In February of 2016, Chang, Joonhyuk, an Associate Professor in the Department of Electronic Engineering at Hanyang University(HYU), and his research team became the world’s first to implement Deep Learning Artificial Intelligence in telecommunication technology, thus paving the way toward a substantial improvement in voice quality in mobile atmosphere. The thesis the team composed was even published in the world renowned Institute of Electrical and Electronics Engineers (IEEE) academic journal this past February.
“The Internet network is not perfect,” stressed Professor Chang. “The number of email delivery failures explicitly shows how the Internet network is susceptible to the possibility of information loss. This vulnerability is the reason that prompted me to implement Deep Learning in telecommunication to prevent such loss of mobile information.” Korean telecommunication corporations such as SKT and KT currently depend on conventional “Packet” technology to deliver the voice of their customers. Although Packet technology may be efficient in data delivery, it has constantly received a concern in regard to its susceptibility to information loss during the delivery procedure. Deep Learning, however, compensates such loss. The Artificial Intelligence system inside the Deep Learning technology, based on its database of past information on people’s voices, allows the computer to regenerate any loss in information. “Artificial Intelligence, back in the old days, did not have the capacity to do this. Such regeneration of lost information shows how Artificial Intelligence began to possess the level of intelligence that humans do. This also signals the great potential AI has.”
Chang’s research accomplishment is a great steppingstone for Korea’s Deep Learning field. His research is renowned not only for being the world’s first implementation to telecommunication technology, but also for making big corporations in Korea more aware of the wide range of potential of Deep Learning technology. “I have already signed a contract with Samsung, LG, Hyundai, SK, and other large firms and am looking forward to seeing my work adapted in our daily lives,” Chang commented. “Even now at this point in time, about twenty of my fellow graduate students and I are working very hard to use Deep Learning technology for greater precision in biological diagnoses.”