<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)本研究聚焦深度学习崛起的30年历程中，科研与产业间的知识转移动态规律。深度学习堪称人工智能领域的范式革新，且被学界认定为该领域70年发展史上唯一真正意义上的突破性进展。本研究以专利引用论文作为知识转移的衡量指标，探讨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概率的各类因素。本次研究的数据集包含18009个人工智能专利族。（2023-05-28）