# Cao Ting says embodied AI is now chasing self-evolution as data factories cool

> Original title: 清华曹婷：具身今年才追自进化，我们已在这条路上走很远了 | 世界模型 50 人

- Source: Leiphone
- Published: 2026-11-12T07:11:00.000Z
- Bad Influence: https://badinfluence.news/items/acgf7ncivvbskie1zjyv8dzvg
- Original: https://www.leiphone.com/category/ai/YcIBZiMtehhzYJsR.html

## Summary

Tsinghua AIR professor Cao Ting tells Leiphone that robots trained offline still fail in real settings, so teams are turning to in-context learning. She says her group's Zeva and Zeva-Ego models extract action-effect pairs from video, and that factory deployment still relies on fine-tuning for 99% precision. Zeva-Ego was trained on about 10K hours of unlabeled ego data, and she argues physical self-improvement is needed for robots to learn beyond their training data.