英伟达Jim Fan：“世界建模”是新一代预训练范式

Core Insights - The emergence of world modeling as a new pre-training paradigm is anticipated to significantly impact robotics and multimodal AI by 2026 [1][2][20] - World modeling involves predicting the next reasonable state of the world given an action, expanding beyond traditional AI video applications [5][20] - The shift from language-centered models to vision-centered models is expected to enhance physical AI capabilities [6][10][30] Group 1: World Modeling Definition and Implications - World modeling is defined as predicting the next reasonable world state based on a given action, which is crucial for advancements in physical AI [5][20] - The current hype around world models is primarily focused on AI video, but a breakthrough in physical AI is expected by 2026 [5][20] - A new reasoning form is anticipated, emphasizing visual space thinking chains rather than language-based reasoning [16][17] Group 2: Technical Challenges and Developments - The transition from pixel-based to physical action generation in large world models presents significant challenges, including geometric consistency and real-time response [28] - Visual reasoning is gaining attention, suggesting that reasoning does not necessarily depend on language but can be achieved through visual simulations [28][30] - The need for high-frequency response in robotics highlights the importance of reducing latency in large world models [28] Group 3: Industry Trends and Investments - Major players like Google and NVIDIA are investing in world modeling technologies, indicating a competitive landscape in virtual gaming, video, and physical robotics [26][31] - Recent funding activities, such as World Labs seeking a valuation of approximately $5 billion and AMI Labs potentially reaching $3.5 billion, reflect rapid commercial advancements in this field [31]