Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
Deep convolutional neural networks (DCNNs) don't see objects the way humans do -- using configural shape perception -- and that could be dangerous in real-world AI applications. The study employed ...
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Humanoid robots reliably manipulate different objects with 87% success using new framework
Robotic systems that mirror humans both in their appearance and movements, also known as humanoid robots, could be best suited for tackling many tasks that are currently performed by human agents.
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