深度｜李飞飞：创办World Labs的初衷，就是想无所畏惧地解决空间智能问题，没有空间智能，AI将是不完整的

Core Viewpoint - The article discusses the insights of Fei-Fei Li, a prominent AI expert, on the development of spatial intelligence and its significance in AI, emphasizing the need for 3D world modeling to enhance AI capabilities [2][5][19]. Group 1: Spatial Intelligence - Spatial intelligence refers to the ability to understand, reason, interact with, and generate 3D worlds, which is fundamental to both human and animal cognition [5][9]. - The development of 3D world models is seen as a critical challenge in AI, with the potential to unlock numerous applications in design, navigation, and augmented reality [6][20]. - Li believes that without spatial intelligence, AI remains incomplete, as it is essential for interaction within the 3D world [9][19]. Group 2: Challenges in AI Development - Data acquisition and processing for creating 3D models pose significant challenges, as the availability of suitable data is not as abundant as in natural language processing [20]. - The complexity of delivering 3D experiences to users is greater than that of language, making productization more challenging [20]. - Li highlights the importance of integrating tactile data into AI systems, which has been underexplored but is crucial for enhancing robotic capabilities [16]. Group 3: Future of AI and Robotics - The future of robotics is envisioned as a coexistence with humans, where robots will take on various forms beyond humanoid shapes, optimizing for specific tasks [15][17]. - Li emphasizes the need for diverse backgrounds in AI teams to tackle the multifaceted challenges of spatial intelligence [32]. - The potential for AI to enhance human creativity in fields like design and content creation is seen as a promising area for future development [17][30]. Group 4: Personal Insights and Career Reflections - Li reflects on her career, particularly the creation of the ImageNet dataset, which played a pivotal role in advancing deep learning and AI [26][27]. - The journey of developing ImageNet involved significant challenges, including data collection and processing, which were crucial for training effective models [23][24]. - Li encourages young researchers to be fearless in their pursuits, emphasizing the importance of creativity and innovation in AI research [30][31].