This is the first in a two-part series on AI. Join us for a discussion toward a better understanding of AI by Assistant Professor Junjie Hu.
Junjie Hu is an assistant professor with appointments in the Department of Biostatistics, Department of Computer Science and Data Science Institute at the University of Wisconsin-Madison. He obtained his Ph.D. from School of Computer Science at Carnegie Mellon University.
Hu has a broad interest in natural language processing (NLP) and machine learning. His research goal is to build robust intelligent systems that evolve with changes in the environment and interact with people speaking different languages.
Over the past few years, artificial intelligence (AI) researchers have had phenomenal success in developing systems such as ChatGPT and GPT-4 that are capable of understanding and writing natural language. This has been achieved by exposing specialized computer systems (large language models or LLMs) to vast quantities of written text. While LLMs have been booming, concerns about their reliability, especially in complex, unforeseen scenarios, have also arisen. Junjie will discuss several research questions: (1) How do LLMs learn transferable language features? (2) How can we prompt LLMs to generate reliable answers to complex language questions? He will discuss his lab's ongoing work on LLMs' multi-step reasoning capability and share their initial findings.
If you have preliminary questions for the speaker, please send to Program Coordinator Millard Susman at firstname.lastname@example.org by Thursday, October 19.
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Registration Deadline: Friday, November 3
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Madison WI 53715-1218