Intern World Foundational Models Task-Agnostic Latent Representations H/F

Summary World Foundational Models (WFMs) are self-supervised AI models trained on vast datasets of sensors sequences (visual, sound, Lidar) to learn the underlying physics, temporal dynamics, and spatial structures of physical environments.

Rather than predicting full-resolution, high-dimensional pixels for future states-which is computationally expensive and spends capacity on irrelevant noise like background texture changes-modern WFMs learn task-agnostic latent representations.

The goal of t…