数据工厂的构成、建设模式和运营机制研究OA

High-quality datasets are the core fuel for training large AI models.Currently,the construction of high-quality datasets is mainly carried out by AI enterprises themselves,which presents the characteristics of fragmentation,workshop-style operation and non-standardization,making it difficult to meet the rapid development needs of large AI models.Drawing on the development patterns of resource-based infrastruc-ture such as water and power plants,and combining domestic and international best practices in facility-based production,this paper proposes the concept of"data factory",defining it as a production facility specifically designed for the application of large AI models and for the facility-based,large-scale construction of high-quality datasets.The paper systematically expounds the three-level architecture system of the data facto-ry,which consists of storage workshop,production workshop,and pilot workshop.Four construction models and four operation mechanisms are proposed,providing theoretical support and practical references for promoting the facility-based and large-scale supply of high-quality datasets.