Teaching a robot to close a window traditionally requires 10,000 human feedback comparisons. That's three days of tedious labor—per task. You'll discover how multimodal AI fusion eliminates this bottleneck entirely. Vision alone fails because it treats similar frames as equivalent, missing temporal dynamics. Language alone hallucinates success based on commands. But together, with smart conflict resolution using Probabilistic Soft Logic, they become reliable synthetic teachers. The result? Zero-shot robotics training. No human labels required. This is how foundation models are finally making robotics scalable.

Topics Covered

- The human-in-the-loop bottleneck (10,000 labels per task!)

- Why vision alone fails (treats similar frames as equal)

- Why language alone fails (hallucinates success based on commands)

- Multimodal fusion: how disagreement reveals truth

- PSL (Probabilistic Soft Logic) for conflict resolution

- Zero-shot robotics training

- Foundation models as teachers