（本文作者为 Chelsea_Sun，钛媒体经授权发布）

NextFin News — Wang Xingxing is moving his timeline. In August, speaking the day after Unitree’s STAR Market debut, he placed a true “ChatGPT moment” for embodied machines somewhere between a few years and a decade—defined as a robot that could enter an unfamiliar home and finish most daily tasks on voice or text alone. In Hangzhou on October 22, at the World Physical AI Conference and Unitree partner summit, he struck a sharper note: physical AI already shows signs of being “broken through,” with a decisive step possible in one to two years, or two to three at the outside.

The bottleneck he named did not change. Models must align what they predict with what motors, fingers and imperfect sensors actually do in the real world. That alignment problem—inputs and outputs that drift by centimeters and milliseconds—still separates choreography from chores. What shifted was his reading of the curve. Frontier software labs, he said, have in some internal sense already reached model self-evolution: systems that write code, gather data and improve with only light human steering. The lag the public feels is diffusion, which he still put at five to ten years from lab breakthrough to everyday use.