<b>The Dynamics of Science-Industry Knowledge Transfer During the Emergence of Deep Learning</b>

We consider the dynamics of science-industry knowledge transfer during the 30-year emergence of deep learning. Deep learning constituted a paradigm shift in artificial intelligence and has been identified as the only true breakthrough in the 70-year history of the field. Using patent-to-paper citations as an indicator of knowledge transfer, we examine the factors that affect the likelihood that private technology developers absorb and build upon the research of pioneer scientists Geoffrey Hinton, Yoshua Bengio, and Yann LeCun. The data are 18,009 AI patent families. (2023-05-28)本研究考察深度学习兴起的30年间，学界与产业界之间的知识转移动态。深度学习堪称人工智能领域的范式转变，且被公认为该领域70年发展历程中唯一真正意义上的突破性进展。本研究以专利引用论文（patent-to-paper citations）作为知识转移的衡量指标，探究影响私营技术研发主体吸收并拓展杰弗里·辛顿（Geoffrey Hinton）、约书亚·本吉奥（Yoshua Bengio）与扬·勒丘恩（Yann LeCun）三位先驱科学家研究成果的可能性的各类因素。本研究数据集涵盖18009个人工智能专利族。（2023-05-28）