name---->TBD-12(字串長度:6)---->許大山(字串長度:9)```hide---->0(字串長度:1)---->0
(字串長度:2)```name2---->(字串長度:0)---->Da-shan Shiu(字串長度:12)```talk_title---->(字串長度:0)---->Case Studies of Applying Generative AI Concepts to Low Resource Domains(字串長度:71)```can_playback---->no(字串長度:2)---->yes(字串長度:3)```company---->(字串長度:0)---->MediaTek Research(字串長度:17)```position---->(字串長度:0)---->Managing Director(字串長度:17)```desc---->(字串長度:0)---->Generative AI has achieved significant advances in a very short amount of time, in areas of language, vision, coding, speech and audio. In this talk we share two cases in which generative AI are applied to two low resource scenarios. In the first case, we have some very precious samples of cellular channel responses from real-world measurement. We would like to draw synthetic channel responses from the same distribution. In the second case, we are asked to customize an automatic speech recognition system to a use doamin, for which we do not have any audio-transcript pairs. We share our experience in how to tackle such low or even no resource challenges. (字串長度:662)```me_desc---->(字串長度:0)---->Dr. Da-shan Shiu is currently the Managing Director of MediaTek Research. Prior to this, he co-founded Mobilepeak Systems and served as its Chief Technology Officer. He was also an Associate Professor at the Department of Electrical Engineering and the Graduate School of Communications Engineering of National Taiwan University, as well as leading the Cellular modem algorithm development of Qualcomm in San Jose. He holds a Ph.D. from UC Berkeley. His research interests lie in fundamental communication and computational theory. He applies theoretical principles to practical applications, such as cellular communications, virtual and augmented reality, foundation model-driven autonomous agents, and machine learning for electronic design automation (EDA).(字串長度:760)```talkfile_link---->簡報12(字串長度:8)---->V(字串長度:1)```position_for_agenda---->
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