One way that scientists train robots and artificial intelligence (AI) models to perform tasks - think self-driving cars - is by feeding them a perfect demonstration of what to do and asking them to copy it. This process, called imitation learning, is slow and expensive, and the resulting systems often can't handle more complex real-world scenarios. Instead, what if researchers could provide lots of imperfect demonstrations and have the system piece together a better approach? This strategy, called superhuman imitation learning, is the focus of a new project co-led by Sanjiban Choudhury , assistant professor of computer science in the Cornell Ann S.

https://www.miragenews.com/project-explores-improved-methods-for-ai-1082836/

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