Deep learning of artificial intelligence and information digitization model

Artificial intelligence (AI) deep learning capabilities and information digitization processes are studied in this work to reveal the underlying mechanisms of information transformation and optimization． Self-cognitive learning in AI, dynamic learning processes, and interactive information transformation mechanisms are elaborated． A model for information digitization is constructed． Deep learning in AI could achieve information transformation and optimization through symbolic processing and probabilistic mapping． Digital technologies could convert information on physical-world activities into computable digital symbols, and the central operational logic of AI in dynamic information organization lies in establishing a dynamic correspondence among data, resource allocation, and economic decision-making． The process of how generated information shapes future actions is examined, to un-cover fundamental principles of digital creation of productive forces by AI． This work provides theoretical insights into the new productive forces in the intelligent economy, but also strengthens the theoretical framework of the intelligent digital economy． Strategic recommendations are proposed for the development of China’s intelligent economy．