Long-WAM: Does Longer Visual Context Improve Real-Time Robot Control?

Podcast: Embodied AI 101 · Shaoqing Tan

Opublikowano: 2026-10-10

Can longer video histories make robot manipulation more reliable without making control too slow? This episode examines Long-WAM to clarify when temporal context helps, what autoregressive pretraining contributes, and how to interpret the deployment evidence. We focus on three questions: whether the context-scaling study isolates the effect of pretraining, whether predicting future visual latents improves actions enough to justify its cost, and what the reported inference latency does—and does not—measure. We connect the work to Fast-WAM's investigation of test-time imagination, LingBot-VA 2.0's causal pretraining, and DOMINO's dynamic manipulation benchmark. The discussion spans simulation experiments and physical manipulation on Unit...