MATEC Web of Conferences (Jan 2024)

Industrial large model: A survey

  • Zhou Jiehan,
  • Cao Yang,
  • Lu Quanbo,
  • Zhang Yan,
  • Liu Cong,
  • Zhang Shouhua,
  • Qu Junsuo

DOI
https://doi.org/10.1051/matecconf/202440110009
Journal volume & issue
Vol. 401
p. 10009

Abstract

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Industrial large models are attracting significant attention for their roles in improving industrial production efficiency and product quality. This paper categorises and reviews current research on industrial large models in three main areas: pre-training, fine-tuning, and Retrieval-Augmented Generation (RAG). It also introduces a generic platform for industrial large models, including a model for interaction between industrial large and small models. Furthermore, it specifies the application areas of large industrial models within product lifecycle management, and discusses the challenges encountered during their development.