According to @drfeifei, the team showcased an interactive 3D world model aimed at learning robotic actions in dynamic, complex environments as their latest work, highlighting practical robotics learning applications for real-world settings (source: Fei-Fei Li on X, Jan 15, 2026). According to Wenlong Huang, PointWorld-1B is a large pre-trained 3D world model that can simulate an interactive 3D world in real time from a single image, emphasizing real-time inference from minimal visual input (source: Wenlong Huang on X). According to Wenlong Huang, the model predicts environment dynamics given RGB-D captures and robot actions, and further information is provided on the project page point-world.github.io (source: Wenlong Huang on X). According to Wenlong Huang, the work is from Stanford and NVIDIA, directly tying the release to academic research and compute hardware ecosystems often monitored by AI-focused traders (source: Wenlong Huang on X).