Can Large Language Models Learn Common Sense and Creativity?

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Large language models struggle with extrapolating beyond what they've been trained on
It is uncertain if large language models can learn common sense or be truly creative
There may be a potential for large language models to develop understanding and explanation abilities
The implications of these advancements are vast and difficult to predict
Remaining open-minded and adaptable is important during this transformative phase

Over the last year, AI large-language models (LLMs) like ChatGPT have demonstrated a remarkable ability to carry on human-like conversations in a variety of different concepts. But the way these LLMs "learn" is very different from how human beings learn, and the same can be said for how they "reason." It's reasonable to ask, do these AI programs really understand the world they are talking about? Do they possess a common-sense picture of reality, or can they just string together words in convincing ways without any underlying understanding? Computer scientist Yejin Choi is a leader in trying to understand the sense in which AIs are actually intelligent, and why in some ways they're still shockingly stupid.

Blog post with transcript: https://www.preposterousuniverse.com/podcast/2023/08/28/248-yejin-choi-on-ai-and-common-sense/

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Yejin Choi received a Ph.D. in computer science from Cornell University. She is currently the Wissner-Slivka Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and also a senior research director at AI2 overseeing the project Mosaic. Among her awards are a MacArthur fellowship and a fellow of the Association for Computational Linguistics.

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