Sunday Robotics hits 99% laundry-folding success, no tuning

Sunday Robotics' ACT-2 folded laundry correctly 99.1% of the time across 785 attempts in homes it had never seen, per Import AI 466. It handled nine garment types with zero home- or garment-specific tuning.

The 99.1% figure matters because manual tuning is what's kept household robots stuck in demos, never products. Zero-shot transfer across new homes and garments is the difference between the two.

Anthropic's own numbers point the same way. Opus 4.7 completed a robot task in 9 minutes, down from 181 minutes on earlier technology, according to the same newsletter.

Sunday's recipe, per Import AI: scale pretraining, then hill-climb with a small amount of in-house data. Sunday found that as its pretrained model gets stronger, gains from that small dataset get more transferable, not less.

Clark's read: the bitter lesson has arrived for robotics. Sunday rode a general-purpose model up its scaling curve, doing little robot-specific engineering on top. If he's right, the next leap in home robots comes from the next foundation model release, not new robotics research. Worth watching whether Sunday's transfer gains keep climbing as pretrained models get stronger, or hit a wall that more compute doesn't fix.