Academic lectures：Lecture｜CMU Ding Zhao: Towards Trustworthy AI Generalist
Speaker： Ding Zhao Carnegie Mellon University Associate Professor ;
Invitor： Song An Zhang Assistant Professor
Time： 2024.05.20 15:30 ~ 2024.05.20 16:30
Location： Auditorium 200, East Wing of Pao Yue-Kong Library, Minhang Campus, Shanghai Jiao Tong University
Abstract： As AI becomes more integrated into physical autonomy, it presents a dual spectrum of opportunities and risks. In this talk, I will introduce our efforts in deploying trustworthy intelligent autonomy at a large scale for vital civil usage such as self-driving cars and assistant robots. During the deployment and transition, training data often exhibit significant imbalance, multi-modal complexity, and nonstationarity. I will initiate the discussion by analyzing 'long-tailed' problems with rare events and their connection to safety evaluation and safe reinforcement learning. I will then discuss how modeling multi-modal uncertainties as ‘tasks’ may enhance generalizability by learning across domains. In cases involving unknown-unknown tasks with severely limited data, we explore the potential of leveraging external knowledge from legislative sources, causal reasoning, and large language models. Lastly, I will discuss the potential social benefits/concerns regarding deploying intelligent autonomy at a large scale.
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