摘要
当前业内外已形成共识,数据是人工智能(Artificial Intelligence,AI)发展的关键要素。文章尝试梳理数据治理的发展脉络,并从数据治理视角总结AI的发展现状;同时,以AI生命周期为参考,归纳AI发展中的源数据采集、预训练、微调、推理运行和评估五个关键环节的数据治理成果,最后展望其未来发展态势。
There is now a consensus both within and outside the industry that data is a key factor in the development of artificial intelligence(AI).The article attempts to outline the evolution of data governance and summarize the current state of AI development from a data governance perspective.Additionally,using the AI lifecycle as a reference,it categorizes the data governance achievements in five critical stages of AI development:source data collection,pre-training,fine-tuning,inference operation,and evaluation.Finally,it looks ahead to future trends in this field.
作者
刘波
王磊
阮洪新
崔润兴
刘建民
LIU Bo;WANG Lei;RUAN Hongxin;CUI Runxing;LIU Jianmin(Yunding Technology Co.,Ltd.,Jinan Shandong 250000,China;Yankuang Energy Xinglongzhuang Coal Mine,Jining Shandong 272102,China)
出处
《信息与电脑》
2026年第4期55-57,共3页
Information & Computer
关键词
人工智能
数据
数据治理
artificial intelligence
data
data governance
