JD Industry Unveils Industrial World Model at China International Industry Fair

People's Daily reported that JD Industry released an industrial world model at the 26th China International Industry Fair. This launch extends the enterprise model framework from cognitive understanding of industrial supply chains to interfacing directly with the physical world. The model addresses requirements across manufacturing, equipment operation and maintenance, logistics circulation, and quality inspection to deliver forward-looking decisions. Its core technology incorporates model training algorithms alongside deep computational inference optimization with AMD, leveraging JD Industry industrial data, industry knowledge, and operational workflows to deliver an industrial vertical world model. Combining AMD capabilities in high-performance computing and edge deployment, the system explores industrial applications capable of on-site status understanding, dynamic deduction, and risk prediction. According to JD Industry, initial deployments will focus on industrial safety warnings and human-machine collaboration scenarios, driving a shift from post-incident handling toward proactive early warnings. The company technical head stated that the next stage for industrial artificial intelligence moves from centralized analysis toward edge real-time decisions, equipping complex operating sites with forward-looking perception capabilities. At the event, the China Industrial Internet Research Institute and JD Industry jointly issued a research study on evaluating enterprise value driven by artificial intelligence. The study introduces a scenario-oriented quantitative assessment framework, shifting evaluation perspectives from artificial intelligence adoption levels toward driven capability and value while detailing four specific calculation stages for corporate assessments.

This approach drives industrial artificial intelligence from centralized analysis toward edge real-time decisions, enabling local risk anticipation, change deduction, task comprehension, and assisted decision-making while reducing response latency, reinforcing data security, and increasing deployment flexibility.