In this episode of Talking Robots, Sabine Howard interviews Michael Arbib, a professor at USC with expertise in computer science, biological sciences, and neuroscience. Arbib discusses his work on mirror neurons, their role in understanding actions, language acquisition, and emotions, and how these systems can be implemented in robots for learning and imitation. He explains the parity principle in language and the potential for robots to emulate emotions for better human interaction, while also cautioning against the downsides of unchecked "passionate" robots. Arbib also touches on the challenges and joys of interdisciplinary research and shares insights on the future of robotics, emphasizing a distributed computer architecture that combines brain-like elements with specialized systems.
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