I will discuss recent advances in generative AI and share my reflections. We will cover topics ranging from open-source data and models to AI safety and trustworthiness, societal impacts, malicious attacks on models and data, protection against content creators' work being ripped off, tensions between safety, participation, and progress, prompt jailbreaking, domain-specific foundation models, "stochastic parrot", and emerging computing for generative AI.

H. T. Kung is William H. Gates Professor of Computer Science and Electrical Engineering at Harvard University. He conducts research on topics related to the application of artificial intelligence in manufacturing and healthcare, AI accelerators, VLSI design, high-performance computing, parallel and distributed computing, computer architectures, and computer networks. Professor Kung received his bachelor's degree from National Tsing Hua University in Taiwan in 1968. He received his Ph.D. degree from Carnegie Mellon University in 1973. He taught at Carnegie Mellon for 19 years before joining Harvard in 1992. Professor Kung is an elected member of the US National Academy of Engineering for introducing the idea of systolic computation, contributions to parallel computing, and applying complexity analysis to very-large-scale-integrated (VLSI) computation. In addition, Professor Kung is a Guggenheim Fellow, an elected member of the Academia Sinica in Taiwan, as well as the president and co-founder of the Taiwan AI Academy, a non-profit organization which has cultivated over 10,000 AI talents for industries since 2019. Professor Kung received the 1990 IEEE Computer Society Charles Babbage Award, the 1991 Pittsburgh Intellectual Property Law Association Inventor of the Year Award, the 2015 ACM Special Interest Group in Operating Systems (SIGOPS) Hall of Fame Award, and the 2023 IEEE Computer Society Technical Community on Distributed Processing (TCDP) Award for his contributions to concurrency control and systolic arrays in distributed systems .