# Patent Portfolio Analysis of the Synergy between Machine Learning and Photonics
## 5 Conclusions  
### Discussion and Implications  
This study used correspondence analysis and cluster analysis to explore the mainstream technologies of machine learning in photonics and conduct patent portfolio analysis. The empirical results indicate that the mainstream technologies include image data and electric digital data processing, optical elements, wireless communication networks, and healthcare informatics and diagnosis; these technologies are not located within a specific field. In addition, the main developers of machine learning in photonics are leading companies of information and communication technology (ICT), wafers, and smart software and services. These companies include AT&T Intellectual Property, Intel Corporation, International Business Machines Corporation, Microsoft Technology Licensing, and Samsung Electronics Co., Ltd. Magic Leap focuses on augmented reality technologies that map the light field into the retina. California Institute of Technology and Leland Stanford Junior University (Stanford University) (Stanford, CA, USA) are known in academia for their natural sciences, engineering, and entrepreneurial atmospheres. HeartFlow, Inc. and Align Technology Inc. are devoted to using deep learning technologies to develop innovative medical materials. In conclusion, companies concerned with ICT, wafers, and medical materials, along with academia, all play a crucial role in the development of new technologies of machine learning in photonics. Governments should consider allocating more research funds to academia to support technological developments in this field. Figure 4: Number of patents and papers in 2019 and 2020. A field that is being developed by more companies is more competitive. Align Technology Inc., California Institute of Technology, HeartFlow, Inc., Magic Leap, Samsung Electronics Co., Ltd., and Stanford University are all investing in research in image data processing and optical elements, systems, or apparatuses. Therefore, these fields are more competitive. The main company investing in research and development in wireless communication networks is AT&T Intellectual Property, which signifies that this field is relatively less competitive. Conventional information technology companies such as International Business Machines Corporation, Intel Corporation, and Microsoft Technology Licensing focus on electric digital data processing and specific computational models, such as computer systems based on biological models. The analysis demonstrated that the synergy between the technological development of machine learning and photonics is centralized on optical communication equipment, smart computing, and medical applications. The use of machine learning and photonics increased communication efficiency and improved the performance of artificial intelligence and quality of medical diagnosis. In addition, the patent portfolio positioning analysis demonstrated that academic institutions among the top ten assignees, such as California Institute of Technology and Leland Stanford Junior University, were grouped in the same cluster as firms related to medical applications, such as HeartFlow and Align Technology. This suggests that academic institutions have a strong interest in the integration of machine learning and photonics in the field of medicine. Subsequent studies can investigate patents in academia. In terms of the theoretical contributions of this study, past studies of machine learning in photonics focused on algorithm technologies [2; 9; 10; 11] or specific applications [1; 3; 6; 11; 12; 13]; however, they did not determine the technology distribution or the patent portfolio of technology developers from a macro perspective. This study revealed the distribution of primary technology and positioning of patentees in the synergy between machine learning and photonics.