On June 22, addressing the challenges of deployment difficulties and limited adaptability of embodied intelligent robots in industrial environments, the team led by Associate Professor Zeng Long and Professor Feng Pingfa from Tsinghua Shenzhen International Graduate School presented a systematic conceptual framework for Embodied Intelligent Industrial Robots (EIIR), along with a knowledge-driven technological framework. This framework consists of five core modules: the world model, high-level task planner, low-level skill controller, simulator, and physical system. It aims to enable industrial robots to achieve task-level flexibility, marking a significant application of general artificial intelligence within the industrial sector. The team also elucidated the relationships between EIIR and related concepts such as AI, EI, and EIR, highlighting that EIIR necessitates three types of knowledge: natural language understanding, work environment comprehension, and operational object awareness. At present, certain technological modules within this framework have already been industrialized, yielding economic benefits.