Home Autonomous Self Driving Toyota invests into the future of automated driving technology

Toyota invests into the future of automated driving technology

3 min read

With the aim of accelerating joint research and development of artificial intelligence technologies in mobility-related fields, such as automated driving technology, Toyota Motor Corporation and Preferred Networks, Inc. (PFN) agreed to an additional Toyota investment in PFN. The investment will amount to 10.5 billion yen (around RM407million), and Toyota will acquire stock in PFN through the allocation of new shares to a third party.

Toyota and PFN have been working on joint research and development since October 2014, and for the purpose of strengthening the relationship, Toyota invested approximately 1 billion yen in PFN in December 2015. To date, the joint research and development have focused on object-recognition technology and analysis technology of vehicle information. This additional investment will further enhance the relationship between Toyota and PFN and spur joint research and development.

Toyota is actively researching and developing a wide range of technologies, including automated driving technologies that are expected to significantly affect the nature of mobility in the future. PFN’s world-leading, intelligence-related technologies (including machine learning, deep learning, and big data processing) are essential to Toyota. The overall goal of these initiatives is to foster the creation of a society in which mobility means safety and freedom.

PFN was founded in March 2014 with the aim of business utilization of deep learning technology focused on IoT. PFN advocates “Edge Heavy Computing” as a way to handle the enormous amount of data generated by devices in a distributed and collaborative manner at the edge of the network and realizes innovation in the three priority business areas of transportation systems, the manufacturing industry, and bio/healthcare. PFN collaborates with various organizations and promotes advanced initiatives through the development and offering of an open-source deep learning framework (Chainer) and an integrated solution that includes applications (Deep Intelligence in Motion or “DIMo”).