VentureBeat February 6, 2024
Humans use expressive behaviors to communicate goals and intents. We nod to acknowledge the presence of a coworker, shake our heads to convey a negative response, or use simple utterances like “excuse me” to ask others to make way. Mobile robots that want to share their environments with humans should be able to show such behavior. This remains one of the important challenges of robotics, and current solutions are rigid and limited in scope.
In a new study, researchers at the University of Toronto, Google DeepMind and Hoku Labs propose a solution that uses the vast social context available in large language models (LLM) to create expressive behaviors for robots. Called GenEM, the technique uses various prompting methods to understand...
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