摘要
通过研究人工智能(artificial intelligence,AI)深度学习功能及信息数字化转换过程,揭示了二者内在的信息变换与优化机制,系统阐释了AI自我认知学习、动态学习,以及信息交互变换机制,并构建了信息数字化模型.结果表明:AI深度学习借助符号处理与概率映射,实现了信息变换与优化;数字化技术将物理世界的活动信息转化为可计算的数字符号,AI的运行逻辑是以信息动态组织为核心,使得数据信息与资源配置、经济决策动态对应.通过创新信息知识作用于未来行为,获得AI数字化创造生产力的深层原理,以期为理解智能经济中的新生产力提供理论参考,为智能数字经济提供理论支撑,并对中国智能经济发展提出建议.
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.Selfcognitive 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 uncover 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.
作者
张永林
姜恒
ZHANG Yonglin;JIANG Heng(School of Statistics,Beijing Normal University,Beijing,China;School of Economics and Management,Tsinghua University,Beijing,China)
出处
《北京师范大学学报(自然科学版)》
北大核心
2025年第4期591-597,共7页
Journal of Beijing Normal University(Natural Science)
基金
国家社科基金重点资助项目(20AJY001)
教育部规划基金资助项目(18YJA790110)。
关键词
人工智能
深度学习
信息交互变换
数字化模型
artificial intelligence
deep learning
information interactive transformation
digitization model
