马斯克旗下xAI加入“世界模型”竞赛，“视觉模型”会是下一个“大语言模型”吗？

Core Viewpoint - The competition in artificial intelligence is shifting from text-based models to "world models" that can understand and simulate the physical world, with xAI entering the race alongside major players like Google and Meta [2][3][4]. Group 1: xAI's Entry and Strategy - xAI has hired AI experts from Nvidia to focus on the development of world models, which are trained on vast amounts of video and robotic data to understand physical laws [3][6]. - The first commercial application planned by xAI for world models is in the gaming sector, aimed at generating interactive 3D environments, signaling a clear path for commercialization [6][8]. - xAI is actively recruiting for its "omni team" with salaries ranging from $180,000 to $440,000, indicating a strong commitment to creating advanced AI experiences beyond text [8]. Group 2: Advancements in Video Models - Google researchers predict that future video models will become as intelligent as language models, showcasing the potential for significant advancements in AI capabilities [4][11]. - Video models are beginning to unlock surprising abilities through "next frame prediction," similar to how language models learn additional skills through simple tasks [11][14]. - The development of smarter video models could lead to the creation of highly capable robotic agents, enhancing the interaction between AI and the physical world [15]. Group 3: Challenges and Industry Perspectives - Despite the promising outlook, the path to world models is fraught with challenges, particularly the high costs associated with acquiring and processing sufficient training data [17]. - Industry experts express skepticism about AI's ability to address fundamental issues in gaming, emphasizing the need for leadership and vision rather than just technical advancements [17]. - The entry of xAI into the world model competition adds momentum to the shift from digital information processing to the simulation and interaction with complex physical realities [18].