diversity, world scale, and cross-device support, allowing users to truly "walk into" AI-generated spaces [2]. Li Feifei's Vision and World Model Narrative - Li Feifei's approach emphasizes a transition from language understanding to world understanding, culminating in spatial intelligence as a pathway to AGI (Artificial General Intelligence) [3][6]. Limitations of LLMs - While acknowledging the achievements of large language models (LLMs), Li Feifei highlights their limitations in understanding the three-dimensional world, asserting that true intelligence requires spatial awareness [5][7]. The Necessity of Spatial Intelligence for AGI - Spatial intelligence is deemed essential for AGI, as the real world is inherently three-dimensional, and understanding it requires more than just two-dimensional observations [16]. Evolution of AI Learning Paradigms - The article outlines three phases of AI learning evolution: supervised learning, generative modeling, and the current focus on three-dimensional world models, emphasizing the importance of data, computation, and algorithms [21][24]. Data Strategy for World Models - A mixed approach to data collection is necessary for training world models, combining real data acquisition, reconstruction, and simulation to overcome the scarcity of high-quality three-dimensional data [26]. Practical Applications and Development Path - The initial focus for Marble's application is on content production, transitioning to robotics and AR/VR, with an emphasis on creating interactive 3D worlds for various industries [29][30].