Authors: Shuo Jiang and Jianxi Luo
Technology is essential to innovation and economic prosperity. Understanding technological changes can guide innovators to find new directions of innovation and thus make breakthroughs. In this work, we construct a technology fitness landscape via deep neural embeddings of patent data. The landscape consists of 1,757 technology domains and their respective improvement rates curated by Singh et al (2021) covering 95% of the patent database. In the landscape, we found a high hill related to information and communication technologies (ICT) and a vast low plain of the remaining domains. The landscape presents a bird’s eye view of the structure of the total technology space, providing a new way for users to interpret technology evolution with a biological analogy, and a biologically-inspired inference to the next innovation.
The location of each domain is aligned to the 2D embedding map (the interactive figure above), and the color represents the rate. The heights correspond to the improvement rates of different domains.
Each item in the matrix represents the number of domains belong to the corresponding subcategories. The matrix has been normalized by column (the sum of each column equals to 1). The categories in figure refer to the NBER subcategories. This figure reveals a clear pattern of technological theme shifts from the global peak to the low plain.