Why it matters
Jason Ma’s publisher notes describe using a video-based progress model to find robot failures, then collecting human demonstrations of recovery and fine-tuning the policy. Napkin folding exposes both bad grasps and quality failures that a nominal task-completion measure can miss. The reported 24-hour success rate belongs to a particular folding evaluation, with no sample size supplied in the notes. Transfer to a new site and recovery from unfamiliar mistakes require separate evidence.
My takeaway: Define acceptable output quality and log interventions, failures and recovery time during extended runs. Use detected failure states to target new demonstrations. Evaluate transfer on sites excluded from adaptation data, and avoid extrapolating one task’s success rate to uninterrupted operation or general robot safety.