The Bottleneck of Spatial AI: Why 3D Model Generation Lags Behind Text AI

Spatial AI''s potential to merge VIRTUAL objects seamlessly with reality faces a critical obstacle: the cumbersome process of 3D model creation. Unlike text generation tools like ChatGPT, which produce outputs instantly, building accurate 3D models remains slow, expensive, and technically demanding.

The current workflow requires thousands of multi-angle images, meticulous labeling, and complex algorithm training—resources beyond the reach of many developers and startups. Depth perception, a natural human ability, must be artificially replicated through sensors and detectors, further complicating the process.

This bottleneck stifles innovation in augmented reality applications and autonomous systems. Until 3D model generation achieves the accessibility of large language models, spatial AI''s adoption will remain constrained by technical and financial barriers.