Robots stagger and run on the field, not only testing their "leg strength", but also testing society's cognition, patience and judgment. The unpredictable starts are a microcosm of the implementation of the embodied intelligent industry: it seems to be staggering, but it is actually down-to-earth and powerful.

  In the spring of Yizhuang, Beijing, a "robot half horse" has become a scientific and technological topic that the entire network is concerned about. Some people joked that robots were “clumsy”, while others lamented that they were “very much like the first time humans learned to learn to walk.” Some robots fell as soon as they started, some people continued to move forward "to their heads" and many people ran to the finish line. This event full of technological colors and dramatic tension is not a simple "show", but a head-on confrontation between technology and reality. The unpredictable starts are a microcosm of the implementation of the embodied intelligent industry: it seems to be staggering, but it is actually down-to-earth and powerful.

  Today's embodied robot is no longer a conceptual model in the laboratory, it is moving towards real scenes step by step. In recent years, we have witnessed the rapid advancement of robotics, especially humanoid robots, which have begun to make their mark in logistics, warehousing, manufacturing, and service industries. Behind these advances is the coordinated evolution of algorithms, computing power and ontology structure. With the deep empowerment of big models in perception, planning and decision-making, the embodied intelligent "brain" and "body" are "integrating knowledge and action". Although their actions are still not flexible enough and their efficiency needs to be improved, they are themselves a huge breakthrough in moving from "active" to "useable" and becoming pioneers in the implementation of technology.

  An engineer introduced that once a robot falls, the background can collect thousands of real-time data, providing valuable samples for optimizing gait algorithms and fault tolerance mechanisms. These data are not records of failure, but the starting point for success. Every "imperfect" action is a necessary path to a higher level of intelligence.

  Nowadays, we are more eager to find the "next star enterprise" than ever. But the question is, do we have the vision to identify early value? Is there a mechanism for accommodating imperfections? Are you ready for patient waiting “years and days”? In a sense, today's embodied robots are on the road that big models took when they started. Looking back at the "domestic big model breakthrough" that people are talking about is the result of correcting the direction and accumulating potential energy from repeated failures. Only by experiencing repeated integration of technology and scenarios can big models move from concept to product and from laboratory to daily life. This development path is also applicable to embodied intelligence: not only should we pay attention to the data and reports in front of us, but we should also see the "seed technologies" that can still get up during falls and keep moving forward in experiments.

  "Where does the next DeepSeek come from?" If we really care about this issue, we need to turn our attention to prototypes that are not perfect enough, and even seem "won't defeat". From open source models in the laboratory to humanoid robots outside the laboratory, it seems that the technical routes are different, but in fact it points to the same topic: what is the general capability that the industry really needs. Imperfect robots, immature chips, and uncertain industrial paths may not have a clear answer yet, but the problem they are solving is the foundation of the future industry. Every breakthrough in underlying capabilities may give birth to a new enterprise; every time it is not optimistic, it may also form the prototype of an industry.

  Robots stagger and run on the field, not only testing their "leg strength", but also testing society's cognition, patience and judgment. In this schedule for the future industry, it does not depend on who starts perfectly, but on who sets out earlier, is not afraid of falling, and is able to accumulate strength to move forward through trial and error. (Han Bingzhi)

[Editor in charge: Ran Xiaoning]