The significance, challenges and opportunities of driving innovative development in manufacturing industry with artificial intelligence technologies including large language models were explored. The technological system of large language models was analyzed, its basic engineering concepts were clarified, and the pan-${\mathrm{L}}_{\mathrm{C}}$ theory-a scientific explanation for next token prediction-was presented. Based on the theory, the causes and consequences of some weird behaviors of large language models were explained, giving a more comprehensive and in-depth understanding of large language models. On the basis, three main requirements for artificial intelligence technologies in manufacturing industry were sorted out, and the core difficulties in the integration of large language models and the artificial intelligence brute-force technology were revealed. A closedness-based solution is proposed for the construction of artificial intelligence systems in manufacturing sectors, such that these systems satisfy the main requirements of specialization, logical validity and knowledge ability, as well as explainability and controllability. Finally, the trend of shifting from "industrial application of new technologies" to "sector innovation driven by new technologies" in the high-quality development of manufacturing industry is discussed briefly.

large language models  /  artificial intelligence  /  explainability  /  manufacturing industry  /  sector-oriented artificial intelligence  /  sector innovation