As generative AI tools become increasingly sophisticated, a growing number of people are exploring them for emotional support, raising questions about why some choose digital assistance while others still seek human therapists.
New research demonstrates an automated approach to understanding how people feel during interactions with robots, moving beyond reliance on subjective feedback.
A new review reveals the outsized influence of major technology companies on artificial intelligence research, and the resulting societal and environmental costs.
A new framework leverages cross-embodiment to simultaneously optimize both the physical design and control systems of robotic hands, paving the way for more adaptable and skillful manipulation.
As we increasingly turn to apps and chatbots for self-assessment and memory-keeping, a fundamental shift is occurring in how we understand and construct our personal identities.
Researchers have developed a new framework that allows robots to reliably and safely accept objects from a human hand using reinforcement learning and a novel safety system.
New research reveals that artificial intelligence models trained on diverse scientific data-from molecules to materials-are beginning to ‘understand’ matter in a remarkably similar way.
A new framework proposes that reciprocal effort – the give and take of focus – is central to building successful interactions between humans and robots.
New research demonstrates how reinforcement learning can create AI systems that optimize their strategies in real-time based on user feedback, without the need for extensive labeled datasets.
A new framework empowers robots to understand and replicate actions observed in videos, bridging the gap between visual perception and physical manipulation.