Toward AGI: Automating "Slow" Thinking in AI
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Speakers
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Gopal Gupta, PhD – Professor of Computer Science, UT Dallas
About the Talk
Over the last decade, AI technology has advanced significantly and received worldwide attention, especially after the advent of generative AI (GenAI) and large language models (LLMs). Much of these advances have come about because of progress in machine learning and deep learning research. However, the holy grail of AGI (artificial general intelligence) — AI that is as good as humans — still seems elusive.
Nobel laureate Kahneman characterized human intelligence as consisting of “fast” (intuitive) and “slow” (deliberative) thinking. While machine learning technology has resulted in rapid automation of “fast” thinking, automation of “slow” thinking has been lagging. In this talk, Dr. Gupta discusses how “slow” thinking can be automated and presents UTD's s(CASP) system that automates human (commonsense) reasoning. He also discusses how AI systems that can match human capabilities can be built by combining learning and reasoning, i.e., by combining the capabilities of both GenAI/LLMs and the s(CASP) system, including several practical applications of this approach, e.g., reliable interactive chatbots and autonomous driving.
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Gopal Gupta, PhD, is a professor of computer science at The University of Texas at Dallas. He co-directs the university's Center for Applied AI and Machine Learning, which focuses on applying AI for solving industrial problems. From 2009 to 2020, he served as head of the Compter Science Department at UTD, and also previously served as president of the International Association for Logic Programming. He has published extensive research on topics including automated reasoning, computational logic and explainable AI. His research group has authored several software systems, including ones that are publicly available and some that have formed the basis of start-up companies. His current research is focused on automating commonsense reasoning.
Dr. Gupta's research has won several best-paper awards as well as the ICLP 2016 test-of-time award, and his work has been supported by the National Science Foundation, DARPA and industry financing. He obtained his MS and PhD from UNC Chapel Hill and his bachelor's in computer science from the Indian Institute of Technology, Kanpur.
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