World Models and Video Intelligence
This page tracks world models, video intelligence, 3D generation, and neural-computer style architectures.
Sources in this batch
- A video asks what world models are.
- Efficient Video Intelligence in 2026 surveys video-model efficiency.
- Microsoft TRELLIS.2 focuses on native compact structured latents for 3D generation.
- Vision Banana is a Google DeepMind source in this area.
- “Neural Computers” and LeWorldModel point toward architectures that blend representation learning, prediction, and environment modeling.
- An arXiv PDF in this batch likely belongs to this world-model/video-intelligence cluster and should be revisited for exact claims.
Research interest
The surprising angle is the possible convergence of video generation, JEPA-style predictive learning, 3D structured latents, and neural-computer abstractions. For a CS researcher, the key question is whether these systems learn actionable state representations or merely compress/generate perceptual streams. That distinction matters for robotics, planning, and embodied agents.
Open questions:
- Can learned video/world representations support counterfactual planning?
- Are structured 3D latents better interfaces for agents than pixels or text?
- What evals separate physical understanding from interpolation over video data?