The Missing Data for Spatial Intelligence

Spatial data, specifically stereo imagery, serves as a critical foundation for training advanced AI world models by providing accurate geometric representations that monocular video lacks. While current foundation models rely heavily on flat 2D data, integrating stereo information allows AI to better understand depth, scale, and real-world physics, effectively grounding models in reality and reducing hallucinations. David Fattal, founder and CTO of Leah Inc., highlights that while synthetic data and 2D video are useful for pre-training, stereo data captures the "long tail" of messy, real-world conditions necessary for general-purpose intelligence. The transition toward ubiquitous 3D content hinges on hardware advancements that enable seamless stereo capture and visualization on consumer devices like smartphones and laptops, moving beyond the limitations of expensive, tethered headsets. This shift creates a data flywheel where increased 3D content creation accelerates the development of more capable, spatially aware AI.