Science

As robots become increasingly integrated into our lives, researchers are exploring how to equip them with the ability to understand and respond to human emotions.

A new framework proposes harnessing the collective intelligence of AI agents to simulate scientific collaboration and accelerate discovery.

Researchers have released HortiMulti, a comprehensive dataset designed to push the boundaries of robot localization and mapping within the complex environments of agricultural polytunnels.

As generative AI models enter the realm of educational assessment, a rigorous examination of their validity is crucial to ensure fair and accurate scoring of complex student responses.

A new teleoperation framework, KUKAloha, blends human expertise with robotic precision to significantly improve the efficiency and safety of construction tasks.

A new study reveals that how students are motivated-not just that they have motivation-profoundly impacts their adoption of generative AI tools for tasks like math and writing.

Researchers have developed a streamlined, open-source system to accelerate the development of complex skills in humanoid robots, addressing key challenges in reinforcement learning and real-world deployment.

Fermilab is laying the groundwork for integrating artificial intelligence and machine learning into its complex accelerator systems to optimize performance and anticipate maintenance needs.

A new framework, SOFTMAP, leverages simulation and mesh alignment to enable accurate 3D modeling and control of deformable robotic manipulators.

A new review explores how analyzing human dialogue is unlocking deeper insights into the dynamics of successful teamwork.